scholarly journals SARS-CoV-2 Infection Fatality Rates in India: Systematic Review, Meta-analysis and Model-based Estimation

2021 ◽  
pp. 232102222110543
Author(s):  
Lauren Zimmermann ◽  
Subarna Bhattacharya ◽  
Soumik Purkayastha ◽  
Ritoban Kundu ◽  
Ritwik Bhaduri ◽  
...  
Keyword(s):  
Meta Analysis ◽  
Case Fatality ◽  
Fatality Rate ◽  
Excess Death ◽  
Seir Model ◽  
Model Based ◽  
Quantitative Synthesis ◽  
Primary Focus ◽  
Using Data ◽  
Excess Deaths

Introduction: Fervourous investigation and dialogue surrounding the true number of SARS-CoV-2-related deaths and implied infection fatality rates in India have been ongoing throughout the pandemic, and especially pronounced during the nation’s devastating second wave. We aim to synthesize the existing literature on the true SARS-CoV-2 excess deaths and infection fatality rates (IFR) in India through a systematic search followed by viable meta-analysis. We then provide updated epidemiological model-based estimates of the wave 1, wave 2 and combined IFRs using an extension of the Susceptible-Exposed-Infected-Removed (SEIR) model, using data from 1 April 2020 to 30 June 2021. Methods: Following PRISMA guidelines, the databases PubMed, Embase, Global Index Medicus, as well as BioRxiv, MedRxiv and SSRN for preprints (accessed through iSearch), were searched on 3 July 2021 (with results verified through 15 August 2021). Altogether, using a two-step approach, 4,765 initial citations were screened, resulting in 37 citations included in the narrative review and 19 studies with 41datapoints included in the quantitative synthesis. Using a random effects model with DerSimonian-Laird estimation, we meta-analysed IFR1, which is defined as the ratio of the total number of observed reported deaths divided by the total number of estimated infections, and IFR2 (which accounts for death underreporting in the numerator of IFR1). For the latter, we provided lower and upper bounds based on the available range of estimates of death undercounting, often arising from an excess death calculation. The primary focus is to estimate pooled nationwide estimates of IFRs with the secondary goal of estimating pooled regional and state-specific estimates for SARS-CoV-2-related IFRs in India. We also tried to stratify our empirical results across the first and second waves. In tandem, we presented updated SEIR model estimates of IFRs for waves 1, 2, and combined across the waves with observed case and death count data from 1 April 2020 to 30 June 2021. Results: For India, countrywide, the underreporting factors (URF) for cases (sourced from serosurveys) range from 14.3 to 29.1 in the four nationwide serosurveys; URFs for deaths (sourced from excess deaths reports) range from 4.4 to 11.9 with cumulative excess deaths ranging from 1.79 to 4.9 million (as of June 2021). Nationwide pooled IFR1 and IFR2 estimates for India are 0.097% (95% confidence interval [CI]: 0.067–0.140) and 0.365% (95% CI: 0.264–0.504) to 0.485% (95% CI: 0.344–0.685), respectively, again noting that IFR2 changes as excess deaths estimates vary. Among the included studies in this meta-analysis, IFR1 generally appears to decrease over time from the earliest study end date to the latest study end date (from 4 June 2020 to 6 July 2021, IFR1 changed from 0.199 to 0.055%), whereas a similar trend is not as readily evident for IFR2 due to the wide variation in excess death estimates (from 4 June 2020 to 6 July 2021, IFR2 ranged from (0.290–1.316) to (0.241–0.651)%). Nationwide SEIR model-based combined estimates for IFR1 and IFR2 are 0.101% (95% CI: 0.097–0.116) and 0.367% (95% CI: 0.358–0.383), respectively, which largely reconcile with the empirical findings and concur with the lower end of the excess death estimates. An advantage of such epidemiological models is the ability to produce daily estimates with updated data, with the disadvantage being that these estimates are subject to numerous assumptions, arduousness of validation and not directly using the available excess death data. Whether one uses empirical data or model-based estimation, it is evident that IFR2 is at least 3.6 times more than IFR1. Conclusion: When incorporating case and death underreporting, the meta-analysed cumulative infection fatality rate in India varied from 0.36 to 0.48%, with a case underreporting factor ranging from 25 to 30 and a death underreporting factor ranging from 4 to 12. This implies, by 30 June 2021, India may have seen nearly 900 million infections and 1.7–4.9 million deaths when the reported numbers stood at 30.4 million cases and 412 thousand deaths (Coronavirus in India) with an observed case fatality rate (CFR) of 1.35%. We reiterate the need for timely and disaggregated infection and fatality data to examine the burden of the virus by age and other demographics. Large degrees of nationwide and state-specific death undercounting reinforce the call to improve death reporting within India. JEL Classifications: I15, I18

scholarly journals SARS-CoV-2 infection fatality rates in India: systematic review, meta-analysis and model-based estimation

2021 ◽  
Author(s):  
Lauren Zimmermann ◽  
Subarna Bhattacharya ◽  
Soumik Purkayastha ◽  
Ritoban Kundu ◽  
Ritwik Bhaduri ◽  
...  
Keyword(s):  
Meta Analysis ◽  
Case Fatality ◽  
Fatality Rate ◽  
Excess Death ◽  
Seir Model ◽  
Model Based ◽  
Quantitative Synthesis ◽  
Using Data ◽  
Second Wave ◽  
Excess Deaths

AbstractIntroductionFervorous investigation and dialogue surrounding the true number of SARS-CoV-2 related deaths and implied infection fatality rates in India have been ongoing throughout the pandemic, and especially pronounced during the nation’s devastating second wave. We aim to synthesize the existing literature on the true SARS-CoV-2 excess deaths and infection fatality rates (IFR) in India, through a systematic search followed by viable meta-analysis. We then provide updated epidemiological model-based estimates of the wave 1, wave 2 and combined IFRs using an extension of the Susceptible-Exposed-Infected-Removed (SEIR) model, using data from April 1, 2020 to June 30, 2021.MethodsFollowing PRISMA guidelines, the databases PubMed, Embase, Global Index Medicus, as well as BioRxiv, MedRxiv, and SSRN for preprints (accessed through iSearch), were searched on July 3, 2021 (with results verified through August 15, 2021). Altogether using a two-step approach, 4,765 initial citations were screened resulting in 37 citations included in the narrative review and 19 studies with 41 datapoints included in the quantitative synthesis. Using a random effects model with DerSimonian-Laird estimation, we meta-analyze IFR1 which is defined as the ratio of the total number of observed reported deaths divided by the total number of estimated infections and IFR2 (which accounts for death underreporting in the numerator of IFR1). For the latter, we provide lower and upper bounds based on the available range of estimates of death undercounting, often arising from an excess death calculation. The primary focus is to estimate pooled nationwide estimates of IFRs with the secondary goal of estimating pooled regional and state-specific estimates for SARS-CoV-2 related IFRs in India. We also try to stratify our empirical results across the first and the second wave. In tandem, we present updated SEIR model estimates of IFRs for waves 1, 2, and combined across the waves with observed case and death count data from April 1, 2020 to June 30, 2021.ResultsFor India countrywide, underreporting factors (URF) for cases (sourced from serosurveys) range from 14.3-29.1 in the four nationwide serosurveys; URFs for deaths (sourced from excess deaths reports) range from 4.4-11.9 with cumulative excess deaths ranging from 1.79-4.9 million (as of June 2021). Nationwide pooled IFR1 and IFR2 estimates for India are 0.097% (95% confidence interval [CI]: 0.067 – 0.140) and 0.365% (95% CI: 0.264 – 0.504) to 0.485% (95% CI: 0.344 – 0.685), respectively, again noting that IFR2 changes as excess deaths estimates vary. Among the included studies in this meta-analysis, the IFR1 generally appear to decrease over time from the earliest study end date to the latest study end date (from 4 June 2020 to 6 July 2021, IFR1 changed from 0.199 to 0.055%), whereas a similar trend is not as readily evident for IFR2 due to the wide variation in excess death estimates (from 4 June 2020 to 6 July 2021, IFR2 ranged from (0.290-1.316) to (0.241-0.651) %).Nationwide SEIR model-based combined estimates for IFR1 and IFR2 are 0.101% (95% CI: 0.097 – 0.116) and 0.367% (95% CI: 0.358 – 0.383), respectively, which largely reconcile with the empirical findings and concur with the lower end of the excess death estimates. An advantage of such epidemiological models is the ability to produce daily estimates with updated data with the disadvantages being that these estimates are subject to numerous assumptions, arduousness of validation and not directly using the available excess death data. Whether one uses empirical data or model-based estimation, it is evident that IFR2 is at least 3.6 times more than IFR1.ConclusionWhen incorporating case and death underreporting, the meta-analyzed cumulative infection fatality rate in India varies from 0.36%-0.48%, with a case underreporting factor ranging from 25-30 and a death underreporting factor ranging from 4-12. This implies, by June 30, 2021, India may have seen nearly 900 million infections and 1.7-4.9 million deaths when the reported numbers stood at 30.4 million cases and 412 thousand deaths (covid19india.org) with an observed case fatality rate (CFR) of 1.35%. We reiterate the need for timely and disaggregated infection and fatality data to examine the burden of the virus by age and other demographics. Large degrees of nationwide and state-specific death undercounting reinforce the call to improve death reporting within India.

scholarly journals Meta-analysis and metaregression of risk factors associated with mortality in hip fracture patients during the COVID-19 pandemic

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Firas J. Raheman ◽  
Djamila M. Rojoa ◽  
Jvalant Nayan Parekh ◽  
Reshid Berber ◽  
Robert Ashford
Keyword(s):  
Hip Fracture ◽  
Hip Fractures ◽  
Case Fatality Rate ◽  
Excess Mortality ◽  
Meta Analysis ◽  
Case Fatality ◽  
Pooled Analysis ◽  
Fatality Rate ◽  
Increased Risk ◽  
The Impact

AbstractIncidence of hip fractures has remained unchanged during the pandemic with overlapping vulnerabilities observed in patients with hip fractures and those infected with COVID-19. We aimed to investigate the independent impact of COVID-19 infection on the mortality of these patients. Healthcare databases were systematically searched over 2-weeks from 1st–14th November 2020 to identify eligible studies assessing the impact of COVID-19 on hip fracture patients. Meta-analysis of proportion was performed to obtain pooled values of prevalence, incidence and case fatality rate of hip fracture patients with COVID-19 infection. 30-day mortality, excess mortality and all-cause mortality were analysed using a mixed-effects model. 22 studies reporting 4015 patients were identified out of which 2651 (66%) were assessed during the pandemic. An excess mortality of 10% was seen for hip fractures treated during the pandemic (OR 2.00, p = 0.007), in comparison to the pre-pandemic controls (5%). Estimated mortality of COVID-19 positive hip fracture patients was four-fold (RR 4.59, p < 0.0001) and 30-day mortality was 38.0% (HR 4.73, p < 0.0001). The case fatality rate for COVID-19 positive patients was 34.74%. Between-study heterogeneity for the pooled analysis was minimal (I2 = 0.00) whereas, random effects metaregression identified subgroup heterogeneity for male gender (p < 0.001), diabetes (p = 0.002), dementia (p = 0.001) and extracapsular fractures (p = 0.01) increased risk of mortality in COVID-19 positive patients.

scholarly journals Crimean-Congo hemorrhagic fever-induced liver injury: a systematic review and meta-analysis

2021 ◽  
Author(s):  
Sawai Singh Rathore ◽  
Ade Harrison Manju ◽  
Qingqing Wen ◽  
Manush Sondhi ◽  
Reshma Pydi ◽  
...  
Keyword(s):  
Liver Injury ◽  
Case Fatality Rate ◽  
Meta Analysis ◽  
Case Series ◽  
Case Fatality ◽  
Hemorrhagic Fever ◽  
Fatality Rate ◽  
High Case Fatality Rate ◽  
Crimean Congo Hemorrhagic Fever ◽  
Pooled Prevalence

Background: Crimean-Congo hemorrhagic fever (CCHF) is a fatal acute tick-borne viral infection and a substantial emerging global public health threat. This illness has a high case fatality rate of up to 40%. The liver is one of the important target organs of the CCHF virus. Objective: The aim of this meta-analysis to evaluate the correlation between CCHF  and liver injury and draw more generalized inferences about the abnormal serum markers of liver injury such as alanine aminotransferase (ALT), aspartate aminotransferase (AST) in CCHF patients. Methods: A literature search was accomplished for published eligible articles with MEDLINE/PubMed and Embase databases. All eligible observational studies and case series were included from around the world. The inclusion criteria were articles describing liver injury biomarkers AST and ALT amongst patients diagnosed with CCHF. Results: Data from 18 studies, consisting of 1238 patients with CCHF  were included in this meta-analysis. The overall pooled prevalence of at least one raised liver injury biomarker was 77.95% (95% CI, I2 = 88.50%, p < 0.0001). Similarly, pooled prevalence of elevated AST and ALT was 85.92% (95% CI, I2 = 85.27%,  p < 0.0001) and 64.30% (95% CI, I2 = 88.32%,  p < 0.0001) respectively.  Both Egger and Begg-Mazumdar’s tests detected no apparent publication bias in all three meta-analyses(p > 0.05).  Conclusion: These elevated liver injury biomarkers have been identified as significant prognostic factors. Hence, Physicians must recognize and continuously monitor these biomarkers, since these aid early stratification of prognosis and the prevention of severe outcomes in infection with such a high case fatality rate.

scholarly journals An Evidence Base for School Health Policy during the COVID-19 Pandemic

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Saif Badran ◽  
Omran Musa ◽  
Somaya Al-maadeed ◽  
Egon Toft ◽  
Suhail Doi
Keyword(s):  
Dose Response ◽  
Case Fatality Rate ◽  
School Health ◽  
Meta Analysis ◽  
Case Fatality ◽  
Evidence Base ◽  
Mortality Data ◽  
Response Analysis ◽  
Fatality Rate ◽  
Epidemiological Characteristics

Objective: Children represent a small fraction of confirmed COVID-19 cases, with a low case fatality rate (CFR). In this paper, we lay out an evidence-based policy for reopening schools. Methods: We gathered age-specific COVID-19 case counts and identified mortality data for 14 countries. Dose-response meta-analysis was used to examine the relationship of the incremental case fatality rate (CFR) to age. In addition, an evidence-to-decision framework (EtD) was used to correlate the dose-response data with other epidemiological characteristics of COVID-19 in childhood. Results: In the dose-response analysis, we found that there was an almost negligible fatality below age 18. CFR rose little between ages 5 to 50 years. The confidence intervals were narrow, suggesting relative homogeneity across countries. Further data suggested decreased childhood transmission from respiratory droplets and a low viral load among children. Conclusions: Opening up schools and kindergartens is unlikely to impact COVID-19 case or mortality rates in both the child and adult populations. We outline a robust plan for schools that recommends that general principles not be micromanaged, with authority left to schools and monitored by public health authorities.

scholarly journals COVID-19 Healthcare Planning: Predicting Mortality and the Role of the Herd Immunity Barrier in the General Population

2020 ◽  
Vol 12 (13) ◽  
pp. 5228
Author(s):  
Julio Emilio Marco-Franco ◽  
Natividad Guadalajara-Olmeda ◽  
Silvia González-de Julián ◽  
David Vivas-Consuelo
Keyword(s):  
General Population ◽  
Case Fatality Rate ◽  
Meta Analysis ◽  
Herd Immunity ◽  
Case Fatality ◽  
Fatality Rate ◽  
Daily Monitoring ◽  
Age Related ◽  
The Impact ◽  
Carlos Iii

Using a mathematical model for COVID-19 incorporating data on excess of mortality compared to the corresponding period of the previous year obtained from the daily monitoring of mortality in Spain (MoMo), the prediction of total number of casualties in Spain for the first outbreak has been computed. From this figure, and following a stepwise meta-analysis of available reports, the case fatality rate (CFR) and the infectious case fatality rate (IFR) for the outbreak have been estimated. As the impact of age on these rates is notable, it is proposed to include an age-related adjusted fatality ratio in future comparative analyses between studies, calculated by adjusting the results by risk ratio to a reference age band (e.g., 60–69). From the casualty figures, and the corresponding CFR and IFR ratios, the forecast of serologically positive cases in the general Spanish population has been estimated at approximately 1% (0.87–1.3%) of the samples. If the data are confirmed by the ongoing study of the Carlos III Institute, until a vaccine is found, the immunity acquired in the general population after the infectious outbreak is far from the 65–70% herd immunity required as a barrier for COVID-19.

scholarly journals Clinical Characteristics and Outcomes of COVID-19–Infected Cancer Patients: A Systematic Review and Meta-Analysis

2020 ◽  
Author(s):  
Hua Zhang ◽  
Han Han ◽  
Tianhui He ◽  
Kristen E Labbe ◽  
Adrian V Hernandez ◽  
...  
Keyword(s):  
Risk Factors ◽  
Systematic Review ◽  
Case Fatality Rate ◽  
Meta Analysis ◽  
Univariate Analysis ◽  
Case Fatality ◽  
The United States ◽  
Fatality Rate ◽  
Patients With Cancer ◽  
Increased Risk

Abstract Background Previous studies have indicated coronavirus disease 2019 (COVID-19) patients with cancer have a high fatality rate. Methods We conducted a systematic review of studies that reported fatalities in COVID-19 patients with cancer. A comprehensive meta-analysis that assessed the overall case fatality rate and associated risk factors was performed. Using individual patient data, univariate and multivariable logistic regression analyses were used to estimate odds ratios (OR) for each variable with outcomes. Results We included 15 studies with 3019 patients, of which 1628 were men; 41.0% were from the United Kingdom and Europe, followed by the United States and Canada (35.7%), and Asia (China, 23.3%). The overall case fatality rate of COVID-19 patients with cancer measured 22.4% (95% confidence interval [CI] = 17.3% to 28.0%). Univariate analysis revealed age (OR = 3.57, 95% CI = 1.80 to 7.06), male sex (OR = 2.10, 95% CI = 1.07 to 4.13), and comorbidity (OR = 2.00, 95% CI = 1.04 to 3.85) were associated with increased risk of severe events (defined as the individuals being admitted to the intensive care unit, or requiring invasive ventilation, or death). In multivariable analysis, only age greater than 65 years (OR = 3.16, 95% CI = 1.45 to 6.88) and being male (OR = 2.29, 95% CI = 1.07 to 4.87) were associated with increased risk of severe events. Conclusions Our analysis demonstrated that COVID-19 patients with cancer have a higher fatality rate compared with that of COVID-19 patients without cancer. Age and sex appear to be risk factors associated with a poorer prognosis.

scholarly journals Global epidemiology of septic shock: a protocol for a systematic review and meta-analysis

BMJ Open ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. e032289
Author(s):  
Frank Leonel Tianyi ◽  
Joel Noutakdie Tochie ◽  
Celestin Danwang ◽  
Aime Mbonda ◽  
Mazou N Temgoua ◽  
...  
Keyword(s):  
Systematic Review ◽  
Septic Shock ◽  
Case Fatality Rate ◽  
Hospital Admissions ◽  
Meta Analysis ◽  
Case Fatality ◽  
Primary Study ◽  
Fatality Rate ◽  
Cross Sectional ◽  
Global Epidemiology

BackgroundSeptic shock is a life-threatening infection frequently responsible for hospital admissions or may be acquired as nosocomial infection in hospitalized patients with resultant significant morbidity and mortality . There is a dearth of data on a résumé and meta-analysis on the global epidemiology of this potentially deadly condition. Therefore, we propose the first systematic review to synthesize existing data on the global incidence, prevalence and case fatality rate of septic shock worldwide.MethodsWe will include cross-sectional, case-control and cohort studies reporting on the incidence, and case fatality rate of septic shock. Electronic databases including PubMed, Embase, WHO Global Health Library and Web of Science will be searched for relevant records published between 1 January 2000 and 31 August 2019. Independents reviewers will perform study selection and data extraction, as well as assessment of methodological quality of included studies. Appropriate meta-analysis will then be used to pool studies judged to be clinically homogenous. Egger’s test and funnel plots will be used to detect publication bias. Findings will be reported and compared by human development level of countries.Ethics and disseminationBeing a review, ethical approval is not required as it was obtained in the primary study which will make up the review. This review is expected to provide relevant data to help in evaluating the burden of septic shock in the general population. The overall findings of this research will be published in a peer-reviewed journal.PROSPERO registration numberCRD42019129783.

scholarly journals Bacterial pathogens and resistance causing community acquired paediatric bloodstream infections in low- and middle-income countries: a systematic review and meta-analysis

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Nina Droz ◽  
Yingfen Hsia ◽  
Sally Ellis ◽  
Angela Dramowski ◽  
Mike Sharland ◽  
...  
Keyword(s):  
Systematic Review ◽  
Blood Culture ◽  
Case Fatality Rate ◽  
Bacterial Pathogens ◽  
Meta Analysis ◽  
Case Fatality ◽  
Bloodstream Infections ◽  
Fatality Rate ◽  
Middle Income ◽  
Middle Income Countries

Abstract Background Despite a high mortality rate in childhood, there is limited evidence on the causes and outcomes of paediatric bloodstream infections from low- and middle-income countries (LMICs). We conducted a systematic review and meta-analysis to characterize the bacterial causes of paediatric bloodstream infections in LMICs and their resistance profile. Methods We searched Pubmed and Embase databases between January 1st 1990 and October 30th 2019, combining MeSH and free-text terms for “sepsis” and “low-middle-income countries” in children. Two reviewers screened articles and performed data extraction to identify studies investigating children (1 month-18 years), with at least one blood culture. The main outcomes of interests were the rate of positive blood cultures, the distribution of bacterial pathogens, the resistance patterns and the case-fatality rate. The proportions obtained from each study were pooled using the Freeman-Tukey double arcsine transformation, and a random-effect meta-analysis model was used. Results We identified 2403 eligible studies, 17 were included in the final review including 52,915 children (11 in Africa and 6 in Asia). The overall percentage of positive blood culture was 19.1% [95% CI: 12.0–27.5%]; 15.5% [8.4–24.4%] in Africa and 28.0% [13.2–45.8%] in Asia. A total of 4836 bacterial isolates were included in the studies; 2974 were Gram-negative (63.9% [52.2–74.9]) and 1858 were Gram-positive (35.8% [24.9–47.5]). In Asia, Salmonella typhi (26.2%) was the most commonly isolated pathogen, followed by Staphylococcus aureus (7.7%) whereas in Africa, S. aureus (17.8%) and Streptococcus pneumoniae (16.8%) were predominant followed by Escherichia coli (10.7%). S. aureus was more likely resistant to methicillin in Africa (29.5% vs. 7.9%), whereas E. coli was more frequently resistant to third-generation cephalosporins (31.2% vs. 21.2%), amikacin (29.6% vs. 0%) and ciprofloxacin (36.7% vs. 0%) in Asia. The overall estimate for case-fatality rate among 8 studies was 12.7% [6.6–20.2%]. Underlying conditions, such as malnutrition or HIV infection were assessed as a factor associated with bacteraemia in 4 studies each. Conclusions We observed a marked variation in pathogen distribution and their resistance profiles between Asia and Africa. Very limited data is available on underlying risk factors for bacteraemia, patterns of treatment of multidrug-resistant infections and predictors of adverse outcomes.

scholarly journals Estimation of the SARS-CoV-2 infection fatality rate in Germany

2021 ◽  
Author(s):  
Thomas Dimpfl ◽  
Jantje Sönksen ◽  
Ingo Bechmann ◽  
Joachim Grammig
Keyword(s):  
Meta Analysis ◽  
Case Fatality ◽  
Total Probability ◽  
Controversial Issues ◽  
Fatality Rate ◽  
Robert Koch Institute ◽  
Specificity And Sensitivity ◽  
Test Specificity ◽  
The Difference ◽  
Official Data

Abstract Assessing the infection fatality rate (IFR) of SARS-CoV-2 is one of the most controversial issues during the pandemic. Due to asymptomatic or mild courses of COVID-19, many infections remain undetected. Reported case fatality rates - COVID-19-associated deaths divided by number of detected infections - are therefore poor estimates of the IFR. Endogenous changes of the population at risk of a SARS-CoV-2 infection, changing test practices and an improved understanding of the pathogenesis of COVID-19 further exacerbate the estimation of the IFR. Here, we propose a strategy to estimate the IFR of SARS-CoV-2 in Germany that combines official data on reported cases and fatalities supplied by the Robert Koch Institute (RKI) with data from seroepidemiological studies in two infection hotspots, the Austrian town Ischgl and the German municipality Gangelt, respectively. For this purpose, we use the law of total probability to derive an approximate formula for the IFR that is based on a set of assumptions regarding data quality and test specificity and sensitivity. The resulting estimate of the IFR in Germany of 0.83% (95% CI: [0.69%; 0.98%]) that is based on a combination of the RKI and Ischgl data is notably higher than the IFR estimate reported in the Gangelt study (0.36% [0.29%; 0.45%]). It is closer to the consolidated estimate based on a meta-analysis (0.68% [0.53%; 0.82%]), where the difference can be explained by Germany's disadvantageous age structure. As a result of virus mutations, vaccination strategies, and improved therapy, a re-estimation of the IFR will eventually be mandated; the proposed method is able to account for such developments.

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