# ent

id: cord-343449-4uxwojzo
type: WORK_OF_ART
entity:
  The Search for Optimal Oxygen Saturation Targets in Critically Ill Patients Observational Data From Large ICU Databases Liberal or Conservative Oxygen Therapy for Acute Respiratory Distress Syndrome Hypoxia


id: cord-343449-4uxwojzo
type: ORG
entity:
  the Ministry of Health and Medical Education 2020 Control Division Directorate General of Health Services Ministry of Health Family Welfare Government


id: cord-245047-d81cf3ms
type: CELL_LINE
entity:
  India Global Covid 19 Case Fatality Rates Ministry of Health and Family Welfare Government of India Addressing Social Stigma


id: cord-245047-d81cf3ms
type: WORK_OF_ART
entity:
  Emergencies Preparedness Response WHO Zika Virus Infection India Emergencies Preparedness Response Strategy for COVID19


id: cord-021907-omruua6n
type: DNA
entity:
  p t e r 3 6 Personal Protective Equipment John L Hick and Craig D Thorne Personal protective equipment PPE


id: cord-021907-omruua6n
type: ORG
entity:
  Minnesota Department of Health Chapter Association for Practitioners of Infection Control Personal Protective Equipment for Smallpox


id: cord-347353-ll2pnl81
type: ORG
entity:
  the Chinese Center for Disease Control and Prevention Centre for Mathematical Modelling of Infectious Disease London School of Hygiene Tropical Medicine


id: cord-296992-2vp35fwv
type: DISEASE
entity:
  influenza A H1N1 pandemic in the Netherlands Optimizing the precision of case fatality ratio estimates under the surveillance pyramid


id: cord-291975-y8ck4lo8
type: ORG
entity:
  The United Nations Probabilistic Population Projections An Introduction to Demographic Forecasting with


id: cord-000916-b22s00es
type: DISEASE
entity:
  influenza A H5N1 in poultry in South East Asia 14 and recent experimental results which have shown that the A H5N1 virus


id: cord-000916-b22s00es
type: DISEASE
entity:
  influenza A H5N1 virus between ferrets Experimental adaptation of an influenza H5 HA confers respiratory droplet transmission


id: cord-303991-pjycxlse
type: ORG
entity:
  Early Epidemiological Assessment of the Virulence of Emerging Infectious Diseases A Case Study of an Influenza Pandemic A Bayesian


id: cord-354133-11b0d499
type: ORG
entity:
  World Health Organization Cumulative Number of Reported Probable Cases of Severe Acute Respiratory Syndrome SARS Epidemiological


id: cord-315536-fgjhli0p
type: WORK_OF_ART
entity:
  1 Methods for Estimating the Case Fatality Ratio for a Novel Emerging Infectious Disease Potential Biases in Estimating Absolute and Relative Case Fatality Risks


id: cord-286958-e1ey31eo
type: ORG
entity:
  Notice of the People s Government of Hubei Province on Strengthening the Prevention and Control of Pneumonia Infected


# bib

id: cord-000916-b22s00es
title: Economic analysis of pandemic influenza mitigation strategies for five pandemic severity categories
author: Kelso, Joel K
date: 2013-03-08
txt: ./txt/cord-000916-b22s00es.txt
cache: ./cache/cord-000916-b22s00es.txt
extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3606600/
doi: 10.1186/1471-2458-13-211
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] .

abstract:
  BACKGROUND: The threat of emergence of a human-to-human transmissible strain of highly pathogenic influenza A(H5N1) is very real, and is reinforced by recent results showing that genetically modified A(H5N1) may be readily transmitted between ferrets. Public health authorities are hesitant in introducing social distancing interventions due to societal disruption and productivity losses. 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. METHODS: An economic analysis was conducted using a simulation model of a community of ~30,000 in Australia. Data from the 2009 pandemic was used to derive relationships between the Case Fatality Rate (CFR) and hospitalization rates for each of five pandemic severity categories, with CFR ranging from 0.1% to 2.5%. RESULTS: For a pandemic with basic reproduction number R(0) = 1.8, adopting no interventions resulted in total costs ranging from $441 per person for a pandemic at category 1 (CFR 0.1%) to $8,550 per person at category 5 (CFR 2.5%). 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. This strategy was highly effective, reducing the attack rate to 5%. With low severity pandemics costs are dominated by productivity losses due to illness and social distancing interventions, whereas higher severity pandemic costs are dominated by healthcare costs and costs arising from productivity losses due to death. CONCLUSIONS: For pandemics in high severity categories the strategies with the lowest total cost to society involve rigorous, sustained social distancing, which are considered unacceptable for low severity pandemics due to societal disruption and cost.


id: cord-127109-jdizyzbl
title: Visual explanation of country specific differences in Covid-19 dynamics
author: Bertschinger, Nils
date: 2020-04-15
txt: ./txt/cord-127109-jdizyzbl.txt
cache: ./cache/cord-127109-jdizyzbl.txt
extension: .txt
mime: text/plain
url: https://arxiv.org/pdf/2004.07334v1.pdf
doi: nan
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.

abstract:
  This report provides a visual examination of Covid-19 case and death data. In particular, it shows that country specific differences can too a large extend be explained by two easily interpreted parameters. Namely, the delay between reported cases and deaths and the fraction of cases observed. Furthermore, this allows to lower bound the actual total number of people already infected.


id: cord-245047-d81cf3ms
title: Epidemic parameters for COVID-19 in several regions of India
author: Gupta, Sourendu
date: 2020-05-18
url: https://arxiv.org/pdf/2005.08499v1.pdf
doi: nan
abstract:
  Bayesian analysis of publicly available time series of cases and fatalities in different geographical regions of India during April 2020 is reported. It is found that the initial apparent rapid growthin infections could be partly due to confounding factors such as initial rapid ramp-up of disease surveillance. A brief discussion is given of the fallacies which arise if this possibility is neglected. The growth after April 10 is consistent with a time independent but region dependent exponential. From this, R0 is extracted using both known cases and fatalities. The two estimates are seen to agree in many cases; for these CFR is reported. It is seen that CFR and R0 increase together. Some public health implications of this observation are discussed, including a target doubling interval if medical facilities are to remain adequate.


id: cord-258235-khdyxiwe
author: Chakraborty, Tanujit
date: 2020-04-30
txt: ./txt/cord-258235-khdyxiwe.txt
cache: ./cache/cord-258235-khdyxiwe.txt
extension: .txt
mime: text/plain
url: https://api.elsevier.com/content/article/pii/S0960077920302502
doi: 10.1016/j.chaos.2020.109850
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.

title:
  Real-time forecasts and risk assessment of novel coronavirus (COVID-19) cases: A data-driven analysis

abstract:
  The coronavirus disease 2019 (COVID-19) has become a public health emergency of international concern affecting 201 countries and territories around the globe. As of April 4, 2020, it has caused a pandemic outbreak with more than 11,16,643 confirmed infections and more than 59,170 reported deaths worldwide. The main focus of this paper is two-fold: (a) generating short term (real-time) forecasts of the future COVID-19 cases for multiple countries; (b) risk assessment (in terms of case fatality rate) of the novel COVID-19 for some profoundly affected countries by finding various important demographic characteristics of the countries along with some disease characteristics. 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. The predictions of the future outbreak for different countries will be useful for the effective allocation of health care resources and will act as an early-warning system for government policymakers. In the second problem, we applied an optimal regression tree algorithm to find essential causal variables that significantly affect the case fatality rates for different countries. This data-driven analysis will necessarily provide deep insights into the study of early risk assessments for 50 immensely affected countries.


id: cord-263044-o8aosx2q
title: Potential Biases in Estimating Absolute and Relative Case-Fatality Risks during Outbreaks
author: Lipsitch, Marc
date: 2015-07-16
url: https://www.ncbi.nlm.nih.gov/pubmed/26181387/
doi: 10.1371/journal.pntd.0003846
abstract:
  Estimating the case-fatality risk (CFR)—the probability that a person dies from an infection given that they are a case—is a high priority in epidemiologic investigation of newly emerging infectious diseases and sometimes in new outbreaks of known infectious diseases. The data available to estimate the overall CFR are often gathered for other purposes (e.g., surveillance) in challenging circumstances. We describe two forms of bias that may affect the estimation of the overall CFR—preferential ascertainment of severe cases and bias from reporting delays—and review solutions that have been proposed and implemented in past epidemics. Also of interest is the estimation of the causal impact of specific interventions (e.g., hospitalization, or hospitalization at a particular hospital) on survival, which can be estimated as a relative CFR for two or more groups. When observational data are used for this purpose, three more sources of bias may arise: confounding, survivorship bias, and selection due to preferential inclusion in surveillance datasets of those who are hospitalized and/or die. We illustrate these biases and caution against causal interpretation of differential CFR among those receiving different interventions in observational datasets. Again, we discuss ways to reduce these biases, particularly by estimating outcomes in smaller but more systematically defined cohorts ascertained before the onset of symptoms, such as those identified by forward contact tracing. Finally, we discuss the circumstances in which these biases may affect non-causal interpretation of risk factors for death among cases.


id: cord-266989-n040i865
title: Coronavirus disease 2019: The harms of exaggerated information and non‐evidence‐based measures
author: Ioannidis, John P. A.
date: 2020-04-09
url: https://www.ncbi.nlm.nih.gov/pubmed/32191341/
doi: 10.1111/eci.13222
abstract:
  The evolving coronavirus disease 2019 (COVID-19) epidemic1 is certainly cause for concern. Proper communication and optimal decision-making is an ongoing challenge, as data evolve. The challenge is compounded, however, by exaggerated information. This can lead to inappropriate actions. It is important to differentiate promptly the true epidemic from an epidemic of false claims and potentially harmful actions.


id: cord-269455-pkjov371
author: Faust, Jeremy Samuel
date: 2020-05-30
url: https://www.ncbi.nlm.nih.gov/pubmed/32472126/
doi: 10.1093/cid/ciaa639
abstract: nan
title:
  Towards a better case fatality estimate for SARS-CoV-2 during the early phase of the United States outbreak


id: cord-279539-s2zv7hr4
title: Modeling the COVID-19 outbreak in the United States
author: Narayanan, C. S.
date: 2020-05-05
url: http://medrxiv.org/cgi/content/short/2020.04.30.20086884v1?rss=1
doi: 10.1101/2020.04.30.20086884
abstract:
  The COVID-19 contagion has developed at an alarming rate in the US and as of April 24, 2020, tens of thousands of people have already died from the disease. In the event of an outbreak like such, forecasting the extent of the mortality that will occur is crucial to aid the implementation of effective interventions. Mortality depends on two factors: the case fatality rate and the case incidence. We combine a cohort-based model that determines case fatality rates along with a modified logistic model that evaluates the case incidence to determine the number of deaths in all the US states over time; the model is also able to include the impact of interventions. Both models yield exceptional goodness-of-fit. The model predicted a range of death outcomes (79k to 246k) all of which are considerably greater than the figures presented in mainstream media. This model can be used more effectively than current models to estimate the number of deaths during an outbreak, allowing for better planning.


id: cord-280672-6x968dwk
title: Age Is Just a Number: A Critically Important Number for COVID-19 Case Fatality
author: Fisman, David N.
date: 2020-07-22
url: https://www.ncbi.nlm.nih.gov/pubmed/32698604/
doi: 10.7326/m20-4048
abstract:
  In their article, Sudharsanan and colleagues show the importance of adjusting for the age distribution of cases of coronavirus disease 2019 before doing cross-country comparisons of case-fatality rates. The editorialists explore the effect of age distribution on these rates and other determinants of between-country variation in the severity of this disease.


id: cord-281508-zl2url8z
title: Is death from Covid-19 a multistep process?
author: Pearce, N.
date: 2020-06-03
url: http://medrxiv.org/cgi/content/short/2020.06.01.20116608v1?rss=1
doi: 10.1101/2020.06.01.20116608
abstract:
  Covid-19 death has a different relationship with age than is the case for other severe respiratory pathogens. The Covid-19 death rate increases exponentially with age, and the main risk factors are age itself, as well as having underlying conditions such as hypertension, diabetes, cardiovascular disease, severe chronic respiratory disease and cancer. Furthermore, the almost complete lack of deaths in children suggests that infection alone is not sufficient to cause death; rather, one must have gone through a number of changes, either as a result of undefined aspects of aging, or as a result of chronic disease. These characteristics of Covid-19 death are consistent with the multistep model of disease, a model which has primarily been used for cancer, and more recently for amyotrophic lateral sclerosis (ALS). We applied the multi-step model to data on Covid-19 case fatality rates (CFRs) from China, South Korea, Italy, Spain and Japan. In all countries we found that a plot of ln (CFR) against ln (age) was approximately linear with a slope of about 5. As a comparison, we also conducted similar analyses for selected other respiratory diseases. SARS showed a similar log-log age-pattern to that of Covid-19, albeit with a lower slope, whereas seasonal and pandemic influenza showed quite different age-patterns. Thus, death from Covid-19 and SARS appears to follow a distinct age-pattern, consistent with a multistep model of disease that in the case of Covid-19 is probably defined by comorbidities and age producing immune-related susceptibility. Identification of these steps would be potentially important for prevention and therapy for SARS-COV-2 infection.


id: cord-285546-5tjhdczt
author: Green, Manfred S.
date: 2020-10-21
url: https://doi.org/10.1371/journal.pone.0241031
doi: 10.1371/journal.pone.0241031
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

abstract:
  BACKGROUND: Crude case-fatality rates (CFRs) for COVID-19 vary widely between countries. There are serious limitations in the CFRs when making comparisons. We examined how the age distribution of the cases is responsible for the COVID-19 CFR differences between countries. METHODS: COVID-19 cases and deaths, by ten-year age-groups, were available from the reports of seven countries. The overall and age-specific CFRs were computed for each country. The age-adjusted CFRs were computed by the direct method, using the combined number of cases in all seven countries in each age group as the standard population. A meta-analytic approach was used to obtain pooled age-specific CFRs. FINDINGS: The crude overall CFRs varied between 0.82% and 14.2% in the seven countries and the variation in the age-specific CFRs were much smaller. There was wide variation in the age distribution of the cases between countries. The ratio of the crude CFR for the country with the highest CFR to that with the lowest (6.28) was much lower for the age-adjusted CFRs rates (2.57). CONCLUSIONS: The age structure of the cases explains much of differences in the crude CFRs between countries and adjusting for age substantially reduces this variation. Other factors such as the definition of cases, coding of deaths and the standard of healthcare are likely to account for much of the residual variation. It is misleading to compare the crude COVID-19 CFRs between countries and should be avoided. At the very least, age-specific and age-adjusted CFRs should be used for comparisons.


id: cord-286958-e1ey31eo
author: Patel, Urvish
date: 2020-08-15
url: https://doi.org/10.7189/jogh.10.020506
doi: 10.7189/jogh.10.020506
title:
  Early epidemiological indicators, outcomes, and interventions of COVID-19 pandemic: A systematic review

abstract:
  BACKGROUND: Coronavirus disease-2019 (COVID-19), a pandemic that brought the whole world to a standstill, has led to financial and health care burden. We aimed to evaluate epidemiological characteristics, needs of resources, outcomes, and global burden of the disease. METHODS: Systematic review was performed searching PubMed from December 1, 2019, to March 25, 2020, for full-text observational studies that described epidemiological characteristics, following MOOSE protocol. Global data were collected from the JHU-Corona Virus Resource Center, WHO-COVID-2019 situation reports, KFF.org, and Worldometers.info until March 31, 2020. The prevalence percentages were calculated. The global data were plotted in excel to calculate case fatality rate (CFR), predicted CFR, COVID-19 specific mortality rate, and doubling time for cases and deaths. CFR was predicted using Pearson correlation, regression models, and coefficient of determination. RESULTS: From 21 studies of 2747 patients, 8.4% of patients died, 20.4% recovered, 15.4% were admitted to ICU and 14.9% required ventilation. COVID-19 was more prevalent in patients with hypertension (19.3%), smoking (11.3%), diabetes mellitus (10%), and cardiovascular diseases (7.4%). Common complications were pneumonia (82%), cardiac complications (26.4%), acute respiratory distress syndrome (15.7%), secondary infection (11.2%), and septic shock (4.3%). Though CFR and COVID-19 specific death rates are dynamic, they were consistently high for Italy, Spain, and Iran. Polynomial growth models were best fit for all countries for predicting CFR. Though many interventions have been implemented, stern measures like nationwide lockdown and school closure occurred after very high infection rates (>10cases per 100 000population) prevailed. Given the trend of government measures and decline of new cases in China and South Korea, most countries will reach the peak between April 1-20, if interventions are followed. CONCLUSIONS: A collective approach undertaken by a responsible government, wise strategy implementation and a receptive population may help contain the spread of COVID-19 outbreak. Close monitoring of predictive models of such indicators in the highly affected countries would help to evaluate the potential fatality if the second wave of pandemic occurs. The future studies should be focused on identifying accurate indicators to mitigate the effect of underestimation or overestimation of COVID-19 burden.


id: cord-291400-o9skj94r
title: Re-evaluation of the therapy of severe pneumonia caused by Streptococcus pneumoniae
author: Plouffe, Joseph F.
date: 2004-12-31
txt: ./txt/cord-291400-o9skj94r.txt
cache: ./cache/cord-291400-o9skj94r.txt
extension: .txt
mime: text/plain
url: https://www.sciencedirect.com/science/article/pii/S0891552004001023
doi: 10.1016/j.idc.2004.07.010
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] .

abstract:
  Pneumonia caused by Streptococcus pneumoniae is the most deadly form of community-acquired pneumonia. The death rate of bacteremic pneumococcal pneumonia has remained constant over the past 50 years. 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. These studies are reviewed, potential mechanisms are suggested, and future studies are discussed.


id: cord-291975-y8ck4lo8
title: Robust Estimation of Infection Fatality Rates during the Early Phase of a Pandemic
author: Simon, Perikles
date: 2020-04-10
txt: ./txt/cord-291975-y8ck4lo8.txt
cache: ./cache/cord-291975-y8ck4lo8.txt
extension: .txt
mime: text/plain
url: https://doi.org/10.1101/2020.04.08.20057729
doi: 10.1101/2020.04.08.20057729
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.

abstract:
  During a pandemic, robust estimation of case fatality rates (CFRs) is essential to plan and control suppression and mitigation strategies. At present, estimates for the CFR of COVID-19 caused by SARS-CoV-2 infection vary considerably. Expert consensus of 0.1-1% covers in practical terms a range from normal seasonable Influenza to Spanish Influenza. In the following, I deduce a formula for an adjusted Infection Fatality Rate (IFR) to assess mortality in a period following a positive test adjusted for selection bias. Official datasets on cases and deaths were combined with data sets on number of tests. After data curation and quality control, a total of IFR (n=819) was calculated for 21 countries for periods of up to 26 days between registration of a case and death. Estimates for IRFs increased with length of period, but levelled off at >9days with a median for all 21 countries of 0.11 (95%-CI: 0.073-0.15). An epidemiologically derived IFR of 0.040 % (95%-CI: 0.029%-0.055%) was determined for Iceland and was very close to the calculated IFR of 0.057% (95%-CI: 0.042-0.078), but 2.7-6-fold lower than CFRs. IFRs, but not CFRs, were positively associated with increased proportions of elderly in age-cohorts (n=21, spearman's ρ =.73, p =.02). Real-time data on molecular and serological testing may further displace classical diagnosis of disease and its related death. I will critically discuss, why, how and under which conditions the IFR, provides a more solid early estimate of the global burden of a pandemic than the CFR.


id: cord-296992-2vp35fwv
title: Using Clinical Research Networks to Assess Severity of an Emerging Influenza Pandemic
author: Simonsen, Lone
date: 2018-05-08
url: https://academic.oup.com/cid/article-pdf/67/3/341/25156461/ciy088.pdf
doi: 10.1093/cid/ciy088
abstract:
  BACKGROUND: Early clinical severity assessments during the 2009 influenza A H1N1 pandemic (pH1N1) overestimated clinical severity due to selection bias and other factors. We retrospectively investigated how to use data from the International Network for Strategic Initiatives in Global HIV Trials, a global clinical influenza research network, to make more accurate case fatality ratio (CFR) estimates early in a future pandemic, an essential part of pandemic response. METHODS: We estimated the CFR of medically attended influenza (CFR(MA)) as the product of probability of hospitalization given confirmed outpatient influenza and the probability of death given hospitalization with confirmed influenza for the pandemic (2009–2011) and post-pandemic (2012–2015) periods. We used literature survey results on health-seeking behavior to convert that estimate to CFR among all infected persons (CFR(AR)). RESULTS: During the pandemic period, 5.0% (3.1%–6.9%) of 561 pH1N1-positive outpatients were hospitalized. Of 282 pH1N1-positive inpatients, 8.5% (5.7%–12.6%) died. CFR(MA) for pH1N1 was 0.4% (0.2%–0.6%) in the pandemic period 2009–2011 but declined 5-fold in young adults during the post-pandemic period compared to the level of seasonal influenza in the post-pandemic period 2012–2015. CFR for influenza-negative patients did not change over time. We estimated the 2009 pandemic CFR(AR) to be 0.025%, 16-fold lower than CFR(MA). CONCLUSIONS: Data from a clinical research network yielded accurate pandemic severity estimates, including increased severity among younger people. Going forward, clinical research networks with a global presence and standardized protocols would substantially aid rapid assessment of clinical severity. CLINICAL TRIALS REGISTRATION: NCT01056354 and NCT010561.


id: cord-300750-huyl21vz
author: Shagam, Lev
date: 2020-04-27
url: https://doi.org/10.1101/2020.04.22.20075580
doi: 10.1101/2020.04.22.20075580
title:
  Untangling factors associated with country-specific COVID-19 incidence, mortality and case fatality rates during the first quarter of 2020

abstract:
  At early stages of the COVID-19 pandemic which we are experiencing, the publicly reported incidence, mortality and case fatality rates (CFR) vary significantly between countries. Here we aim to untangle factors that are associated with the differences during the first quarter of the year 2020. Number of performed COVID-19 tests has a strong correlation with country-specific incidence (p <2×10-16) and mortality rate (p = 5.1×10-8). Using multivariate linear regression we show that incidence and mortality rates correlate significantly with GDP per capita (p = 2.6×10-15 and 7.0×10-4, respectively), country-specific duration of the outbreak (2.6×10-4 and 0.0019), fraction of citizens over 65 years old (p = 0.0049 and 3.8×10-4) and level of press freedom (p = 0.021 and 0.019) which cumulatively explain 80% of variability of incidence and more than 60% of variability of mortality of the disease during the period analyzed. Country hemisphere demonstrated significant correlation only with mortality (p = 0.17 and 0.036) whereas population density (p = 0.94 and p = 0.75) and latitude (p = 0.61 and 0.059) did not reach significance in our model. Case fatality rate is shown to rise as the outbreak progresses (p = 0.028). We rank countries by COVID-19 mortality corrected for incidence and the factors that were shown to affect it, and by CFR corrected for outbreak duration, yielding very similar results. Among the countries where the outbreak started after the 15th of February and with at least 1000 registered patients during the period analyzed, the lowest corrected CFR are seen in Israel, South Africa and Chile. The ranking results should be considered with caution as they do not consider all confounding factors or data reporting biases.


id: cord-303991-pjycxlse
title: Finding the real COVID-19 case-fatality rates for SAARC countries
author: Shah, M. R. T.
date: 2020-10-27
url: http://medrxiv.org/cgi/content/short/2020.10.24.20218909v1?rss=1
doi: 10.1101/2020.10.24.20218909
abstract:
  Crude case fatality rate (CFR) is the most accurate when the pandemic is over. Adjustments to the crude CFR measure can better explain the pandemic situation by improving the CFR estimation. However, no study has thoroughly investigated COVID-19 adjusted CFR of the South Asian Association for Regional Cooperation (SAARC) countries. In this study, we estimated both survival interval and underreporting adjusted CFR of COVID-19 for the SAARC countries and observed the CFR changes due to the imposition of fees on COVID-19 tests in Bangladesh. Using the daily records up to 9th October, we implemented a statistical method to remove both the bias in crude CFR, i.e., the delay between disease onset and outcome bias and due to asymptomatic or mild symptomatic cases, reporting rates lower than 50% (95% CI: 10%-50%) bias. According to our findings, Afghanistan had the highest CFR, followed by Pakistan, India, Bangladesh, Nepal, Maldives, and Sri Lanka. Our estimated crude CFR varied from 3.71% to 0.29%, survival interval adjusted CFR varied from 3.77% to 0.3% and further underreporting adjusted CFR varied from 1.1% to 0.08%. We have also found that crude CFR increased from 1.261% to 1.572% after imposing the COVID-19 test fees in Bangladesh. Therefore, the authorities of countries with higher CFR should be looking for strategic counsel from the countries with lower CFR to equip themselves with the necessary knowledge to combat the pandemic. Moreover, caution is needed to report the CFR.


id: cord-315536-fgjhli0p
title: Estimates of COVID-19 case-fatality risk from individual-level data
author: Bignami, Simona
date: 2020-04-22
url: https://doi.org/10.1101/2020.04.16.20067751
doi: 10.1101/2020.04.16.20067751
abstract:
  When calculated from aggregate data on confirmed cases and deaths, the case-fatality risk (CFR) is a simple ratio between the former and the latter, which is prone to numerous biases. With individual-level data, the CFR can be estimated as a true measure of risk as the proportion of incidence for the disease. We present the first estimates of the CFR for COVID-19 by age and sex based on event history modelling of the risk of dying among confirmed positive individuals in the Canadian province of Ontario, which maintains one of the few individual-level datasets on COVID-19 in the world.


id: cord-330338-i6ozygkp
author: Babacic, H.
date: 2020-06-02
url: http://medrxiv.org/cgi/content/short/2020.05.28.20114934v1?rss=1
doi: 10.1101/2020.05.28.20114934
title:
  Global between-countries variance in SARS-CoV-2 mortality is driven by reported prevalence, age distribution, and case detection rate

abstract:
  Objective: To explain the global between-countries variance in number of deaths per million citizens (nDpm) and case fatality rate (CFR) due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Design: Systematic analysis. Data sources: Worldometer, European Centre for Disease Prevention and Control, United Nations Main outcome measures: The explanators of nDpm and CFR were mathematically hypothesised and tested on publicly-available data from 88 countries with linear regression models on May 1st 2020. The derived explanators - age-adjusted infection fatality rate (IFRadj) and case detection rate (CDR) - were estimated for each country based on a SARS-CoV-2 model of China. The accuracy and agreement of the models with observed data was assessed with R2 and Bland-Altman plots, respectively. Sensitivity analyses involved removal of outliers and testing the models at five retrospective and two prospective time points. Results: Globally, IFRadj estimates varied between countries, ranging from below 0.2% in the youngest nations, to above 1.3% in Portugal, Greece, Italy, and Japan. The median estimated global CDR of SARS-CoV-2 infections on April 16th 2020 was 12.9%, suggesting that most of the countries have a much higher number of cases than reported. At least 93% and up to 99% of the variance in nDpm was explained by reported prevalence expressed as cases per million citizens (nCpm), IFRadj, and CDR. IFRadj and CDR accounted for up to 97% of the variance in CFR, but this model was less reliable than the nDpm model, being sensitive to outliers (R2 as low as 67.5%). Conclusions: The current differences in SARS-CoV-2 mortality between countries are driven mainly by reported prevalence of infections, age distribution, and CDR. The nDpm might be a more stable estimate than CFR in comparing mortality burden between countries.


id: cord-330742-m5xx8861
title: Age-dependent gender differences of COVID-19 in mainland China: comparative study
author: Qian, Jie
date: 2020-05-30
txt: ./txt/cord-330742-m5xx8861.txt
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mime: text/plain
url: https://doi.org/10.1093/cid/ciaa683
doi: 10.1093/cid/ciaa683
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.

abstract:
  BACKGROUND: The ongoing pandemic of novel coronavirus disease 2019 (COVID-19) is challenging global public health system. Sex-differences in infectious diseases are a common but neglected problem. 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. RESULTS: The overall AR was significantly higher in female population than in males (63.9 versus 60.5 per million persons; P ˂ .001). By contrast, PSCC and CFR were significantly lower among female patients (16.9% and 4.0%) than among males (19.5% and 7.2%), with ORs of 0.87 and 0.57, respectively (both P ˂ .001). The female-to-male differences were age-dependent, which were significant among people aged 50–69 years for AR, and in the patients of 30-years or older for both PSCC and CFR (all P ≤ .001). The AR, PSCC and CFR varied greatly from province to province. However, female-to-male differences in AR, PSCC and CFR were significant in the epicenter, Hubei province, where 82.2% confirmed cases and 97.4% deaths occurred. 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. CONCLUSIONS: We elucidate an age-dependent gender dimorphism for COVID-19, in which the females have higher susceptibility but lower severity and fatality. Further epidemiological and biological investigations are required to better understand the sex-specific differences for effective interventions.


id: cord-333827-zpdnzwle
author: Zhao, Jinqiu
date: 2020-08-17
txt: ./txt/cord-333827-zpdnzwle.txt
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extension: .txt
mime: text/plain
url: https://www.ncbi.nlm.nih.gov/pubmed/33131974/
doi: 10.1016/j.ajem.2020.08.039
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).

title:
  Potential risk factors for case fatality rate of novel coronavirus (COVID-19) in China: A pooled analysis of individual patient data

abstract:
  BACKGROUND AND OBJECTIVE: Since the first case of the pneumonia caused by 2019 novel coronavirus (COVID-19) is found in Wuhan, there have been more than 70,000 cases reported in China. This study aims to perform the meta-analysis of risk factors for the case fatality rate (CFR) of the 2019 novel coronavirus (COVID-19). DESIGN AND METHODS: We have searched PubMed, Google scholar and medRxiv for the cohort studies involving risk factors for the CFR of COVID-19. This meta-analysis compares the risk factors of CFR between fatal patients and non-fatal patients. RESULTS: Two cohort studies are included in this study. 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). As the advancement of early diagnosis and treatment, the CFR after January 21 (or 22), 2020 is substantially decreased in COVID-19 than before (OR = 0.21; 95% CI = 0.19 to 0.24; P < .00001). CONCLUSIONS: Several factors are confirmed to significantly improve the CFR in patients with COVID-19, which is very important for the treatment and good prognosis of these patients.


id: cord-338184-899km704
title: Covid-19: A Dynamic Analysis of Fatality Risk in Italy
author: Iosa, Marco
date: 2020-04-30
url: https://www.ncbi.nlm.nih.gov/pubmed/32426362/
doi: 10.3389/fmed.2020.00185
abstract:
  Italy was the second country in the world to face a wide epidemic of Covid-19 after China. The ratio of the number of fatalities to the number of cases (case fatality ratio, CFR) recorded in Italy was surprisingly high and increased in the month of March. The older mean age of population, the changes in testing policy, and the methodological computation of CFR were previously reported as possible explanations for the incremental trend of CFR, a parameter theoretically expected to be constant. In this brief report, the official data provided by the Italian Ministry of Health were analyzed using fitting models and the linear fit method approach. This last methodology allowed us to reach two findings. The trend of the number of deaths followed a 1–3-day delay of positive cases. This delay was not compatible with a biological course of Covid-19 but was compatible with a health management explanation. The second finding is that the Italian number of deaths did not increase linearly with the number of positive cases, but their relationship could be modeled by a second-order polynomial function. The high number of positive cases might have a direct and an indirect effect on the number of deaths, the latter being related to the overwhelmed bed capacity of intensive care units.


id: cord-338462-muetf7l1
author: OKPOKORO, E.
date: 2020-05-02
url: http://medrxiv.org/cgi/content/short/2020.04.28.20082370v1?rss=1
doi: 10.1101/2020.04.28.20082370
title:
  Ecologic correlation between underlying population level morbidities and COVID-19 case fatality rate among countries infected with SARS-CoV-2

abstract:
  Background: The ongoing Coronavirus disease 2019 (COVID-19) pandemic is unprecedented in scope. High income countries (HIC) seemingly account for the majority of the mortalities considering that these countries have screened more persons. Low middle income countries (LMIC) countries may experience far worse mortalities considering the existence of a weaker health care system and the several underlying population level morbidities. As a result, it becomes imperative to understand the ecological correlation between critical underlying population level morbidities and COVID-19 case fatality rates (CFR). Method: This is an ecological study using data on COVID-19 cases, prevalence of COPD, prevalence of tobacco use, adult HIV prevalence, quality of air and life expectancy. We plotted a histogram, performed the Shapiro-Wilk normality test and used spearman correlation to assess the degree of correlation between COVID-19 case fatality rate (CFR) and other covariates mentioned above. Result: As at the 31st of March 2020, there were a total of 846,281 cases of COVID-19 from 204 countries and a global case fatality rate of 5% (range 0% to 29%). Angola and Sudan both had the highest CFR of 29%, while Italy had the highest number of deaths (i.e. 12,428) as at 31st of March 2020. Adult HIV prevalence has a significant but weak negative correlation with CFR (correlation coefficient = - 0.24, p value =0.01) while all the other variables have positive correlation with CFR due to COVID-19 though not statistically significant. Of the 204 countries analyzed, only 11 countries (i.e. 5%) had complete datasets across all 5 population level morbidities (i.e. prevalence of COPD, prevalence of tobacco use, life expectancy, quality of air, and adult HIV prevalence variables). Correlations of CFR from these 11 countries were similar to that from the 204 countries except for the correlation with quality of air and prevalence of tobacco use. Conclusion: While we interpret our data with caution given the fact that this is an ecological study, our findings suggest that population level factors such as prevalence of COPD, prevalence of tobacco use, life expectancy and quality of air are positively correlated with CFR from COVID-19 but, adult HIV prevalence has a weak and negative correlation with COVID-19 CFR and would require extensive research.


id: cord-342996-honeavwj
author: Mair-Jenkins, John
date: 2015-01-01
url: https://www.ncbi.nlm.nih.gov/pubmed/25030060/
doi: 10.1093/infdis/jiu396
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

abstract:
  Background. Administration of convalescent plasma, serum, or hyperimmune immunoglobulin may be of clinical benefit for treatment of severe acute respiratory infections (SARIs) of viral etiology. We conducted a systematic review and exploratory meta-analysis to assess the overall evidence. Methods. Healthcare databases and sources of grey literature were searched in July 2013. All records were screened against the protocol eligibility criteria, using a 3-stage process. Data extraction and risk of bias assessments were undertaken. Results. We identified 32 studies of SARS coronavirus infection and severe influenza. Narrative analyses revealed consistent evidence for a reduction in mortality, especially when convalescent plasma is administered early after symptom onset. Exploratory post hoc meta-analysis showed a statistically significant reduction in the pooled odds of mortality following treatment, compared with placebo or no therapy (odds ratio, 0.25; 95% confidence interval, .14–.45; I(2) = 0%). Studies were commonly of low or very low quality, lacked control groups, and at moderate or high risk of bias. Sources of clinical and methodological heterogeneity were identified. Conclusions. Convalescent plasma may reduce mortality and appears safe. This therapy should be studied within the context of a well-designed clinical trial or other formal evaluation, including for treatment of Middle East respiratory syndrome coronavirus CoV infection.


id: cord-343449-4uxwojzo
author: The Gibraltar COVID-19 Research Group Health Systems,
date: 2020-07-04
url: https://doi.org/10.1101/2020.07.03.20145763
doi: 10.1101/2020.07.03.20145763
title:
  Oxygen and mortality in COVID-19 pneumonia: a comparative analysis of supplemental oxygen policies and health outcomes across 26 countries.

abstract:
  Introduction Hypoxia is the main cause of morbidity and mortality in COVID-19. During the COVID-19 pandemic some countries have reduced access to supplemental oxygen (e.g. oxygen rationing), whereas other nations have maintained and even improved access to supplemental oxygen. We examined whether such variation in the access to supplemental oxygen had any bearing on mortality in COVID-19. Methods Three independent investigators searched for, identified and extracted the nationally recommended target oxygen levels for the commencement of oxygen in COVID-19 pneumonia from the 29 worst affected countries. Mortality estimates were calculated from three independent sources. We then applied linear regression analysis to examine for potential association between national targets for the commencement of oxygen and case fatality rates. Results Of the 26 nations included, 15 had employed conservative oxygen strategies to manage COVID-19 pneumonia. Of them, Belgium, France, USA, Canada, China, Germany, Mexico, Spain, Sweden and the UK guidelines advised commencing oxygen when oxygen saturations (SpO2) fell to 91% or less. Target SpO2 ranged from 92% to 95% in the other 16 nations. Linear regression analysis demonstrated a strong inverse correlation between the national target for the commencement of oxygen and national case fatality rates (Spearmans Rho = -0.622, p < 0.001). Conclusion Our study highlights the disparity in oxygen provision for COVID-19 patients between the nations analysed, and indicates such disparity in access to supplemental oxygen may represent a modifiable factor associated with mortality during the pandemic.


id: cord-347182-oj3v1x99
title: Robust estimation of diagnostic rate and real incidence of COVID-19 for European policymakers
author: Catala, M.
date: 2020-05-06
url: http://medrxiv.org/cgi/content/short/2020.05.01.20087023v1?rss=1
doi: 10.1101/2020.05.01.20087023
abstract:
  Policymakers need a clear and fast assessment of the real spread of the epidemic of COVID-19 in each of their respective countries. Standard measures of the situation provided by the governments include reported positive cases and total deaths. While total deaths immediately indicate that countries like Italy and Spain have the worst situation as of mid April 2020, on its own, reported cases do not provide a correct picture of the situation. The reason is that different countries diagnose diversely and present very distinctive reported case fatality rate (CFR). The same levels of reported incidence and mortality might hide a very different underlying picture. Here we present a straightforward and robust estimation of the diagnostic rate in each European country. From that estimation we obtain an uniform unbiased incidence of the epidemic. The method to obtain the diagnostic rate is transparent and empiric. The key assumption of the method is that the real CFR in Europe of COVID-19 is not strongly country-dependent. We show that this number is not expected to be biased due to demography nor the way total deaths are reported. The estimation protocol has a dynamic nature, and it has been giving converging numbers for diagnostic rates in all European countries as of mid April 2020. From this diagnostic rate, policy makers can obtain an Effective Potential Growth (EPG) updated everyday providing an unbiased assessment of the countries with more potential to have an uncontrolled situation. The method developed will be used to track possible improvements on the diagnostic rate in European countries as the epidemic evolves.


id: cord-347353-ll2pnl81
author: Saberi, M.
date: 2020-05-06
url: https://doi.org/10.1101/2020.05.02.20087270
doi: 10.1101/2020.05.02.20087270
title:
  Accounting for underreporting in mathematical modelling of transmission and control of COVID-19 in Iran

abstract:
  BACKGROUND: Iran has been the hardest hit country by the outbreak of SARS-CoV-2 in the Middle East with 74,877 confirmed cases and 4,683 deaths as of 15 April 2020. With a relatively high case fatality ratio and limited testing capacity, the number of confirmed cases reported is suspected to suffer from significant under-reporting. Therefore, understanding the transmission dynamics of COVID-19 and assessing the effectiveness of the interventions that have taken place in Iran while accounting for the uncertain level of underreporting is of critical importance. We use a mathematical epidemic model utilizing official confirmed data and estimates of underreporting to understand how transmission in Iran has been changing between February and April 2020. METHODS: We developed a compartmental transmission model to estimate the effective reproduction number and its fluctuations since the beginning of the outbreak in Iran. We associate the variations in the effective reproduction number with a timeline of interventions and national events. The estimation method also accounts for the underreporting due to low case ascertainment by estimating the percentage of symptomatic cases using delay adjusted case fatality ratio based on the distribution of the delay from hospitalization to death. FINDINGS: Our estimates of the effective reproduction number ranged from 0.66 to 1.73 between February and April 2020, with a median of 1.16. We estimate a reduction in the effective reproduction number during this period, from 1.73 (95% CI 1.60-1.87) on 1 March 2020 to 0.69 (95% CI 0.68-0.70) on 15 April 2020, due to various non-pharmaceutical interventions including school closures, a ban on public gatherings including sports and religious events, and full or partial closure of non-essential businesses. Based on these estimates and given that a near complete containment is no longer feasible, it is likely that the outbreak may continue until the end of the 2020 if the current level of physical distancing and interventions continue and no effective vaccination or therapeutic are developed and made widely available. INTERPRETATION: The series of non-pharmaceutical interventions and the public compliance that took place in Iran are found to be effective in slowing down the speed of the spread of COVID-19 within the studied time period. However, we argue that if the impact of underreporting is overlooked, the estimated transmission and control dynamics could mislead the public health decisions, policy makers, and general public especially in the earlier stages of the outbreak. FUNDING: Nil.


id: cord-348056-kx9wvw8c
author: Goh, H. P.
date: 2020-05-25
url: https://doi.org/10.1101/2020.05.20.20108449
doi: 10.1101/2020.05.20.20108449
title:
  Risk factors affecting COVID-19 case fatality rate: A quantitative analysis of top 50 affected countries

abstract:
  Background: Latest clinical data on treatment on coronavirus disease 2019 (COVID-19) indicated that older patients and those with underlying history of smoking, hypertension or diabetes mellitus might have poorer prognosis of recovery from COVID-19. We aimed to examine the relationship of various prevailing population-based risk factors in comparison with mortality rate and case fatality rate (CFR) of COVID-19. Methods: Demography and epidemiology data which have been identified as verified or postulated risk factors for mortality of adult inpatients with COVID-19 were used. The number of confirmed cases and the number of deaths until April 16, 2020 for all affected countries were extracted from Johns Hopkins University COVID-19 websites. Datasets for indicators that are fitting with the factors of COVID-19 mortality were extracted from the World Bank database. Out of about 185 affected countries, only top 50 countries were selected to be analyzed in this study. The following seven variables were included in the analysis, based on data availability and completeness: 1) proportion of people aged 65 above, 2) proportion of male in the population, 3) diabetes prevalence, 4) smoking prevalence, 5) current health expenditure, 6) number of hospital beds and 7) number of nurses and midwives. Quantitative analysis was carried out to determine the correlation between CFR and the aforementioned risk factors. Results: United States shows about 0.20% of confirmed cases in its country and it has about 4.85% of CFR. Luxembourg shows the highest percentage of confirmed cases of 0.55% but a low 2.05% of CFR, showing that a high percentage of confirmed cases does not necessarily lead to high CFR. There is a significant correlation between CFR, people aged 65 and above (p = 0.35) and diabetes prevalence (p = 0.01). However, in our study, there is no significant correlation between CFR of COVID-19, male gender (p = 0.26) and smoking prevalence (p = 0.60). Conclusion: Older people above 65 years old and diabetic patients are significant risk factors for COVID-19. Nevertheless, gender differences and smoking prevalence failed to prove a significant relationship with COVID-19 mortality rate and CFR. Keywords: Coronavirus, COVID-19, risk, epidemiology, fatality, age, diabetes


id: cord-349921-v1tewoi0
author: Giorgi Rossi, Paolo
date: 2020-05-05
url: https://doi.org/10.1016/j.jcv.2020.104415
doi: 10.1016/j.jcv.2020.104415
abstract: nan
title:
  Case fatality rate in patients with COVID-19 infection and its relationship with length of follow up()


id: cord-349978-zklwovba
title: Inferring the number of COVID-19 cases from recently reported deaths
author: Jombart, Thibaut
date: 2020-04-27
txt: ./txt/cord-349978-zklwovba.txt
cache: ./cache/cord-349978-zklwovba.txt
extension: .txt
mime: text/plain
url: https://doi.org/10.12688/wellcomeopenres.15786.1
doi: 10.12688/wellcomeopenres.15786.1
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.

abstract:
  We estimate the number of COVID-19 cases from newly reported deaths in a population without previous reports. Our results suggest that by the time a single death occurs, hundreds to thousands of cases are likely to be present in that population. This suggests containment via contact tracing will be challenging at this point, and other response strategies should be considered. Our approach is implemented in a publicly available, user-friendly, online tool.


id: cord-354073-tn76muv6
title: Geographic risk assessment of COVID-19 transmission using recent data: An observational study
author: Jen, Tung-Hui
date: 2020-06-12
url: https://doi.org/10.1097/md.0000000000020774
doi: 10.1097/md.0000000000020774
abstract:
  BACKGROUND: The US Centers for Disease Control and Prevention (CDC) regularly issues “travel health notices” that address disease outbreaks of novel coronavirus disease (COVID)-19 in destinations worldwide. The notices are classified into 3 levels based on the risk posed by the outbreak and what precautions should be in place to prevent spreading. What objectively observed criteria of these COVID-19 situations are required for classification and visualization? This study aimed to visualize the epidemic outbreak and the provisional case fatality rate (CFR) using the Rasch model and Bayes's theorem and developed an algorithm that classifies countries/regions into categories that are then shown on Google Maps. METHODS: We downloaded daily COVID-19 outbreak numbers for countries/regions from the GitHub website, which contains information on confirmed cases in more than 30 Chinese locations and other countries/regions. The Rasch model was used to estimate the epidemic outbreak for each country/region using data from recent days. All responses were transformed by using the logarithm function. The Bayes's base CFRs were computed for each region. The geographic risk of transmission of the COVID-19 epidemic was thus determined using both magnitudes (i.e., Rasch scores and CFRs) for each country. RESULTS: The top 7 countries were Iran, South Korea, Italy, Germany, Spain, China (Hubei), and France, with values of {4.53, 3.47, 3.18, 1.65, 1.34 1.13, 1.06} and {13.69%, 0.91%, 47.71%, 0.23%, 24.44%, 3.56%, and 16.22%} for the outbreak magnitudes and CFRs, respectively. The results were consistent with the US CDC travel advisories of warning level 3 in China, Iran, and most European countries and of level 2 in South Korea on March 16, 2020. CONCLUSION: We created an online algorithm that used the CFRs to display the geographic risks to understand COVID-19 transmission. The app was developed to display which countries had higher travel risks and aid with the understanding of the outbreak situation.


id: cord-354133-11b0d499
title: Estimating the Case Fatality Ratio for COVID-19 using a Time-Shifted Distribution Analysis
author: Thomas, B. S.
date: 2020-10-27
url: http://medrxiv.org/cgi/content/short/2020.10.25.20216671v1?rss=1
doi: 10.1101/2020.10.25.20216671
abstract:
  Estimating the case fatality ratio (CFR) for COVID-19 is an important aspect of public health. However, calculating CFR accurately is problematic early in a novel disease outbreak, due to uncertainties regarding the time course of disease and difficulties in diagnosis and reporting of cases. In this work, we present a simple method for calculating the case fatality ratio using only public case and death data over time by exploiting the correspondence between the time distributions of cases and deaths. The time-shifted distribution (TSD) analysis generates two parameters of interest: the delay time between reporting of cases and deaths and the case fatality ratio. These parameters converge reliably over time once the exponential growth phase has finished. Analysis is performed for early COVID 19 outbreaks in many countries, and we discuss corrections to CFR values using excess-death and seroprevalence data to estimate the infection fatality ratio (IFR). While CFR values range from 0.2-20% in different countries, estimates for IFR are mostly around 0.5-0.8% for countries that experienced moderate outbreaks and 1-3% for severe outbreaks. The simplicity and transparency of TSD analysis enhance its usefulness in characterizing a new disease as well as the state of the health and reporting systems.


