# ent

id: cord-024683-3v8i39rk
type: GGP
entity:
  seizures 57 2 Serious Adverse Events Events that significantly influence patient s daily activity or require additional medicine or require inpatient treatment 3 Lack of Efficacy A reduction of seizure frequency in the last month of less than 50 of baseline or any deterioration of seizures either in frequency or in manifestation Emotional Impact severe anxiety or depression By reviewing patient reported data such system allows community caregivers to filter and separate patients into different subgroups according to their actual medical demand Patients below such threshold would maintain their current management and stay within the first level Those beyond the first threshold need to contact


id: cord-024683-3v8i39rk
type: WORK_OF_ART
entity:
  the Treatment of Epilepsy Development of Digital Therapeutics Comprising Behavioral and Music Based Interventions for


id: cord-024683-3v8i39rk
type: CHEMICAL
entity:
  carbamazepine valproic acid phenytoin lamotrigine levetiracetam topiramate oxcarbazepine gabapentin pregabalin lacosamide


id: cord-018151-5su98uan
type: GGP
entity:
  Poussin s 1665 The Plague of Ashdod as evidence of a pre bacteriological knowledge of this zoonotic connection for a critique see S Barker Yellow Peril Epidemics The Political Ontology of Degeneration and Emergence A Plague of Kinyounism The Caricatures of


id: cord-018151-5su98uan
type: ORG
entity:
  South Africa American Anthropological Association Engagement Modern Management of Rats British Agricultural Science


id: cord-018761-vm86d4mj
type: WORK_OF_ART
entity:
  Guidance Note on Using the Cluster Approach to Strengthen Humanitarian Response Panel on Humanitarian Financing Report


id: cord-018761-vm86d4mj
type: EVENT
entity:
  Reference 1 World Health Organization Department of Communicable Disease Surveillance and Response Highlights


id: cord-020544-kc52thr8
type: WORK_OF_ART
entity:
  Guidance Note on Using the Cluster Approach to Strengthen Humanitarian Response International Conference on Primary Health Care Selective


id: cord-020544-kc52thr8
type: ORG
entity:
  Source World Health Organization World Health Organization Department of Communicable Disease Surveillance and Response Highlights


id: cord-024746-ijlnefz3
type: ORG
entity:
  The Hidden Geometry of Complex Network Driven Contagion Phenomena Effective Distances for Epidemics Spreading on Complex Networks Locating the Source of Large Scale Outbreaks


id: cord-024746-ijlnefz3
type: FAC
entity:
  Complex Networks Assessing Node Risk and Vulnerability in Epidemics on Networks Analytical Computation of the Epidemic Threshold on Temporal Networks Analytical Computation of the Epidemic Threshold on Temporal Networks Containing Epidemic Outbreaks


id: cord-024746-ijlnefz3
type: ORG
entity:
  the Mathematical Theory of Epidemics The Mathematical Theory of Infectious Diseases and Its Applications Exact Epidemic Models


id: cord-020610-hsw7dk4d
type: WORK_OF_ART
entity:
  Bushmeat Hunting Deforestation and Prediction of Zoonoses Emergence Uncovering Zoonoses Awareness in an Emerging Disease Hotspot Social Science


id: cord-020610-hsw7dk4d
type: WORK_OF_ART
entity:
  Unintended Consequences of the Bushmeat Ban Impact of the Ebola Virus Disease Outbreak on Market Chains and Trade of Agricultural Products


id: cord-220618-segffkbn
type: GGP
entity:
  IL 5 2 10 2 b rmax GE 5 10 3 c rmax U S 3 10 4 d rmax SP 7 10 3 e rmax U K 5 3 10 3 f rmax F R 4 2 10 3


id: cord-270679-heg1h19l
type: WORK_OF_ART
entity:
  IAEP Theory of Planned Behavior From Intentions to Actions A Theory of Planned Behavior in Action Control From Cognitions to Behavior The Prediction of Behavior


id: cord-048339-nzh87aux
type: WORK_OF_ART
entity:
  The Theory of Branching Processes Matrix Population Models Construction Analysis and Interpretation Superspreading


id: cord-281437-cb3u1s7s
type: ORG
entity:
  Ebola Towards People Centred Epidemic Preparedness and Response From Knowledge to Action Anthropology


id: cord-281437-cb3u1s7s
type: ORG
entity:
  ZIKV Research Pregnancy Pregnant Women the Zika Virus Vaccine Research Agenda Ethics Guidance on Priorities Inclusion


id: cord-238342-ecuex64m
type: ORG
entity:
  Composite Monte Carlo Decision Making under High Uncertainty of Novel Coronavirus Epidemic Using Hybridized Deep Learning


id: cord-238342-ecuex64m
type: ORG
entity:
  Stochastic Evacuation Models for Decision Support in Actual Emergencies On Algorithmic Decision Procedures in Emergency Response Systems


id: cord-234552-0pbg0ldm
type: GGP
entity:
  V v 1 v 2 v n denote the set of n nodes Each node remains in one of the three possible states susceptible S infected without symptoms or asymptomatic X and


id: cord-298872-gbi74g0n
type: DNA
entity:
  b Figure 3 Dotted blue the Italian cumulative curve red cubic approximant black logistic approximant


id: cord-301463-jzke8fop
type: WORK_OF_ART
entity:
  Reducing the Impact of the Next Influenza Pandemic Using Household Based Public Health Interventions Strategies


id: cord-347349-caz5fwl1
type: EVENT
entity:
  the COVID 19 epidemic medRxiv 2020 Modeling Return of the Epidemic Impact of Population Structure Asymptomatic Infection Case Importation and


id: cord-329256-7njgmdd1
type: ORG
entity:
  edn Vienna Austria R Foundation for Statistical Computing Development Core Team A Language and Environment for Statistical Computing Generalizing


id: cord-329256-7njgmdd1
type: ORG
entity:
  Division of Epidemiology University of Utah School of Medicine Salt Lake City USA 2 Department of Pediatrics University of Utah School of Medicine Salt Lake City USA 3 Division of Disease Control and Prevention Utah Department of Health Salt Lake City USA Authors


id: cord-335886-m0d72ntg
type: ORG
entity:
  epidemics National Health Commission of the People s Republic of China Prevention of Epidemics Health Commission of Hubei Province Anti Prevention New Coronary Disease Infection Information Number


id: cord-341187-jqesw4e8
type: WORK_OF_ART
entity:
  Modeling Return of the Epidemic Impact of Population Structure Asymptomatic Infection Case Importation and Personal Contacts


# bib

id: cord-006203-wwpd26bx
title: When the world catches cold: Thinking with influenza
author: Nguyen, Vinh-Kim
date: 2016-02-26
txt: ./txt/cord-006203-wwpd26bx.txt
cache: ./cache/cord-006203-wwpd26bx.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7100313/
doi: 10.1057/biosoc.2016.2
abstract: nan
summary:
  Caduff, Keck and MacPhail all write against more sensationalistic accounts of pandemic flu with their dramatic tropes of virus hunters and looming catastrophe, seeking rather to demystify and explain in these ethnographies of influenza research. The temporal modality, perhaps most familiar to readers of this journal from the concept of the experiment as a "machine for producing the future" (Rheinberger,1997, quoting the Nobel prize-winning molecular biologist François Jacob), is most explicitly indebted to classical studies of witchcraft, oracles and divination (Evans-Pritchard, 1963) to more contemporary examinations of risk and uncertainty in clinical practice, global health and everyday life. Thinking about regimes of anticipation can bring in conversations that have emerged in contemporary ethnography around the work of Elizabeth Povinelli and specifically her notions of social tense and "the future anterior" as a mode of late liberal governmentalitya gesture made by Caduff.


id: cord-015967-kqfyasmu
title: Epidemic Models: Their Spread, Analysis and Invasions in Scale-Free Networks
author: Tagore, Somnath
date: 2015-03-20
txt: ./txt/cord-015967-kqfyasmu.txt
cache: ./cache/cord-015967-kqfyasmu.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7120102/
doi: 10.1007/978-3-319-15916-4_1
summary:
  For instance, hub individuals of such high-risk individuals help in maintaining sexually transmitted diseases (STDs) in different populations where majority belong to long-term monogamous relationships, whereas in case of SARS epidemic, a significant proportion of all infections are due to high risk connected individuals. Likewise, models for epidemic spread in static heavy-tailed networks have illustrated that with a degree distribution having moments resulted in lesser prevalence and/or termination for smaller rates of infection [14] . Generally, epidemic models consider contact networks to be static in nature, where all links are existent throughout the infection course. But, in cases like HIV, which spreads through a population over longer time scales, the course of infection spread is heavily dependent on the properties of the contact individuals. Likewise, for a wide range of scale-free networks, epidemic threshold is not existent, and infections with low spreading rate prevail over the entire population [10] .

abstract:
  The mission of this chapter is to introduce the concept of epidemic outbursts in network structures, especially in case of scale-free networks. The invasion phenomena of epidemics have been of tremendous interest among the scientific community over many years, due to its large scale implementation in real world networks. This chapter seeks to make readers understand the critical issues involved in epidemics such as propagation, spread and their combat which can be further used to design synthetic and robust network architectures. The primary concern in this chapter focuses on the concept of Susceptible-Infectious-Recovered (SIR) and Susceptible-Infectious-Susceptible (SIS) models with their implementation in scale-free networks, followed by developing strategies for identifying the damage caused in the network. The relevance of this chapter can be understood when methods discussed in this chapter could be related to contemporary networks for improving their performance in terms of robustness. The patterns by which epidemics spread through groups are determined by the properties of the pathogen carrying it, length of its infectious period, its severity as well as by network structures within the population. Thus, accurately modeling the underlying network is crucial to understand the spread as well as prevention of an epidemic. Moreover, implementing immunization strategies helps control and terminate theses epidemics.


id: cord-016387-ju4130bq
title: A Brief History of Advances Toward Health
author: Last, John
date: 2005
txt: ./txt/cord-016387-ju4130bq.txt
cache: ./cache/cord-016387-ju4130bq.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7120648/
doi: 10.1007/0-387-24103-5_1
summary:
  From time to time, this steady drain on long life and good health was punctuated by great and terrifying epidemics-smallpox, typhus, influenza, and, most terrible of all, the plague, or the "black death." The causes of these periodic devastations, the contributing reasons to why they happened, were a mystery. After Fracastorius, the pathfinders on the road to health became numerous, but mention here will be made of only a handful of public health heroes: Paracelsus, John Graunt, Antoni van Leeuwenhoek, Bernardino Ramazzini, James Lind, Edward Jenner, Johann Peter Frank, John Snow, Ignaz Semmelweiss, and Louis Pasteur. Many others belong in their company: The great German pathologist Rudolph Virchow recognized that political action as well as rational science are necessary to initiate effective action to control public health problems; Edwin Chadwick and Lemuel Shattuck reported on the appalling sanitary conditions associated with the unacceptably high infant and child death rates that prevailed in 19 th century industrial towns; William Farr established vital statistics in England as a model for other nations to follow.

abstract:
  Three major discoveries determined the health and history of the human species. The first occurred almost a million years ago, when our hominid precursors discovered how to use fire to cook the meat they had hunted. They found that cooked meat tasted better, it didn’t go bad so quickly, and eating it was less likely to make them ill. Our understanding of nutrition, a basic tenet of public health science, and the art of cooking have been improving ever since.


id: cord-018151-5su98uan
title: Introduction: Infectious Animals and Epidemic Blame
author: Lynteris, Christos
date: 2019-10-12
txt: ./txt/cord-018151-5su98uan.txt
cache: ./cache/cord-018151-5su98uan.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7122954/
doi: 10.1007/978-3-030-26795-7_1
summary:
  Providing original studies of rats, mosquitoes, marmots, dogs and ''bushmeat'', which at different points in the history of modern medicine and public health have come to embody social and scientific concerns about infection, this volume aims to elucidate the impact of framing non-human animals as epidemic villains. Whether it is stray dogs as spreaders of rabies in colonial and contemporary India, bushmeat as the source of Ebola in West Africa, mosquitoes as vectors of malaria, dengue, Zika and yellow fever in the Global South, or rats and marmots as hosts of plague during the third pandemic, this volume shows framings of non-human animals to be entangled in local webs of signification and, at the same time, to be global agents of modern epidemic imaginaries.

abstract:
  The Introduction to the edited volume summarises the chapters of the volume and discusses their contribution in the context of current historical and anthropological studies of zoonotic and vector-borne disease, with a particular focus on how epidemic blame is articulated in different historical, social and political contexts.


id: cord-018761-vm86d4mj
title: Technical Annexes
author: Bradt, David A.
date: 2017-11-08
txt: ./txt/cord-018761-vm86d4mj.txt
cache: ./cache/cord-018761-vm86d4mj.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7123725/
doi: 10.1007/978-3-319-69871-7_8
abstract:
  This chapter provides guidance on technical issues in the health sector. The annexes contain selective compilations of frequently used reference information.


id: cord-019114-934xczf3
title: Epidemic dynamics on information-driven adaptive networks
author: Zhan, Xiu-Xiu
date: 2018-02-16
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7126912/
doi: 10.1016/j.chaos.2018.02.010
abstract:
  Research on the interplay between the dynamics on the network and the dynamics of the network has attracted much attention in recent years. In this work, we propose an information-driven adaptive model, where disease and disease information can evolve simultaneously. For the information-driven adaptive process, susceptible (infected) individuals who have abilities to recognize the disease would break the links of their infected (susceptible) neighbors to prevent the epidemic from further spreading. Simulation results and numerical analyses based on the pairwise approach indicate that the information-driven adaptive process can not only slow down the speed of epidemic spreading, but can also diminish the epidemic prevalence at the final state significantly. In addition, the disease spreading and information diffusion pattern on the lattice as well as on a real-world network give visual representations about how the disease is trapped into an isolated field with the information-driven adaptive process. Furthermore, we perform the local bifurcation analysis on four types of dynamical regions, including healthy, a continuous dynamic behavior, bistable and endemic, to understand the evolution of the observed dynamical behaviors. This work may shed some lights on understanding how information affects human activities on responding to epidemic spreading.


id: cord-020544-kc52thr8
title: Technical Annexes
author: Bradt, David A.
date: 2019-12-03
txt: ./txt/cord-020544-kc52thr8.txt
cache: ./cache/cord-020544-kc52thr8.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7138430/
doi: 10.1007/978-3-030-04801-3_7
summary:
  However, if Dukoral is readily available and staff are properly trained in its use according to the guidelines that come with the vaccine, the COTS program PERMITS Dukoral''s use (ideally before an outbreak) in the following high-risk populations: refugee populations in which cholera is present, health care workers managing cholera cases, and communities in which the incidence rate is greater than 1 in 1000 annually." [2] Epidemiological Surveillance (specific to cholera)

abstract:
  7.1 Humanitarian Programs 141; 7.2 Security Sector 153; 7.3 Health Sector 158: Core Disciplines in Disaster Health 161. Primary Health Care Programs 162. Disease Prevention 162. Clinical Facilities 164. Reproductive Health 165. Water and Sanitation 166. Food and Nutrition 171. Chemical Weapons 181. Epi Methods 184; 7.4 Tropical Medicine 187: Tropical Infectious Diseases—Vector-borne and Zoonotic 196. Tropical Infectious Diseases—Non-vector-borne 215; 7.5 Epidemic Preparedness and Response 239; 7.6 Communicable Disease Control 242: Diarrhea 244. Influenza 257. Malaria 263. Measles 267. Meningitis 269. Viral Hemorrhagic Fever 272; 7.7 Diagnostic Laboratory 275: Indications, Laboratory Tests, and Expected Availability 276. Specimen Handling 278; 7.8 Acronyms 282;


id: cord-020610-hsw7dk4d
author: Thys, Séverine
date: 2019-10-12
txt: ./txt/cord-020610-hsw7dk4d.txt
cache: ./cache/cord-020610-hsw7dk4d.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7141173/
doi: 10.1007/978-3-030-26795-7_7
summary:
  Combined with a divergent political practice and lived experiences of the state, especially between Sierra Leone and Guinea, the working hypothesis drawn from my ethnographic observations in Macenta and related literature review is that part of the continuing episodes of hostility and social resistance manifested by Guinean communities regarding the adoption of the proposed control measures against the scourge of Ebola has its origins in the divergence between explanatory systems of the disease; on the one hand, biomedical explanatory systems, and, on the other hand, popular explanatory systems. By framing ''bushmeat'' hunting, as well as local burials, as the main persisting cultural practices among the ''forest people'' to explain (or to justify) the maintenance of the EVD transmission during the West African epidemic, the notion of culture that fuelled sensational news coverage has strongly stigmatised this ''patient zero'' community both globally and within Guinea, and has been employed to obscure the actual, political, economic and political-economic drivers of infectious disease patterns.

title:
  Contesting the (Super)Natural Origins of Ebola in Macenta, Guinea: Biomedical and Popular Approaches

abstract:
  In December 2013, a two-year-old child died from viral haemorrhagic fever in Méliandou village in the South-East of Guinea, and constituted the likely index case of a major epidemic. When the virus was formally identified as Ebola, epidemiologists started to investigate the chains of transmission, while local people were trying to make sense out of these deaths. The epidemic control measures taken by national and international health agencies were soon faced by strong reluctance and a sometimes aggressive attitude of the affected communities. Based on ethnographic work in Macenta (Forest region) in the autumn of 2014 for the Global Outbreak and Alert Response Network (GOARN) of the World Health Organization, this chapter shows that while epidemiologists involved in the outbreak response attributed the first Ebola deaths in the Forest region to the transmission of a virus from an unknown animal reservoir, local citizens believed these deaths were caused by the breach of a taboo. Epidemiological and popular explanations, mainly evolving in parallel, but sometimes overlapping, were driven by different explanatory models: a biomedical model embodying nature in the guise of an animal disease reservoir, which in turn poses as threat to humanity, and a traditional-religious model wherein nature and culture are not dichotomized. The chapter will argue that epidemic responses must be flexible and need to systematically document popular discourse(s), rumours, codes, practices, knowledge and opinions related to the outbreak event. This precious information must be used not only to shape and adapt control interventions and health promotion messages, but also to trace the complex biosocial dynamics of such zoonotic disease beyond the usual narrow focus on wild animals as the sources of infection.


id: cord-024683-3v8i39rk
title: Epilepsy control during an epidemic: emerging approaches and a new management framework
author: Chen, Deng
date: 2020-05-12
txt: ./txt/cord-024683-3v8i39rk.txt
cache: ./cache/cord-024683-3v8i39rk.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7215138/
doi: 10.1186/s42494-020-00015-z
summary:
  Here we review recent development of potential approaches for epilepsy control during an epidemic and propose a new three-level management framework to address these challenges. Hence, the proposed new approaches for treatment such as structured letter therapy [41] for consultation on mental problem during COVID-19 epidemic can be easily deployed in App. These Apps are largely available online and have helped different groups of patients improving their mental and emotional health. The patient & family level focuses on self-management, including all six components mentioned above [32] and is facilitated by epilepsy-related Apps, while the community support level, consisting of general physicians and other local caregivers from the community, acts both as a threshold for hospitalization and an outpost for providing basic intervention, including education, adjusting AED doses, rehabilitation and mental health management.

abstract:
  Epidemics are a big threat to world health. The ongoing pandemic of corona virus disease 2019 (COVID-19) has caused a series of challenges to public health. One such challenge is the management of chronic diseases such as epilepsy during an epidemic event. Studies on this topic are rather limited and the related medical practice is full of uncertainty. Here we review recent development of potential approaches for epilepsy control during an epidemic and propose a new three-level management framework to address these challenges.


id: cord-024746-ijlnefz3
title: Contact-Based Model for Epidemic Spreading on Temporal Networks
author: Koher, Andreas
date: 2019-08-02
txt: ./txt/cord-024746-ijlnefz3.txt
cache: ./cache/cord-024746-ijlnefz3.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7219481/
doi: 10.1103/physrevx.9.031017
summary:
  We present a contact-based model to study the spreading of epidemics by means of extending the dynamic message-passing approach to temporal networks. The shift in perspective from nodeto edge-centric quantities enables accurate modeling of Markovian susceptible-infected-recovered outbreaks on time-varying trees, i.e., temporal networks with a loop-free underlying topology. On arbitrary graphs, the proposed contact-based model incorporates potential structural and temporal heterogeneities of the contact network and improves analytic estimations with respect to the individual-based (node-centric) approach at a low computational and conceptual cost. Our comparison between MC simulations and analytic estimations from the CB and IB models followed a bottom-up approach: We looked at (i) epidemic trajectories of individual nodes, (ii) averaged trajectories given the same outbreak location, and (iii) the final outbreak size for a range of infection probabilities and with random initial condition.

abstract:
  We present a contact-based model to study the spreading of epidemics by means of extending the dynamic message-passing approach to temporal networks. The shift in perspective from node- to edge-centric quantities enables accurate modeling of Markovian susceptible-infected-recovered outbreaks on time-varying trees, i.e., temporal networks with a loop-free underlying topology. On arbitrary graphs, the proposed contact-based model incorporates potential structural and temporal heterogeneities of the contact network and improves analytic estimations with respect to the individual-based (node-centric) approach at a low computational and conceptual cost. Within this new framework, we derive an analytical expression for the epidemic threshold on temporal networks and demonstrate the feasibility of this method on empirical data.


id: cord-027757-zb4wxt85
title: The Influenza Epidemic of 1918 and the Adivasis of Western India
author: Hardiman, David
date: 2012-03-09
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7313811/
doi: 10.1093/shm/hks015
abstract:
  The influenza epidemic of 1918 was the single worst outbreak of this disease known in history. This article examines an area of western India that was affected very badly—that of a tract inhabited by impoverished indigenous peoples, who are known in India as adivasis. The reasons for this are discussed. Some oral accounts help to bring out the enduring memory of that terrible time. The general health of the adivasis and the existing medical facilities in this area are examined. Attempts to check and treat the disease by the colonial government and its doctors, as well as missionary doctors and other non-governmental agencies, are considered to see why they had so little overall impact. Some comparisons are made with the fate of indigenous people in other parts of the world during the epidemic, in particular with the Inuits of Alaska.


id: cord-028048-0oqv2jom
title: Establishing seasonal and alert influenza thresholds in Morocco
author: Rguig, Ahmed
date: 2020-06-29
txt: ./txt/cord-028048-0oqv2jom.txt
cache: ./cache/cord-028048-0oqv2jom.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7323370/
doi: 10.1186/s12889-020-09145-y
summary:
  The objective of this study was to evaluate the performance of two methods using means and medians to establish thresholds using data from the Moroccan national influenza-like illness (ILI) syndromic surveillance system. Using three seasons of virologic ILI surveillance data (2014/2015 to 2016/2017), we used the MEM method to make calculations using the composite parameter recommended by WHO [20] ; this method estimates the proportion of laboratory-confirmed influenza ILI consultations among all outpatient consultations, or the product of weekly ILI consultations of total outpatient visits and weekly percentage of influenzapositive specimens among respiratory tests. Whichever method is used, analysis of surveillance data will provide information about seasonal thresholds and epidemic curves that may help health care personnel in the clinical management of respiratory illness after the start of influenza season.

abstract:
  BACKGROUND: Several statistical methods of variable complexity have been developed to establish thresholds for influenza activity that may be used to inform public health guidance. We compared the results of two methods and explored how they worked to characterize the 2018 influenza season performance–2018 season. METHODS: Historical data from the 2005/2006 to 2016/2018 influenza season performance seasons were provided by a network of 412 primary health centers in charge of influenza like illness (ILI) sentinel surveillance. We used the WHO averages and the moving epidemic method (MEM) to evaluate the proportion of ILI visits among all outpatient consultations (ILI%) as a proxy for influenza activity. We also used the MEM method to evaluate three seasons of composite data (ILI% multiplied by percent of ILI with laboratory-confirmed influenza) as recommended by WHO. RESULTS: The WHO method estimated the seasonal ILI% threshold at 0.9%. The annual epidemic period began on average at week 46 and lasted an average of 18 weeks. The MEM model estimated the epidemic threshold (corresponding to the WHO seasonal threshold) at 1.5% of ILI visits among all outpatient consultations. The annual epidemic period began on week 49 and lasted on average 14 weeks. Intensity thresholds were similar using both methods. When using the composite measure, the MEM method showed a clearer estimate of the beginning of the influenza epidemic, which was coincident with a sharp increase in confirmed ILI cases. CONCLUSIONS: We found that the threshold methodology presented in the WHO manual is simple to implement and easy to adopt for use by the Moroccan influenza surveillance system. The MEM method is more statistically sophisticated and may allow a better detection of the start of seasonal epidemics. Incorporation of virologic data into the composite parameter as recommended by WHO has the potential to increase the accuracy of seasonal threshold estimation.


id: cord-029245-ay15ybcm
title: Pandemics and the consequences of COVID‐19
author: Davies, Stephen
date: 2020-06-29
txt: ./txt/cord-029245-ay15ybcm.txt
cache: ./cache/cord-029245-ay15ybcm.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7361832/
doi: 10.1111/ecaf.12415
abstract: nan
summary:
  There is also an inescapable economic aspect to pandemics, in terms of both their dynamics (the way they spread and the reasons why they appear when and where they do), and their consequences, among which economic impacts loom large. (In 1918-19 the time it took Spanish flu to travel from one part of the world to another was measured in months.) All this leads to the conclusion that several features of the world we live in, such as high levels of economic integration and trade, widespread mass travel, and rapid modes of transport, make it much more vulnerable to a true pandemic. These and other features of the modern world also mean that the economic impact of an extensive epidemic is going to be much greater than was the case in, for example, 1968-69. Moreover, the early signs are that lockdowns may not have had such a dramatic effect on rates of infection and rapidity of spread during the first phase of this pandemic.


id: cord-048339-nzh87aux
title: The Waiting Time for Inter-Country Spread of Pandemic Influenza
author: Caley, Peter
date: 2007-01-03
txt: ./txt/cord-048339-nzh87aux.txt
cache: ./cache/cord-048339-nzh87aux.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1764036/
doi: 10.1371/journal.pone.0000143
summary:
  On the other hand, the model predicts that border screening for symptomatic infection, wearing a protective mask during travel, promoting early presentation of cases arising among arriving passengers and moderate reduction in travel volumes increase the delay only by a matter of days or weeks. In this paper we demonstrate how the delay to importation of an epidemic of pandemic strain influenza may be quantified in terms of the growing infection incidence in the source region, traveler volumes, border screening measures, travel duration, inflight transmission and the delay until an infected arrival initiates a chain of transmission that gathers momentum. For example, if R = 1.5, and we reduce the number of intending travelers from 400 to 10 per day, implement 100% flight-based quarantining, implement compulsory mask wearing during travel and presentation at 6 hours following symptom onset then there is a substantial probability (0.74) that the pandemic strain will never be imported (assuming the epidemic is confined to the source country).

abstract:
  BACKGROUND: The time delay between the start of an influenza pandemic and its subsequent initiation in other countries is highly relevant to preparedness planning. We quantify the distribution of this random time in terms of the separate components of this delay, and assess how the delay may be extended by non-pharmaceutical interventions. METHODS AND FINDINGS: The model constructed for this time delay accounts for: (i) epidemic growth in the source region, (ii) the delay until an infected individual from the source region seeks to travel to an at-risk country, (iii) the chance that infected travelers are detected by screening at exit and entry borders, (iv) the possibility of in-flight transmission, (v) the chance that an infected arrival might not initiate an epidemic, and (vi) the delay until infection in the at-risk country gathers momentum. Efforts that reduce the disease reproduction number in the source region below two and severe travel restrictions are most effective for delaying a local epidemic, and under favourable circumstances, could add several months to the delay. On the other hand, the model predicts that border screening for symptomatic infection, wearing a protective mask during travel, promoting early presentation of cases arising among arriving passengers and moderate reduction in travel volumes increase the delay only by a matter of days or weeks. Elevated in-flight transmission reduces the delay only minimally. CONCLUSIONS: The delay until an epidemic of pandemic strain influenza is imported into an at-risk country is largely determined by the course of the epidemic in the source region and the number of travelers attempting to enter the at-risk country, and is little affected by non-pharmaceutical interventions targeting these travelers. Short of preventing international travel altogether, eradicating a nascent pandemic in the source region appears to be the only reliable method of preventing country-to-country spread of a pandemic strain of influenza.


id: cord-103418-deogedac
title: Shift of percolation thresholds for epidemic spread between static and dynamic small-world networks
author: Ochab, J. K.
date: 2010-11-12
txt: ./txt/cord-103418-deogedac.txt
cache: ./cache/cord-103418-deogedac.txt
extension: .txt
mime: text/plain
url: https://arxiv.org/pdf/1011.2985v1.pdf
doi: 10.1140/epjb/e2011-10975-6
summary:
  title: Shift of percolation thresholds for epidemic spread between static and dynamic small-world networks The network was constructed as a 2-dimensional Watts-Strogatz model (500x500 square lattice with additional shortcuts), and the dynamics involved rewiring shortcuts in every time step of the epidemic spread. For both dynamic and static small-world we observe suppression of the average epidemic size dependence on network size in comparison with finite-size scaling known for regular lattice. Nonetheless, qualitatively the epidemic on dynamic small world behaves in the same way as on the static one for the given range of parameters (φ = 0.5 corresponds to every node in the network having on average two additional links). We have shown that introducing dynamics of the long-range links in a smallworld network significantly lowers an epidemic threshold in terms of probability of disease transmission, although the overall dependence on number of shortcuts stays the same.

abstract:
  The aim of the study was to compare the epidemic spread on static and dynamic small-world networks. The network was constructed as a 2-dimensional Watts-Strogatz model (500x500 square lattice with additional shortcuts), and the dynamics involved rewiring shortcuts in every time step of the epidemic spread. The model of the epidemic is SIR with latency time of 3 time steps. The behaviour of the epidemic was checked over the range of shortcut probability per underlying bond 0-0.5. The quantity of interest was percolation threshold for the epidemic spread, for which numerical results were checked against an approximate analytical model. We find a significant lowering of percolation thresholds for the dynamic network in the parameter range given. The result shows that the behaviour of the epidemic on dynamic network is that of a static small world with the number of shortcuts increased by 20.7 +/- 1.4%, while the overall qualitative behaviour stays the same. We derive corrections to the analytical model which account for the effect. For both dynamic and static small-world we observe suppression of the average epidemic size dependence on network size in comparison with finite-size scaling known for regular lattice. We also study the effect of dynamics for several rewiring rates relative to latency time of the disease.


id: cord-131667-zl5txjqx
title: EPIC30M: An Epidemics Corpus Of Over 30 Million Relevant Tweets
author: Liu, Junhua
date: 2020-06-09
txt: ./txt/cord-131667-zl5txjqx.txt
cache: ./cache/cord-131667-zl5txjqx.txt
extension: .txt
mime: text/plain
url: https://arxiv.org/pdf/2006.08369v2.pdf
doi: nan
summary:
  In this paper, we present EPIC30M, a large-scale epidemic corpus that contains 30 millions micro-blog posts, i.e., tweets crawled from Twitter, from year 2006 to 2020. Furthermore, a time-series analysis also suggests that some of the epidemics, i.e. 2010 Haiti Cholera and 2018 Kivu Ebola, show a surge in tweets before the respective start dates of the outbreaks, which signifies the importance of leveraging social media to conduct early signal detection. Through the time-series line plots, we observe that some of the epidemics, i.e. 2010 Haiti Cholera and 2018 Kivu Ebola, show a surge in tweets before the respective official start dates of the outbreaks, which signifies the importance of leveraging social media to conduct early signal detection. While early detection and warning systems for crisis events may reduce overall damage and negative impacts [31] , EPIC30M provides high volume and timely information that facilitate trend analysis and pattern recognition tasks for epidemic events.

abstract:
  Since the start of COVID-19, several relevant corpora from various sources are presented in the literature that contain millions of data points. While these corpora are valuable in supporting many analyses on this specific pandemic, researchers require additional benchmark corpora that contain other epidemics to facilitate cross-epidemic pattern recognition and trend analysis tasks. During our other efforts on COVID-19 related work, we discover very little disease related corpora in the literature that are sizable and rich enough to support such cross-epidemic analysis tasks. In this paper, we present EPIC30M, a large-scale epidemic corpus that contains 30 millions micro-blog posts, i.e., tweets crawled from Twitter, from year 2006 to 2020. EPIC30M contains a subset of 26.2 millions tweets related to three general diseases, namely Ebola, Cholera and Swine Flu, and another subset of 4.7 millions tweets of six global epidemic outbreaks, including 2009 H1N1 Swine Flu, 2010 Haiti Cholera, 2012 Middle-East Respiratory Syndrome (MERS), 2013 West African Ebola, 2016 Yemen Cholera and 2018 Kivu Ebola. Furthermore, we explore and discuss the properties of the corpus with statistics of key terms and hashtags and trends analysis for each subset. Finally, we demonstrate the value and impact that EPIC30M could create through a discussion of multiple use cases of cross-epidemic research topics that attract growing interest in recent years. These use cases span multiple research areas, such as epidemiological modeling, pattern recognition, natural language understanding and economical modeling.


id: cord-204796-zy1608lw
title: Confinement strategies in a simple SIR model
author: Nakamura, G.
date: 2020-04-20
txt: ./txt/cord-204796-zy1608lw.txt
cache: ./cache/cord-204796-zy1608lw.txt
extension: .txt
mime: text/plain
url: https://arxiv.org/pdf/2004.09314v1.pdf
doi: nan
summary:
  In order for our simulations to be as realistic as possible it is important that we calibrate our model, introduce the proper time scale, choose the proper parameters and initial conditions, and, finally consider the adequate confinement strategies. Thus in Figure 11 we show the ratio of the second to the first epidemic peak, i.e. the one reached after the exit from lockdown to the one obtained during the confinement, as a function of the duration of the strict confinement, T 1 . For example, suppose that the confinement lasts 10 units of time in the model, or 50 days, (this situation corresponds to curve (c) in Figure 12 ), then any value of a 1 (the intermediate value of the infection rate of confined people) smaller than 1.8 would lead to a second peak lower than the first one.

abstract:
  We propose a simple SIR model in order to investigate the impact of various confinement strategies on a most virulent epidemic. Our approach is motivated by the current COVID-19 pandemic. The main hypothesis is the existence of two populations of susceptible persons, one which obeys confinement and for which the infection rate does not exceed 1, and a population which, being non confined for various imperatives, can be substantially more infective. The model, initially formulated as a differential system, is discretised following a specific procedure, the discrete system serving as an integrator for the differential one. Our model is calibrated so as to correspond to what is observed in the COVID-19 epidemic. Several conclusions can be reached, despite the very simple structure of our model. First, it is not possible to pinpoint the genesis of the epidemic by just analysing data from when the epidemic is in full swing. It may well turn out that the epidemic has reached a sizeable part of the world months before it became noticeable. Concerning the confinement scenarios, a universal feature of all our simulations is that relaxing the lockdown constraints leads to a rekindling of the epidemic. Thus we sought the conditions for the second epidemic peak to be lower than the first one. This is possible in all the scenarios considered (abrupt, progressive or stepwise exit) but typically a progressive exit can start earlier than an abrupt one. However, by the time the progressive exit is complete, the overall confinement times are not too different. From our results, the most promising strategy is that of a stepwise exit. And in fact its implementation could be quite feasible, with the major part of the population (minus the fragile groups) exiting simultaneously but obeying rigorous distancing constraints.


id: cord-211511-56q57zwc
title: How Epidemic Psychology Works on Social Media: Evolution of responses to the COVID-19 pandemic
author: Aiello, Luca Maria
date: 2020-07-26
txt: ./txt/cord-211511-56q57zwc.txt
cache: ./cache/cord-211511-56q57zwc.txt
extension: .txt
mime: text/plain
url: https://arxiv.org/pdf/2007.13169v1.pdf
doi: nan
summary:
  Each of them is characterized by different regimes of the three social epidemics: in the refusal phase, people refused to accept reality despite the increasing numbers of deaths in other countries; in the suspended reality phase (started after the announcement of the first death in the country), people''s fear translated into anger about the looming feeling that things were about to change; finally, in the acceptance phase (started after the authorities imposed physical-distancing measures), people found a"new normal"for their daily activities. These change-points identify three phases, which are described next by dwelling on the peaks of the different language categories (days when their standardized fractions reached the maximum) and reporting the percentage increase at peak (the increase is compared to the average over the whole period of study, and its peak is denoted by ''max peak'' in Table 1 ).

abstract:
  Disruptions resulting from an epidemic might often appear to amount to chaos but, in reality, can be understood in a systematic way through the lens of"epidemic psychology". According to the father of this research field, Philip Strong, not only is the epidemic biological; there is also the potential for three social epidemics: of fear, moralization, and action. This work is the first study to empirically test Strong's model at scale. It does so by studying the use of language on 39M social media posts in US about the COVID-19 pandemic, which is the first pandemic to spread this quickly not only on a global scale but also online. We identified three distinct phases, which parallel Kuebler-Ross's stages of grief. Each of them is characterized by different regimes of the three social epidemics: in the refusal phase, people refused to accept reality despite the increasing numbers of deaths in other countries; in the suspended reality phase (started after the announcement of the first death in the country), people's fear translated into anger about the looming feeling that things were about to change; finally, in the acceptance phase (started after the authorities imposed physical-distancing measures), people found a"new normal"for their daily activities. Our real-time operationalization of Strong's model makes it possible to embed epidemic psychology in any real-time model (e.g., epidemiological and mobility models).


id: cord-211611-c9w6235b
author: Cacciapaglia, Giacomo
date: 2020-05-11
txt: ./txt/cord-211611-c9w6235b.txt
cache: ./cache/cord-211611-c9w6235b.txt
extension: .txt
mime: text/plain
url: https://arxiv.org/pdf/2005.04956v1.pdf
doi: nan
summary:
  We demonstrate that the epidemic renormalisation group approach to pandemics provides an effective and simple way to investigate the dynamics of disease transmission and spreading across different regions of the world. Our epidemic renormalisation group (eRG) approach is based * g.cacciapaglia@ipnl.in2p3.fr † sannino@cp3.sdu.dk upon a simpler set of equations, which can be extended in a straightforward way to include interactions between multiple regions of the world, without the need for powerful numerical simulations. Thus, the dictionary between the eRG equation for the epidemic strength α and the high-energy physics analog is It has been shown in [3] that α captures the essential information about the infected population within a sufficiently isolated region of the world. To quantitatively estimate the interaction between two regions of the world, we consider benchmark values for the parameters in the two beta functions using the results given in [3] .

title:
  Interplay of social distancing and border restrictions for pandemics (COVID-19) via the epidemic Renormalisation Group framework

abstract:
  We demonstrate that the epidemic renormalisation group approach to pandemics provides an effective and simple way to investigate the dynamics of disease transmission and spreading across different regions of the world. The framework also allows for reliable projections on the impact of travel limitations and social distancing measures on global epidemic spread. We test and calibrate it on reported cases while unveiling the mechanism that governs the delay in the relative peaks of newly infected cases among different regions of the globe. We discover that social distancing measures are more effective than travel limitations across borders in delaying the epidemic peak. We further provide the link to compartmental models such as the simplistic and time-honoured SIR-like models. We also show how to generalise the framework to account for the interactions across several regions of the world, replacing or complementing large scale simulations.


id: cord-220618-segffkbn
title: Geometric characterization of SARS-CoV-2 pandemic events
author: Bonamassa, Ivan
date: 2020-07-20
txt: ./txt/cord-220618-segffkbn.txt
cache: ./cache/cord-220618-segffkbn.txt
extension: .txt
mime: text/plain
url: https://arxiv.org/pdf/2007.10450v1.pdf
doi: nan
summary:
  Disposing of a robust and comprehensive framework to classify the SARS-CoV-2 pandemic events reported across different countries not only can enhance early [19, 20] public and governmental responses in containing the spreading and/or better absorbing the impact of a rapidly emerging epidemic outbreak, but it can further provide new information to better understand real-world epidemics and to boost the forecasting power of existing models [21] [22] [23] [24] [25] [26] [27] [28] [29] . Moving to a polar representation, we classify the plumes'' form through a set of three geometric parameters yielding two complementary rating scales for the SARS-CoV-2 pandemic types: one according to their epidemic magnitude-labeled with roman numbers from I to X for increasing strengths-and measuring the "size" of a national outbreak, and a second one according to their intensity-labeled alphabetically from A to D for increasing speed-quantifying instead the damage inflicted on the population.

abstract:
  While the SARS-CoV-2 keeps spreading world-wide, comparing its evolution across different nations is a timely challenge of both theoretical and practical importance. The large variety of dissimilar and country-dependent epidemiological factors, in fact, makes extremely difficult to understand their influence on the epidemic trends within a unique and coherent framework. We present a geometric framework to characterize, in an integrated and low-dimensional fashion, the epidemic plume-like trajectories traced by the infection rate, $I$, and the fatality rate, $D$, in the $(I,D)$ plane. Our analysis enables the definition of an epidemiometric system based on three geometric observables rating the SARS-CoV-2 pandemic events via scales analogous to those for the magnitude and the intensity of seismic events. Being exquisitely geometric, our framework can be applied to classify other epidemic data and secondary waves, raising the possibility of designing epidemic alerts or early warning systems to enhance public and governmental responses to a rapidly emerging outbreak.


id: cord-222193-0b4o0ccp
title: A simple statistical physics model for the epidemic with incubation period
author: Saakian, David B.
date: 2020-04-13
txt: ./txt/cord-222193-0b4o0ccp.txt
cache: ./cache/cord-222193-0b4o0ccp.txt
extension: .txt
mime: text/plain
url: https://arxiv.org/pdf/2004.05778v1.pdf
doi: nan
summary:
  Based on the classical SIR model, we derive a simple modification for the dynamics of epidemics with a known incubation period of infection. We use the proposed model to analyze COVID-19 epidemic data in Armenia. Moreover, it is crucial to consider the final incubation period of the disease to construct a correct model for the COVID-19 case. In this study, we derive a system of integro-differential equations based on the rigorous master equation that adequately describes infection dynamics with an incubation period, e.g., COVID-19. In fact, the real data allows us to measure three main parameters: the exponential growth coefficient at the beginning of the epidemic; the minimum period of time, in which an infected person can transmit the infection; and the maximum period, when an infected person ceases to transmit the infection. In this paper, we introduced a version of SIR model for infection spreading with known incubation period. This model was applied to analyze the COVID-19 epidemic data in Armenia.

abstract:
  Based on the classical SIR model, we derive a simple modification for the dynamics of epidemics with a known incubation period of infection. The model is described by a system of integro-differential equations. Parameters of our model directly related to epidemiological data. We derive some analytical results, as well as perform numerical simulations. We use the proposed model to analyze COVID-19 epidemic data in Armenia. We propose a strategy: organize a quarantine, and then conduct extensive testing of risk groups during the quarantine, evaluating the percentage of the population among risk groups and people with symptoms.


id: cord-234552-0pbg0ldm
author: Hota, Ashish R.
date: 2020-07-26
txt: ./txt/cord-234552-0pbg0ldm.txt
cache: ./cache/cord-234552-0pbg0ldm.txt
extension: .txt
mime: text/plain
url: https://arxiv.org/pdf/2008.00826v1.pdf
doi: nan
summary:
  Specifically, [1] defines the discrete-time activity-driven adaptive-SIS model bound on the decay ratio of the infection probabilities of the nodes and proposes tractable optimization problems for optimal containment of the epidemic by minimizing the bound on the decay ratio. In this paper, we propose a new activity-driven and adaptive generalized SIS epidemic model, referred to as the A-SIYS epidemic, where we treat asymptomatic and symptomatic individuals as distinct infection states (see Section II for a formal definition and discussion). As a second contribution, we highlight a potential inaccuracy in the derivation of the upper bound on the decay ratio of the A-SIS epidemic model in [1] and obtain a counterpart of their result for a more general setting where nodes choose different numbers of other nodes to connect to (Section III). With the above definition in place, we now formally define the activity-driven and state-dependent evolution of the network or contact pattern and the epidemic states of individual nodes.

title:
  A Generalized SIS Epidemic Model on Temporal Networks with Asymptomatic Carriers and Comments on Decay Ratio

abstract:
  We study the class of SIS epidemics on temporal networks and propose a new activity-driven and adaptive epidemic model that captures the impact of asymptomatic and infectious individuals in the network. In the proposed model, referred to as the A-SIYS epidemic, each node can be in three possible states: susceptible, infected without symptoms or asymptomatic and infected with symptoms or symptomatic. Both asymptomatic and symptomatic individuals are infectious. We show that the proposed A-SIYS epidemic captures several well-established epidemic models as special cases and obtain sufficient conditions under which the disease gets eradicated by resorting to mean-field approximations. In addition, we highlight a potential inaccuracy in the derivation of the upper bound on the decay ratio in the activity-driven adaptive SIS (A-SIS) model in (Ogura et. al., 2019) and present a more general version of their result. We numerically illustrate the evolution of the fraction of infected nodes in the A-SIS epidemic model and show that the bound in (Ogura et. al., 2019) often fails to capture the behavior of the epidemic in contrast with our results.


id: cord-238342-ecuex64m
author: Fong, Simon James
date: 2020-03-22
txt: ./txt/cord-238342-ecuex64m.txt
cache: ./cache/cord-238342-ecuex64m.txt
extension: .txt
mime: text/plain
url: https://arxiv.org/pdf/2003.09868v1.pdf
doi: nan
summary:
  Composite Monte-Carlo (CMC) simulation is a forecasting method which extrapolates available data which are broken down from multiple correlated/casual micro-data sources into many possible future outcomes by drawing random samples from some probability distributions. Section 2 describes the proposed methodology called GROOMS+CMCM, followed by introduction of two key soft computing algorithms -BFGS-PNN and FRI which is adopted for forecasting some particular future trends as inputs to the MC model and generating fuzzy decision rules respectively. Being able to work with limited data, flexible in simulating input variables (hybrid deterministic and its counterpart), and informative outcomes coupled with fuzzy rules and risks, would be useful for experts making sound decision at the critical time.

title:
  Composite Monte Carlo Decision Making under High Uncertainty of Novel Coronavirus Epidemic Using Hybridized Deep Learning and Fuzzy Rule Induction

abstract:
  In the advent of the novel coronavirus epidemic since December 2019, governments and authorities have been struggling to make critical decisions under high uncertainty at their best efforts. Composite Monte-Carlo (CMC) simulation is a forecasting method which extrapolates available data which are broken down from multiple correlated/casual micro-data sources into many possible future outcomes by drawing random samples from some probability distributions. For instance, the overall trend and propagation of the infested cases in China are influenced by the temporal-spatial data of the nearby cities around the Wuhan city (where the virus is originated from), in terms of the population density, travel mobility, medical resources such as hospital beds and the timeliness of quarantine control in each city etc. Hence a CMC is reliable only up to the closeness of the underlying statistical distribution of a CMC, that is supposed to represent the behaviour of the future events, and the correctness of the composite data relationships. In this paper, a case study of using CMC that is enhanced by deep learning network and fuzzy rule induction for gaining better stochastic insights about the epidemic development is experimented. Instead of applying simplistic and uniform assumptions for a MC which is a common practice, a deep learning-based CMC is used in conjunction of fuzzy rule induction techniques. As a result, decision makers are benefited from a better fitted MC outputs complemented by min-max rules that foretell about the extreme ranges of future possibilities with respect to the epidemic.


id: cord-251581-8ubyveyt
title: In-store epidemic behavior: scale development and validation
author: Szymkowiak, Andrzej
date: 2020-05-04
url: https://arxiv.org/pdf/2005.02764v1.pdf
doi: nan
abstract:
  Epidemics of infectious diseases have accompanied humans for a long time and, depending on the scale, cause various undesirable social and economic consequences. During the ongoing COVID-19 pandemic, governments of many countries impose restrictions to inhibit spreading of infection. Isolation and limiting interpersonal contacts are particularly recommended actions. Adhering to the rule of isolation may involve restrictions in freedom during daily activities, such as shopping. The aim of the study was to develop a scale of in-store pandemic behavior. The whole process involved 3 stages: qualitative inquiry, scale purification and scale validation, which were based on 3 studies: 1 qualitative (20 in-depth interviews) 2 two quantitative (373 and 584 respondents, respectively), and allowed to identify 8 factors. Following, a theoretical model was created to investigate the impact of in-store infection threat on identified variables. All identified factors significantly correlated with the in-store infection threat which reiterates the importance of providing information revealing the true scale of the pandemic and not leaving space for individuals to create subjective probability judgments. The developed scale can help counteract disinformation and assess consumer behavior compliance and understanding of the official recommendations imposed by governments, enabling more efficient educational efforts.


id: cord-266898-f00628z4
author: Nikitenkova, S.
date: 2020-06-03
txt: ./txt/cord-266898-f00628z4.txt
cache: ./cache/cord-266898-f00628z4.txt
extension: .txt
mime: text/plain
url: http://medrxiv.org/cgi/content/short/2020.06.01.20118869v1?rss=1
doi: 10.1101/2020.06.01.20118869
summary:
  Processing statistical data of countries that have reached an epidemic peak has shown that this regular monitoring obeys a simple analytical regularity which allows us to answer the question: is this or that country that has already passed the threshold of the epidemic close to its peak or is still far from it? To achieve this goal, it is necessary to identify, evaluate and study the mentioned regular component of the error, using the statistics of those countries that have already reached a peak -the stationary level of the epidemic dynamics. This regular error component explains the reason for the failure of a priori mathematical modelling of probable epidemic events in different countries of the world. Processing statistical data of countries that have reached an epidemic peak has shown that this regular monitoring obeys a simple analytical regularity.

title:
  It''s the very time to learn a pandemic lesson: why have predictive techniques been ineffective when describing long-term events?

abstract:
  We have detected a regular component of the monitoring error of officially registered total cases of the spread of the current pandemic. This regular error component explains the reason for the failure of a priori mathematical modelling of probable epidemic events in different countries of the world. Processing statistical data of countries that have reached an epidemic peak has shown that this regular monitoring obeys a simple analytical regularity which allows us to answer the question: is this or that country that has already passed the threshold of the epidemic close to its peak or is still far from it?


id: cord-267030-khzivbzy
title: Understanding the Epidemic Course in Order to Improve Epidemic Forecasting
author: Jia, Peng
date: 2020-10-01
txt: ./txt/cord-267030-khzivbzy.txt
cache: ./cache/cord-267030-khzivbzy.txt
extension: .txt
mime: text/plain
url: https://doi.org/10.1029/2020gh000303
doi: 10.1029/2020gh000303
summary:
  Spatial lifecourse epidemiology provides a new perspective to understand the course of epidemics, especially pandemics, and a new toolkit to predict the course of future epidemics on the basis of big data. The advanced spatial and digital technologies provide a new perspective to understand the transmission patterns of epidemics, especially pandemics, and a new toolkit to predict the progression of future epidemics on the basis of big data. Transparent, anonymous reporting of travel and contact history of a relatively large number of COVID-19 cases has been realized in China for the first time in the history of pandemics, thus opening a new avenue in the era of big data for more advanced, transdisciplinary approaches to refine results from mathematical prediction models and achieve a data-driven epidemic course of the COVID-19 in China (Kummitha, 2020) .

abstract:
  The epidemic course of the severe acute respiratory syndrome (SARS) has been differently divided according to its transmission pattern and the infection and mortality status. Unfortunately, such efforts for the coronavirus disease 2019 (COVID‐19) have been lacking. Does every epidemic have a unique epidemic course? Can we coordinate two arbitrary courses into an integrated course, which could better reflect a common real‐world progression pattern of the epidemics? To what degree can such arbitrary divisions help predict future trends of the COVID‐19 pandemic and future epidemics? Spatial lifecourse epidemiology provides a new perspective to understand the course of epidemics, especially pandemics, and a new toolkit to predict the course of future epidemics on the basis of big data. In the present data‐driven era, data should be integrated to inform us how the epidemic is transmitting at the present moment, how it will transmit at the next moment, and which interventions would be most cost‐effective to curb the epidemic. Both national and international legislations are needed to facilitate the integration of relevant policies of data sharing and confidentiality protection into the current pandemic preparedness guidelines.


id: cord-270679-heg1h19l
title: Perception-based influence factors of intention to adopt COVID-19 epidemic prevention in China
author: Ahmad, Munir
date: 2020-07-27
txt: ./txt/cord-270679-heg1h19l.txt
cache: ./cache/cord-270679-heg1h19l.txt
extension: .txt
mime: text/plain
url: https://doi.org/10.1016/j.envres.2020.109995
doi: 10.1016/j.envres.2020.109995
summary:
  title: Perception-based influence factors of intention to adopt COVID-19 epidemic prevention in China OBJECTIVE: This work has attempted to examine the perception-based influence factors of individuals'' intention to adopt COVID-19 epidemic prevention in a modified behavioral framework. Therefore, there is a clear scope of identifying perception-based influence factors (PIFs) of individuals'' intention to adopt epidemic prevention (IAEP) during the outbreak of the COVID-19 epidemic. To sum up, first, governments'' guidelines on epidemic prevention, risk perception, epidemic knowledge, risk aversion, perceived behavioral control, subjective norms, and attitude towards epidemic prevention are suspected to be the drivers of individuals'' IAEP. A modified behavioral framework depicting the influence factors of individuals'' intention to adopt epidemic prevention. The core focus of this work was to examine the perception-based factors influencing the individuals'' intention to adopt COVID-19 epidemic prevention in a modified behavioral framework in terms of estimating the relevance as well as the relative importance of those factors.

abstract:
  BACKGROUND: The researches investigating the influence factors of epidemic prevention are not only scarce, but also provide a gap in the domain of perception-based influence factors of intention to adopt COVID-19 epidemic prevention. OBJECTIVE: This work has attempted to examine the perception-based influence factors of individuals’ intention to adopt COVID-19 epidemic prevention in a modified behavioral framework. THEORETICAL FRAMEWORK: A behavioral framework composed of the theory of reasoned action and the theory of planned behavior is developed to incorporate some additional perception-based influence factors. METHODS: A partial least square-based path analysis has been employed to estimate the path coefficients of those factors in terms of drivers, barriers, and neutral factors based on questionnaire data of 302 respondents from six universities and two hospitals in China. RESULTS: Among the perception-based influence factors, governments’ guidelines on epidemic prevention is found to be the most important and influential factor, which was followed by risk perception. Finally, attitude towards epidemic prevention exhibited the least degree of impact on individuals’ intention to adopt epidemic prevention. Moral norms did not show any contribution to individuals’ intention to adopt epidemic prevention. CONCLUSION: Concerning importance ranking, the governments’ guidelines on epidemic prevention, risk perception, and epidemic knowledge are revealed as the top three drivers of individuals’ intention to adopt epidemic prevention, while the perceived feasibility to adopt epidemic prevention is found to be a barrier. Moreover, moral norms is identified to have an insignificant influence on individuals’ intention to adopt epidemic prevention. Given the empirical results, dissemination of Governments’ guidelines on epidemic prevention, proper risk perception, and knowledge about epidemic would help prevent the COVID-19 pandemic outbreak within China and worldwide.


id: cord-272031-o2hx667i
title: Porcine epidemic diarrhoea: new insights into an old disease
author: Carvajal, Ana
date: 2015-09-29
txt: ./txt/cord-272031-o2hx667i.txt
cache: ./cache/cord-272031-o2hx667i.txt
extension: .txt
mime: text/plain
url: https://doi.org/10.1186/s40813-015-0007-9
doi: 10.1186/s40813-015-0007-9
summary:
  Mortality in piglets less than two weeks old varied from 0 to 100 %, but it was usually lower than that described in outbreaks of diarrhoea caused by transmissible gastroenteritis virus (TGEV) which is another porcine coronavirus classically recognized as a cause of diarrhoea disease in swine. Although some reports have suggested that they could be associated with differences in the virulence of PEDV isolates, exhaustive challenge studies using pig adapted virus (not cell culture adapted isolates) in suckling piglets are needed to elucidate the role of the strain. The detection of PEDV specific antibodies is very useful, not for the investigation of diarrhoea outbreaks, but to determine whether an animal or a herd has previously been infected by this virus. Genetic characterization of porcine epidemic diarrhoea virus (PEDV) isolates from southern Vietnam during 2009-2010 outbreaks

abstract:
  Porcine epidemic diarrhea (PED) is an enteric disease in swine caused by an alphacoronavirus. It affects swine of all ages causing acute diarrhoea and can lead to severe dehydration and death in suckling piglets. Being recognized for the first time in Europe and Asia during the seventies and the eighties, respectively, it has remained a relevant cause of diarrhea outbreaks in Asia for years and to the present. It has become a major concern in swine production since 2013 when the virus was detected for first time in the USA and in other American countries causing a high number of pig deaths and significant economic losses. The present review aims at approaching the reader to the state of the art of PED giving answer to some of the most recent questions which have arisen related to this disease.


id: cord-272744-j4q7pcfa
title: Coupling dynamics of epidemic spreading and information diffusion on complex networks
author: Zhan, Xiu-Xiu
date: 2018-09-01
txt: ./txt/cord-272744-j4q7pcfa.txt
cache: ./cache/cord-272744-j4q7pcfa.txt
extension: .txt
mime: text/plain
url: https://api.elsevier.com/content/article/pii/S0096300318302236
doi: 10.1016/j.amc.2018.03.050
summary:
  Generally, epidemic spreading is considered to be a dynamic process in which the disease is transmitted from one individual to another via physical contact in peer-to-peer networks. Therefore, the effect of behavioral changes arises in three aspects [27] : (i) disease state of the individuals, e.g., vaccination [38] [39] [40] [41] [42] ; (ii) epidemic transmission and recovery rate [35, 43] ; (iii) topological structure of contact network, e.g., the adaptive process [44] [45] [46] [47] . Considering the two small peaks of information in Fig. 1 (b1) and (b2), we can also find the same relationship between the the two dynamic processes as that of two largest peaks, suggesting also the possible coupling effect of the awareness of epidemics and the infected cases of dengue. Inspired by the empirical results, we propose a network based nonlinear model to describe the interaction between epidemic spreading and information diffusion in this section.

abstract:
  The interaction between disease and disease information on complex networks has facilitated an interdisciplinary research area. When a disease begins to spread in the population, the corresponding information would also be transmitted among individuals, which in turn influence the spreading pattern of the disease. In this paper, firstly, we analyze the propagation of two representative diseases (H7N9 and Dengue fever) in the real-world population and their corresponding information on Internet, suggesting the high correlation of the two-type dynamical processes. Secondly, inspired by empirical analyses, we propose a nonlinear model to further interpret the coupling effect based on the SIS (Susceptible-Infected-Susceptible) model. Both simulation results and theoretical analysis show that a high prevalence of epidemic will lead to a slow information decay, consequently resulting in a high infected level, which shall in turn prevent the epidemic spreading. Finally, further theoretical analysis demonstrates that a multi-outbreak phenomenon emerges via the effect of coupling dynamics, which finds good agreement with empirical results. This work may shed light on the in-depth understanding of the interplay between the dynamics of epidemic spreading and information diffusion.


id: cord-281437-cb3u1s7s
title: A new twenty-first century science for effective epidemic response
author: Bedford, Juliet
date: 2019-11-06
txt: ./txt/cord-281437-cb3u1s7s.txt
cache: ./cache/cord-281437-cb3u1s7s.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pubmed/31695207/
doi: 10.1038/s41586-019-1717-y
summary:
  The science of epidemiology has described patterns of disease in human populations, investigated the causes of those diseases, evaluated attempts to control them 7 and has been the foundation for public health responses to epidemic infections for over 100 years. The vulnerability of populations to outbreaks of zoonotic diseases such as Ebola, Middle East respiratory syndrome (MERS) and Nipah has increased, the rise and spread of drug-resistant infections, marked shifts in the ecology of known vectors (for example, the expanding range of Aedes mosquitoes) and massive amplification of transmission through globally connected, high-density urban areas (particularly relevant to Ebola, dengue, influenza and severe acute respiratory syndrome-related coronavirus SARS-CoV). Preparing for epidemics, therefore, requires global health, economic and political systems to be integrated just as much as infectious disease epidemiology, translational research and development, and community engagement.

abstract:
  With rapidly changing ecology, urbanization, climate change, increased travel and fragile public health systems, epidemics will become more frequent, more complex and harder to prevent and contain. Here we argue that our concept of epidemics must evolve from crisis response during discrete outbreaks to an integrated cycle of preparation, response and recovery. This is an opportunity to combine knowledge and skills from all over the world—especially at-risk and affected communities. Many disciplines need to be integrated, including not only epidemiology but also social sciences, research and development, diplomacy, logistics and crisis management. This requires a new approach to training tomorrow’s leaders in epidemic prevention and response.


id: cord-283485-xit6najq
title: The COVID-19 pandemic: diverse contexts; different epidemics—how and why?
author: Van Damme, Wim
date: 2020-07-27
url: https://doi.org/10.1136/bmjgh-2020-003098
doi: 10.1136/bmjgh-2020-003098
abstract:
  It is very exceptional that a new disease becomes a true pandemic. Since its emergence in Wuhan, China, in late 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes COVID-19, has spread to nearly all countries of the world in only a few months. However, in different countries, the COVID-19 epidemic takes variable shapes and forms in how it affects communities. Until now, the insights gained on COVID-19 have been largely dominated by the COVID-19 epidemics and the lockdowns in China, Europe and the USA. But this variety of global trajectories is little described, analysed or understood. In only a few months, an enormous amount of scientific evidence on SARS-CoV-2 and COVID-19 has been uncovered (knowns). But important knowledge gaps remain (unknowns). Learning from the variety of ways the COVID-19 epidemic is unfolding across the globe can potentially contribute to solving the COVID-19 puzzle. This paper tries to make sense of this variability—by exploring the important role that context plays in these different COVID-19 epidemics; by comparing COVID-19 epidemics with other respiratory diseases, including other coronaviruses that circulate continuously; and by highlighting the critical unknowns and uncertainties that remain. These unknowns and uncertainties require a deeper understanding of the variable trajectories of COVID-19. Unravelling them will be important for discerning potential future scenarios, such as the first wave in virgin territories still untouched by COVID-19 and for future waves elsewhere.


id: cord-283793-ab1msb2m
title: Modeling and analysis of epidemic spreading on community network with node's birth and death
author: Chanchan, Li
date: 2016-10-31
url: https://api.elsevier.com/content/article/pii/S1005888516600614
doi: 10.1016/s1005-8885(16)60061-4
abstract:
  Abstract In this paper, a modified susceptible infected susceptible (SIS) epidemic model is proposed on community structure networks considering birth and death of node. For the existence of node's death would change the topology of global network, the characteristic of network with death rate is discussed. Then we study the epidemiology behavior based on the mean-field theory and derive the relationships between epidemic threshold and other parameters, such as modularity coefficient, birth rate and death rates (caused by disease or other reasons). In addition, the stability of endemic equilibrium is analyzed. Theoretical analysis and simulations show that the epidemic threshold increases with the increase of two kinds of death rates, while it decreases with the increase of the modularity coefficient and network size.


id: cord-284220-55mckelv
author: batista, m.
date: 2020-09-02
txt: ./txt/cord-284220-55mckelv.txt
cache: ./cache/cord-284220-55mckelv.txt
extension: .txt
mime: text/plain
url: https://doi.org/10.1101/2020.08.31.20185165
doi: 10.1101/2020.08.31.20185165
summary:
  title: Estimation of a state of Corona 19 epidemic in August 2020 by multistage logistic model: a case of EU, USA, and World The article provides an estimate of the size and duration of the Covid-19 epidemic in August 2020 for the European Union (EU), the United States (US), and the World using a multistage logistical epidemiological model. The second is that at the beginning of the outbreak or at a new wave, the parameters of the models are not known (Keeling & Rohani, 2008) , or better they depend on the course of the epidemic. In the graph in Figure 4 , we can see that the trend in predicting the size of the epidemic and its duration was linear, then began to rise sharply at the end of June and reached its peak in mid-June with an estimate of 10 million final infections.

title:
  Estimation of a state of Corona 19 epidemic in August 2020 by multistage logistic model: a case of EU, USA, and World

abstract:
  The article provides an estimate of the size and duration of the Covid-19 epidemic in August 2020 for the European Union (EU), the United States (US), and the World using a multistage logistical epidemiological model.


id: cord-288342-i37v602u
title: Coupled disease–behavior dynamics on complex networks: A review
author: Wang, Zhen
date: 2015-07-08
txt: ./txt/cord-288342-i37v602u.txt
cache: ./cache/cord-288342-i37v602u.txt
extension: .txt
mime: text/plain
url: https://www.sciencedirect.com/science/article/pii/S1571064515001372
doi: 10.1016/j.plrev.2015.07.006
summary:
  Incorporating adaptive behavior into a model of disease spread can provide important insight into population health outcomes, as the activation of social distancing and other nonpharmaceutical interventions (NPIs) have been observed to have the ability to alter the course of an epidemic [50] [51] [52] . The authors studied their coupled "disease-behavior" model in well-mixed populations, in square lattice populations, in random network populations, and in SF network populations, and found that population structure acts as a "double-edged sword" for public health: it can promote high levels of voluntary vaccination and herd immunity given that the cost for vaccination is not too large, but small increases in the cost beyond a certain threshold would cause vaccination to plummet, and infections to rise, more dramatically than in well-mixed populations. The first mathematical models studied the adaptive dynamics of disease-behavior responses in the homogeneously mixed population, assuming that individuals interact with each other at the same contact rate, without restrictions on selecting potential partners.

abstract:
  It is increasingly recognized that a key component of successful infection control efforts is understanding the complex, two-way interaction between disease dynamics and human behavioral and social dynamics. Human behavior such as contact precautions and social distancing clearly influence disease prevalence, but disease prevalence can in turn alter human behavior, forming a coupled, nonlinear system. Moreover, in many cases, the spatial structure of the population cannot be ignored, such that social and behavioral processes and/or transmission of infection must be represented with complex networks. Research on studying coupled disease–behavior dynamics in complex networks in particular is growing rapidly, and frequently makes use of analysis methods and concepts from statistical physics. Here, we review some of the growing literature in this area. We contrast network-based approaches to homogeneous-mixing approaches, point out how their predictions differ, and describe the rich and often surprising behavior of disease–behavior dynamics on complex networks, and compare them to processes in statistical physics. We discuss how these models can capture the dynamics that characterize many real-world scenarios, thereby suggesting ways that policy makers can better design effective prevention strategies. We also describe the growing sources of digital data that are facilitating research in this area. Finally, we suggest pitfalls which might be faced by researchers in the field, and we suggest several ways in which the field could move forward in the coming years.


id: cord-289003-vov6o1jx
author: Burdet, C.
date: 2018-02-28
url: https://doi.org/10.1016/j.respe.2017.08.001
doi: 10.1016/j.respe.2017.08.001
title:
  Need for integrative thinking to fight against emerging infectious diseases. Proceedings of the 5th seminar on emerging infectious diseases, March 22, 2016 – current trends and proposals

abstract:
  Abstract We present here the proceedings of the 5th seminar on emerging infectious diseases, held in Paris on March 22nd, 2016, with seven priority proposals that can be outlined as follows: encourage research on the prediction, screening and early detection of new risks of infection; develop research and surveillance concerning transmission of pathogens between animals and humans, with their reinforcement in particular in intertropical areas (“hot-spots”) via public support; pursue aid development and support in these areas of prevention and training for local health personnel, and foster risk awareness in the population; ensure adapted patient care in order to promote adherence to treatment and to epidemic propagation reduction measures; develop greater awareness and better education among politicians and healthcare providers, in order to ensure more adapted response to new types of crises; modify the logic of governance, drawing from all available modes of communication and incorporating new information-sharing tools; develop economic research on the fight against emerging infectious diseases, taking into account specific driving factors in order to create a balance between preventive and curative approaches.


id: cord-292026-cj43pn0f
title: Approaches to Daily Monitoring of the SARS-CoV-2 Outbreak in Northern Italy
author: Moirano, Giovenale
date: 2020-05-22
txt: ./txt/cord-292026-cj43pn0f.txt
cache: ./cache/cord-292026-cj43pn0f.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pubmed/32574301/
doi: 10.3389/fpubh.2020.00222
summary:
  We (i) estimated the time-varying reproduction number (R(t)), the average number of secondary cases that each infected individual would infect at time t, to monitor the positive impact of restriction measures; (ii) applied the generalized logistic and the modified Richards models to describe the epidemic pattern and obtain short-term forecasts. Both models were fitted to data in order to characterize the pattern of the epidemic in its early phases, produce 5 days forecast of the number of new infections, and estimate the peak time and the final size of the epidemic curve. Estimated time trends and 5-day forecasts for daily COVID-19 deaths should theoretically follow, by ∼1-15 days, the trends of new cases, and are thus less informative for decision making, but are possibly less affected by testing and reporting variations (Figure 4 , results from the GLM model only).

abstract:
  Italy was the first European country affected by the Sars-Cov-2 pandemic, with the first autochthonous case identified on Feb 21st. Specific control measures restricting social contacts were introduced by the Italian government starting from the beginning of March. In the current study we analyzed public data from the four most affected Italian regions. We (i) estimated the time-varying reproduction number (R(t)), the average number of secondary cases that each infected individual would infect at time t, to monitor the positive impact of restriction measures; (ii) applied the generalized logistic and the modified Richards models to describe the epidemic pattern and obtain short-term forecasts. We observed a monotonic decrease of R(t) over time in all regions, and the peak of incident cases ~2 weeks after the implementation of the first strict containment measures. Our results show that phenomenological approaches may be useful to monitor the epidemic growth in its initial phases and suggest that costly and disruptive public health controls might have had a positive impact in limiting the Sars-Cov-2 spread in Northern Italy.


id: cord-295534-bwa4wz94
author: Jung, Kwonil
date: 2015-02-26
txt: ./txt/cord-295534-bwa4wz94.txt
cache: ./cache/cord-295534-bwa4wz94.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pubmed/25841898/
doi: 10.1016/j.tvjl.2015.02.017
summary:
  Porcine epidemic diarrhea virus (PEDV), a member of the genera Alphacoronavirus in the family Coronaviridae, causes acute diarrhea/vomiting, dehydration and high mortality in seronegative neonatal piglets. Porcine epidemic diarrhea virus (PEDV), a member of the genera Alphacoronavirus in the family Coronaviridae of the order Nidovirales, causes acute diarrhea, vomiting, dehydration and high mortality in neonatal piglets, resulting in significant economic losses. A recent study confirmed that PDCoV is enteropathogenic in pigs and acutely infects the small intestine, causing severe diarrhea and/or vomiting and atrophic enteritis, similar to the clinical signs of PEDV and TGEV infections (Jung et al., 2015) . Decreased activity of brush border membrane-bound digestive enzymes in small intestines from pigs experimentally infected with porcine epidemic diarrhea virus Isolation of porcine epidemic diarrhea virus in porcine cell cultures and experimental infection of pigs of different ages

title:
  Porcine epidemic diarrhea virus infection: Etiology, epidemiology, pathogenesis and immunoprophylaxis

abstract:
  Porcine epidemic diarrhea virus (PEDV), a member of the genera Alphacoronavirus in the family Coronaviridae, causes acute diarrhea/vomiting, dehydration and high mortality in seronegative neonatal piglets. For the last three decades, PEDV infection has resulted in significant economic losses in the European and Asian pig industries, but in 2013–2014 the disease was also reported in the US, Canada and Mexico. The PED epidemic in the US, from April 2013 to the present, has led to the loss of more than 10% of the US pig population. The disappearance and re-emergence of epidemic PED indicates that the virus is able to escape from current vaccination protocols, biosecurity and control systems. Endemic PED is a significant problem, which is exacerbated by the emergence (or potential importation) of multiple PEDV variants. Epidemic PEDV strains spread rapidly and cause a high number of pig deaths. These strains are highly enteropathogenic and acutely infect villous epithelial cells of the entire small and large intestines although the jejunum and ileum are the primary sites. PEDV infections cause acute, severe atrophic enteritis accompanied by viremia that leads to profound diarrhea and vomiting, followed by extensive dehydration, which is the major cause of death in nursing piglets. A comprehensive understanding of the pathogenic characteristics of epidemic or endemic PEDV strains is needed to prevent and control the disease in affected regions and to develop an effective vaccine. This review focuses on the etiology, epidemiology, disease mechanisms and pathogenesis as well as immunoprophylaxis against PEDV infection.


id: cord-298872-gbi74g0n
title: Estimating the epidemic growth dynamics within the first week
author: FIORITI, V.
date: 2020-08-16
txt: ./txt/cord-298872-gbi74g0n.txt
cache: ./cache/cord-298872-gbi74g0n.txt
extension: .txt
mime: text/plain
url: https://doi.org/10.1101/2020.08.14.20170878
doi: 10.1101/2020.08.14.20170878
summary:
  It is only necessary to collect the cumulative data of the daily infected over a week in some of the most important cities involved in the outbreak, to form a unique sequence of these numbers and then to calculate the first digit distribution. The main idea is to estimate an approximating function for the epidemic growth curve within a time horizon of Tf days, using only the first seven epidemic data points of fifty Italian cities, accounting for about the 30% of the population, considered as a unique sequence formed of 50x7 data-points, called 50_cities sequence. To classify various possible approximant curves we have calculated their Benford gof, showed in the Table 1 , together with the gof of the real Italian epidemic data, the logistic curve, of the cubic curve and of the 50_cities.

abstract:
  Information about the early growth of infectious outbreaks are indispensable to estimate the epidemic spreading. A large number of mathematical tools have been developed to this end, facing as much large number of different dynamic evolutions, ranging from sub-linear to super-exponential growth. Of course, the crucial point is that we do not have enough data during the initial outbreak phase to make reliable inferences. Here we propose a methodology to estimate the epidemic growth dynamics from the infected cumulative data of just a week, provided a surveillance system is available over the whole territory. The methodology, based on the Newcomb-Benford Law, is applied to Italian covid 19 case-study. Results show that it is possible to discriminate the epidemic dynamics using the first seven data points collected over fifty Italian cities. Moreover, the form of the most probable approximating function of the growth, within a six weeks epidemic scenario, is identified.


id: cord-299846-yx18oyv6
title: Pandæsim: An Epidemic Spreading Stochastic Simulator
author: Amar, Patrick
date: 2020-09-18
url: https://www.ncbi.nlm.nih.gov/pubmed/32962157/
doi: 10.3390/biology9090299
abstract:
  SIMPLE SUMMARY: In order to study the efficiency of countermeasures used against the Covid-19 pandemic at the scale of a country, we designed a model and developed an efficient simulation program based on a well known discrete stochastic simulation framework along with a standard, coarse grain, spatial localisation extension. Our particular approach allows us also to implement deterministic continuous resolutions of the same model. We applied it to the Covid-19 epidemic in France where lockdown countermeasures were used. With the stochastic discrete method, we found good correlations between the simulation results and the statistics gathered from hospitals. In contrast, the deterministic continuous approach lead to very different results. We proposed an explanation based on the fact that the effects of discretisation are high for small values, but low for large values. When we add stochasticity, it can explain the differences in behaviour of those two approaches. This system is one more tool to study different countermeasures to epidemics, from lockdowns to social distancing, and also the effects of mass vaccination. It could be improved by including the possibility of individual reinfection. ABSTRACT: Many methods have been used to model epidemic spreading. They include ordinary differential equation systems for globally homogeneous environments and partial differential equation systems to take into account spatial localisation and inhomogeneity. Stochastic differential equations systems have been used to model the inherent stochasticity of epidemic spreading processes. In our case study, we wanted to model the numbers of individuals in different states of the disease, and their locations in the country. Among the many existing methods we used our own variant of the well known Gillespie stochastic algorithm, along with the sub-volumes method to take into account the spatial localisation. Our algorithm allows us to easily switch from stochastic discrete simulation to continuous deterministic resolution using mean values. We applied our approaches on the study of the Covid-19 epidemic in France. The stochastic discrete version of Pandæsim showed very good correlations between the simulation results and the statistics gathered from hospitals, both on day by day and on global numbers, including the effects of the lockdown. Moreover, we have highlighted interesting differences in behaviour between the continuous and discrete methods that may arise in some particular conditions.


id: cord-301463-jzke8fop
title: Mitigation Strategies for Pandemic Influenza A: Balancing Conflicting Policy Objectives
author: Hollingsworth, T. Déirdre
date: 2011-02-10
url: https://www.ncbi.nlm.nih.gov/pubmed/21347316/
doi: 10.1371/journal.pcbi.1001076
abstract:
  Mitigation of a severe influenza pandemic can be achieved using a range of interventions to reduce transmission. Interventions can reduce the impact of an outbreak and buy time until vaccines are developed, but they may have high social and economic costs. The non-linear effect on the epidemic dynamics means that suitable strategies crucially depend on the precise aim of the intervention. National pandemic influenza plans rarely contain clear statements of policy objectives or prioritization of potentially conflicting aims, such as minimizing mortality (depending on the severity of a pandemic) or peak prevalence or limiting the socio-economic burden of contact-reducing interventions. We use epidemiological models of influenza A to investigate how contact-reducing interventions and availability of antiviral drugs or pre-pandemic vaccines contribute to achieving particular policy objectives. Our analyses show that the ideal strategy depends on the aim of an intervention and that the achievement of one policy objective may preclude success with others, e.g., constraining peak demand for public health resources may lengthen the duration of the epidemic and hence its economic and social impact. Constraining total case numbers can be achieved by a range of strategies, whereas strategies which additionally constrain peak demand for services require a more sophisticated intervention. If, for example, there are multiple objectives which must be achieved prior to the availability of a pandemic vaccine (i.e., a time-limited intervention), our analysis shows that interventions should be implemented several weeks into the epidemic, not at the very start. This observation is shown to be robust across a range of constraints and for uncertainty in estimates of both R(0) and the timing of vaccine availability. These analyses highlight the need for more precise statements of policy objectives and their assumed consequences when planning and implementing strategies to mitigate the impact of an influenza pandemic.


id: cord-303030-8unrcb1f
title: Social distancing versus early detection and contacts tracing in epidemic management
author: Gaeta, Giuseppe
date: 2020-07-16
txt: ./txt/cord-303030-8unrcb1f.txt
cache: ./cache/cord-303030-8unrcb1f.txt
extension: .txt
mime: text/plain
url: https://arxiv.org/pdf/2003.14102v3.pdf
doi: 10.1016/j.chaos.2020.110074
summary:
  In this paper we discuss the different effects of these ingredients on the epidemic dynamics; the discussion is conducted with the help of two simple models, i.e. the classical SIR model and the recently introduced variant A-SIR (arXiv:2003.08720) which takes into account the presence of a large set of asymptomatic infectives. In the SIR model [1] [2] [3] [4] [5] , a population of constant size (this means the analysis is valid over a relatively short time-span, or we should consider new births and also deaths not due to the epidemic) is subdivided in three classes: Susceptibles, Infected (and by this also Infectives), and Removed. Acting on α or on β to get the same γ will produce different timescales for the dynamics; see Fig. 1 , in which we have used values of the parameters resulting from our fit of early data for the Northern Italy COVID-19 epidemic [7] .

abstract:
  Different countries – and sometimes different regions within the same countries – have adopted different strategies in trying to contain the ongoing COVID-19 epidemic; these mix in variable parts social confinement, early detection and contact tracing. In this paper we discuss the different effects of these ingredients on the epidemic dynamics; the discussion is conducted with the help of two simple models, i.e. the classical SIR model and the recently introduced variant A-SIR (arXiv:2003.08720) which takes into account the presence of a large set of asymptomatic infectives.


id: cord-303651-fkdep6cp
title: Key questions for modelling COVID-19 exit strategies
author: Thompson, Robin N.
date: 2020-08-12
url: https://arxiv.org/pdf/2006.13012v4.pdf
doi: 10.1098/rspb.2020.1405
abstract:
  Combinations of intense non-pharmaceutical interventions (lockdowns) were introduced worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement exit strategies that relax restrictions while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute ‘Models for an exit strategy’ workshop (11–15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, would allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. This roadmap requires a global collaborative effort from the scientific community and policymakers, and has three parts: (i) improve estimation of key epidemiological parameters; (ii) understand sources of heterogeneity in populations; and (iii) focus on requirements for data collection, particularly in low-to-middle-income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health.


id: cord-304925-9gvx3swf
author: Xie, Zhixiang
date: 2020-07-14
txt: ./txt/cord-304925-9gvx3swf.txt
cache: ./cache/cord-304925-9gvx3swf.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pubmed/32687995/
doi: 10.1016/j.scitotenv.2020.140929
summary:
  Abstract This paper uses the exploratory spatial data analysis and the geodetector method to analyze the spatial and temporal differentiation characteristics and the influencing factors of the COVID-19 (corona virus disease 2019) epidemic spread in mainland China based on the cumulative confirmed cases, average temperature, and socio-economic data. Thus, we selected the indicators reflecting the population distribution, population inflow from Wuhan, traffic accessibility, economic connection intensity, average temperature, and medical facilities conditions J o u r n a l P r e -p r o o f as the detection factors (Table 2) , and the epidemic spread rate as the detected factor to assess the formation mechanism for the spatial pattern of COVID-19 epidemic. Specifically, the influence of the population distribution (X1) on the spatial distribution of the epidemic spread rate was significantly different from the population inflow from Wuhan (X2), economic connection intensity (X4), and average temperature (X5), but not different from the traffic accessibility (X3) and medical facility conditions (X6).

title:
  Spatial and temporal differentiation of COVID-19 epidemic spread in mainland China and its influencing factors

abstract:
  Abstract This paper uses the exploratory spatial data analysis and the geodetector method to analyze the spatial and temporal differentiation characteristics and the influencing factors of the COVID-19 (corona virus disease 2019) epidemic spread in mainland China based on the cumulative confirmed cases, average temperature, and socio-economic data. The results show that: (1) the epidemic spread rapidly from January 24 to February 20, 2020, and the distribution of the epidemic areas tended to be stable over time. The epidemic spread rate in Hubei province, in its surrounding, and in some economically developed cities was higher, while that in western part of China and in remote areas of central and eastern China was lower. (2) The global and local spatial correlation characteristics of the epidemic distribution present a positive correlation. Specifically, the global spatial correlation characteristics experienced a change process from agglomeration to decentralization. The local spatial correlation characteristics were mainly composed of the‘high-high’ and ‘low-low’ clustering types, and the situation of the contiguous layout was very significant. (3) The population inflow from Wuhan and the strength of economic connection were the main factors affecting the epidemic spread, together with the population distribution, transport accessibility, average temperature, and medical facilities, which affected the epidemic spread to varying degrees. (4) The detection factors interacted mainly through the mutual enhancement and nonlinear enhancement, and their influence on the epidemic spread rate exceeded that of single factors. Besides, each detection factor has an interval range that is conducive to the epidemic spread.


id: cord-305327-hayhbs5u
title: Global Spread of Hemorrhagic Fever Viruses: Predicting Pandemics
author: Gonzalez, Jean-Paul
date: 2017-09-19
url: https://doi.org/10.1007/978-1-4939-6981-4_1
doi: 10.1007/978-1-4939-6981-4_1
abstract:
  As successive epidemics have swept the world, the scientific community has quickly learned from them about the emergence and transmission of communicable diseases. Epidemics usually occur when health systems are unprepared. During an unexpected epidemic, health authorities engage in damage control, fear drives action, and the desire to understand the threat is greatest. As humanity recovers, policy-makers seek scientific expertise to improve their “preparedness” to face future events. Global spread of disease is exemplified by the spread of yellow fever from Africa to the Americas, by the spread of dengue fever through transcontinental migration of mosquitos, by the relentless influenza virus pandemics, and, most recently, by the unexpected emergence of Ebola virus, spread by motorbike and long haul carriers. Other pathogens that are remarkable for their epidemic expansions include the arenavirus hemorrhagic fevers and hantavirus diseases carried by rodents over great geographic distances and the arthropod-borne viruses (West Nile, chikungunya and Zika) enabled by ecology and vector adaptations. Did we learn from the past epidemics? Are we prepared for the worst? The ultimate goal is to develop a resilient global health infrastructure. Besides acquiring treatments, vaccines, and other preventive medicine, bio-surveillance is critical to preventing disease emergence and to counteracting its spread. So far, only the western hemisphere has a large and established monitoring system; however, diseases continue to emerge sporadically, in particular in Southeast Asia and South America, illuminating the imperfections of our surveillance. Epidemics destabilize fragile governments, ravage the most vulnerable populations, and threaten the global community. Pandemic risk calculations employ new technologies like computerized maintenance of geographical and historical datasets, Geographic Information Systems (GIS), Next Generation sequencing, and Metagenomics to trace the molecular changes in pathogens during their emergence, and mathematical models to assess risk. Predictions help to pinpoint the hot spots of emergence, the populations at risk, and the pathogens under genetic evolution. Preparedness anticipates the risks, the needs of the population, the capacities of infrastructure, the sources of emergency funding, and finally, the international partnerships needed to manage a disaster before it occurs. At present, the world is in an intermediate phase of trying to reduce health disparities despite exponential population growth, political conflicts, migration, global trade, urbanization, and major environmental changes due to global warming. For the sake of humanity, we must focus on developing the necessary capacities for health surveillance, epidemic preparedness, and pandemic response.


id: cord-307945-wkz43axo
title: Endocrine surgery during and after the Covid-19 epidemic: Expert guidelines in France
author: Baud, Grégory
date: 2020-04-30
txt: ./txt/cord-307945-wkz43axo.txt
cache: ./cache/cord-307945-wkz43axo.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pubmed/32448761/
doi: 10.1016/j.jviscsurg.2020.04.018
summary:
  Guidelines drafted by an expert group led by the French-speaking Association of Endocrine Surgery (AFCE) propose specific surgical management principles for thyroid, parathyroid, endocrine pancreas and adrenal surgery during and after the Covid-19 epidemic. Likewise, to meet their need for specific guidelines, the Frenchspeaking Association of Endocrine Surgery (AFCE) brought together a group of experts to propose principles for the surgical management of thyroid, parathyroid, endocrine pancreas and adrenal pathologies during the Covid-19 epidemic and afterwards, when surgical activity will be able to return gradually to its normal pattern. In the Covid-19 epidemic setting, its scheduling depends on the presence or absence of severe hypercalcemia, defined by a very high level of blood calcium > 3.5 mmol/l (140 mg/l) (17) , and/or the presence of clinical complications -acute pancreatitis secondary to HPT, brown tumor, calciphylaxis, fracture osteopenia, heart rhythm disorders (QT shortening on ECG, bradycardia with risk of asystole) with cardiac insufficiency (17) (18) (19) (20) .

abstract:
  Abstract The Covid-19 pandemic commands a major reorganization of the entire French healthcare system. In France, general rules have been issued nationally and implemented by each healthcare center, both public and private, throughout France. Guidelines drafted by an expert group led by the French-speaking Association of Endocrine Surgery (AFCE) propose specific surgical management principles for thyroid, parathyroid, endocrine pancreas and adrenal surgery during and after the Covid-19 epidemic.


id: cord-307946-1olapsmv
author: Xu, Zhijie
date: 2020-08-31
url: https://www.ncbi.nlm.nih.gov/pubmed/32869200/
doi: 10.1007/s11606-020-06107-3
title:
  Primary Care Practitioners’ Barriers to and Experience of COVID-19 Epidemic Control in China: a Qualitative Study

abstract:
  BACKGROUND: The coronavirus disease 2019 (COVID-19) emerged in December 2019 and posed numerous challenges to China’s health system. Almost 4 million primary care practitioners (PCPs) participated in controlling the outbreak. However, PCPs’ barriers to and experience of the epidemic control remain unknown and are essential for improving countermeasures. OBJECTIVE: To better understand the barriers PCPs faced in COVID-19 epidemic control and their psychological and occupational impacts, and explore potential solutions. DESIGN: This qualitative study was conducted through semi-structured, in-depth interviews from February 12, to March 10, 2020. PARTICIPANTS: A purposive sample of frontline PCPs affiliated with either community health centers or township health centers in four provinces of China were recruited. APPROACH: Interviews were conducted by telephone, and then recorded, transcribed, and content analyzed. Themes surrounding PCPs’ barriers to COVID-19 epidemic control, their experience, and potential solutions were iteratively identified using the constant comparative method. KEY RESULTS: Of the 21 PCPs interviewed, 10 (48%) were women and 5 (24%) worked in rural areas. Barriers to epidemic control in primary care included inappropriate PCP scheduling and role ambiguity, difficult tasks and inadequate capacities, and inexperienced community workers and insufficient cooperation. Some PCPs perceived respect and a sense of accomplishment and were preoccupied with the outbreak, while others were frustrated by fatigue and psychological distress. PCPs reported potential solutions for improving countermeasures, such as improving management, optimizing workflows, providing additional support, facilitating cooperation, and strengthening the primary care system. CONCLUSIONS: Due to their roles in controlling the COVID-19 epidemic, PCPs in China faced a series of barriers that affected them physically and mentally. Support for PCPs should help them to overcome these barriers and work efficiently. The current findings provide insight into the challenges and potential solutions for strengthening the preparedness and response of China’s primary care system in future disease outbreaks. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11606-020-06107-3) contains supplementary material, which is available to authorized users.


id: cord-309359-85xiqz2w
title: Porcine epidemic diarrhea: a review of current epidemiology and available vaccines
author: Song, Daesub
date: 2015-07-29
url: https://www.ncbi.nlm.nih.gov/pubmed/26273575/
doi: 10.7774/cevr.2015.4.2.166
abstract:
  Porcine epidemic diarrhea virus (PEDV), an Alphacoronavirus in the family Coronaviridae, causes acute diarrhea, vomiting, dehydration, and high mortality rates in neonatal piglets. PEDV can also cause diarrhea, agalactia, and abnormal reproductive cycles in pregnant sows. Although PEDV was first identified in Europe, it has resulted in significant economic losses in many Asian swine-raising countries, including Korea, China, Japan, Vietnam, and the Philippines. However, from April 2013 to the present, major outbreaks of PEDV have been reported in the United States, Canada, and Mexico. Moreover, intercontinental transmission of PEDV has increased mortality rates in seronegative neonatal piglets, resulting in 10% loss of the US pig population. The emergence and re-emergence of PEDV indicates that the virus is able to evade current vaccine strategies. Continuous emergence of multiple mutant strains from several regions has aggravated porcine epidemic diarrhea endemic conditions and highlighted the need for new vaccines based on the current circulating PEDV. Epidemic PEDV strains tend to be more pathogenic and cause increased death in pigs, thereby causing substantial financial losses for swine producers. In this review, we described the epidemiology of PEDV in several countries and present molecular characterization of current strains. We also discuss PEDV vaccines and related issues.


id: cord-313991-u2rkn5uh
author: Dimaschko, J.
date: 2020-08-16
txt: ./txt/cord-313991-u2rkn5uh.txt
cache: ./cache/cord-313991-u2rkn5uh.txt
extension: .txt
mime: text/plain
url: http://medrxiv.org/cgi/content/short/2020.08.14.20174557v1?rss=1
doi: 10.1101/2020.08.14.20174557
summary:
  Within the framework of a two-component model of the COVID-19 epidemic, taking into account the special role of superspreaders, we consider the impact of the recovery factor and quarantine measures on the course of the epidemic, as well as the possibility of a second wave of morbidity. In its second part, we consider the impact of recovery processes on the dynamics of the epidemic in the framework of the two-component model, as well as the impact of the quarantine as a factor affecting the spread rate. In this phase, the spread rates are suppressed by quarantine measures with a factor of Q < 1, the relative number of the superspreaders reaches the endemic equilibrium value s 2 = 1 − γ/(Qg) and stops growing. After the quarantine is released, the number of the superspreaders returns to the former endemic equilibrium non-zero value, and a new wave of infected people appears among the sensitive.

title:
  Superspreading as a Regular Factor of the COVID-19 Pandemic: II. Quarantine Measures and the Second Wave

abstract:
  Within the framework of a two-component model of the COVID-19 epidemic, taking into account the special role of superspreaders, we consider the impact of the recovery factor and quarantine measures on the course of the epidemic, as well as the possibility of a second wave of morbidity. It is assumed that there is no long-term immunity in asymptomatic superspreaders who have under- gone the infection, and the emergence of long-term immunity in those who have undergone severe illness. It is shown that, under these assumptions, the relaxation of quarantine measures leads to the resumption of virus circulation among asymptomatic superspreaders. Depending on the charac- teristics of the quarantine, its removal may or may not lead to a renewed wave of daily morbidity. A criterion for the occurrence and repeated wave of morbidity is proposed based on the analysis of the final phase of the first wave. Based on this criterion, the repeated wave of the epidemic is predicted in New Zealand. A natural explanation is given for the decrease in lethality among the infected against the background of an absolute increase in their number.


id: cord-315885-iu5wg5ik
author: Hoang, Hai
date: 2013-12-19
txt: ./txt/cord-315885-iu5wg5ik.txt
cache: ./cache/cord-315885-iu5wg5ik.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pubmed/24356830/
doi: 10.1128/genomea.01049-13
summary:
  title: Full-Length Genome Sequence of a Plaque-Cloned Virulent Porcine Epidemic Diarrhea Virus Isolate (USA/Iowa/18984/2013) from a Midwestern U.S. Swine Herd The complete genome sequence of PEDV strain USA/Iowa/18984/2013 was submitted to GenBank under the accession no. Complete genome sequence of porcine epidemic diarrhea virus strain USA/Colorado/2013 from the United States Complete genome sequence of porcine epidemic diarrhea virus strain AJ1102 isolated from a suckling piglet with acute diarrhea in China Complete genome sequence of a Chinese virulent porcine epidemic diarrhea virus strain Complete genome sequence of a recombinant porcine epidemic diarrhea virus strain from eastern China Complete genome sequence of a highly prevalent isolate of porcine epidemic diarrhea virus in south China Complete genome sequence of a variant porcine epidemic diarrhea virus strain isolated in central China Complete genome sequence of novel porcine epidemic diarrhea virus strain GD-1 in China

title:
  Full-Length Genome Sequence of a Plaque-Cloned Virulent Porcine Epidemic Diarrhea Virus Isolate (USA/Iowa/18984/2013) from a Midwestern U.S. Swine Herd

abstract:
  Porcine epidemic diarrhea (PED) was recognized in U.S. swine for the first time in early 2013. A plaque-purified PED virus (PEDV) isolate (USA/Iowa/18984/2013) was obtained from a diarrheic piglet. The isolate is genetically close to other previously reported U.S. PEDVs and recent Chinese PEDVs and was virulent when inoculated into neonatal pigs.


id: cord-317939-9x377kdv
author: Fu, You-Lei
date: 2020-09-16
url: https://doi.org/10.1016/j.cmpb.2020.105762
doi: 10.1016/j.cmpb.2020.105762
title:
  Fuzzy Logic Programming and Adaptable Design of Medical Products for the COVID-19 Anti-epidemic Normalization

abstract:
  BACKGROUND: The COVID-19 prevention and control constantly affects lives worldwide. In this paper, household medical products were analyzed. Considering the household anti-epidemic status, economic and environmental benefits, the adaptable design method of anti-epidemic products in the vestibule was proposed. The measure of adaptable design method still have shortcomings. Therefore, an improved method that is based on fuzzy logic programming is required. METHOD: Firstly, common medical product types used in vestibules and household anti-epidemic products were identified and summarized into product sets through the literature review, focus groups and questionnaires. Then matching degree matrix was obtained by functional configuration decomposition and matching calculations. Secondly, experts were invited to evaluate the paired comparative probability matrices and linguistic variables, and the evaluation data were converted by trapezoidal membership functions, fuzzy numbers and the defuzzification method to obtain the usage probability values for product functions. Finally, the matching degree value and the product function were calculated by adaptability measure formula, and product function, the adaptability factor and the adaptability were obtained. RESULTS: Our results show that the degree of adaptability of each product function in the product set. The higher value of the product function, the more it can be prioritized for design development with functional cost savings, simplification or clustering. CONCLUSION: This study proposes an adaptable design method based on fuzzy logic programming. The data results in this study can guide the development and programming of the vestibule anti-epidemic products. The higher adaptability value of a product function indicates that it is more capable of being simplified, clustered, and adapting to changes in the product set.


id: cord-318004-r08k40ob
title: Converging and emerging threats to health security
author: Raina MacIntyre, C.
date: 2017-11-27
url: https://doi.org/10.1007/s10669-017-9667-0
doi: 10.1007/s10669-017-9667-0
abstract:
  Advances in biological sciences have outpaced regulatory and legal frameworks for biosecurity. Simultaneously, there has been a convergence of scientific disciplines such as synthetic biology, data science, advanced computing and many other technologies, which all have applications in health. For example, advances in cybercrime methods have created ransomware attacks on hospitals, which can cripple health systems and threaten human life. New kinds of biological weapons which fall outside of traditional Cold War era thinking can be created synthetically using genetic code. These convergent trajectories are dramatically expanding the repertoire of methods which can be used for benefit or harm. We describe a new risk landscape for which there are few precedents, and where regulation and mitigation are a challenge. Rapidly evolving patterns of technology convergence and proliferation of dual-use risks expose inadequate societal preparedness. We outline examples in the areas of biological weapons, antimicrobial resistance, laboratory security and cybersecurity in health care. New challenges in health security such as precision harm in medicine can no longer be addressed within the isolated vertical silo of health, but require cross-disciplinary solutions from other fields. Nor can they cannot be managed effectively by individual countries. We outline the case for new cross-disciplinary approaches in risk analysis to an altered risk landscape.


id: cord-329256-7njgmdd1
title: Modeling the variations in pediatric respiratory syncytial virus seasonal epidemics
author: Leecaster, Molly
date: 2011-04-21
url: https://www.ncbi.nlm.nih.gov/pubmed/21510889/
doi: 10.1186/1471-2334-11-105
abstract:
  BACKGROUND: Seasonal respiratory syncytial virus (RSV) epidemics occur annually in temperate climates and result in significant pediatric morbidity and increased health care costs. Although RSV epidemics generally occur between October and April, the size and timing vary across epidemic seasons and are difficult to predict accurately. Prediction of epidemic characteristics would support management of resources and treatment. METHODS: The goals of this research were to examine the empirical relationships among early exponential growth rate, total epidemic size, and timing, and the utility of specific parameters in compartmental models of transmission in accounting for variation among seasonal RSV epidemic curves. RSV testing data from Primary Children's Medical Center were collected on children under two years of age (July 2001-June 2008). Simple linear regression was used explore the relationship between three epidemic characteristics (final epidemic size, days to peak, and epidemic length) and exponential growth calculated from four weeks of daily case data. A compartmental model of transmission was fit to the data and parameter estimated used to help describe the variation among seasonal RSV epidemic curves. RESULTS: The regression results indicated that exponential growth was correlated to epidemic characteristics. The transmission modeling results indicated that start time for the epidemic and the transmission parameter co-varied with the epidemic season. CONCLUSIONS: The conclusions were that exponential growth was somewhat empirically related to seasonal epidemic characteristics and that variation in epidemic start date as well as the transmission parameter over epidemic years could explain variation in seasonal epidemic size. These relationships are useful for public health, health care providers, and infectious disease researchers.


id: cord-331771-fhy98qt4
title: Modeling the competitive diffusions of rumor and knowledge and the impacts on epidemic spreading
author: Huang, He
date: 2021-01-01
url: https://doi.org/10.1016/j.amc.2020.125536
doi: 10.1016/j.amc.2020.125536
abstract:
  The interaction between epidemic spreading and information diffusion is an interdisciplinary research problem. During an epidemic, people tend to take self-protective measures to reduce the infection risk. However, with the diffusion of rumor, people may be difficult to make an appropriate choice. How to reduce the negative impact of rumor and to control epidemic has become a critical issue in the social network. Elaborate mathematical model is instructive to understand such complex dynamics. In this paper, we develop a two-layer network to model the interaction between the spread of epidemic and the competitive diffusions of information. The results show that knowledge diffusion can eradicate both rumor and epidemic, where the penetration intensity of knowledge into rumor plays a vital role. Specifically, the penetration intensity of knowledge significantly increases the thresholds for rumor and epidemic to break out, even when the self-protective measure is not perfectly effective. But eradicating rumor shouldn’t be equated with eradicating epidemic. The epidemic can be eradicated with rumor still diffusing, and the epidemic may keep spreading with rumor being eradicated. Moreover, the communication-layer network structure greatly affects the spread of epidemic in the contact-layer network. When people have more connections in the communication-layer network, the knowledge is more likely to diffuse widely, and the rumor and epidemic can be eradicated more efficiently. When the communication-layer network is sparse, a larger penetration intensity of knowledge into rumor is required to promote the diffusion of knowledge.


id: cord-332898-gi23un26
title: CIRD-F: Spread and Influence of COVID-19 in China
author: Zhou, Lingyun
date: 2020-04-07
url: https://doi.org/10.1007/s12204-020-2168-1
doi: 10.1007/s12204-020-2168-1
abstract:
  The outbreak of coronavirus disease 2019 (COVID-19) has been spreading rapidly in China and the Chinese government took a series of policies to control the epidemic. Therefore, it will be helpful to predict the tendency of the epidemic and analyze the influence of official policies. Existing models for prediction, such as cabin models and individual-based models, are either oversimplified or too meticulous, and the influence of the epidemic was studied much more than that of official policies. To predict the epidemic tendency, we consider four groups of people, and establish a propagation dynamics model. We also create a negative feedback to quantify the public vigilance to the epidemic. We evaluate the tendency of epidemic in Hubei and China except Hubei separately to predict the situation of the whole country. Experiments show that the epidemic will terminate around 17 March 2020 and the final number of cumulative infections will be about 78 191 (prediction interval, 74 872 to 82 474). By changing the parameters of the model accordingly, we demonstrate the control effect of the policies of the government on the epidemic situation, which can reduce about 68% possible infections. At the same time, we use the capital asset pricing model with dummy variable to evaluate the effects of the epidemic and official policies on the revenue of multiple industries.


id: cord-335886-m0d72ntg
title: Relations of parameters for describing the epidemic of COVID―19 by the Kermack―McKendrick model
author: Tomie, Toshihisa
date: 2020-03-03
url: https://doi.org/10.1101/2020.02.26.20027797
doi: 10.1101/2020.02.26.20027797
abstract:
  In order to quantitatively characterize the epidemic of COVID―19, useful relations among parameters describing an epidemic in general are derived based on the Kermack-McKendrick model. The first relation is 1/τgrow=1/τtrans−1/τinf, where τgrow is the time constant of the exponential growth of an epidemic, τtrans is the time for a pathogen to be transmitted from one patient to uninfected person, and the infectious time τinf is the time during which the pathogen keeps its power of transmission. The second relation p(∞) ≈1−exp(−(R0−1)/0.60) is the relation between p(∞), the final size of the disaster defined by the ratio of the total infected people to the population of the society,and the basic reproduction number, R0, which is the number of persons infected by the transmission of the pathogen from one infected person during the infectious time. The third relation 1/τend=1/τinf−(1−p(∞))/τtrans gives the decay time constant τend at the ending stage of the epidemic. Derived relations are applied to influenza in Japan in 2019 for characterizing the epidemic.


id: cord-341187-jqesw4e8
author: Yu, Xinhua
date: 2020-08-27
url: https://doi.org/10.1016/j.tmaid.2020.101858
doi: 10.1016/j.tmaid.2020.101858
title:
  Modeling Return of the Epidemic: Impact of Population Structure, Asymptomatic Infection, Case Importation and Personal Contacts

abstract:
  BACKGROUND: Proactive interventions have halted the pandemic of coronavirus infected disease in some regions. However, without reaching herd immunity, the return of epidemic is possible. We investigate the impact of population structure, case importation, asymptomatic cases, and the number of contacts on a possible second wave of epidemic through mathematical modelling. METHODS: we built a modified Susceptible-exposed-Infectious-Removed (SEIR) model with parameters mirroring those of the COVID-19 pandemic and reported simulated characteristics of epidemics for incidence, hospitalizations and deaths under different scenarios. RESULTS: A larger percent of elderly people leads to higher number of hospitalizations, while a large percent of prior infection will effectively curb the epidemic. The number of imported cases and the speed of importation have small impact on the epidemic progression. However, a higher percent of asymptomatic cases slows the epidemic down and reduces the number of hospitalizations and deaths at the epidemic peak. Finally, reducing the number of contacts among young people alone has moderate effects on themselves, but little effects on the elderly population. However, reducing the number of contacts among elderly people alone can mitigate the epidemic significantly in both age groups, even though young people remain active within themselves. CONCLUSION: Reducing the number of contacts among high risk populations alone can mitigate the burden of epidemic in the whole society. Interventions targeting high risk groups may be more effective in containing or mitigating the epidemic.


id: cord-345567-8d1076ge
author: Ivanov, Dmitry
date: 2020-03-24
url: https://api.elsevier.com/content/article/pii/S1366554520304300
doi: 10.1016/j.tre.2020.101922
title:
  Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case

abstract:
  Epidemic outbreaks are a special case of supply chain (SC) risks which is distinctively characterized by a long-term disruption existence, disruption propagations (i.e., the ripple effect), and high uncertainty. We present the results of a simulation study that opens some new research tensions on the impact of COVID-19 (SARS-CoV-2) on the global SCs. First, we articulate the specific features that frame epidemic outbreaks as a unique type of SC disruption risks. Second, we demonstrate how simulation-based methodology can be used to examine and predict the impacts of epidemic outbreaks on the SC performance using the example of coronavirus COVID-19 and anyLogistix simulation and optimization software. We offer an analysis for observing and predicting both short-term and long-term impacts of epidemic outbreaks on the SCs along with managerial insights. A set of sensitivity experiments for different scenarios allows illustrating the model’s behavior and its value for decision-makers. The major observation from the simulation experiments is that the timing of the closing and opening of the facilities at different echelons might become a major factor that determines the epidemic outbreak impact on the SC performance rather than an upstream disruption duration or the speed of epidemic propagation. Other important factors are lead-time, speed of epidemic propagation, and the upstream and downstream disruption durations in the SC. The outcomes of this research can be used by decision-makers to predict the operative and long-term impacts of epidemic outbreaks on the SCs and develop pandemic SC plans. Our approach can also help to identify the successful and wrong elements of risk mitigation/preparedness and recovery policies in case of epidemic outbreaks. The paper is concluded by summarizing the most important insights and outlining future research agenda.


id: cord-347349-caz5fwl1
author: Yu, Xinhua
date: 2020-07-02
url: https://www.sciencedirect.com/science/article/pii/S1201971220305361?v=s5
doi: 10.1016/j.ijid.2020.06.101
title:
  Distinctive trajectories of COVID-19 epidemic by age and gender: a retrospective modeling of the epidemic in South Korea

abstract:
  OBJECTIVES: Elderly people had suffered disproportional burden of COVID-19. We hypothesized that males and females in different age groups might have different epidemic trajectories. METHODS: Using publicly available data from South Korea, daily new COVID-19 cases were fitted with generalized additive models, assuming Poisson and negative binomial distributions. Epidemic dynamics by age and gender groups were explored with interactions between smoothed time terms and age and gender. RESULTS: A negative binomial distribution fitted the daily case counts best. Interaction between the dynamic patterns of daily new cases and age groups was statistically significant (p < 0.001), but not with gender group. People aged 20-39 years led the epidemic processes in the society with two peaks: one major peak around March 1 and a smaller peak around April 7, 2020. The epidemic process among people aged 60 or above was trailing behind that of younger people with smaller magnitude. After March 15, there was a consistent decline of daily new cases among elderly people, despite large fluctuations of case counts among young adults. CONCLUSIONS: Although young people drove the COVID-19 epidemic in the whole society with multiple rebounds, elderly people could still be protected from virus infection after the peak of epidemic.


id: cord-348658-fz5nfdf9
author: Weiner, Joseph A.
date: 2020-06-04
txt: ./txt/cord-348658-fz5nfdf9.txt
cache: ./cache/cord-348658-fz5nfdf9.txt
extension: .txt
mime: text/plain
url: https://doi.org/10.1007/s00586-020-06477-6
doi: 10.1007/s00586-020-06477-6
summary:
  The current study addressed whether prior experience with disease epidemics among the spine surgeon community had an impact on preparedness and response toward COVID-19. The current study addresses the role of prior infectious disease outbreaks on the preparedness, response, and impact of COVID-19 on spine surgeons across the world. In total, 902 spine surgeons responded to the survey, representing 91 distinct countries and 7 global regions (Africa, Asia, Australia, Europe, the Middle East, North America, and South America/Latin America Respondents overall reported a moderate to high level of concern regarding the COVID-19 outbreak, with a mean score of 3.7 ± 1.2 on a scale of one to five. Multivariate regression analysis, controlling for statistically significant demographic differences (geographic region, population, fellowship training, and practice breakdown), revealed that prior epidemic exposure was independently associated with an increase in respondents reporting personal health as a source of stress (OR 1.66; 95% CI 1.21-2.27; p = 0.0015), music as a coping strategy (OR 1.67; 95% CI 1.21-2.30; p < 0.001, and still performing elective spine surgery (OR 1.55; 95% CI 1.01-2.38; p = 0.0035).

title:
  Learning from the past: did experience with previous epidemics help mitigate the impact of COVID-19 among spine surgeons worldwide?

abstract:
  PURPOSE: Spine surgeons around the world have been universally impacted by COVID-19. The current study addressed whether prior experience with disease epidemics among the spine surgeon community had an impact on preparedness and response toward COVID-19. METHODS: A 73-item survey was distributed to spine surgeons worldwide via AO Spine. Questions focused on: demographics, COVID-19 preparedness, response, and impact. Respondents with and without prior epidemic experience (e.g., SARS, H1NI, MERS) were assessed on preparedness and response via univariate and multivariate modeling. Results of the survey were compared against the Global Health Security Index. RESULTS: Totally, 902 surgeons from 7 global regions completed the survey. 24.2% of respondents had prior experience with global health crises. Only 49.6% reported adequate access to personal protective equipment. There were no differences in preparedness reported by respondents with prior epidemic exposure. Government and hospital responses were fairly consistent around the world. Prior epidemic experience did not impact the presence of preparedness guidelines. There were subtle differences in sources of stress, coping strategies, performance of elective surgeries, and impact on income driven by prior epidemic exposure. 94.7% expressed a need for formal, international guidelines to help mitigate the impact of the current and future pandemics. CONCLUSIONS: This is the first study to note that prior experience with infectious disease crises did not appear to help spine surgeons prepare for the current COVID-19 pandemic. Based on survey results, the GHSI was not an effective measure of COVID-19 preparedness. Formal international guidelines for crisis preparedness are needed to mitigate future pandemics.


id: cord-349421-qzgxe24c
title: Modeling epidemic spread with awareness and heterogeneous transmission rates in networks
author: Shang, Yilun
date: 2013-05-03
url: https://doi.org/10.1007/s10867-013-9318-8
doi: 10.1007/s10867-013-9318-8
abstract:
  During an epidemic outbreak in a human population, susceptibility to infection can be reduced by raising awareness of the disease. In this paper, we investigate the effects of three forms of awareness (i.e., contact, local, and global) on the spread of a disease in a random network. Connectivity-correlated transmission rates are assumed. By using the mean-field theory and numerical simulation, we show that both local and contact awareness can raise the epidemic thresholds while the global awareness cannot, which mirrors the recent results of Wu et al. The obtained results point out that individual behaviors in the presence of an infectious disease has a great influence on the epidemic dynamics. Our method enriches mean-field analysis in epidemic models.


id: cord-355291-fq0h895i
author: Yasir, Ammar
date: 2020-04-24
txt: ./txt/cord-355291-fq0h895i.txt
cache: ./cache/cord-355291-fq0h895i.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pubmed/32344770/
doi: 10.3390/ijerph17082954
summary:
  In this study, we attempted to identify the role of E-government and COVID-19 word of mouth in terms of their direct impact on online social presence during the outbreak as well as their impacts mediated by epidemic protection and attitudes toward epidemic outbreaks. The study results revealed that the roles of E-government and COVID-19 word of mouth are positively related to online social presence during the outbreak. Epidemic protection and attitude toward epidemic outbreak were found to positively moderate the impact of the role of E-government and COVID-19 word of mouth on online social presence during the outbreak. We used five constructs (2019-nCoV-WOM, role of E-Govt, attitude toward epidemic outbreak, epidemic protection, and online social presence in the outbreak) with a conceptual multi-mediation model. Our study results revealed that attitude toward epidemic outbreak has a strong mediation effect between the role of E-Govt and online social presence during outbreaks, indicating that other governments and organizations can follow China''s safety model.

title:
  Modeling Impact of Word of Mouth and E-Government on Online Social Presence during COVID-19 Outbreak: A Multi-Mediation Approach

abstract:
  Although social presence plays an essential role under general conditions, its role becomes significant for societal protection during the quarantine period in epidemic outbreak. In this study, we attempted to identify the role of E-government and COVID-19 word of mouth in terms of their direct impact on online social presence during the outbreak as well as their impacts mediated by epidemic protection and attitudes toward epidemic outbreaks. For this purpose, a unique multi-mediation model is proposed to provide a new direction for research in the field of epidemic outbreaks and their control. Through random sampling, an online survey was conducted and data from 683participants were analyzed. Partial least squares structural equation modeling was used to test the relationships between the variables of interest. The study results revealed that the roles of E-government and COVID-19 word of mouth are positively related to online social presence during the outbreak. Epidemic protection and attitude toward epidemic outbreak were found to positively moderate the impact of the role of E-government and COVID-19 word of mouth on online social presence during the outbreak. The key findings of this study have both practical and academic implications.


id: cord-355419-8txtk0b3
title: Epidemic in networked population with recurrent mobility pattern
author: Feng, Liang
date: 2020-06-25
txt: ./txt/cord-355419-8txtk0b3.txt
cache: ./cache/cord-355419-8txtk0b3.txt
extension: .txt
mime: text/plain
url: https://www.sciencedirect.com/science/article/pii/S0960077920304148
doi: 10.1016/j.chaos.2020.110016
summary:
  In this paper, we utilize a discrete-time Markov chain approach and propose an epidemic model to describe virus propagation in the heterogeneous graph, which is used to represent individuals with intra social connections and mobility between individuals and common locations. Different from commonly used homogeneous mixing approaches [2, 3] , we give an analysis of epidemic spreading in population following a structured network with recurrent mobility pattern in this work. One widely used approach to analyse epidemic spreading in complex networks is metapopulation model, which divides the whole population into several geographical structured parts [13, 18] , and contacts among individuals in the same subpopulation are assumed to be well-mixed. In Section 2 , we give the formulation of epidemic model for virus spreading in networked population with recurrent mobility pattern, along with theoretical results of epidemic threshold. We formulate an epidemic model of virus propagating in networked population with recurrent mobility pattern between individuals and public areas.

abstract:
  The novel Coronavirus (COVID-19) has caused a global crisis and many governments have taken social measures, such as home quarantine and maintaining social distance. Many recent studies show that network structure and human mobility greatly influence the dynamics of epidemic spreading. In this paper, we utilize a discrete-time Markov chain approach and propose an epidemic model to describe virus propagation in the heterogeneous graph, which is used to represent individuals with intra social connections and mobility between individuals and common locations. There are two types of nodes, individuals and public places, and disease can spread by social contacts among individuals and people gathering in common areas. We give theoretical results about epidemic threshold and influence of isolation factor. Several numerical simulations are performed and experimental results further demonstrate the correctness of proposed model. Non-monotonic relationship between mobility possibility and epidemic threshold and differences between Erdös-Rényi and power-law social connections are revealed. In summary, our proposed approach and findings are helpful to analyse and prevent the epidemic spreading in networked population with recurrent mobility pattern.


