# ent

id: cord-198272-s0lk1812
type: CHEMICAL
entity:
  N players N 2 in the game incentive of player i N takes strategy s h i without considering others strategy is given as


id: cord-017590-w5copp1z
type: ORG
entity:
  Distributed Computing Artificial Intelligence Bioinformatics Soft Computing and Ambient Assisted Living


id: cord-223332-51670qld
type: ORG
entity:
  the Council of European Union The Personal Data Protection Bill Social Security Number Protection Act


id: cord-223332-51670qld
type: WORK_OF_ART
entity:
  Large Sparse Datasets Security Without Identification Transaction Systems to Make Big Brother Obsolete Showing Credentials Without Identification


id: cord-223332-51670qld
type: WORK_OF_ART
entity:
  Credential Sharing A Pitfall of Anonymous Credentials Untraceable Electronic Mail Return Addresses and Digital Pseudonyms


id: cord-223332-51670qld
type: WORK_OF_ART
entity:
  Towards Defining Semantic Foundations for Purpose Based Privacy Policies Formalizing and Enforcing Purpose Restrictions in Privacy Policies


id: cord-223332-51670qld
type: ORG
entity:
  Order Execution Sanctum Minimal Hardware Extensions for Strong Software Isolation Practical Techniques for Searches on Encrypted Data Public Key Encryption


id: cord-223332-51670qld
type: ORG
entity:
  India Apps Gone Rogue Maintaining Personal Privacy in an Epidemic Anonymous Collocation Discovery Harnessing Privacy to Tame the Coronavirus Epione Lightweight Contact Tracing with Strong


id: cord-284424-6gljl7n5
type: GGP
entity:
  Alzheimer s disease the mobile wearable devices opportunity Sensing Technology to Monitor Behavioral and Psychological Symptoms and to Assess Treatment Response in People


id: cord-227156-uy4dykhg
type: PROTEIN
entity:
  OfeFernandez PatoBullrich macri macrismo mauriciomacri pichetto MiguelPichetto JuntosPorElCambio alferdez


id: cord-227156-uy4dykhg
type: WORK_OF_ART
entity:
  Proceedings of the 21st International Conference on World Wide Web Use of Machine Learning to Detect Illegal Wildlife Product Promotion and Sales on Twitter Frontiers in Big Data Analyzing


id: cord-243634-4qcq5soy
type: FAC
entity:
  Dept Art Therapy and Cultural Studies Applied Ecology and System Dynamics Lab Alfonso Fuggetta Politecnico


id: cord-302937-3yivxfi8
type: WORK_OF_ART
entity:
  The Theory of Demand for Health Insurance Effects of a Cost Sharing Exemption on Use of Preventive Services


id: cord-302937-3yivxfi8
type: ORG
entity:
  British Animal Disease Management Memorandum on Prioritization of Home Confinement as Appropriate in Response


id: cord-018101-zd4v222b
type: ORG
entity:
  Bell and World Health Organization Working Group on Prevention of International and Community Transmission of SARS


id: cord-018101-zd4v222b
type: ORG
entity:
  Bell and World Health Organization Working Group on Prevention of International and Community Transmission of SARS 2004


id: cord-018101-zd4v222b
type: LAW
entity:
  Chap 5 World Health Organization World Health Organization Working Group on Prevention of International and Community Transmission of SARS


id: cord-018746-s9knxdne
type: CELL_LINE
entity:
  h1n1 A monte carlo likelihood analysis based on human mobility The transmissibility and control of pandemic influenza a h1n1 virus Pandemic potential of a strain of influenza a h1n1 Early findings Real time numerical forecast of global epidemic spreading Case study of 2009 a h1n1pdm Comparing large scale computational approaches to epidemic modeling agent based versus structured metapopulation models Creating synthetic baseline populations Transims transportation analysis simulation system Determinants of the spatiotemporal dynamics of the 2009


id: cord-288024-1mw0k5yu
type: ORG
entity:
  Practice Journal of Applied Psychology Journal of Small Business Management and Family Business Review


id: cord-253711-a0prku2k
type: CELL_LINE
entity:
  NetLog and Repast Robertson 2005 With regard to the second assumption both the infection and communication networks


id: cord-349476-iac9fak3
type: WORK_OF_ART
entity:
  The Effectiveness of Policies to Control a Human Influenza Pandemic A Literature Review Data Releases Spatial


id: cord-281836-j1r771nq
type: FAC
entity:
  the Instituto de Salud Carlos III Spanish Network for Research on Infectious Diseases RD16 0016 0011


id: cord-281836-j1r771nq
type: ORG
entity:
  Leviathan Baltimore Penguin Books Culture s Consequences Comparing Values Behaviors Institutions and Organizations Across Nations Adsorption


id: cord-281836-j1r771nq
type: WORK_OF_ART
entity:
  The Essential Rousseau The Social Contract Discourse on the Origin of Inequality Discourse on the Arts and Sciences


id: cord-319170-idv2cio4
type: DISEASE
entity:
  cognitive behavioral and affective changes occurring during quarantine and on the other hand the suggestions


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-306056-4jx0u7js
type: ORG
entity:
  Evolutionary Ecology Sociology Economics History Psychology Physiology Anatomy Molecular Biology and Genetics Physics


id: cord-306056-4jx0u7js
type: WORK_OF_ART
entity:
  Philosophy of Medicine as the Source for Medical Ethics Antifoundationalism and the Possibility of a Moral Philosophy of Medicine


id: cord-306056-4jx0u7js
type: ORG
entity:
  Sickness A Critique of Essentialism in Medicine In Health Disease and Causal Explanations in Medicine Identity and Necessity


id: cord-355689-mo4mvwch
type: GGP
entity:
  Refs 7 8 9 10 explore the impact of various topological structures within the population on the infectious diseases spread and it is convincingly found that heterogeneous networks may quicken the disease spreading within the population even lead to the absence of epidemic threshold 11 Meanwhile the individual reactions to infectious diseases may also substantially influence the diffusion processes of epidemics One of the most striking cases regarding the outbreaks


# bib

id: cord-005068-3ddb38de
title: Biobanking and public health: is a human rights approach the tie that binds?
author: Meslin, Eric M.
date: 2011-07-15
txt: ./txt/cord-005068-3ddb38de.txt
cache: ./cache/cord-005068-3ddb38de.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7088251/
doi: 10.1007/s00439-011-1061-2
summary:
  One definition of public health illustrates its breadth and focus: the promotion of health and the prevention of disease and disability; the collection and use of epidemiological data, population surveillance, and other forms of empirical quantitative assessment; a recognition of the multidimensional nature of the determinants of health; and a focus on the complex interactions of many factors -biological, behavioral, social, and environmental -in developing effective interventions (Childress et al. These developments notwithstanding, commentators have been quick to point out the limitations of adopting human rights approach for public health and genome-based medicine. Adopting human rights as a public health ethic is not an ideal guide for drafting specific rules governing individual focused biobanking issues such as consent, privacy and secondary uses. We have taken the view that one of the ethical challenges raised by genomic medicine reflects an enduring problem in public health: the appropriate balancing of individual and collective values, rights and interests.

abstract:
  Ethical principles guiding public health and genomic medicine are often at odds: whereas public health practice adopts collectivist principles that emphasize population-based benefits, recent advances in genomic and personalized medicine are grounded in an individualist ethic that privileges informed consent, and the balancing of individual risk and benefit. Indeed, the attraction of personalized medicine is the promise it holds out to help individuals get the “right medicine for the right problem at the right time.” Research biobanks are an effective tool in the genomic medicine toolbox. Biobanking in public health presents a unique case study to unpack some of these issues in more detail. For example, there is a long history of using banked tissue obtained under clinical diagnostic conditions for later public health uses. But despite the collectivist approach of public health, the principles applied to the ethical challenges of biobanking (e.g. informed consent, autonomy, privacy) remain individualist. We demonstrate the value of using human rights as a public health ethics framework to address this tension in biobanking by applying it to two illustrative cases.


id: cord-010310-jqh75340
title: Next Generation Technology for Epidemic Prevention and Control: Data-Driven Contact Tracking
author: nan
date: 2018-12-24
txt: ./txt/cord-010310-jqh75340.txt
cache: ./cache/cord-010310-jqh75340.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7176034/
doi: 10.1109/access.2018.2882915
summary:
  Furthermore, the transmission networks of infectious diseases established using contact tracking technology can aid in the visualization of actual virus transmission paths, which enables simulations and predictions of the transmission process, assessment of the outbreak trend, and further development and deployment of more effective prevention and control strategies. Tracking the contact interactions of individuals can effectively restore the ''''invisible'''' virus transmission paths, quickly locate and isolate high-risk individuals who were in contact with infected persons, and can aid in quantitative analysis of the transmission paths, processes, and trends of the infectious diseases, all leading to the development of corresponding effective epidemic control strategies. With the aim to collect dynamic, complete, and accurate individual contact information, some researchers began to use mobile phone, wireless sensors, RFID, and GPS devices to track individual contact behaviors. Although detailed individual contact information can be collected through non-automatic methods, e.g., offline and online questionnaire, and automatic methods, e.g., mobile phone, wearable wireless sensors, RFID, and GPS devices.

abstract:
  Contact tracking is one of the key technologies in prevention and control of infectious diseases. In the face of a sudden infectious disease outbreak, contact tracking systems can help medical professionals quickly locate and isolate infected persons and high-risk individuals, preventing further spread and a large-scale outbreak of infectious disease. Furthermore, the transmission networks of infectious diseases established using contact tracking technology can aid in the visualization of actual virus transmission paths, which enables simulations and predictions of the transmission process, assessment of the outbreak trend, and further development and deployment of more effective prevention and control strategies. Exploring effective contact tracking methods will be significant. Governments, academics, and industries have all given extensive attention to this goal. In this paper, we review the developments and challenges of current contact tracing technologies regarding individual and group contact from both static and dynamic perspectives, including static individual contact tracing, dynamic individual contact tracing, static group contact tracing, and dynamic group contact tracing. With the purpose of providing useful reference and inspiration for researchers and practitioners in related fields, directions in multi-view contact tracing, multi-scale contact tracing, and AI-based contact tracing are provided for next-generation technologies for epidemic prevention and control.


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-017137-6pmts7ui
title: Microbial Forensics: Beyond a Fascination
author: Nema, Vijay
date: 2018-07-12
txt: ./txt/cord-017137-6pmts7ui.txt
cache: ./cache/cord-017137-6pmts7ui.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7121623/
doi: 10.1007/978-981-13-1583-1_17
summary:
  When leftover microbes in the biological material or objects used by the culprit or the person in question are used to correlate the identity of the individual, it takes us to the new field of science—"microbial forensics." Technological advances in the field of forensics, molecular biology, and microbiology have all helped to refine the techniques of collecting and processing of the samples for microbiological identification using DNA-based methods followed by its inference in the form of evidence. Herein the microbial forensics could be defined as "the discipline of applying scientific methods to the analysis of evidence related to bioterrorism, biocrimes, hoaxes, or the accidental release of a biological agent or toxin for attribution purposes" [21] . Microbial forensics has a role in such cases by applying scientific methods for the analysis of evidence from such a bioterrorism attack. The most reliable technique till date for microbial forensics is metagenomics-a culture-independent approach for identifying and enumerating microbes.

abstract:
  Microbiology has seen a great transition from culture-based identification of microbes using various biochemical and microscopic observations to identify and functionally characterize the microbes by just collecting the DNA and sequencing it. This advancement has not only moved in and around microbiology but has found its applications in fields which were earlier considered to be the remote ones. Forensics is one such field, where tracing the leftover evidence on a crime scene can lead to the identification and prosecution of the culprit. When leftover microbes in the biological material or objects used by the culprit or the person in question are used to correlate the identity of the individual, it takes us to the new field of science—“microbial forensics.” Technological advances in the field of forensics, molecular biology, and microbiology have all helped to refine the techniques of collecting and processing of the samples for microbiological identification using DNA-based methods followed by its inference in the form of evidence. Studies have supported the assumption that skin or surface microflora of an individual is somewhat related with the microflora found on the objects used by that individual and efforts are ongoing to see if this is found consistently in various surroundings and with different individuals. Once established, this technique would facilitate accurate identification and differentiation of an individual or suspect to guide investigations along with conventional evidence. Legal investigations are not only the field where microbial forensic could help. Agriculture, defense, public health, tourism, etc. are the fields wherein microbial forensics with different names based on the fields are helping out and have potential to further support other fields.


id: cord-017272-r5en82s1
title: Health Impact of Urban Physicochemical Environment Considering the Mobility of the People
author: Watanabe, Chiho
date: 2018-08-14
txt: ./txt/cord-017272-r5en82s1.txt
cache: ./cache/cord-017272-r5en82s1.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7121789/
doi: 10.1007/978-981-13-2526-7_2
summary:
  [11] pointed out that due to the accumulation of highly sophisticated spatial and spatiotemporal technology like GIS, GPS, remote sensing, and computer cartography, collectively termed as geographic information science, it becomes possible to model the disease process involving multiple spatiotemporal data obtained in different disciplines. Also, mobility has been one of a classical topic in the area of human ecology since it is associated with the question of how a population utilizes the environment spatially as well as temporally (time allocation studies). Time allocation studies observe the individuals in the targeted field and record the location and type of activity for a given period, which is useful to answer some of the basic questions in human Unlikely Large ecology or other related fields as noted above. A relatively large spatial scale study has been conducted covering approximately 80 × 200 km area in Belgium [3] , which compared regional exposure estimates for two representative air pollutants, NOx and ozone, under two alternative assumptions.

abstract:
  Most of the current environmental health researches assumes that exposure to the environmental agents occurs either in the residence or workplace, neglecting the mobility of the people due to commuting and daily activities. Mobility of the people varies in terms of spatial and temporal range, that is, from momentary short ones to generation-scale long ones. Focusing on the daily movement of the people, various methods for grasping the mobility, which also range from simple observational methods like time allocation to methods with advanced technology like global navigation satellite systems, will be reviewed. Referring environmental health studies examining the health effects of either air pollution or heat, importance of the mobility of the people is discussed. Assessing the mobility will open a new research avenue for the study of infectious diseases as well as noncommunicable diseases.


id: cord-017590-w5copp1z
title: A SIS Epidemiological Model Based on Cellular Automata on Graphs
author: Fresnadillo, María J.
date: 2009
txt: ./txt/cord-017590-w5copp1z.txt
cache: ./cache/cord-017590-w5copp1z.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7122184/
doi: 10.1007/978-3-642-02481-8_160
summary:
  The main goal of this work is to introduce a new SIS epidemic model based on a particular type of finite state machines called cellular automata on graphs. The state of each cell stands for the fraction of the susceptible and infected individuals of the cell at a particular time step and the evolution of these classes is given in terms of a local transition function. The model introduced in this paper deals with SIS epidemic diseases (for example the group of those responsible for the common cold), that is, the population is divided into susceptible individuals (S) and infected individuals (I). The main goal of this work is to introduce a new SIS model to simulate the spread of a general epidemic based on cellular automata on graph. Nevertheless, in this paper we will consider a more efficient topology to model an epidemic disease, which is given by an undirected graph where its nodes stand for the cells of the cellular automata.

abstract:
  The main goal of this work is to introduce a new SIS epidemic model based on a particular type of finite state machines called cellular automata on graphs. The state of each cell stands for the fraction of the susceptible and infected individuals of the cell at a particular time step and the evolution of these classes is given in terms of a local transition function.


id: cord-018101-zd4v222b
title: Disease Outbreaks: Critical Biological Factors and Control Strategies
author: Kawashima, Kent
date: 2016-05-31
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7122892/
doi: 10.1007/978-3-319-39812-9_10
abstract:
  Disease outbreaks remain a major threat to human health and welfare especially in urban areas in both developed and developing countries. A large body of theoretical work has been devoted to modeling disease emergence, and critical factors that predict outbreak occurrence and severity have been proposed. In this chapter, we focus on biological factors that underlie both theoretical models and urban planning. We describe the SARS 2002–2003 pandemic as a case study of epidemic control of a human infectious disease. We then describe theoretical analyses of disease dynamics and control strategies. An important conclusion is that epidemic control will be strongly dependent on particular aspects of pathogen biology including host breadth, virulence, incubation time, and/or mutation rate. The probability, and potential cost, of future outbreaks, may be high and lessons from both past cases and theoretical work should inform urban design and policy. Interdisciplinary collaboration in planning, swiftness of information dissemination and response, and willingness to forgo personal liberties during a crisis may be key factors in resilience to infectious disease outbreaks.


id: cord-018746-s9knxdne
title: Modeling and Predicting Human Infectious Diseases
author: Perra, Nicola
date: 2015-04-23
txt: ./txt/cord-018746-s9knxdne.txt
cache: ./cache/cord-018746-s9knxdne.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7123706/
doi: 10.1007/978-3-319-14011-7_4
summary:
  Building on these concepts we present two realistic data-driven epidemiological models able to forecast the spreading of infectious diseases at different geographical granularities. The unprecedented amount of data on human dynamics made available by recent advances technology has allowed the development of realistic epidemic models able to capture and predict the unfolding of infectious disease at different geographical scales [59] . The new approach allows for the early detection of disease outbreaks [62] , the real time monitoring of the evolution of a disease with an incredible geographical granularity [63] [64] [65] , the access to health related behaviors, practices and sentiments at large scales [66, 67] , inform data-driven epidemic models [68, 69] , and development of statistical based models with prediction power [67, [70] [71] [72] [73] [74] [75] [76] [77] [78] .

abstract:
  The spreading of infectious diseases has dramatically shaped our history and society. The quest to understand and prevent their spreading dates more than two centuries. Over the years, advances in Medicine, Biology, Mathematics, Physics, Network Science, Computer Science, and Technology in general contributed to the development of modern epidemiology. In this chapter, we present a summary of different mathematical and computational approaches aimed at describing, modeling, and forecasting the diffusion of viruses. We start from the basic concepts and models in an unstructured population and gradually increase the realism by adding the effects of realistic contact structures within a population as well as the effects of human mobility coupling different subpopulations. Building on these concepts we present two realistic data-driven epidemiological models able to forecast the spreading of infectious diseases at different geographical granularities. We conclude by introducing some recent developments in diseases modeling rooted in the big-data revolution.


id: cord-019055-k5wcibdk
title: Disease Spreading in Time-Evolving Networked Communities
author: Pacheco, Jorge M.
date: 2017-10-05
txt: ./txt/cord-019055-k5wcibdk.txt
cache: ./cache/cord-019055-k5wcibdk.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7124106/
doi: 10.1007/978-981-10-5287-3_13
summary:
  We show that the effective infectiousness of a disease taking place along the edges of this temporal network depends on the population size, the number of infected individuals in the population and the capacity of healthy individuals to sever contacts with the infected, ultimately dictated by availability of information regarding each individual''s health status. Furthermore, the knowledge an individual has (based on local and/or social media information) about the health status of acquaintances, partners, relatives, etc., combined with individual preventive strategies [42] [43] [44] [45] [46] [47] [48] [49] [50] (such as condoms, vaccination, the use of face masks or prophylactic drugs, avoidance of visiting specific web-pages, staying away from public places, etc.), also leads to changes in the structure and shape of the contact networks that naturally acquire a temporal dimension that one should not overlook.

abstract:
  Human communities are organized in complex webs of contacts that may be represented by a graph or network. In this graph, vertices identify individuals and edges establish the existence of some type of relations between them. In real communities, the possible edges may be active or not for variable periods of time. These so-called temporal networks typically result from an endogenous social dynamics, usually coupled to the process under study taking place in the community. For instance, disease spreading may be affected by local information that makes individuals aware of the health status of their social contacts, allowing them to reconsider maintaining or not their social contacts. Here we investigate the impact of such a dynamical network structure on disease dynamics, where infection occurs along the edges of the network. To this end, we define an endogenous network dynamics coupled with disease spreading. We show that the effective infectiousness of a disease taking place along the edges of this temporal network depends on the population size, the number of infected individuals in the population and the capacity of healthy individuals to sever contacts with the infected, ultimately dictated by availability of information regarding each individual’s health status. Importantly, we also show how dynamical networks strongly decrease the average time required to eradicate a disease.


id: cord-026742-us7llnva
author: Gonçalves, Judite
date: 2020-06-15
txt: ./txt/cord-026742-us7llnva.txt
cache: ./cache/cord-026742-us7llnva.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7293961/
doi: 10.1007/s11187-020-00360-w
summary:
  Our main findings, based on a sample of about 6,500 individuals followed monthly from 2005 to 2011 and who switch between self-employment and wage work along that period, suggest that self-employment has a positive effect on health as it reduces the likelihood of hospital admission by at least half. A recent study finds significantly lower work-related stress among self-employed individuals without employees compared with wage workers, using longitudinal data from Australia and controlling for individual fixed effects (Hessels et al. The main research question in this study is "What is the impact of self-employment on the likelihood of hospital admission?" We answer this question based on a large sample of administrative social security records representative of the working-age population in Portugal, that includes almost 130,000 self-employed and wage workers followed between January 2005 and December 2011.

title:
  Effects of self-employment on hospitalizations: instrumental variables analysis of social security data

abstract:
  The importance of self-employment and small businesses raises questions about their health effects and public policy implications, which can only be addressed with suitable data. We explore the relationship between self-employment and health by drawing on comprehensive longitudinal administrative data to explore variation in individual work status and by applying novel instrumental variables. We focus on an objective outcome—hospital admissions—that is not subject to recall or other biases that may affect previous studies. Our main findings, based on a sample of about 6,500 individuals followed monthly from 2005 to 2011 and who switch between self-employment and wage work along that period, suggest that self-employment has a positive effect on health as it reduces the likelihood of hospital admission by at least half.


id: cord-034566-rfncgtnf
title: Self-reliant India: self of a nation or a national self?
author: Sarukkai, Sundar
date: 2020-11-02
txt: ./txt/cord-034566-rfncgtnf.txt
cache: ./cache/cord-034566-rfncgtnf.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7605322/
doi: 10.1007/s40847-020-00115-z
summary:
  Then I try and attempt to understand why the notion of the self (which is so much related to the individual) is invoked in the context of the nation. As I also mentioned above, these new examples of self-reliance came in response to the prior situation of our society functioning largely as a ''service society'' as well as the deeply social nature of individual lives in places like India. (It is important not to conflate the outsider and the other in this context.) The idea of self-rule is an essential component of any notion of the nation since the nation, by definition, gets defined with respect to the insider-outsider dichotomy. Gandhi''s understanding of self-rule illustrates the need for invoking the idea of self in the context of the nation. The difference between these formulations is quite stark and impacts the way we understand self-reliance in the context of the nation.

abstract:
  The pandemic has led to a renewed reflection on what it means to be self-reliant in terms of our everyday practices. Nations too follow this logic in their own claims of self-reliance. This paper discusses the implications in these claims of self-reliance in the context of the nation by positioning this claim within the tension between two different formulations of the self: self of the nation as against the idea of national self.


id: cord-103291-nqn1qzcu
author: Chapman, Lloyd A. C.
date: 2020-02-25
txt: ./txt/cord-103291-nqn1qzcu.txt
cache: ./cache/cord-103291-nqn1qzcu.txt
extension: .txt
mime: text/plain
url: https://doi.org/10.1101/2020.02.24.20023325
doi: 10.1101/2020.02.24.20023325
summary:
  ú CI = credible interval, calculated as the 95% highest posterior density interval † risk of subsequent VL/asymptomatic infection if susceptible ‡ based on assumed infectiousness § in the absence of background transmission and relative to living directly outside the case household. Based on the relative infectiousness of VL and the di erent 151 types of PKDL from the xenodiagnostic data, in the absence 152 of any other sources of transmission, the estimated probability 153 of being infected and developing VL if living in the same 154 household as a single symptomatic individual for 1 month 155 following their onset was 0.018 (95% CI: 0.013, 0.024) for VL 156 and ranged from 0.009 to 0.023 (95% CIs: (0.007,0.013)-(0.018, 157 0.031)) for macular/papular PKDL to nodular PKDL. We estimate the historical asymptomatic infection rate, ⁄0, by fitting the model to age-prevalence data on leishmanin skin 186 test (LST) positivity amongst non-symptomatic individuals from a cross-sectional survey of three of the study paras conducted 187 in 2002 (28) (see Figure S4 ).

title:
  Inferring transmission trees to guide targeting of interventions against visceral leishmaniasis and post-kala-azar dermal leishmaniasis

abstract:
  Understanding of spatiotemporal transmission of infectious diseases has improved significantly in recent years. Advances in Bayesian inference methods for individual-level geo-located epidemiological data have enabled reconstruction of transmission trees and quantification of disease spread in space and time, while accounting for uncertainty in missing data. However, these methods have rarely been applied to endemic diseases or ones in which asymptomatic infection plays a role, for which novel estimation methods are required. Here, we develop such methods to analyse longitudinal incidence data on visceral leishmaniasis (VL), and its sequela, post-kala-azar dermal leishmaniasis (PKDL), in a highly endemic community in Bangladesh. Incorporating recent data on infectiousness of VL and PKDL, we show that while VL cases drive transmission when incidence is high, the contribution of PKDL increases significantly as VL incidence declines (reaching 55% in this setting). Transmission is highly focal: >85% of mean distances from inferred infectors to their secondary VL cases were <300m, and estimated average times from infector onset to secondary case infection were <4 months for 90% of VL infectors, but up to 2.75yrs for PKDL infectors. Estimated numbers of secondary VL cases per VL and PKDL case varied from 0-6 and were strongly correlated with the infector's duration of symptoms. Counterfactual simulations suggest that prevention of PKDL could have reduced VL incidence by up to a quarter. These results highlight the need for prompt detection and treatment of PKDL to achieve VL elimination in the Indian subcontinent and provide quantitative estimates to guide spatiotemporally-targeted interventions against VL.


id: cord-149069-gpnaldjk
title: A pragmatic approach to account for individual risks to optimise health policy
author: Gomes, M. Gabriela M.
date: 2020-09-02
txt: ./txt/cord-149069-gpnaldjk.txt
cache: ./cache/cord-149069-gpnaldjk.txt
extension: .txt
mime: text/plain
url: https://arxiv.org/pdf/2009.01354v1.pdf
doi: nan
summary:
  As the virus spreads in the human population, individuals at higher risk are predominantly infected as indicated at endemic equilibrium (Figure 1 A, B , C, density plots on the right, coloured red) and after 100 years of control (Figure 1 D, E, F). The control strategy applied to endemic equilibrium in the figure is the 90-90-90 treatment as prevention target advocated by the Joint United Nations Programme on HIV/AIDS 4 whereby 90% of infected individuals should be detected, with 90% of these receiving antiretroviral therapy, and 90% of these should achieve viral suppression (becoming effectively non-infectious). Selection on individual variation in disease susceptibility thus offers an explanation for vaccine efficacy trends that is entirely based on population level heterogeneity, in contrast with waning vaccine-induced immunity, an individual-level effect 20 .

abstract:
  Developing feasible strategies and setting realistic targets for disease prevention and control depends on representative models, whether conceptual, experimental, logistical or mathematical. Mathematical modelling was established in infectious diseases over a century ago, with the seminal works of Ross and others. Propelled by the discovery of etiological agents for infectious diseases, and Koch's postulates, models have focused on the complexities of pathogen transmission and evolution to understand and predict disease trends in greater depth. This has led to their adoption by policy makers; however, as model-informed policies are being implemented, the inaccuracies of some predictions are increasingly apparent, most notably their tendency to overestimate the impact of control interventions. Here, we discuss how these discrepancies could be explained by methodological limitations in capturing the effects of heterogeneity in real-world systems. We suggest that improvements could derive from theory developed in demography to study variation in life-expectancy and ageing. Using simulations, we illustrate the problem and its impact, and formulate a pragmatic way forward.


id: cord-151198-4fjya9wn
title: Ending the COVID-19 epidemic in the United Kingdom
author: Rogers, L C G
date: 2020-04-26
txt: ./txt/cord-151198-4fjya9wn.txt
cache: ./cache/cord-151198-4fjya9wn.txt
extension: .txt
mime: text/plain
url: https://arxiv.org/pdf/2004.12462v1.pdf
doi: nan
summary:
  Social distancing and lockdown are the two main non-pharmaceutical interventions being used by the UK government to contain and control the COVID-19 epidemic; these are being applied uniformly across the entire country, even though the results of the Imperial College report by Ferguson et al show that the impact of the infection increases sharply with age. We will denote by N j (t) the total number of j-individuals in the population at time t, and allow this to change gradually with the influx of new births, visitors from other countries; this is to model the possibility that new infecteds come in from outside and reignite the epidemic. where ι j and σ j are known functions of time representing the arrival of new asymptomatic infec-1 https://colab.research.google.com/drive/1tbB47uSGIA0WehY-hvIYgdO0mpnZU5A8 tives and susceptibles respectively 2 ; and the final term on the right-hand side of (3) allows for the possibility that removed infectives may not in fact be immune, and some may return to the population ready for reinfection.

abstract:
  Social distancing and lockdown are the two main non-pharmaceutical interventions being used by the UK government to contain and control the COVID-19 epidemic; these are being applied uniformly across the entire country, even though the results of the Imperial College report by Ferguson et al show that the impact of the infection increases sharply with age. This paper develops a variant of the workhorse SIR model for epidemics, where the population is classified into a number of age groups. This allows us to understand the effects of age-dependent controls on the epidemic, and explore possible exit strategies.


id: cord-193947-vcm3v0ix
title: Causal Inference for Spatial Treatments
author: Pollmann, Michael
date: 2020-10-31
txt: ./txt/cord-193947-vcm3v0ix.txt
cache: ./cache/cord-193947-vcm3v0ix.txt
extension: .txt
mime: text/plain
url: https://arxiv.org/pdf/2011.00373v1.pdf
doi: nan
summary:
  Even when the differences in levels between inner and outer ring are differenced out with individual fixed effects in panel data, the parallel trends assumption is particularly strong in spatial treatment settings. With individuals and treatment locations distributed across space, a large number of covariates, such as population density or average income at different distances, are predictive of both outcomes and treatment assignment probabilities. In the ideal spatial experiment considered in this section, treatment is randomized similar to a completely randomized experiment across regions with outcomes aggregated within regions (and distance bins).Ë�( ) ( ) is the variance of aggregated treated potential outcomes,Ë�( 0) ( ) is the variance of aggregated control potential outcomes, and ( ) ( ) resembles a variance of treatment effects, such thatË�( ) ( ) +Ë�( 0) ( ) â�� ( ) ( ) resembles the variance of the difference in means under repeated sampling of fixed individuals but varying treatment assignment, the framework of this paper.

abstract:
  I propose a framework, estimators, and inference procedures for the analysis of causal effects in a setting with spatial treatments. Many events and policies (treatments), such as opening of businesses, building of hospitals, and sources of pollution, occur at specific spatial locations, with researchers interested in their effects on nearby individuals or businesses (outcome units). However, the existing treatment effects literature primarily considers treatments that could be assigned directly at the level of the outcome units, potentially with spillover effects. I approach the spatial treatment setting from a similar experimental perspective: What ideal experiment would we design to estimate the causal effects of spatial treatments? This perspective motivates a comparison between individuals near realized treatment locations and individuals near unrealized candidate locations, which is distinct from current empirical practice. Furthermore, I show how to find such candidate locations and apply the proposed methods with observational data. I apply the proposed methods to study the causal effects of grocery stores on foot traffic to nearby businesses during COVID-19 lockdowns.


id: cord-198272-s0lk1812
title: Controlling the Outbreak of COVID-19: A Noncooperative Game Perspective
author: Bairagi, Anupam Kumar
date: 2020-07-27
txt: ./txt/cord-198272-s0lk1812.txt
cache: ./cache/cord-198272-s0lk1812.txt
extension: .txt
mime: text/plain
url: https://arxiv.org/pdf/2007.13305v1.pdf
doi: nan
summary:
  Furthermore, the sustainability of the lockdown policy is interpreted with the help of our proposed game-theoretic incentive model for maintaining social distancing where there exists a Nash equilibrium. Finally, we perform an extensive numerical analysis that shows the effectiveness of the proposed approach in terms of achieving the desired social-distancing to prevent the outbreak of the COVID-19 in a noncooperative environment. Therefore, different from the existing literature, we focus on the design of a model that can measure individual''s isolation and social distance to prevent the epidemic of COVID-19. The model considers both isolation and social distancing features of individuals to control the outbreak of COVID-19. Our objective is to keep δ minimum for reducing the spread of COVID-19 from infected individuals, which is an isolation strategy. In this paper, we have introduced a mathematical model for controlling the outbreak of COVID-19 by augmenting isolation and social distancing features of individuals.

abstract:
  COVID-19 is a global epidemic. Till now, there is no remedy for this epidemic. However, isolation and social distancing are seemed to be effective preventive measures to control this pandemic. Therefore, in this paper, an optimization problem is formulated that accommodates both isolation and social distancing features of the individuals. To promote social distancing, we solve the formulated problem by applying a noncooperative game that can provide an incentive for maintaining social distancing to prevent the spread of COVID-19. Furthermore, the sustainability of the lockdown policy is interpreted with the help of our proposed game-theoretic incentive model for maintaining social distancing where there exists a Nash equilibrium. Finally, we perform an extensive numerical analysis that shows the effectiveness of the proposed approach in terms of achieving the desired social-distancing to prevent the outbreak of the COVID-19 in a noncooperative environment. Numerical results show that the individual incentive increases more than 85% with an increasing percentage of home isolation from 25% to 100% for all considered scenarios. The numerical results also demonstrate that in a particular percentage of home isolation, the individual incentive decreases with an increasing number of individuals.


id: cord-223332-51670qld
title: An operational architecture for privacy-by-design in public service applications
author: Agrawal, Prashant
date: 2020-06-08
txt: ./txt/cord-223332-51670qld.txt
cache: ./cache/cord-223332-51670qld.txt
extension: .txt
mime: text/plain
url: https://arxiv.org/pdf/2006.04654v1.pdf
doi: nan
summary:
  In this paper, we present an operational architecture for privacy-by-design based on independent regulatory oversight stipulated by most data protection regimes, regulated access control, purpose limitation and data minimisation. an interest in preventing information about the self from being disseminated and controlling the extent of access to information." It would be the role of a future Indian data protection law to create some objective standards for informational privacy to give all actors in society an understanding of the "ground rules" for accessing an individuals'' personal information. The need for early alignment of legal and technical design principles of data systems, such as access controls, purpose limitation and clear liability frameworks under appropriate regulatory jurisdictions are essential to create secure and trustworthy public data infrastructures [5, 6, 7] . We have presented the design sketch of an operational architecture for privacy-by-design [3] based on regulatory oversight, regulated access control, purpose limitation and data minimisation.

abstract:
  Governments around the world are trying to build large data registries for effective delivery of a variety of public services. However, these efforts are often undermined due to serious concerns over privacy risks associated with collection and processing of personally identifiable information. While a rich set of special-purpose privacy-preserving techniques exist in computer science, they are unable to provide end-to-end protection in alignment with legal principles in the absence of an overarching operational architecture to ensure purpose limitation and protection against insider attacks. This either leads to weak privacy protection in large designs, or adoption of overly defensive strategies to protect privacy by compromising on utility. In this paper, we present an operational architecture for privacy-by-design based on independent regulatory oversight stipulated by most data protection regimes, regulated access control, purpose limitation and data minimisation. We briefly discuss the feasibility of implementing our architecture based on existing techniques. We also present some sample case studies of privacy-preserving design sketches of challenging public service applications.


id: cord-227156-uy4dykhg
title: Predicting Shifting Individuals Using Text Mining and Graph Machine Learning on Twitter
author: Albanese, Federico
date: 2020-08-24
txt: ./txt/cord-227156-uy4dykhg.txt
cache: ./cache/cord-227156-uy4dykhg.txt
extension: .txt
mime: text/plain
url: https://arxiv.org/pdf/2008.10749v1.pdf
doi: nan
summary:
  Moreover, this machine learning framework allows us to identify not only which topics are more persuasive (using low dimensional topic embedding), but also which individuals are more likely to change their affiliation given their topological properties in a Twitter graph. Using graph topological information and detecting topics of discussion of the first network, we built and trained a model that effectively predicts when an individual will change his/her community over time, identifying persuasive topics and relevant features of the shifting users. Given that our objective was to identify shifting individuals and persuasive arguments, we implemented a predictive model whose instances are the Twitter users who were active during both time periods [34] and belonged to one of the biggest communities in both time periods networks. In this paper we presented a machine learning framework approach in order to identify shifting individuals and persuasive topics that, unlike previous works, focused on the persuadable users rather than studying the political polarization on social media as a whole.

abstract:
  The formation of majorities in public discussions often depends on individuals who shift their opinion over time. The detection and characterization of these type of individuals is therefore extremely important for political analysis of social networks. In this paper, we study changes in individual's affiliations on Twitter using natural language processing techniques and graph machine learning algorithms. In particular, we collected 9 million Twitter messages from 1.5 million users and constructed the retweet networks. We identified communities with explicit political orientation and topics of discussion associated to them which provide the topological representation of the political map on Twitter in the analyzed periods. With that data, we present a machine learning framework for social media users classification which efficiently detects"shifting users"(i.e. users that may change their affiliation over time). Moreover, this machine learning framework allows us to identify not only which topics are more persuasive (using low dimensional topic embedding), but also which individuals are more likely to change their affiliation given their topological properties in a Twitter graph.


id: cord-243634-4qcq5soy
title: PeopleTraffic: a common framework for harmonizing privacy and epidemic risks
author: Caravita, Ruggero
date: 2020-05-20
txt: ./txt/cord-243634-4qcq5soy.txt
cache: ./cache/cord-243634-4qcq5soy.txt
extension: .txt
mime: text/plain
url: https://arxiv.org/pdf/2005.10061v1.pdf
doi: nan
summary:
  The system is based on a real-time people'' locations gathering and mapping system from available 2G, 3G and 4G mobile networks operators, enforcing privacy-by-design through the adoption of an innovative data anonymizing algorithm inspired by quantum information de-localizing processes. Here we consider the two limiting cases: A) the mere counting of number of connections per mobile network cell (also known as localization through cell identity, CI) and B) accurate individual UE positioning by the net-work via the highest accuracy available methods, e.g. RSSI triangulation or observed time difference of arrival (OTDOA). The spatial resolution analysis here performed shows that anonymous number of connections data (scenario A) could provide reliable information about population density on the scale of hundreds of meters in most urban contexts, i.e. allowing only big crowds to be distinguished, unless further capillarization of the networks are made available.

abstract:
  PeopleTraffic is a proposed initiative to develop a real-time, open-data population density mapping tool open to public institutions, private companies and the civil society, providing a common framework for infection spreading prevention. The system is based on a real-time people' locations gathering and mapping system from available 2G, 3G and 4G mobile networks operators, enforcing privacy-by-design through the adoption of an innovative data anonymizing algorithm inspired by quantum information de-localizing processes. Besides being originally targeted to help balancing social distancing regulations during the Phase-2 of the COVID-19 pandemics, PeopleTraffic would be beneficial for any infection spreading prevention event, e.g. supporting policy-makers in strategic decision-making.


id: cord-253711-a0prku2k
author: Mao, Liang
date: 2011-11-26
txt: ./txt/cord-253711-a0prku2k.txt
cache: ./cache/cord-253711-a0prku2k.txt
extension: .txt
mime: text/plain
url: https://www.sciencedirect.com/science/article/pii/S0277953611006551
doi: 10.1016/j.socscimed.2011.10.012
summary:
  title: Coupling infectious diseases, human preventive behavior, and networks – A conceptual framework for epidemic modeling Both infectious diseases and preventive behavior diffuse simultaneously through human networks and interact with one another, but few existing models have coupled them together. In the current literature, models of disease transmission and behavioral diffusion have been developed separately for decades, both based on human networks (Deffuant, Huet, & Amblard, 2005; Keeling & Eames, 2005; Valente, 1996; Watts & Strogatz, 1998) . Corresponding to the five assumptions, this article introduces a number of approaches to represent individuals, networks, infectious diseases, and preventive behavior, as four model components, and depicts the relationships between the four. To illustrate the proposed coupled-diffusion model, an influenza epidemic was simulated in a hypothetic population of 5000 individuals (N ¼ 5000), each with characteristics and behaviors as described in Fig. 2 . The key to simulate the diffusion of preventive behavior was to estimate thresholds of infection risk and that of adoption pressure for individuals.

title:
  Coupling infectious diseases, human preventive behavior, and networks – A conceptual framework for epidemic modeling

abstract:
  Human-disease interactions involve the transmission of infectious diseases among individuals and the practice of preventive behavior by individuals. Both infectious diseases and preventive behavior diffuse simultaneously through human networks and interact with one another, but few existing models have coupled them together. This article proposes a conceptual framework to fill this knowledge gap and illustrates the model establishment. The conceptual model consists of two networks and two diffusion processes. The two networks include: an infection network that transmits diseases and a communication network that channels inter-personal influence regarding preventive behavior. Both networks are composed of same individuals but different types of interactions. This article further introduces modeling approaches to formulize such a framework, including the individual-based modeling approach, network theory, disease transmission models and behavioral models. An illustrative model was implemented to simulate a coupled-diffusion process during an influenza epidemic. The simulation outcomes suggest that the transmission probability of a disease and the structure of infection network have profound effects on the dynamics of coupled-diffusion. The results imply that current models may underestimate disease transmissibility parameters, because human preventive behavior has not been considered. This issue calls for a new interdisciplinary study that incorporates theories from epidemiology, social science, behavioral science, and health psychology.


id: cord-262966-8b1esll4
author: Huang, Ganyu
date: 2020-04-07
txt: ./txt/cord-262966-8b1esll4.txt
cache: ./cache/cord-262966-8b1esll4.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pubmed/32288415/
doi: 10.1007/s12204-020-2167-2
summary:
  Furthermore, we propose the BAT model, which is composed of three parts: simulation of the return rush (Back), analytic hierarchy process (AHP) method, and technique for order preference by similarity to an ideal solution (TOPSIS) method, to figure out the best return date for university students. Nomenclature c-The average number of contacts of an exposed person without isolation each day n-The number of individuals nD-The death toll nE-The number of exposed individuals nI-The number of infectious individuals nR-The number of recovered individuals nS-The number of susceptible individuals N -The total population of China p-Intensity of isolation for exposed individuals r-Correlation coefficient R 2 -Coefficient of determination t0-Moment when the government began to take measures t-Outbreak duration α-Incubation rate β-Infectious rate of contacts of an exposed person γ-Recovery rate μ-Pneumonia mortality 0 Introduction On 12 December 2019, the first patient with unexplained pneumonia was admitted into the hospital in Wuhan.

title:
  Prediction of COVID-19 Outbreak in China and Optimal Return Date for University Students Based on Propagation Dynamics

abstract:
  On 12 December 2019, a novel coronavirus disease, named COVID-19, began to spread around the world from Wuhan, China. It is useful and urgent to consider the future trend of this outbreak. We establish the 4+1 penta-group model to predict the development of the COVID-19 outbreak. In this model, we use the collected data to calibrate the parameters, and let the recovery rate and mortality change according to the actual situation. Furthermore, we propose the BAT model, which is composed of three parts: simulation of the return rush (Back), analytic hierarchy process (AHP) method, and technique for order preference by similarity to an ideal solution (TOPSIS) method, to figure out the best return date for university students. We also discuss the impacts of some factors that may occur in the future, such as secondary infection, emergence of effective drugs, and population flow from Korea to China.


id: cord-265372-vytmwmoj
title: Control Strategies to Curtail Transmission of COVID-19
author: Shah, Nita H
date: 2020-04-07
txt: ./txt/cord-265372-vytmwmoj.txt
cache: ./cache/cord-265372-vytmwmoj.txt
extension: .txt
mime: text/plain
url: https://doi.org/10.1101/2020.04.04.20053173
doi: 10.1101/2020.04.04.20053173
summary:
  During the initial stages of COVID-19 outbreak, such human transmissions were taking place because, wide-range of public was unaware of these risk factors, and the infected individuals were also not isolated and were spreading the virus unknowingly to other individuals. Moreover, to minimise mortality rate of COVID-19, 3 u control variable is taken which helps to reduce critically infected cases by taking extra medical care of infected individuals. [1] In this section, the COVID-19 model is simulated numerically, wherein the parametric values for simulation are taken from recent pandemic outbreak of coronavirus (https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports). Figure 6 (e) shows that mortality rate due to COVID-19 can be reduced effectively within three weeks of outbreak by applying 1 u , 2 u and 3 u control strategies. That means self-quarantine for an exposed individual, isolation of an infected individual and reducing critical cases by taking extra care of infected individuals are effective strategies to control further transmission of COVID-19.

abstract:
  Recently, the World Health Organization has declared the outbreak of a severe acute respiratory syndrome coronavirius as a pandemic, and declared it as Public Health Emergency of International Concern. More than 6,83,536 positive cases and 32,139 deaths caused by coronavirus 2019 affecting 199 countries and territories. This pandemic can transform into an extremely destructive form if we still do not take it seriously. In this present study, we propose a generalized SEIR model of COVID-2019 to study the behavior of its transmission under different control strategies.


id: cord-268298-25brblfq
author: Mao, Liang
date: 2014-03-04
txt: ./txt/cord-268298-25brblfq.txt
cache: ./cache/cord-268298-25brblfq.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pubmed/32287519/
doi: 10.1016/j.apgeog.2014.02.005
summary:
  title: Modeling triple-diffusions of infectious diseases, information, and preventive behaviors through a metropolitan social network—An agent-based simulation The disease could be transmitted through person-to-person contact, the information is circulated by communication channels, and the preventive behavior can spread via the ''social contagion'' process, such as the observational learning. Without a complete model, health policy makers would not be able to systematically evaluate social-network interventions for disease control, such as mass-media campaigns and behavior promotion strategies. First, the event of symptom manifestation will motivate individuals to discuss disease information, and prompt their social contacts to adopt preventive behavior by posing infection risks. The conceptual framework integrates three interactive processes: the diffusion of influenza, the diffusion of information, and that of preventive behavior, upon a human social network. Particularly, since the model explicitly represents the diffusion of information and human preventive behavior, it permits a systematic evaluation of disease control policies that have not been well studied before, such as the mass-media campaigns and behavioral incentive strategies.

title:
  Modeling triple-diffusions of infectious diseases, information, and preventive behaviors through a metropolitan social network—An agent-based simulation

abstract:
  A typical epidemic often involves the transmission of a disease, the flow of information regarding the disease, and the spread of human preventive behaviors against the disease. These three processes diffuse simultaneously through human social networks, and interact with one another, forming negative and positive feedback loops in the complex human-disease systems. Few studies, however, have been devoted to coupling all the three diffusions together and representing their interactions. To fill the knowledge gap, this article proposes a spatially explicit agent-based model to simulate a triple-diffusion process in a metropolitan area of 1 million people. The individual-based approach, network model, behavioral theories, and stochastic processes are used to formulate the three diffusions and integrate them together. Compared to the observed facts, the model results reasonably replicate the trends of influenza spread and information propagation. The model thus could be a valid and effective tool to evaluate information/behavior-based intervention strategies. Besides its implications to the public health, the research findings also contribute to network modeling, systems science, and medical geography.


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-281836-j1r771nq
author: Hernando-Amado, Sara
date: 2020-08-28
url: https://www.ncbi.nlm.nih.gov/pubmed/32983000/
doi: 10.3389/fmicb.2020.01914
title:
  Antibiotic Resistance: Moving From Individual Health Norms to Social Norms in One Health and Global Health

abstract:
  Antibiotic resistance is a problem for human health, and consequently, its study had been traditionally focused toward its impact for the success of treating human infections in individual patients (individual health). Nevertheless, antibiotic-resistant bacteria and antibiotic resistance genes are not confined only to the infected patients. It is now generally accepted that the problem goes beyond humans, hospitals, or long-term facility settings and that it should be considered simultaneously in human-connected animals, farms, food, water, and natural ecosystems. In this regard, the health of humans, animals, and local antibiotic-resistance–polluted environments should influence the health of the whole interconnected local ecosystem (One Health). In addition, antibiotic resistance is also a global problem; any resistant microorganism (and its antibiotic resistance genes) could be distributed worldwide. Consequently, antibiotic resistance is a pandemic that requires Global Health solutions. Social norms, imposing individual and group behavior that favor global human health and in accordance with the increasingly collective awareness of the lack of human alienation from nature, will positively influence these solutions. In this regard, the problem of antibiotic resistance should be understood within the framework of socioeconomic and ecological efforts to ensure the sustainability of human development and the associated human–natural ecosystem interactions.


id: cord-282035-jibmg4ch
author: Dunbar, R. I. M.
date: 2020-08-26
url: https://doi.org/10.1098/rspa.2020.0446
doi: 10.1098/rspa.2020.0446
title:
  Structure and function in human and primate social networks: implications for diffusion, network stability and health

abstract:
  The human social world is orders of magnitude smaller than our highly urbanized world might lead us to suppose. In addition, human social networks have a very distinct fractal structure similar to that observed in other primates. In part, this reflects a cognitive constraint, and in part a time constraint, on the capacity for interaction. Structured networks of this kind have a significant effect on the rates of transmission of both disease and information. Because the cognitive mechanism underpinning network structure is based on trust, internal and external threats that undermine trust or constrain interaction inevitably result in the fragmentation and restructuring of networks. In contexts where network sizes are smaller, this is likely to have significant impacts on psychological and physical health risks.


id: cord-284424-6gljl7n5
author: Brown, Eric E.
date: 2020-04-18
txt: ./txt/cord-284424-6gljl7n5.txt
cache: ./cache/cord-284424-6gljl7n5.txt
extension: .txt
mime: text/plain
url: https://www.sciencedirect.com/science/article/pii/S1064748120302943?v=s5
doi: 10.1016/j.jagp.2020.04.010
summary:
  The COVID-19 pandemic is causing global morbidity and mortality, straining health systems, and disrupting society, putting individuals with Alzheimer''s disease and related dementias (ADRD) at risk of significant harm. We discuss and propose mitigation strategies for: the risk of COVID-19 infection and its associated morbidity and mortality for individuals with ADRD; the impact of COVID-19 on the diagnosis and clinical management of ADRD; consequences of societal responses to COVID-19 in different ADRD care settings; the effect of COVID-19 on caregivers and physicians of individuals with ADRD; mental hygiene, trauma, and stigma in the time of COVID-19; and the potential impact of COVID-19 on ADRD research. Thus, in the context of a rapidly evolving situation, this Special Article discusses and proposes mitigation strategies for six major issues: (1) why individuals with ADRD are at high risk for COVID-19 and its associated morbidity and mortality; (2) how COVID-19 will impact the diagnosis and clinical 

title:
  Anticipating and Mitigating the Impact of COVID-19 Pandemic on Alzheimer''s Disease and Related Dementias

abstract:
  The COVID-19 pandemic is causing global morbidity and mortality, straining health systems, and disrupting society, putting individuals with Alzheimer's disease and related dementias (ADRD) at risk of significant harm. In this Special Article, we examine the current and expected impact of the pandemic on individuals with ADRD. We discuss and propose mitigation strategies for: the risk of COVID-19 infection and its associated morbidity and mortality for individuals with ADRD; the impact of COVID-19 on the diagnosis and clinical management of ADRD; consequences of societal responses to COVID-19 in different ADRD care settings; the effect of COVID-19 on caregivers and physicians of individuals with ADRD; mental hygiene, trauma, and stigma in the time of COVID-19; and the potential impact of COVID-19 on ADRD research. Amid considerable uncertainty, we may be able to prevent or reduce the harm of the COVID-19 pandemic and its consequences for individuals with ADRD and their caregivers.


id: cord-288024-1mw0k5yu
title: Entrepreneurial entry: The role of social media
author: Wang, Wei
date: 2020-09-29
txt: ./txt/cord-288024-1mw0k5yu.txt
cache: ./cache/cord-288024-1mw0k5yu.txt
extension: .txt
mime: text/plain
url: https://www.sciencedirect.com/science/article/pii/S004016252031163X
doi: 10.1016/j.techfore.2020.120337
summary:
  Thus, we propose that trust propensity, an individual''s tendency to believe in others (Choi, 2019; Gefen et al., 2003) , moderates the relationship between social media use and entrepreneurial entry. Our findings reveal that social media use https://doi.org/10.1016/j.techfore.2020.120337 Received 8 August 2020; Accepted 21 September 2020 has a positive impact on entrepreneurial entry with individuals'' offline network serving as a partial mediator. Second, our study specified a mechanism for the impact of individuals'' social media use on entrepreneurial entry via their offline network and used instrumental variables to help infer the causality. Thus, with higher social media use, individuals will have an expanded offline social network, which provides them the resources needed for successful entrepreneurial entry. We believe trust propensity in social media moderates the impact of individuals'' social media use on entrepreneurial entry by influencing their ability to network with strangers and known associates.

abstract:
  Despite the exponential growth of social media use, whether and how social media use may affect entrepreneurial entry remains a key research gap. In this study we examine whether individuals’ social media use influences their entrepreneurial entry. Drawing on social network theory, we argue that social media use allows individuals to obtain valuable social capital, as indicated by their offline social network, which increases their entrepreneurial entry. We further posit the relationship between social media use and entrepreneurial entry depends on individuals’ trust propensity based on the nature of social media as weak ties. Our model was supported by a nationally representative survey of 18,873 adults in China over two years. As the first paper on the role of social media on entrepreneurial entry, we hope our research highlights and puts forward research intersecting social media and entrepreneurship.


id: cord-288342-i37v602u
title: Coupled disease–behavior dynamics on complex networks: A review
author: Wang, Zhen
date: 2015-07-08
url: https://www.sciencedirect.com/science/article/pii/S1571064515001372
doi: 10.1016/j.plrev.2015.07.006
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-302937-3yivxfi8
title: Indemnifying precaution: economic insights for regulation of a highly infectious disease
author: Robertson, Christopher T
date: 2020-05-30
txt: ./txt/cord-302937-3yivxfi8.txt
cache: ./cache/cord-302937-3yivxfi8.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pubmed/32733690/
doi: 10.1093/jlb/lsaa032
summary:
  For insights, we review health insurance moral hazard, agricultural infectious disease policy, and deterrence theory, but find that classic enforcement strategies of punishing noncompliant people are stymied. Under a strategy of social distancing, lockdown, or quarantine, individuals are directed or suggested to exercise precautions including staying home, closing businesses, wearing masks, and avoiding physical proximity to other persons. 17 For health insurance design, primary moral hazard may have a relatively small effect on risk-taking behavior, because individuals personally suffer many of the other risks associated with illness or injury (including pain, suffering, lost work, chance of death). In this case, although the risk does not approach zero, it is as if relative youth provides partial indemnity insurance against not only the healthcare costs, but also the pain, suffering, lost work, and chance of death that are associated with COVID-19 infection.

abstract:
  Economic insights are powerful for understanding the challenge of managing a highly infectious disease, such as COVID-19, through behavioral precautions including social distancing. One problem is a form of moral hazard, which arises when some individuals face less personal risk of harm or bear greater personal costs of taking precautions. Without legal intervention, some individuals will see socially risky behaviors as personally less costly than socially beneficial behaviors, a balance that makes those beneficial behaviors unsustainable. For insights, we review health insurance moral hazard, agricultural infectious disease policy, and deterrence theory, but find that classic enforcement strategies of punishing noncompliant people are stymied. One mechanism is for policymakers to indemnify individuals for losses associated with taking those socially desirable behaviors to reduce the spread. We develop a coherent approach for doing so, based on conditional cash payments and precommitments by citizens, which may also be reinforced by social norms.


id: cord-306056-4jx0u7js
title: “Diseases and Natural Kinds”
author: Sulmasy, Daniel P.
date: 2005
txt: ./txt/cord-306056-4jx0u7js.txt
cache: ./cache/cord-306056-4jx0u7js.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pubmed/16292605/
doi: 10.1007/s11017-005-2206-x
summary:
  (3) The aim of this classification must be to provide at least a provisional basis for explaining the causes and/or natural history of a disturbance in the internal biological relations of the affected members of X (and, if X is a self-reflective natural kind, can serve as an explanation of the illness of those so affected), (4) and at least some individuals of whom (or which) this class of states of affairs can be predicated are, by virtue of that state, inhibited from flourishing as Xs. I must further explicate this fairly dense definition. H. Setting as the telos the flourishing of the individual as the kind of thing that it is also explains why it can be controversial to classify as diseases certain patterns of variation in the law-like biological principles that determine the characteristic development and typical history of a living natural kind.

abstract:
  David Thomasma called for the development of a medical ethics based squarely on the philosophy of medicine. He recognized, however, that widespread anti-essentialism presented a significant barrier to such an approach. The aim of this article is to introduce a theory that challenges these anti-essentialist objections. The notion of natural kinds presents a modest form of essentialism that can serve as the basis for a foundationalist philosophy of medicine. The notion of a natural kind is neither static nor reductionistic. Disease can be understood as making necessary reference to living natural kinds without invoking the claim that diseases themselves are natural kinds. The idea that natural kinds have a natural disposition to flourish as the kinds of things that they are provides a telos to which to tether the notion of disease – an objective telos that is broader than mere survival and narrower than subjective choice. It is argued that while nosology is descriptive and may have therapeutic implications, disease classification is fundamentally explanatory. Sickness and illness, while referring to the same state of affairs, can be distinguished from disease phenomenologically. Scientific and diagnostic fallibility in making judgments about diseases do not diminish the objectivity of this notion of disease. Diseases are things, not kinds. Injury is a concept parallel to disease that also makes necessary reference to living natural kinds. These ideas provide a new possibility for the development of a philosophy of medicine with implications for medical ethics.


id: cord-308261-hxlebas8
author: Broekhuis, Femke
date: 2019-04-03
txt: ./txt/cord-308261-hxlebas8.txt
cache: ./cache/cord-308261-hxlebas8.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pubmed/30943236/
doi: 10.1371/journal.pone.0213910
summary:
  title: Using GPS collars to investigate the frequency and behavioural outcomes of intraspecific interactions among carnivores: A case study of male cheetahs in the Maasai Mara, Kenya To determine the static interactions between male cheetahs we calculated their space use and the amount of overlap for each dyad to determine the possibility that individuals could encounter each other either directly or indirectly. In general, cheetahs were closer to the encounter location after a possible encounter compared to before for all four time lags, apart from individual M03 in Dyad 3 where the opposite trend was Intraspecific interactions among carnivores: A case study of male cheetahs observed, however none of the results were significant (S1 Table) . Using GPS collar data we documented static and dynamic interactions between male cheetahs in Kenya''s Maasai Mara and investigated the outcomes of these interactions in terms of movement behaviour and mortalities.

title:
  Using GPS collars to investigate the frequency and behavioural outcomes of intraspecific interactions among carnivores: A case study of male cheetahs in the Maasai Mara, Kenya

abstract:
  Intraspecific interactions between individuals or groups of individuals of the same species are an important component of population dynamics. Interactions can be static, such as spatial overlap, or dynamic based on the interactions of movements, and can be mediated through communication, such as the deployment of scent marks. Interactions and their behavioural outcomes can be difficult to determine, especially for species that live at low densities. With the use of GPS collars we quantify both static and dynamic interactions between male cheetahs (Acinonyx jubatus) and the behavioural outcomes. The 99% home-ranges of males overlapped significantly while there was little overlap of the 50% home-ranges. Despite this overlap, male cheetahs rarely came into close proximity of one another, possibly because presence was communicated through frequent visits to marking posts. The minimum distance between individuals in a dyad ranged from 89m to 196m but the average proximity between individuals ranged from 17,145 ± 6,865m to 26,367 ± 11,288m. Possible interactions took place more frequently at night than by day and occurred mostly in the 50% home-range of one individual of a dyad or where cores of both individuals overlapped. After a possible encounter male cheetahs stayed in close proximity to each other for up to 6 hours, which could be the result of a territory defence strategy or the presence of a receptive female. We believe that one of the encounters between a singleton and a 5-male coalition resulted in the death of the singleton. Our results give new insights into cheetah interactions, which could help our understanding of ecological processes such as disease transmission.


id: cord-319170-idv2cio4
author: Devita, Maria
date: 2020-06-24
txt: ./txt/cord-319170-idv2cio4.txt
cache: ./cache/cord-319170-idv2cio4.txt
extension: .txt
mime: text/plain
url: https://doi.org/10.1007/s40520-020-01637-6
doi: 10.1007/s40520-020-01637-6
abstract: nan
summary:
  An increasing amount of data is becoming available on the psychological and social problems resulting from Covid-19 and the interventions to tackle them in the general population [3] ; yet little attention is being paid to elderly population and, in particular, to a frail subgroup of this age: individuals with neurocognitive disorders. Finally, also the possible motor impairments associated to quarantine should not be underestimated: a forced reduction of motor/physical activity can cause, particularly in older individuals with neurocognitive disorders, a progressive loss of personal and instrumental autonomy, as well as a possible worsening of other agingrelated clinical problems, as sarcopenia, with a consequent increased risk of falls, and subsequent medical geriatrics complications. Although the face-to-face clinical visit is undoubtedly always fundamental for cognitive impairment diagnosis and follow-up, remote assessment could be a valid transitional measure for public health needs in the coming months, and would guarantee continuity in patient care (against the currently imposed, though necessary, interruption), while reducing the risk of contagion and the consequent potential negative outcome of infection.

title:
  The psychological and cognitive impact of Covid-19 on individuals with neurocognitive impairments: research topics and remote intervention proposals


id: cord-320953-1st77mvh
author: Overton, ChristopherE.
date: 2020-07-04
url: https://doi.org/10.1016/j.idm.2020.06.008
doi: 10.1016/j.idm.2020.06.008
title:
  Using statistics and mathematical modelling to understand infectious disease outbreaks: COVID-19 as an example

abstract:
  During an infectious disease outbreak, biases in the data and complexities of the underlying dynamics pose significant challenges in mathematically modelling the outbreak and designing policy. Motivated by the ongoing response to COVID-19, we provide a toolkit of statistical and mathematical models beyond the simple SIR-type differential equation models for analysing the early stages of an outbreak and assessing interventions. In particular, we focus on parameter estimation in the presence of known biases in the data, and the effect of non-pharmaceutical interventions in enclosed subpopulations, such as households and care homes. We illustrate these methods by applying them to the COVID-19 pandemic.


id: cord-321491-d0y7r4di
title: Coronavirus‐like particles in adults in melbourne, Australia
author: Marshall, J. A.
date: 2005-12-09
txt: ./txt/cord-321491-d0y7r4di.txt
cache: ./cache/cord-321491-d0y7r4di.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pubmed/2559950/
doi: 10.1002/jmv.1890290404
summary:
  CVLP was found most commonly in three groups: first, intellectually retarded individuals who were usually inmates of institutions; second, recent overseas travellers who were either Indochinese refugees/immigrants or were overseas travellers who had usually visited developing communities for lengthy periods; and, third, male homosexuals who had a history of multiple sexual contacts and/or venereal disease. One individual who was intellectually handicapped but not institutionalised was in the CVLP-excreting gastroenteritis group (Table I) . Two individuals, both male homosexuals, belonged to this category in the CVLP excreting gastroenteritis group (Table I) . (In addition, one over-seas traveller with gastroenteritis, a male airline steward who was excreting CVLP, was also noted to be a homosexual with a history of multiple sexual contacts and venereal disease). In the histories of individuals in the unclassified category of the gastroenteritis control group, no such relationship with poor hygiene was noted.

abstract:
  Coronavirus‐like particle(s) (CVLP) are faecal‐derived pleomorphic membrane bound virus‐like particles characterised by a fringe of clubshaped spikes that measure about 27 nm in length. The association of CVLP with a variety of social, clinical, and epidemiological factors was examined after a 69 month survey of faeces received for routine testing at an infectious diseases hospital. CVLP was found most commonly in three groups: first, intellectually retarded individuals who were usually inmates of institutions; second, recent overseas travellers who were either Indochinese refugees/immigrants or were overseas travellers who had usually visited developing communities for lengthy periods; and, third, male homosexuals who had a history of multiple sexual contacts and/or venereal disease. It was concluded that the excretion of CVLP had a strong association with unhygienic living or working conditions irrespective of any clinical symptoms the individual might show.


id: cord-336283-3q0ujnjq
title: The Nature and Treatment of Pandemic-Related Psychological Distress
author: Sanderson, William C.
date: 2020-06-27
txt: ./txt/cord-336283-3q0ujnjq.txt
cache: ./cache/cord-336283-3q0ujnjq.txt
extension: .txt
mime: text/plain
url: https://doi.org/10.1007/s10879-020-09463-7
doi: 10.1007/s10879-020-09463-7
summary:
  Scientific data are not available to fully understand the nature of the resulting mental health impact given the very recent onset of the pandemic, nevertheless, there is a need to act immediately to develop psychotherapeutic strategies that may alleviate pandemic-related distress. The psychological distress, in particular fear and sadness, is a function of the pandemic''s negative impact upon people''s ability to meet their most basic needs (e.g., physical safety, financial security, social connection, participation in meaningful activities). Once we created this list we developed strategies that would allow people to manage these negative emotional states using a self-help format (this guide can be accessed at www.psych rescu e-covid 19.com or at the permanent DOI address provided in the reference section). While there has been progress, as outlined above, in understanding the nature and interventions for COVID related psychological distress, an additional problem has emerged as a result: the already overburdened mental health system must now provide treatment for a substantial wave of persons in need.

abstract:
  The COVID-19 crisis has created a “mental health pandemic” throughout the world. Scientific data are not available to fully understand the nature of the resulting mental health impact given the very recent onset of the pandemic, nevertheless, there is a need to act immediately to develop psychotherapeutic strategies that may alleviate pandemic-related distress. The psychological distress, in particular fear and sadness, is a function of the pandemic’s negative impact upon people’s ability to meet their most basic needs (e.g., physical safety, financial security, social connection, participation in meaningful activities). This paper presents evidence-based cognitive behavioral strategies that should prove useful in reducing the emotional suffering associated with the COVID crisis.


id: cord-337992-g4bsul8u
title: Stochastic dynamics of an epidemic with recurrent spillovers from an endemic reservoir
author: Voinson, Marina
date: 2018-11-14
url: https://doi.org/10.1016/j.jtbi.2018.08.017
doi: 10.1016/j.jtbi.2018.08.017
abstract:
  Abstract Most emerging human infectious diseases have an animal origin. While zoonotic diseases originate from a reservoir, most theoretical studies have principally focused on single-host processes, either exclusively humans or exclusively animals, without considering the importance of animal to human transmission (i.e. spillover transmission) for understanding the dynamics of emerging infectious diseases. Here we aim to investigate the importance of spillover transmission for explaining the number and the size of outbreaks. We propose a simple continuous time stochastic Susceptible-Infected-Recovered model with a recurrent infection of an incidental host from a reservoir (e.g. humans by a zoonotic species), considering two modes of transmission, (1) animal-to-human and (2) human-to-human. The model assumes that (i) epidemiological processes are faster than other processes such as demographics or pathogen evolution and that (ii) an epidemic occurs until there are no susceptible individuals left. The results show that during an epidemic, even when the pathogens are barely contagious, multiple outbreaks are observed due to spillover transmission. Overall, the findings demonstrate that the only consideration of direct transmission between individuals is not sufficient to explain the dynamics of zoonotic pathogens in an incidental host.


id: cord-345789-lze2ye3q
title: ‘Individual sovereignty’ in pandemic times – A contradiction in terms?
author: Bialasiewicz, Luiza
date: 2020-09-04
txt: ./txt/cord-345789-lze2ye3q.txt
cache: ./cache/cord-345789-lze2ye3q.txt
extension: .txt
mime: text/plain
url: https://doi.org/10.1016/j.polgeo.2020.102277
doi: 10.1016/j.polgeo.2020.102277
abstract: nan
summary:
  In articulating their claims to ''individual sovereignty'', many of the European protesters against COVID-19 measures have appealed to the language of ''fundamental rights''. This double role of fundamental rights is what defines their essential role in ensuring that the inherent tension between individual autonomy and collective self-rule, i.e. sovereignty, does not result in the destruction of one or the other. Within modern constitutional democratic states, individual autonomy is expressed and protected through fundamental rights, which have a double-edged relationship with sovereignty. On the one hand, fundamental rights are, in their specific codified form, an expression of a sovereign choice; on the other hand, they protect individual liberty and autonomy (or self-rule) and limit the exercise of sovereignty. In this core meaning, sovereignty connects state authority with democracy and collective self-rule.


id: cord-349476-iac9fak3
title: Evaluating the Combined Effectiveness of Influenza Control Strategies and Human Preventive Behavior
author: Mao, Liang
date: 2011-10-17
txt: ./txt/cord-349476-iac9fak3.txt
cache: ./cache/cord-349476-iac9fak3.txt
extension: .txt
mime: text/plain
url: https://doi.org/10.1371/journal.pone.0024706
doi: 10.1371/journal.pone.0024706
summary:
  The simulation outcomes suggest that weaker control strategies could suffice to contain influenza epidemics, because individuals voluntarily adopt preventive behavior, rendering these weaker strategies more effective than would otherwise have been expected. Health policy makers are recommended to review current control strategies and comprehend preventive behavior patterns of local populations before making decisions on influenza containment. The control of influenza primarily involves applying health resources to affected people, known as control strategies, for example, medical treatment for infected individuals, closure of affected workplaces/schools, and travel restriction to affected communities [4] . Results from the influenza-only model indicate the effectiveness of control strategies without individual preventive behavior. Meanwhile, outcomes from the dual-diffusion model show the combined effectiveness of both control strategies and individual preventive behavior. These two modeled effectiveness are compared to a baseline epidemic scenario, which represents a worst situation of no control strategies and no preventive behavior. This research estimates the combined effectiveness of both control strategies and individual preventive behavior.

abstract:
  Control strategies enforced by health agencies are a major type of practice to contain influenza outbreaks. Another type of practice is the voluntary preventive behavior of individuals, such as receiving vaccination, taking antiviral drugs, and wearing face masks. These two types of practices take effects concurrently in influenza containment, but little attention has been paid to their combined effectiveness. This article estimates this combined effectiveness using established simulation models in the urbanized area of Buffalo, NY, USA. Three control strategies are investigated, including: Targeted Antiviral Prophylaxis (TAP), workplace/school closure, community travel restriction, as well as the combination of the three. All control strategies are simulated with and without regard to individual preventive behavior, and the resulting effectiveness are compared. The simulation outcomes suggest that weaker control strategies could suffice to contain influenza epidemics, because individuals voluntarily adopt preventive behavior, rendering these weaker strategies more effective than would otherwise have been expected. The preventive behavior of individuals could save medical resources for control strategies and avoid unnecessary socio-economic interruptions. This research adds a human behavioral dimension into the simulation of control strategies and offers new insights into disease containment. Health policy makers are recommended to review current control strategies and comprehend preventive behavior patterns of local populations before making decisions on influenza containment.


id: cord-355689-mo4mvwch
title: Role of vaccine efficacy in the vaccination behavior under myopic update rule on complex networks
author: Huang, Jiechen
date: 2019-09-06
txt: ./txt/cord-355689-mo4mvwch.txt
cache: ./cache/cord-355689-mo4mvwch.txt
extension: .txt
mime: text/plain
url: https://api.elsevier.com/content/article/pii/S0960077919303662
doi: 10.1016/j.chaos.2019.109425
summary:
  The results indicate that healthy individuals are often willing to inoculate the vaccine under the myopic update rule, which can stop the infectious disease from being spread, in particular, it is found that the vaccine efficacy influences the fraction of vaccinated individuals much more than the relative cost of vaccination on the regular lattice, Meanwhile, vaccine efficacy is more sensitive on the heterogeneous scale-free network. On the one hand, they classify these models according to source and type of information that individuals base their neighbors on, in which source of information may be local or global and the type of information that individuals change their behaviors are prevalence-based or belief-based; On the other hand, they classify the previous works based on the impact of individual behavior changes on the disease dynamics, which include the following three aspects: (i) the disease state; (ii) model parameters (infection or recovering rate); and (iii) the network contact structure relevant for the spread of epidemics.

abstract:
  How to effectively prevent the diffusion of infectious disease has become an intriguing topic in the field of public hygienics. To be noted that, for the non-periodic infectious diseases, many people hope to obtain the vaccine of epidemics in time to be inoculated, rather than at the end of the epidemic. However, the vaccine may fail as a result of invalid storage, transportation and usage, and then vaccinated individuals may become re-susceptible and be infected again during the outbreak. To this end, we build a new framework that considers the imperfect vaccination during the one cycle of infectious disease within the spatially structured and heterogeneous population. Meanwhile, we propose a new vaccination update rule: myopic update rule, which is only based on one focal player’s own perception regarding the disease outbreak, and one susceptible individual makes a decision to adopt the vaccine just by comparing the perceived payoffs vaccination with the perceived ones of being infected. Extensive Monte-Carlo simulations are performed to demonstrate the imperfect vaccination behavior under the myopic update rule in the spatially structured and heterogeneous population. The results indicate that healthy individuals are often willing to inoculate the vaccine under the myopic update rule, which can stop the infectious disease from being spread, in particular, it is found that the vaccine efficacy influences the fraction of vaccinated individuals much more than the relative cost of vaccination on the regular lattice, Meanwhile, vaccine efficacy is more sensitive on the heterogeneous scale-free network. Current results are helpful to further analyze and model the choice of vaccination strategy during the disease outbreaks.


