Summary of your 'study carrel' ============================== This is a summary of your Distant Reader 'study carrel'. The Distant Reader harvested & cached your content into a collection/corpus. It then applied sets of natural language processing and text mining against the collection. The results of this process was reduced to a database file -- a 'study carrel'. The study carrel can then be queried, thus bringing light specific characteristics for your collection. These characteristics can help you summarize the collection as well as enumerate things you might want to investigate more closely. This report is a terse narrative report, and when processing is complete you will be linked to a more complete narrative report. Eric Lease Morgan Number of items in the collection; 'How big is my corpus?' ---------------------------------------------------------- 34 Average length of all items measured in words; "More or less, how big is each item?" ------------------------------------------------------------------------------------ 4823 Average readability score of all items (0 = difficult; 100 = easy) ------------------------------------------------------------------ 53 Top 50 statistically significant keywords; "What is my collection about?" ------------------------------------------------------------------------- 34 CFR 7 case 6 covid-19 6 COVID-19 3 SARS 2 pandemic 2 IFR 1 protection 1 pneumonia 1 pneumococcal 1 oxygen 1 measure 1 italian 1 european 1 disease 1 datum 1 country 1 cost 1 coronavirus 1 convalescent 1 bias 1 age 1 Rasch 1 PSCC 1 PPE 1 October 1 OSHA 1 Italy 1 Iran 1 Iceland 1 H1N1 1 EMS 1 Coronavirus 1 China 1 ARIMA Top 50 lemmatized nouns; "What is discussed?" --------------------------------------------- 1385 case 791 % 760 country 670 death 559 datum 551 number 527 study 476 rate 461 patient 450 time 399 model 387 pandemic 375 infection 366 analysis 357 disease 357 age 352 day 332 fatality 315 mortality 304 outbreak 304 influenza 300 population 260 preprint 260 epidemic 256 risk 248 health 222 estimate 216 factor 208 intervention 187 value 186 bias 186 author 185 treatment 185 license 183 severity 173 cost 173 coronavirus 171 group 168 result 166 delay 162 test 159 difference 156 pneumonia 156 figure 150 p 146 period 141 r 141 level 141 distribution 138 medRxiv Top 50 proper nouns; "What are the names of persons or places?" -------------------------------------------------------------- 981 CFR 416 COVID-19 196 SARS 188 China 120 April 113 Italy 107 Coronavirus 106 March 105 CoV-2 99 Health 92 IFR 77 CC 74 H1N1 74 BY 73 Table 73 Korea 71 • 69 NC 66 Wuhan 66 South 60 PPE 60 Iran 56 United 56 Spain 55 May 54 ND 48 ICU 47 Disease 46 al 45 India 44 States 44 October 43 February 42 medRxiv 42 World 41 Germany 41 Fig 41 CI 40 UK 40 ARIMA 38 et 37 CoV 36 USA 36 Novel 35 New 34 France 33 US 32 Rasch 32 Control 32 Canada Top 50 personal pronouns nouns; "To whom are things referred?" ------------------------------------------------------------- 580 we 459 it 115 they 77 i 40 them 25 one 22 us 15 itself 8 you 5 themselves 3 she 2 me 2 he 1 yourself 1 y8ck4lo8 1 u 1 s 1 ours 1 ifradj 1 age≥70 Top 50 lemmatized verbs; "What do things do?" --------------------------------------------- 4636 be 970 have 531 use 365 report 251 show 236 estimate 207 include 165 make 164 do 157 base 154 provide 154 increase 154 follow 145 calculate 140 confirm 137 give 135 compare 122 display 120 adjust 110 identify 109 post 107 grant 105 suggest 103 find 102 take 102 require 99 relate 97 affect 96 reduce 95 occur 92 consider 91 test 89 need 89 infect 87 assume 85 see 78 associate 74 die 72 observe 70 obtain 66 present 65 predict 65 define 65 assess 64 know 64 cause 62 explain 61 result 61 determine 61 depend Top 50 lemmatized adjectives and adverbs; "How are things described?" --------------------------------------------------------------------- 506 not 388 high 290 more 258 other 239 low 231 also 197 available 194 different 194 covid-19 184 clinical 172 severe 165 early 164 such 164 - 158 only 144 first 140 most 139 respiratory 138 however 132 total 126 well 126 specific 110 public 108 likely 103 many 98 even 97 due 94 international 94 as 93 cumulative 91 large 91 effective 89 positive 86 old 85 significant 85 same 85 novel 83 possible 81 new 81 important 80 similar 79 global 76 very 75 pneumococcal 74 social 74 non 73 potential 73 infectious 71 thus 71 real Top 50 lemmatized superlative adjectives; "How are things described to the extreme?" ------------------------------------------------------------------------- 61 most 33 high 29 least 20 low 20 good 15 Most 9 bad 6 young 6 old 6 late 5 large 5 great 5 early 3 strong 2 simple 2 sick 1 small 1 narrow 1 broad 1 -γ Top 50 lemmatized superlative adverbs; "How do things do to the extreme?" ------------------------------------------------------------------------ 79 most 27 least 7 well 4 hard 1 worst 1 lowest 1 highest 1 -uk Top 50 Internet domains; "What Webbed places are alluded to in this corpus?" ---------------------------------------------------------------------------- 61 doi.org 6 github.com 2 links.lww.com 1 www.frontiersin.org 1 www.csti.cn 1 www.cqmu.edu.cn 1 www.aje 1 rsf.org 1 ourworldindata.org 1 opendata.ecdc 1 ncov2019 1 jid.oxfordjournals.org 1 data.ontario.ca 1 covid19stats.alberta.ca 1 cmmid.github.io 1 cmmid Top 50 URLs; "What is hyperlinked from this corpus?" ---------------------------------------------------- 21 http://doi.org/10.1101/2020.10.25.20216671 11 http://doi.org/10.1101/2020.06.01.20116608 6 http://doi.org/10.1101/2020.05.28.20114934 5 http://doi.org/10.1101/2020.04.28.20082370 4 http://doi.org/10.1101 3 http://doi.org/10.1101/2020.05.02.20087270 3 http://doi.org/10.1101/2020 3 http://doi.org/10 2 http://github.com/indrajitg-r/COVID 2 http://doi.org/10.1101/2020.10.24.20218909 1 http://www.frontiersin.org/articles/10.3389/fmed 1 http://www.csti.cn/govwebnew 1 http://www.cqmu.edu.cn/ 1 http://www.aje 1 http://rsf.org/en/ranking_table 1 http://ourworldindata.org/coronavirus-testing 1 http://opendata.ecdc 1 http://ncov2019 1 http://links.lww.com/MD/E415 1 http://links.lww.com/MD/E414 1 http://jid.oxfordjournals.org 1 http://github.com/thibautjombart/covid19_cases_from_deaths 1 http://github.com/harbab/covid_19_morta 1 http://github.com/bertschi/Covid 1 http://github.com/TheEconomist/covid-19-excess-deaths-tracker 1 http://doi.org/10.1101/2020.07.03.20145763 1 http://doi.org/10.1101/2020.05.01.20087023 1 http://doi.org/10.1101/2020.04.16.20067751 1 http://data.ontario.ca/dataset?keywords_en=COVID-19 1 http://covid19stats.alberta.ca 1 http://cmmid.github.io/visualisations/ 1 http://cmmid Top 50 email addresses; "Who are you gonna call?" ------------------------------------------------- Top 50 positive assertions; "What sentences are in the shape of noun-verb-noun?" ------------------------------------------------------------------------------- 5 mortality following covid-19 4 data are available 4 infections is unknown 4 studies reported outcomes 3 cases using delay 3 cfr is also 3 countries using seroprevalence 3 countries were outliers 3 covid-19 is not 3 influenza showed quite 3 patients did not 2 % were younger 2 cases are likely 2 cfr identified here 2 cfr is higher 2 cfr is not 2 cfr is still 2 cfr was only 2 cfr were significant 2 cfr were significantly 2 countries is very 2 covid-19 adjusted cfr 2 covid-19 confirmed positive 2 days post - 2 death are consistent 2 death given hospitalization 2 deaths are close 2 deaths have not 2 estimates are available 2 model was more 2 number is not 2 pandemic is unprecedented 2 patients were more 2 rate is straightforward 2 studies did not 2 study has thoroughly 2 study using data 1 % are theoretically 1 % being asymptomatic 1 % calculated early 1 % confirmed cases 1 % is almost 1 % is likely 1 % required ventilation 1 % were older 1 age is just 1 age requires estimation 1 age was due 1 analyses are available 1 analyses is likely Top 50 negative assertions; "What sentences are in the shape of noun-verb-no|not-noun?" --------------------------------------------------------------------------------------- 1 analyses was not compatible 1 case is no longer 1 cases does not necessarily 1 cfr is not as 1 countries is not significantly 1 country were not necessarily 1 covid-19 is not as 1 covid-19 is not strongly 1 death has not yet 1 deaths have not yet 1 epidemic was not severe 1 mortality are not currently 1 numbers are not as 1 pandemic is not surprisingly 1 patient is not strongly A rudimentary bibliography -------------------------- id = cord-330338-i6ozygkp author = Babacic, H. title = Global between-countries variance in SARS-CoV-2 mortality is driven by reported prevalence, age distribution, and case detection rate date = 2020-06-02 keywords = CFR; SARS summary = doi = 10.1101/2020.05.28.20114934 id = cord-127109-jdizyzbl author = Bertschinger, Nils title = Visual explanation of country specific differences in Covid-19 dynamics date = 2020-04-15 keywords = CFR; case summary = Indeed, I show here that SIR type models -and others exhibiting similarly flexible growth dynamics -are non-identified with respect to the CFR and the fraction of observed infections. Figure 4 shows the country specific estimates of reporting delay, CFR and fraction of observed cases (assuming a true CFR of 1%) obtained in this fashion. In turn, Figure 5 shows the implied relative case counts when shifted by the estimated delays and scaled to reflect the unobserved fraction of cases for each country. A suitable reporting delay τ c can be estimated by visual inspection of the data, but again the fraction of observed cases α c and CFR cfr are not jointly identifiable if there exist sets of parameters such that a t−τ = αa t , as is the case for dynamic SIR type models. Assuming that only a fraction α of cases is observed, the model is estimated with the following Relative days since two death per mill. doi = nan id = cord-315536-fgjhli0p author = Bignami, Simona title = Estimates of COVID-19 case-fatality risk from individual-level data date = 2020-04-22 keywords = CFR summary = doi = 10.1101/2020.04.16.20067751 id = cord-336115-7ykvl3u6 author = Binns, Colin title = The COVID-19 Pandemic: Public Health and Epidemiology date = 2020-05-19 keywords = CFR; COVID-19; disease summary = doi = 10.1177/1010539520929223 id = cord-347182-oj3v1x99 author = Catala, M. title = Robust estimation of diagnostic rate and real incidence of COVID-19 for European policymakers date = 2020-05-06 keywords = CFR; case; country; european summary = doi = 10.1101/2020.05.01.20087023 id = cord-258235-khdyxiwe author = Chakraborty, Tanujit title = Real-time forecasts and risk assessment of novel coronavirus (COVID-19) cases: A data-driven analysis date = 2020-04-30 keywords = ARIMA; CFR; covid-19 summary = To solve the first problem, we presented a hybrid approach based on autoregressive integrated moving average model and Wavelet-based forecasting model that can generate short-term (ten days ahead) forecasts of the number of daily confirmed cases for Canada, France, India, South Korea, and the UK. In this section, we first briefly discuss these datasets, followed by the development of the proposed hybrid model, and finally, the application of the proposed model to generate short-term forecasts of the future COVID-19 cases for five different countries. Algorithm 1 Proposed Hybrid ARIMA-WBF Model 1 Given a time series of length n, input the in-sample (training) COVID-19 daily cases data. Thus, these real-time short-term forecasts based on the proposed hybrid ARIMA-WBF model for Canada, France, India, South Korea, and the UK will be helpful for government officials and policymakers to allocate adequate health care resources for the coming days. doi = 10.1016/j.chaos.2020.109850 id = cord-269455-pkjov371 author = Faust, Jeremy Samuel title = Towards a better case fatality estimate for SARS-CoV-2 during the early phase of the United States outbreak date = 2020-05-30 keywords = CFR summary = doi = 10.1093/cid/ciaa639 id = cord-280672-6x968dwk author = Fisman, David N. title = Age Is Just a Number: A Critically Important Number for COVID-19 Case Fatality date = 2020-07-22 keywords = CFR summary = doi = 10.7326/m20-4048 id = cord-349921-v1tewoi0 author = Giorgi Rossi, Paolo title = Case fatality rate in patients with COVID-19 infection and its relationship with length of follow up() date = 2020-05-05 keywords = CFR summary = doi = 10.1016/j.jcv.2020.104415 id = cord-348056-kx9wvw8c author = Goh, H. P. title = Risk factors affecting COVID-19 case fatality rate: A quantitative analysis of top 50 affected countries date = 2020-05-25 keywords = CFR; COVID-19 summary = doi = 10.1101/2020.05.20.20108449 id = cord-285546-5tjhdczt author = Green, Manfred S. title = The confounded crude case-fatality rates (CFR) for COVID-19 hide more than they reveal—a comparison of age-specific and age-adjusted CFRs between seven countries date = 2020-10-21 keywords = CFR; age summary = doi = 10.1371/journal.pone.0241031 id = cord-245047-d81cf3ms author = Gupta, Sourendu title = Epidemic parameters for COVID-19 in several regions of India date = 2020-05-18 keywords = CFR; case summary = doi = nan id = cord-021907-omruua6n author = Hick, John L. title = Personal Protective Equipment date = 2009-05-15 keywords = CFR; EMS; OSHA; PPE; protection summary = doi = 10.1016/b978-0-323-03253-7.50043-1 id = cord-266989-n040i865 author = Ioannidis, John P. A. title = Coronavirus disease 2019: The harms of exaggerated information and non‐evidence‐based measures date = 2020-04-09 keywords = CFR; coronavirus; measure summary = doi = 10.1111/eci.13222 id = cord-338184-899km704 author = Iosa, Marco title = Covid-19: A Dynamic Analysis of Fatality Risk in Italy date = 2020-04-30 keywords = CFR; italian summary = doi = 10.3389/fmed.2020.00185 id = cord-354073-tn76muv6 author = Jen, Tung-Hui title = Geographic risk assessment of COVID-19 transmission using recent data: An observational study date = 2020-06-12 keywords = CFR; Rasch; covid-19 summary = doi = 10.1097/md.0000000000020774 id = cord-349978-zklwovba author = Jombart, Thibaut title = Inferring the number of COVID-19 cases from recently reported deaths date = 2020-04-27 keywords = CFR; case summary = We developed a model to use CFR alongside other epidemiological factors underpinning disease transmission to infer the likely number of cases in a population from newly reported deaths. This model combines data on the reproduction number (R) and serial interval distribution to simulate new cases ''y t '' on day ''t'' from a Poisson distribution: Our approach is implemented in the R software 13 and publicly available as R scripts (see Extended data) 14 , as well as in a user-friendly, interactive web-interface available at: https://cmmid.github.io/visualisations/ inferring-covid19-cases-from-deaths 2 . We first used our model to assess likely epidemic sizes when an initial COVID-19 death is reported in a new location. Extended data for: Inferring the number of COVID-19 cases from recently reported deaths This article describes a statistical modeling method for estimating the number of COVID-19 cases from the first reported deaths in a defined location. doi = 10.12688/wellcomeopenres.15786.1 id = cord-000916-b22s00es author = Kelso, Joel K title = Economic analysis of pandemic influenza mitigation strategies for five pandemic severity categories date = 2013-03-08 keywords = CFR; H1N1; cost; pandemic summary = This study estimates the effectiveness and total cost (from a societal perspective, with a lifespan time horizon) of a comprehensive range of social distancing and antiviral drug strategies, under a range of pandemic severity categories. For severe pandemics of category 3 (CFR 0.75%) and greater, a strategy combining antiviral treatment and prophylaxis, extended school closure and community contact reduction resulted in the lowest total cost of any strategy, costing $1,584 per person at category 5. For severe pandemics of category 3 (CFR 0.75%) and greater, a strategy combining antiviral treatment and prophylaxis, extended school closure and community contact reduction resulted in the lowest total cost of any strategy, costing $1,584 per person at category 5. Keywords: Pandemic influenza, Economic analysis, Antiviral medication, Social distancing, Pandemic severity, Case fatality ratio Background While the H1N1 2009 virus spread world-wide and was classed as a pandemic, the severity of resulting symptoms, as quantified by morbidity and mortality rates, was lower than that which had previously occurred in many seasonal epidemics [1] [2] [3] . doi = 10.1186/1471-2458-13-211 id = cord-263044-o8aosx2q author = Lipsitch, Marc title = Potential Biases in Estimating Absolute and Relative Case-Fatality Risks during Outbreaks date = 2015-07-16 keywords = CFR; bias; case summary = doi = 10.1371/journal.pntd.0003846 id = cord-342996-honeavwj author = Mair-Jenkins, John title = The Effectiveness of Convalescent Plasma and Hyperimmune Immunoglobulin for the Treatment of Severe Acute Respiratory Infections of Viral Etiology: A Systematic Review and Exploratory Meta-analysis date = 2015-01-01 keywords = CFR; SARS; convalescent summary = doi = 10.1093/infdis/jiu396 id = cord-279539-s2zv7hr4 author = Narayanan, C. S. title = Modeling the COVID-19 outbreak in the United States date = 2020-05-05 keywords = CFR; case summary = doi = 10.1101/2020.04.30.20086884 id = cord-338462-muetf7l1 author = OKPOKORO, E. title = Ecologic correlation between underlying population level morbidities and COVID-19 case fatality rate among countries infected with SARS-CoV-2 date = 2020-05-02 keywords = CFR; COVID-19 summary = doi = 10.1101/2020.04.28.20082370 id = cord-286958-e1ey31eo author = Patel, Urvish title = Early epidemiological indicators, outcomes, and interventions of COVID-19 pandemic: A systematic review date = 2020-08-15 keywords = CFR; China; Coronavirus; Italy; covid-19 summary = doi = 10.7189/jogh.10.020506 id = cord-281508-zl2url8z author = Pearce, N. title = Is death from Covid-19 a multistep process? date = 2020-06-03 keywords = CFR; SARS; covid-19 summary = doi = 10.1101/2020.06.01.20116608 id = cord-291400-o9skj94r author = Plouffe, Joseph F. title = Re-evaluation of the therapy of severe pneumonia caused by Streptococcus pneumoniae date = 2004-12-31 keywords = CFR; pneumococcal; pneumonia summary = Several retrospective reviews of bacteremic pneumococcal pneumonia suggest that dual therapy with a beta-lactam and a macrolide antimicrobial agent is associated with a lower case fatality rate than therapy with a beta-lactam alone. With the advent of modern microbiology, Streptococcus pneumoniae (pneumococcus) was identified as the cause of community-acquired pneumonia (CAP) in the most patients [1] . Changes that have been associated with improvements in CFR in some series of patients with CAP include more rapid antibiotic delivery [31] , combination therapy with a cephalosporin with good pneumococcal activity and macrolide (versus the cephalosporin alone), and therapy with a fluoroquinolone (ciprofloxacin; versus a cephalosporin alone) [32] . A previous study of patients with CAP, but not nonbacteremic pneumococcal pneumonia, found that treated with blactamase inhibitors and a macrolide were less effective than treatment with a cephalosporin alone [32] . doi = 10.1016/j.idc.2004.07.010 id = cord-330742-m5xx8861 author = Qian, Jie title = Age-dependent gender differences of COVID-19 in mainland China: comparative study date = 2020-05-30 keywords = CFR; PSCC summary = METHODS: We used the national surveillance database of COVID-19 in mainland China to compared gender differences in attack rate (AR), proportion of severe and critical cases (PSCC) and case fatality rate (CFR) in relation to age, affected province, and onset-to-diagnosis interval. After adjusting for age, affected province and onset-to-diagnosis interval, the female-to-male difference in AR, PSCC and CFR remained significant in multivariate logistic regression analyses. In this study, we used the surveillance data containing all confirmed cases in mainland China as of April 28, 2020 to evaluated gender-specific differences in attack rate, proportion of severe and critical cases, and case fatality in relation to age, affected province and onset-to-diagnosis interval, in order to provide evidence-based guidance for more effective and equitable interventions and treatments. doi = 10.1093/cid/ciaa683 id = cord-347353-ll2pnl81 author = Saberi, M. title = Accounting for underreporting in mathematical modelling of transmission and control of COVID-19 in Iran date = 2020-05-06 keywords = CFR; Iran; case summary = doi = 10.1101/2020.05.02.20087270 id = cord-300750-huyl21vz author = Shagam, Lev title = Untangling factors associated with country-specific COVID-19 incidence, mortality and case fatality rates during the first quarter of 2020 date = 2020-04-27 keywords = CFR; covid-19 summary = doi = 10.1101/2020.04.22.20075580 id = cord-303991-pjycxlse author = Shah, M. R. T. title = Finding the real COVID-19 case-fatality rates for SAARC countries date = 2020-10-27 keywords = CFR; COVID-19 summary = doi = 10.1101/2020.10.24.20218909 id = cord-291975-y8ck4lo8 author = Simon, Perikles title = Robust Estimation of Infection Fatality Rates during the Early Phase of a Pandemic date = 2020-04-10 keywords = CFR; IFR; Iceland; datum summary = The estimation of an IFR is based on two different and -regarding the influence of selection biasdivergent procedures to calculate a CFR from infection-related population data. This formula is not relying anymore on cases reported in the official databases of JH or ECDC and it served as a cross-validation figure for the IFR and the CFRs, which are solely based on these data and the population data of Iceland in the validation part of the results section. The IFRdeCode is the figure derived from testing the general population of Iceland and served to cross validate the mortality figures CFR and classic CFR that have been calculated from the data repositories of JH and the IFR that used this repository in conjunction with the test data published by Iceland''s Department of Public Health. doi = 10.1101/2020.04.08.20057729 id = cord-296992-2vp35fwv author = Simonsen, Lone title = Using Clinical Research Networks to Assess Severity of an Emerging Influenza Pandemic date = 2018-05-08 keywords = CFR; pandemic summary = doi = 10.1093/cid/ciy088 id = cord-343449-4uxwojzo author = The Gibraltar COVID-19 Research Group Health Systems, title = Oxygen and mortality in COVID-19 pneumonia: a comparative analysis of supplemental oxygen policies and health outcomes across 26 countries. date = 2020-07-04 keywords = CFR; COVID-19; oxygen summary = doi = 10.1101/2020.07.03.20145763 id = cord-354133-11b0d499 author = Thomas, B. S. title = Estimating the Case Fatality Ratio for COVID-19 using a Time-Shifted Distribution Analysis date = 2020-10-27 keywords = CFR; IFR; October; covid-19 summary = doi = 10.1101/2020.10.25.20216671 id = cord-333827-zpdnzwle author = Zhao, Jinqiu title = Potential risk factors for case fatality rate of novel coronavirus (COVID-19) in China: A pooled analysis of individual patient data date = 2020-08-17 keywords = CFR; COVID-19 summary = title: Potential risk factors for case fatality rate of novel coronavirus (COVID-19) in China: A pooled analysis of individual patient data This study aims to perform the meta-analysis of risk factors for the case fatality rate (CFR) of the 2019 novel coronavirus (COVID-19). After comparing the patients between fatal cases and non-fatal cases, several important factors are found to significantly increase the CFR in patients with COVID-19, and include the age ranging 60–70 (OR = 1.85; 95% CI = 1.62 to 2.11; P < .00001) and especially≥70 (OR = 8.45; 95% CI = 7.47 to 9.55; P < .00001), sex of male (OR = 1.88; 95% CI = 1.30 to 2.73; P = .0008), occupation of retirees (OR = 4.27; 95% CI = 2.50 to 7.28; P < .00001), and severe cases (OR = 691.76; 95% CI = 4.82 to 99,265.63; P = .01). doi = 10.1016/j.ajem.2020.08.039