scholarly journals Estimation of the true infection rate and infection fatality rate of coronavirus disease 2019 in each country

2021 ◽  
Author(s):  
Masahiro Sonoo ◽  
Takamichi Kanbayashi ◽  
Takayoshi Shimohata ◽  
Masahito Kobayashi ◽  
Masashi Idogawa ◽  
...  
Keyword(s):  
Infection Rate ◽  
Fatality Rate ◽  
True Infection

scholarly journals Estimation of the true infection rate and infection fatality rate of coronavirus disease 2019 in each country

2020 ◽  
Author(s):  
Masahiro Sonoo ◽  
Takamichi Kanbayashi ◽  
Takayoshi Shimohata ◽  
Masahito Kobayashi ◽  
Masashi Idogawa ◽  
...  
Keyword(s):  
Infection Rate ◽  
Open Data ◽  
Fatality Rate ◽  
Simple Method ◽  
Viral Virulence ◽  
Wide Range ◽  
True Infection ◽  
Range Of Values

The True Infection Rate (TIR) in the whole population of each country and the Infection Fatality Rate (IFR) for coronavirus disease 2019 (COVID-19) are unknown. We devised a simple method to infer TIR and IFR based on the open data. The estimated TIR was compared with local antibody surveys. Estimated IFR took on a wide range of values up to 10%. The importance of the attenuation of the viral virulence is emphasized.

scholarly journals The true case fatality of COVID-19: An analytical solution

2020 ◽  
Author(s):  
Syamantak Khan
Keyword(s):  
Analytical Solution ◽  
Infection Rate ◽  
Case Fatality Rate ◽  
Case Fatality ◽  
Fatality Rate ◽  
Analytical Test ◽  
True Infection

The exact risk of dying from COVID-19 has remained elusive and a topic of debate. In this study, the observed case fatality rates of 46 different countries are hypothesized to be dependent on their testing rates. An analytical test to this hypothesis suggests that the case fatality rate of COVID-19 could be consistent to a certain degree across all countries and states. The current global fatality rate is estimated to be around 1% and expected to converge between 1-3% when the pandemic ends. This model can be helpful to estimate the true infection rate for individual countries.

scholarly journals Estimating SARS-CoV-2 infections from deaths, confirmed cases, tests, and random surveys

2021 ◽  
Vol 118 (31) ◽  
pp. e2103272118
Author(s):  
Nicholas J. Irons ◽  
Adrian E. Raftery
Keyword(s):  
Herd Immunity ◽  
The United States ◽  
Sir Model ◽  
Mitigation Strategies ◽  
Time Varying ◽  
Fatality Rate ◽  
Multiple Sources ◽  
Population Prevalence ◽  
Sample Testing ◽  
True Infection

There are multiple sources of data giving information about the number of SARS-CoV-2 infections in the population, but all have major drawbacks, including biases and delayed reporting. For example, the number of confirmed cases largely underestimates the number of infections, and deaths lag infections substantially, while test positivity rates tend to greatly overestimate prevalence. Representative random prevalence surveys, the only putatively unbiased source, are sparse in time and space, and the results can come with big delays. Reliable estimates of population prevalence are necessary for understanding the spread of the virus and the effectiveness of mitigation strategies. We develop a simple Bayesian framework to estimate viral prevalence by combining several of the main available data sources. It is based on a discrete-time Susceptible–Infected–Removed (SIR) model with time-varying reproductive parameter. Our model includes likelihood components that incorporate data on deaths due to the virus, confirmed cases, and the number of tests administered on each day. We anchor our inference with data from random-sample testing surveys in Indiana and Ohio. We use the results from these two states to calibrate the model on positive test counts and proceed to estimate the infection fatality rate and the number of new infections on each day in each state in the United States. We estimate the extent to which reported COVID cases have underestimated true infection counts, which was large, especially in the first months of the pandemic. We explore the implications of our results for progress toward herd immunity.

scholarly journals Estimating the COVID-19 Infection Rate: Anatomy of an Inference Problem

2020 ◽  
Author(s):  
Charles F. Manski ◽  
Francesca Molinari
Keyword(s):  
New York ◽  
Missing Data ◽  
Infection Rate ◽  
Severe Illness ◽  
Fatality Rate ◽  
Infection Rates ◽  
Inference Problem ◽  
Logical Problem ◽  
Current Context ◽  
Using Data

AbstractAs a consequence of missing data on tests for infection and imperfect accuracy of tests, reported rates of population infection by the SARS CoV-2 virus are lower than actual rates of infection. Hence, reported rates of severe illness conditional on infection are higher than actual rates. Understanding the time path of the COVID-19 pandemic has been hampered by the absence of bounds on infection rates that are credible and informative. This paper explains the logical problem of bounding these rates and reports illustrative findings, using data from Illinois, New York, and Italy. We combine the data with assumptions on the infection rate in the untested population and on the accuracy of the tests that appear credible in the current context. We find that the infection rate might be substantially higher than reported. We also find that the infection fatality rate in Italy is substantially lower than reported.

scholarly journals Estimating missing deaths in Delhi's COVID-19 data

2020 ◽  
Author(s):  
Shoibal Chakravarty
Keyword(s):  
Infection Rate ◽  
Age Group ◽  
Fatality Rate ◽  
Prevalence Survey

A sero-prevalence survey in Delhi measured an infection rate of 23.48% and an implied infection fatality rate (IFR) of 0.06%. Modeling using age group based IFRs from France, Spain and Lombardia project an average IFR that is significantly higher than currently estimated. We show that at least 1500-2500 COVID-19 deaths in the 60+ age group are missing.

scholarly journals Bounding Infection Prevalence by Bounding Selectivity and Accuracy of Tests: With Application to Early COVID-19

2021 ◽  
Author(s):  
Jörg Stoye
Keyword(s):  
Odds Ratio ◽  
Early Stage ◽  
Partial Identification ◽  
Infection Prevalence ◽  
Test Accuracy ◽  
The Novel ◽  
Fatality Rate ◽  
Infection Status ◽  
The One ◽  
True Infection

Abstract I propose novel partial identification bounds on infection prevalence from information on test rate and test yield. The approach utilizes user-specified bounds on (i) test accuracy and (ii) the extent to which tests are targeted, formalized as restriction on the effect of true infection status on the odds ratio of getting tested and thereby embeddable in logit specifications. The motivating application is to the COVID-19 pandemic but the strategy may also be useful elsewhere. Evaluated on data from the pandemic’s early stage, even the weakest of the novel bounds are reasonably informative. Notably, and in contrast to speculations that were widely reported at the time, they place the infection fatality rate for Italy well above the one of influenza by mid-April.

scholarly journals Force of Infection and True Infection Rate of Dengue in Singapore: Implications for Dengue Control and Management

2019 ◽  
Vol 188 (8) ◽  
pp. 1529-1538 ◽  
Author(s):  
Li Kiang Tan ◽  
Swee Ling Low ◽  
Haoyang Sun ◽  
Yuan Shi ◽  
Lilac Liu ◽  
...  
Keyword(s):  
Confidence Interval ◽  
Disease Control ◽  
Infection Rate ◽  
Disease Transmission ◽  
Dengue Infection ◽  
Control Program ◽  
Notification System ◽  
Force Of Infection ◽  
Dengue Control ◽  
True Infection

Abstract National data on dengue notifications do not capture all dengue infections and do not reflect the true intensity of disease transmission. To assess the true dengue infection rate and disease control efforts in Singapore, we conducted age-stratified serosurveys among residents after a 2013 outbreak that was the largest dengue outbreak on record. The age-weighted prevalence of dengue immunoglobulin G among residents was 49.8% (95% confidence interval: 48.4, 51.1) in 2013 and 48.6% (95% confidence interval: 47.0, 50.0) in 2017; prevalence increased with age. Combining these data with those from previous serosurveys, the year-on-year estimates of the dengue force of infection from 1930 to 2017 revealed a significant decrease from the late 1960s to the mid-1990s, after which the force of infection remained stable at approximately 10 per 1,000 persons per year. The reproduction number (R0) had also declined since the 1960s. The reduction in dengue transmission may be attributed to the sustained national vector program and partly to a change in the age structure of the population. The improved estimated ratio of notified cases to true infections, from 1:14 in 2005–2009 to 1:6 in 2014–2017, signifies that the national notification system, which relies on diagnosed cases, has improved over time. The data also suggest that the magnitudes of dengue epidemics cannot be fairly compared across calendar years and that the current disease control program remains applicable.

scholarly journals Infection fatality rate of SARS-CoV-2 infection in a German community with a super-spreading event

2020 ◽  
Author(s):  
Hendrik Streeck ◽  
Bianca Schulte ◽  
Beate M. Kümmerer ◽  
Enrico Richter ◽  
Tobias Höller ◽  
...  
Keyword(s):  
Infection Rate ◽  
Secondary Infection ◽  
Severe Disease ◽  
Case Fatality ◽  
Infection Risk ◽  
Population Characteristics ◽  
Fatality Rate ◽  
Transient Wave ◽  
The World ◽  
Study Participants

AbstractThe world faces an unprecedented SARS-CoV2 pandemic where many critical factors still remain unknown. The case fatality rates (CFR) reported in the context of the SARS-CoV-2 pandemic substantially differ between countries. For SARS-CoV-2 infection with its broad clinical spectrum from asymptomatic to severe disease courses, the infection fatality rate (IFR) is the more reliable parameter to predict the consequences of the pandemic. Here we combined virus RT-PCR testing and assessment for SARS-CoV2 antibodies to determine the total number of individuals with SARS-CoV-2 infections in a given population.MethodsA sero-epidemiological GCP- and GEP-compliant study was performed in a small German town which was exposed to a super-spreading event (carnival festivities) followed by strict social distancing measures causing a transient wave of infections. Questionnaire-based information and biomaterials were collected from a random, household-based study population within a seven-day period, six weeks after the outbreak. The number of present and past infections was determined by integrating results from anti-SARS-CoV-2 IgG analyses in blood, PCR testing for viral RNA in pharyngeal swabs and reported previous positive PCR tests.ResultsOf the 919 individuals with evaluable infection status (out of 1,007; 405 households) 15.5% (95% CI: [12.3%; 19.0%]) were infected. This is 5-fold higher than the number of officially reported cases for this community (3.1%). Infection was associated with characteristic symptoms such as loss of smell and taste. 22.2% of all infected individuals were asymptomatic. With the seven SARS-CoV-2-associated reported deaths the estimated IFR was 0.36% [0.29%; 0.45%]. Age and sex were not found to be associated with the infection rate. Participation in carnival festivities increased both the infection rate (21.3% vs. 9.5%, p<0.001) and the number of symptoms in the infected (estimated relative mean increase 1.6, p=0.007). The risk of a person being infected was not found to be associated with the number of study participants in the household this person lived in. The secondary infection risk for study participants living in the same household increased from 15.5% to 43.6%, to 35.5% and to 18.3% for households with two, three or four people respectively (p<0.001).ConclusionsWhile the number of infections in this high prevalence community is not representative for other parts of the world, the IFR calculated on the basis of the infection rate in this community can be utilized to estimate the percentage of infected based on the number of reported fatalities in other places with similar population characteristics. Whether the specific circumstances of a super-spreading event not only have an impact on the infection rate and number of symptoms but also on the IFR requires further investigation. The unexpectedly low secondary infection risk among persons living in the same household has important implications for measures installed to contain the SARS-CoV-2 virus pandemic.

scholarly journals Estimating Lower Bounds for COVID-19 Mortality from Northern Italian Towns

2020 ◽  
Author(s):  
Thomas S. Coleman
Keyword(s):  
Infection Rate ◽  
Lower Bounds ◽  
Excess Mortality ◽  
Fatality Rate ◽  
Epidemiological Modeling ◽  
Specific Mortality ◽  
Italian Provinces ◽  
Using Data ◽  
The Town ◽  
Age And Sex

AbstractFor COVID-19 the Infection Fatality Rate or IFR – a crucial variable in epidemiological modeling – is difficult to estimate because many cases are asymptomatic and the overall infection rate is generally not known. Circumstances in the Italian provinces of Milano, Bergamo, Brescia, and Lodi allow estimation of lower bounds for age- and sex-specific all-cause excess mortality (a proxy for IFR) since anecdotal reports indicate some towns were close to fully infected. Using data from ISTAT on mortality from January 1 through April 15 for 2020 and the three preceding years, I estimate excess mortality by sex and age categories (0-14, 15-54, 55-64, 65-74, and 75+ years) while controlling for town-specific mortality that proxies for town-specific infection rate. The 99th percentile from the tail of the town distribution gives a lower-bound estimate for COVID-19 mortality. The overall population-weighted mortality at the 99th percentile is 1.09 percent (95% CI 1.06-1.14). The age- and sex-specific rates vary considerably: for men age 65-74 the estimate is 2.10 percent (95% CI 1.94-2.28) which is 3.5-times higher than men 55-64 and 2.7-times higher than women 65-74.

scholarly journals Infection fatality rate of SARS-CoV2 in a super-spreading event in Germany

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Hendrik Streeck ◽  
Bianca Schulte ◽  
Beate M. Kümmerer ◽  
Enrico Richter ◽  
Tobias Höller ◽  
...  
Keyword(s):  
Observational Study ◽  
Community Participation ◽  
Infection Rate ◽  
Small Town ◽  
Healthcare Systems ◽  
Population Characteristics ◽  
Fatality Rate ◽  
Infection Status ◽  
Ideal Model ◽  
Study Population

AbstractA SARS-CoV2 super-spreading event occurred during carnival in a small town in Germany. Due to the rapidly imposed lockdown and its relatively closed community, this town was seen as an ideal model to investigate the infection fatality rate (IFR). Here, a 7-day seroepidemiological observational study was performed to collect information and biomaterials from a random, household-based study population. The number of infections was determined by IgG analyses and PCR testing. We found that of the 919 individuals with evaluable infection status, 15.5% (95% CI:[12.3%; 19.0%]) were infected. This is a fivefold higher rate than the reported cases for this community (3.1%). 22.2% of all infected individuals were asymptomatic. The estimated IFR was 0.36% (95% CI:[0.29%; 0.45%]) for the community and 0.35% [0.28%; 0.45%] when age-standardized to the population of the community. Participation in carnival increased both infection rate (21.3% versus 9.5%, p < 0.001) and number of symptoms (estimated relative mean increase 1.6, p = 0.007). While the infection rate here is not representative for Germany, the IFR is useful to estimate the consequences of the pandemic in places with similar healthcare systems and population characteristics. Whether the super-spreading event not only increases the infection rate but also affects the IFR requires further investigation.

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