Ascertainment rate of SARS-CoV-2 infections from healthcare and community testing in the UK.

The proportion of SARS-CoV-2 infections ascertained through healthcare and community testing is generally unknown and expected to vary depending on natural factors and changes in test-seeking behaviour. Here we use population surveillance data and reported daily case numbers in the United Kingdom to estimate the rate of case ascertainment. We mathematically describe the relationship between the ascertainment rate, the daily number of reported cases, population prevalence, and the sensitivity of PCR and Lateral Flow tests as a function time since exposure. Applying this model to the data, we estimate that 20%-40% of SARS-CoV-2 infections in the UK were ascertained with a positive test with results varying by time and region. Cases of the Alpha variant were ascertained at a higher rate than the wild type variants circulating in the early pandemic, and higher again for the Delta variant and Omicron BA.1 sub-lineage, but lower for the BA.2 sub-lineage. Case ascertainment was higher in adults than in children. We further estimate the daily number of infections and compare this to mortality data to estimate that the infection fatality rate increased by a factor of 3 during the period dominated by the Alpha variant, and declined in line with the distribution of vaccines. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".

Seroprevalence of SARS-Cov-2 Virus Infection In Kermanshah, Iran: A Population-based Cross-Sectional Study

Background: The aim of this study was to estimate the seroprevalence of SARS-CoV-2 infection in a general population from Kermanshah province, Iran. Method(s): The present study was a population-based cross-sectional design conducted in Kermanshah province in 2020. Sampling was performed in a multi-stage process, and 1967 participants were considered, and also 174 interviewers were assigned to collect data online. Then, 5 mL of blood sample was taken from every participant. The blood samples were centrifuged with the ELISA method to detect SARS-CoV-2-specific IgG and IgM antibodies in serum samples. Seropositive prevalence was adjusted by means of survey analysis. Case fatality rate (CFR) and infection fatality rate (IFR) were estimated. Result(s): A total of 1967 people from 14 cities of the province participated in the study. The mean age of participants was 35.7+/-16.9, and 50.4% were female. The lowest and highest seroprevalence was found in the cities of Paveh (2.3% [0.3-4.2]) and Harsin (61.6% [54.7-68.5]), respectively. The CFR and IFR in men and women were 3.4 vs. 3.3 and 0.1 vs. 0.3. The aged 60 years or older had the highest CFR and IFR with 11.2 and 3.7%, respectively. Conclusion(s): The prevalence of SARS-CoV-2 infection and IFR among the general population of Kermanshah province was 18.3 and 0.3%, respectively. The results of this study can assist the policymaker in assessing risk factors, and transmission dynamics of SARS-CoV-2 in a population and implementing preventive and control interventions.Copyright © 2023 Shadmani et al.

Significantly higher death toll along with COVID-19 mortality than influenza have been reduced by vaccination and restrictions.

The article demonstrates estimated data of influenza and COVID-19 morbidity and infection fatality rate (IFR) mortality in the context of restrictions and vaccination (years 2020-2021 mostly developed countries). A division into two age groups was included: Up to 65 years of age and over 65 years of age. Influenza mortality (IFR) did not change between 2020 and 2021 and was about 0.05% among all, and 0.005 among those under 65 years of age. IFR COVID-19 was on average approx. 0.5% overall, and in groups under 65 years of age a minimum of 0.07%. COVID-19 morbidity varied greatly from about 50/100,000 in Japan to 600/100,000 in Peru during 2020 plus 2021. In the United States and Poland, about 250 per 100 thousand in 2 years. The morbidity rate of COVID-19 in lower risk groups was 70/100 thousand in the United States. The pre-2020 flu morbidity rate in the United States ranged from 1-10 per 100,000 per season. In the 2020/21 season, it decreased to 1/100 thousand. In groups 65 age old and younger, influenza morbidity in the United States was about 0.3 per 100,000 in the 2020/2021 season, and in typical seasons 0.3 to 3/100,000. Examples of absolute numbers. In the United States, in 2021, COVID-19 471,000 victims (a year of available vaccinations). Influenza season 2021 max. 4,500 victims. The average flu season in unrestricted seasons, was about 25,000 victims. Predictions of the consequenc-es of the lack of restrictions and vaccinations are theoretical, because the preliminary ones talk about 2-3 million COVID-19 victims and even more than ten million additional hospitalizations in the United States, which may mean the collapse of the health system, and thus in practice a greater number of victims. The data presented did not result from diagnostic errors. A proper epidemic assessment confirms the effectiveness of vaccination and targeted therapy. COVID-19 vaccination reduced IFR mortality by about 10-fold.Copyright © 2023, Termedia Publishing House Ltd.. All rights reserved.

Seroprevalence of COVID-19 infection in a rural district of Tamil Nadu: A population-based seroepidemiological study

Background: Coronavirus disease 2019 (COVID-19) was a recent global pandemic of the era which posed a great challenge for the health care in terms of preventive, diagnostic and treatment dimensions. The seroprevalence rate of COVID IgG antibodies is very crucial in estimating the susceptibility of a particular area to the viral disease. In our study, we estimated the seroprevalence of COVID-19 in a rural area. Aims and Objectives: We aimed to estimate the seroprevalence of COVID-19 in a rural district of Tamil Nadu, 6 months after the index case. Materials and Methods: We conducted a cross-sectional study of 509 adults aged more than 18 years. From all the seven Taluks, two gram panchayats (administrative cluster of 8-10 villages) were randomly selected followed by one village through convenience. The participants were invited for the study to the community-based study kiosk set up in all the eight villages through village health committees. We collected sociodemographic characteristics and symptoms using a mobile application-based questionnaire, and we tested samples for the presence of IgG antibodies for severe acute respiratory syndrome coronavirus 2 using an electro chemiluminescent immunoassay. We calculated age-gender adjusted and test performance adjusted seroprevalence. Results: The age-and gender-adjusted seroprevalence was 8.5% (95% confidence interval [CI] 6.9-10.8%). The unadjusted seroprevalence among participants with hypertension and diabetes was 16.3% (95% CI: 9.2-25.8) and 10.7% (95% CI: 5.5-18.3), respectively. When we adjusted for the test performance, the seroprevalence was 6.1% (95% CI 4.02-8.17). The study estimated 7 (95% CI 1:4.5-1:9) undetected infected individuals for every reverse transcription polymerase chain reaction confirmed case. Infection fatality rate (IFR) was calculated as 12.38/10,000 infections as on October 22, 2020. History of self-reported symptoms and education were significantly associated with positive status (P<0.05). Conclusion: A significant proportion of the rural population in a district of Tamil Nadu remains susceptible to COVID-19. A higher proportion of susceptible, relatively higher IFR, and a poor tertiary health-care network stress the importance of sustaining the public health measures and promoting early access to the vaccine are crucial to preserving the health of this population. Low population density, good housing, adequate ventilation, limited urbanization combined with public, private, and local health leadership are critical components of curbing future respiratory pandemics. [ FROM AUTHOR] Copyright of Asian Journal of Medical Sciences is the property of Manipal Colleges of Medical Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Estimating COVID-19 Virus Prevalence from Records of Testing Rate and Test Positivity

Introduction: PCR testing for COVID-19 is not done at random but selectively on suspected cases. This paper presents a method to estimate a "genuine virus prevalence” by quantifying and removing the bias related to selective testing. Methods: The data used was from nine (9) neighbouring countries in Western Europe that recorded similar epidemic trends despite differences in testing rate. Regression analysis was used to establish a relationship of declining test positivity with increased testing rate. By extrapolating this trend to an "infinitely complete” testing rate, an unbiased test positivity or "genuine virus prevalence” was computed. Via pairing of "genuine virus prevalence” with excess-deaths, a "genuine infection fatality rate” (IFR) was also derived. Results: Peak levels of "genuine virus prevalence” were around 0.5 to 2% during the 1st epidemic "wave” (week 10 to week 20) and are approaching similar levels in the ongoing 2nd "wave” (week 34 onward). "Genuine virus prevalence” estimates are relatively close to reported seroprevalence in the studied countries with a correlation coefficient of 0.54. "Genuine” IFR is found comparable to closed-community model IFR. Finally, results of community mass-testing in Slovakia are within the estimated range of "genuine virus prevalence”. Conclusions: Estimates of "genuine virus prevalence” benchmark favourably to other indications of virus prevalence suggesting the estimation method is robust and potentially deployable beyond this initial dataset of countries. "Genuine virus prevalence” curves suggest that during the 1st epidemic "wave”, curve flattening and waning happened at very modest levels of infection spread, either naturally or facilitated by government measures. © 2021 The Author(s)..

Twice evasions of Omicron variants explain the temporal patterns in six Asian and Oceanic countries.

BACKGROUND: The ongoing coronavirus 2019 (COVID-19) pandemic has emerged and caused multiple pandemic waves in the following six countries: India, Indonesia, Nepal, Malaysia, Bangladesh and Myanmar. Some of the countries have been much less studied in this devastating pandemic. This study aims to assess the impact of the Omicron variant in these six countries and estimate the infection fatality rate (IFR) and the reproduction number [Formula: see text] in these six South Asia, Southeast Asia and Oceania countries. METHODS: We propose a Susceptible-Vaccinated-Exposed-Infectious-Hospitalized-Death-Recovered model with a time-varying transmission rate [Formula: see text] to fit the multiple waves of the COVID-19 pandemic and to estimate the IFR and [Formula: see text] in the aforementioned six countries. The level of immune evasion and the intrinsic transmissibility advantage of the Omicron variant are also considered in this model. RESULTS: We fit our model to the reported deaths well. We estimate the IFR (in the range of 0.016 to 0.136%) and the reproduction number [Formula: see text] (in the range of 0 to 9) in the six countries. Multiple pandemic waves in each country were observed in our simulation results. CONCLUSIONS: The invasion of the Omicron variant caused the new pandemic waves in the six countries. The higher [Formula: see text] suggests the intrinsic transmissibility advantage of the Omicron variant. Our model simulation forecast implies that the Omicron pandemic wave may be mitigated due to the increasing immunized population and vaccine coverage.

Overview of coronavirus pandemic

During the last months of 2019, numerous cases of respiratory illness such as pneumonia and acute respiratory distress syndrome were described in Wuhan, the capital city of Hubei province in China. At the same time, several research groups identified and reported the etiological agent, that included within the Coronaviridae family and the order Nidovirales, named SARS-CoV-2. Subsequently, the pathological and clinical status caused by the pathogen is commonly known as Coronavirus disease 2019 (COVID-19). In a short period, the outbreak of emerging spread across the world. Therefore the World Health Organization declared a public health emergency of international concern on January 30, 2020, and as a pandemic on March 11, 2020. Many different public health and epidemiological studies have been published since the COVID-19 outbreak, but fatality rates (those that relate the number of cases to mortality) are difficult to assess with certainty. Mean and median case-fatality rates worldwide are near to 3% and 2%, respectively. The median infection fatality calculated from serologic prevalence varies from 0.00% to 1.63% but is mostly estimated between 0.27% and 0.9%. These indexes are influenced by geographic location, socioeconomic status, sex, age, and health conditions, among others. © 2022 Elsevier Inc. All rights reserved.

Jobs, Housing, and Mask Wearing: Cross-Sectional Study of Risk Factors for COVID-19.

BACKGROUND: Many studies have focused on the characteristics of symptomatic patients with COVID-19 and clinical risk factors. This study reports the prevalence of COVID-19 in an asymptomatic population of a hospital service area (HSA) and identifies factors that affect exposure to the virus. OBJECTIVE: The aim of this study is to measure the prevalence of COVID-19 in an HSA, identify factors that may increase or decrease the risk of infection, and analyze factors that increase the number of daily contacts. METHODS: This study surveyed 1694 patients between April 30 and May 13, 2020, about their work and living situations, income, behavior, sociodemographic characteristics, and prepandemic health characteristics. This data was linked to testing data for 454 of these patients, including polymerase chain reaction test results and two different serologic assays. Positivity rate was used to calculate approximate prevalence, hospitalization rate, and infection fatality rate (IFR). Survey data was used to analyze risk factors, including the number of contacts reported by study participants. The data was also used to identify factors increasing the number of daily contacts, such as mask wearing and living environment. RESULTS: We found a positivity rate of 2.2%, a hospitalization rate of 1.2%, and an adjusted IFR of 0.55%. A higher number of daily contacts with adults and older adults increases the probability of becoming infected. Occupation, living in an apartment versus a house, and wearing a face mask outside work increased the number of daily contacts. CONCLUSIONS: Studying prevalence in an asymptomatic population revealed estimates of unreported COVID-19 cases. Occupational, living situation, and behavioral data about COVID-19-protective behaviors such as wearing a mask may aid in the identification of nonclinical factors affecting the number of daily contacts, which may increase SARS-CoV-2 exposure.

Age-stratified infection fatality rate of COVID-19 in the non-elderly population.

The largest burden of COVID-19 is carried by the elderly, and persons living in nursing homes are particularly vulnerable. However, 94% of the global population is younger than 70 years and 86% is younger than 60 years. The objective of this study was to accurately estimate the infection fatality rate (IFR) of COVID-19 among non-elderly people in the absence of vaccination or prior infection. In systematic searches in SeroTracker and PubMed (protocol: https://osf.io/xvupr), we identified 40 eligible national seroprevalence studies covering 38 countries with pre-vaccination seroprevalence data. For 29 countries (24 high-income, 5 others), publicly available age-stratified COVID-19 death data and age-stratified seroprevalence information were available and were included in the primary analysis. The IFRs had a median of 0.034% (interquartile range (IQR) 0.013-0.056%) for the 0-59 years old population, and 0.095% (IQR 0.036-0.119%) for the 0-69 years old. The median IFR was 0.0003% at 0-19 years, 0.002% at 20-29 years, 0.011% at 30-39 years, 0.035% at 40-49 years, 0.123% at 50-59 years, and 0.506% at 60-69 years. IFR increases approximately 4 times every 10 years. Including data from another 9 countries with imputed age distribution of COVID-19 deaths yielded median IFR of 0.025-0.032% for 0-59 years and 0.063-0.082% for 0-69 years. Meta-regression analyses also suggested global IFR of 0.03% and 0.07%, respectively in these age groups. The current analysis suggests a much lower pre-vaccination IFR in non-elderly populations than previously suggested. Large differences did exist between countries and may reflect differences in comorbidities and other factors. These estimates provide a baseline from which to fathom further IFR declines with the widespread use of vaccination, prior infections, and evolution of new variants.

SARS-CoV-2 antibody dynamics in blood donors and COVID-19 epidemiology in eight Brazilian state capitals: A serial cross-sectional study.

Background: The COVID-19 situation in Brazil is complex due to large differences in the shape and size of regional epidemics. Understanding these patterns is crucial to understand future outbreaks of SARS-CoV-2 or other respiratory pathogens in the country. Methods: We tested 97,950 blood donation samples for IgG antibodies from March 2020 to March 2021 in 8 of Brazil's most populous cities. Residential postal codes were used to obtain representative samples. Weekly age- and sex-specific seroprevalence were estimated by correcting the crude seroprevalence by test sensitivity, specificity, and antibody waning. Results: The inferred attack rate of SARS-CoV-2 in December 2020, before the Gamma variant of concern (VOC) was dominant, ranged from 19.3% (95% credible interval [CrI] 17.5-21.2%) in Curitiba to 75.0% (95% CrI 70.8-80.3%) in Manaus. Seroprevalence was consistently smaller in women and donors older than 55 years. The age-specific infection fatality rate (IFR) differed between cities and consistently increased with age. The infection hospitalisation rate increased significantly during the Gamma-dominated second wave in Manaus, suggesting increased morbidity of the Gamma VOC compared to previous variants circulating in Manaus. The higher disease penetrance associated with the health system's collapse increased the overall IFR by a minimum factor of 2.91 (95% CrI 2.43-3.53). Conclusions: These results highlight the utility of blood donor serosurveillance to track epidemic maturity and demonstrate demographic and spatial heterogeneity in SARS-CoV-2 spread. Funding: This work was supported by Itaú Unibanco 'Todos pela Saude' program; FAPESP (grants 18/14389-0, 2019/21585-0); Wellcome Trust and Royal Society Sir Henry Dale Fellowship 204311/Z/16/Z; the Gates Foundation (INV- 034540 and INV-034652); REDS-IV-P (grant HHSN268201100007I); the UK Medical Research Council (MR/S0195/1, MR/V038109/1); CAPES; CNPq (304714/2018-6); Fundação Faculdade de Medicina; Programa Inova Fiocruz-CE/Funcap - Edital 01/2020 Number: FIO-0167-00065.01.00/20 SPU N°06531047/2020; JBS - Fazer o bem faz bem.

Seroprevalence and infection fatality rate of the SARS-CoV-2 Omicron variant in Denmark: A nationwide serosurveillance study.

Background: Introduction of the Omicron variant caused a steep rise in SARS-CoV-2 infections despite high vaccination coverage in the Danish population. We used blood donor serosurveillance to estimate the percentage of recently infected residents in the similarly aged background population with no known comorbidity. Methods: To detect SARS-CoV-2 antibodies induced due to recent infection, and not vaccination, we assessed anti-nucleocapsid (anti-N) immunoglobulin G (IgG) in blood donor samples. Individual level data on SARS-CoV-2 RT-PCR results and vaccination status were available. Anti-N IgG was measured fortnightly from January 18 to April 3, 2022. Samples from November 2021 were analysed to assess seroprevalence before introduction of the Omicron variant in Denmark. Findings: A total of 43 088 donations from 35 309 Danish blood donors aged 17-72 years were screened. In November 2021, 1·2% (103/8 701) of donors had detectable anti-N IgG antibodies. Adjusting for test sensitivity (estimates ranging from 74%-81%) and November seroprevalence, we estimate that 66% (95% confidence intervals (CI): 63%-70%) of the healthy, similarly aged Danish population had been infected between November 1, 2021, and March 15, 2022. One third of infections were not captured by SARS-CoV-2 RT-PCR testing. The infection fatality rate (IFR) was 6·2 (CI: 5·1-7·5) per 100 000 infections. Interpretation: Screening for anti-N IgG and linkage to national registers allowed us to detect recent infections and accurately assess assay sensitivity in vaccinated or previously infected individuals during the Omicron outbreak. The IFR was lower than during previous waves. Funding: The Danish Ministry of Health.

2021 ESC/EACTS Guideline on the diagnosis and treatment of valvular heart disease: Developed by the European Society of Cardiology (ESC) and the European Association for Cardio-Thoracic Surgery (EACTS) Working Groups on the diagnosis and treatment of valvular heart disease

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 although they are important parameters. We devised a simple method to infer TIR and IFR based on the open data. The prevalence rate of the polymerase chain reaction (PCR) tests among the population (Examination Rate;ER) and the positive rate of PCR tests (Infection Rate;IR) for 66 countries were picked up at a website 5 times from April 10th to June 13th, 2020, and the trajectory of each country was drawn over the IR vs. ER plot. IR and ER showed a strong negative correlation for some countries, and TIR was estimated by extrapolating the regression line when the correlation coefficient was between -0.99 and -1. True/Identified Case Ratio (TICR) and IFR were also calculated using the estimated TIR. The estimated TIR well coincided with local antibody surveys. Estimated IFR took on a wide range of values up to 10%: generally high in the Western countries. The estimated IFR of Singapore was very low (0.018%), which may be related to the reported gene mutation causing the attenuation of the viral virulence.

First wave of SARS-CoV-2 in Santiago Chile: Seroprevalence, asymptomatic infection and infection fatality rate.

BACKGROUND: The first wave of SARS-CoV-2 infection in Chile occurred during the cold season reaching a peak by the end of June 2020, with 80 % of the cases concentrated in its capital, Santiago. The main objective of this study was to estimate the attack rate during this first wave of SARS-CoV-2 in a large, densely populated city with more than seven million inhabitants. Since the number of confirmed cases provides biased information due to individuals' potential self-selection, mostly related to asymptomatic patients and testing access, we measured antibodies against SARS-CoV-2 to assess infection prevalence during the first wave in the city, as well as estimate asymptomatic cases, and infection fatality ratio. To our knowledge this is one of the few population-based cross-sectional serosurvey during the first wave in a highly affected emerging country. The challenges of pandemic response in urban settings in a capital city like Santiago, with heterogeneous subpopulations and high mobility through public transportation, highlight the necessity of more accurate information regarding the first waves of new emerging diseases. METHODS: From April 24 to June 21, 2020, 1326 individuals were sampled from a long-standing panel of household representatives of Santiago. Immunochromatographic assays were used to detect IgM and IgG antibody isotypes. RESULTS: Seroprevalence reached 6.79 % (95 %CI 5.58 %-8.26 %) in the first 107 days of the pandemic, without significant differences among sex and age groups; this figure indicates an attack rate 2.8 times higher than the one calculated with registered cases. It also changes the fatality rate estimates, from a 2.33 % case fatality rate reported by MOH to an estimated crude 1.00 % (CI95 % 0.97-1.03) infection fatality rate (adjusted for test performance 1.66 % [CI95 % 1.61-1.71]). Most seropositive were symptomatic (81,1 %). CONCLUSIONS: Despite the high number of cases registered, mortality rates, and the stress produced over the health system, the vast majority of the people remained susceptible to potential new epidemic waves. We contribute to the understanding of the initial spread of emerging epidemic threats. Consequently, our results provide better information to design early strategies that counterattack new health challenges in urban contexts.

Guía ESC/EACTS 2021 sobre el diagnóstico y tratamiento de las valvulopatías: Desarrollada por el Grupo de Trabajo de la Sociedad Europea de Cardiología (ESC) y la European Association for Cardio-Thoracic Surgery (EACTS) sobre el diagnóstico y tratamiento de las valvulopatías

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 although they are important parameters. We devised a simple method to infer TIR and IFR based on the open data. The prevalence rate of the polymerase chain reaction (PCR) tests among the population (Examination Rate;ER) and the positive rate of PCR tests (Infection Rate;IR) for 66 countries were picked up at a website 5 times from April 10th to June 13th, 2020, and the trajectory of each country was drawn over the IR vs. ER plot. IR and ER showed a strong negative correlation for some countries, and TIR was estimated by extrapolating the regression line when the correlation coefficient was between -0.99 and -1. True/Identified Case Ratio (TICR) and IFR were also calculated using the estimated TIR. The estimated TIR well coincided with local antibody surveys. Estimated IFR took on a wide range of values up to 10%: generally high in the Western countries. The estimated IFR of Singapore was very low (0.018%), which may be related to the reported gene mutation causing the attenuation of the viral virulence.

Reduction in the infection fatality rate of Omicron variant compared with previous variants in South Africa.

OBJECTIVE: The SARS-CoV-2 Omicron (B.1.1.529) variant has caused global concern. Previous studies have shown that the variant has enhanced immune evasion ability and transmissibility and reduced severity. METHODS: In this study, we developed a mathematical model with time-varying transmission rate, vaccination, and immune evasion. We fit the model to reported case and death data up to February 6, 2022 to estimate the transmissibility and infection fatality ratio of the Omicron variant in South Africa. RESULTS: We found that the high relative transmissibility of the Omicron variant was mainly due to its immune evasion ability, whereas its infection fatality rate substantially decreased by approximately 78.7% (95% confidence interval: 66.9%, 85.0%) with respect to previous variants. CONCLUSION: On the basis of data from South Africa and mathematical modeling, we found that the Omicron variant is highly transmissible but with significantly lower infection fatality rates than those of previous variants of SARS-CoV-2.

COVID-19 prevalence and mortality in longer-term care facilities.

This essay considers the factors that have contributed to very high COVID-19 mortality in longer-term care facilities (LTCFs). We compare the demographic characteristics of LTCF residents with those of community-dwelling older adults, and then we review the evidence regarding prevalence and infection fatality rates (IFRs), including links to frailty and some comorbidities. Finally, we discuss policy measures that could foster the physical and mental health and well-being of LTCF residents in the present context and in potential future pandemics.

Infection fatality rate and infection attack rate of COVID-19 in South American countries.

BACKGROUND: The ongoing COVID-19 pandemic hit South America badly with multiple waves. Different COVID-19 variants have been storming across the region, leading to more severe infections and deaths even in places with high vaccination coverage. This study aims to assess the spatiotemporal variability of the COVID-19 pandemic and estimate the infection fatality rate (IFR), infection attack rate (IAR) and reproduction number ([Formula: see text]) for twelve most affected South American countries. METHODS: We fit a susceptible-exposed-infectious-recovered (SEIR)-based model with a time-varying transmission rate to the reported COVID-19 deaths for the twelve South American countries with the highest mortalities. Most of the epidemiological datasets analysed in this work are retrieved from the disease surveillance systems by the World Health Organization, Johns Hopkins Coronavirus Resource Center and Our World in Data. We investigate the COVID-19 mortalities in these countries, which could represent the situation  for the overall South American region. We employ COVID-19 dynamic model with-and-without vaccination considering time-varying flexible transmission rate to estimate IFR, IAR and [Formula: see text] of COVID-19 for the South American countries. RESULTS: We simulate the model in each scenario under suitable parameter settings and yield biologically reasonable estimates for IFR (varies between 0.303% and 0.723%), IAR (varies between 0.03 and 0.784) and [Formula: see text] (varies between 0.7 and 2.5) for the 12 South American countries. We observe that the severity, dynamical patterns of deaths and time-varying transmission rates among the countries are highly heterogeneous. Further analysis of the model with the effect of vaccination highlights that increasing the vaccination rate could help suppress the pandemic in South America. CONCLUSIONS: This study reveals possible reasons for the two waves of COVID-19 outbreaks in South America. We observed reductions in the transmission rate corresponding to each wave plausibly due to improvement in nonpharmaceutical interventions measures and human protective behavioral reaction to recent deaths. Thus, strategies coupling social distancing and vaccination could substantially suppress the mortality rate of COVID-19 in South America.

Infection fatality rate of COVID-19 in community-dwelling elderly populations.

This mixed design synthesis aimed to estimate the infection fatality rate (IFR) of Coronavirus Disease 2019 (COVID-19) in community-dwelling elderly populations and other age groups from seroprevalence studies. Protocol: https://osf.io/47cgb . Eligible were seroprevalence studies done in 2020 and identified by any of four existing systematic reviews; with ≥ 500 participants aged ≥ 70 years; presenting seroprevalence in elderly people; aimed to generate samples reflecting the general population; and whose location had available data on cumulative COVID-19 deaths in elderly (primary cutoff ≥ 70 years; ≥ 65 or ≥ 60 also eligible). We extracted the most fully adjusted (if unavailable, unadjusted) seroprevalence estimates; age- and residence-stratified cumulative COVID-19 deaths (until 1 week after the seroprevalence sampling midpoint) from official reports; and population statistics, to calculate IFRs adjusted for test performance. Sample size-weighted IFRs were estimated for countries with multiple estimates. Thirteen seroprevalence surveys representing 11 high-income countries were included in the main analysis. Median IFR in community-dwelling elderly and elderly overall was 2.9% (range 1.8-9.7%) and 4.5% (range 2.5-16.7%) without accounting for seroreversion (2.2% and 4.0%, respectively, accounting for 5% monthly seroreversion). Multiple sensitivity analyses yielded similar results. IFR was higher with larger proportions of people > 85 years. The IFR of COVID-19 in community-dwelling elderly is lower than previously reported.

Estimating the SARS-CoV-2 infection fatality rate by data combination: The case of Germany's first wave*

Assessing the infection fatality rate (IFR) of SARS-CoV-2 in a population is a controversial issue. Due to asymptomatic courses of COVID-19, many infections remain undetected. Reported case fatality rates are therefore poor estimates of the IFR. We propose a strategy to estimate the IFR that combines official data on cases and fatalities with data from seroepidemiological studies in infection hotspots. The application of the method yields an estimate of the IFR of wild-type SARS-CoV-2 in Germany during the first wave of the pandemic of 0.83% (95% CI: [0.69%;0.98%]), notably higher than the estimate reported in the prominent study by Streeck et al. () (0.36% [0.17%;0.77%]) and closer to that obtained from a world-wide meta analysis (0.68% [0.53%;0.82%]), where the difference can be explained by Germany's disadvantageous age structure. Provided that suitable data are available, the proposed method can be applied to estimate the IFR of virus variants and other regions.

Extending the susceptible-exposed-infected-removed (SEIR) model to handle the false negative rate and symptom-based administration of COVID-19 diagnostic tests: SEIR-fansy.

False negative rates of severe acute respiratory coronavirus 2 diagnostic tests, together with selection bias due to prioritized testing can result in inaccurate modeling of COVID-19 transmission dynamics based on reported "case" counts. We propose an extension of the widely used Susceptible-Exposed-Infected-Removed (SEIR) model that accounts for misclassification error and selection bias, and derive an analytic expression for the basic reproduction number R0 as a function of false negative rates of the diagnostic tests and selection probabilities for getting tested. Analyzing data from the first two waves of the pandemic in India, we show that correcting for misclassification and selection leads to more accurate prediction in a test sample. We provide estimates of undetected infections and deaths between April 1, 2020 and August 31, 2021. At the end of the first wave in India, the estimated under-reporting factor for cases was at 11.1 (95% CI: 10.7,11.5) and for deaths at 3.58 (95% CI: 3.5,3.66) as of February 1, 2021, while they change to 19.2 (95% CI: 17.9, 19.9) and 4.55 (95% CI: 4.32, 4.68) as of July 1, 2021. Equivalently, 9.0% (95% CI: 8.7%, 9.3%) and 5.2% (95% CI: 5.0%, 5.6%) of total estimated infections were reported on these two dates, while 27.9% (95% CI: 27.3%, 28.6%) and 22% (95% CI: 21.4%, 23.1%) of estimated total deaths were reported. Extensive simulation studies demonstrate the effect of misclassification and selection on estimation of R0 and prediction of future infections. A R-package SEIRfansy is developed for broader dissemination.