Estimating geographic variation of infection fatality ratios during epidemics.

Objectives: We aim to estimate geographic variability in total numbers of infections and infection fatality ratios (IFR; the number of deaths caused by an infection per 1,000 infected people) when the availability and quality of data on disease burden are limited during an epidemic. Methods: We develop a noncentral hypergeometric framework that accounts for differential probabilities of positive tests and reflects the fact that symptomatic people are more likely to seek testing. We demonstrate the robustness, accuracy, and precision of this framework, and apply it to the United States (U.S.) COVID-19 pandemic to estimate county-level SARS-CoV-2 IFRs. Results: The estimators for the numbers of infections and IFRs showed high accuracy and precision; for instance, when applied to simulated validation data sets, across counties, Pearson correlation coefficients between estimator means and true values were 0.996 and 0.928, respectively, and they showed strong robustness to model misspecification. Applying the county-level estimators to the real, unsimulated COVID-19 data spanning April 1, 2020 to September 30, 2020 from across the U.S., we found that IFRs varied from 0 to 44.69, with a standard deviation of 3.55 and a median of 2.14. Conclusions: The proposed estimation framework can be used to identify geographic variation in IFRs across settings.

The evolution and interpretation of seroprevalence of SARS-CoV-2 antibodies among South African blood donors from the Beta to Omicron variant-driven waves.

BACKGROUND AND OBJECTIVES: Confirmed COVID-19 diagnoses underestimate the total number of infections. Blood donors can provide representative seroprevalence estimates, which can be leveraged into reasonable estimates of total infection counts and infection fatality rate (IFR). MATERIALS AND METHODS: Blood donors who donated after each of three epidemic waves (Beta, Delta and first Omicron waves) were tested for anti-SARS-CoV-2 nucleocapsid antibodies using the Roche Elecsys anti-SARS-CoV-2 total immunoglobulin assay. Roche Elecsys anti-spike antibody testing was done for the post-Omicron sampling. Prevalence of antibodies was estimated by age, sex, race and province and compared to official case reporting. Province and age group-specific IFRs were estimated using external excess mortality estimates. RESULTS: The nationally weighted anti-nucleocapsid seroprevalence estimates after the Beta, Delta and Omicron waves were 47% (46.2%-48.6%), 71% (68.8%-73.5%) and 87% (85.5%-88.4%), respectively. There was no variation by age and sex, but there were statistically and epidemiologically significant differences by province (except at the latest time point) and race. There was a 13-fold higher seroprevalence than confirmed case counts at the first time point. Age-dependent IFR roughly doubled for every 10 years of age increase over 6 decades from 0.014% in children to 6.793% in octogenarians. CONCLUSION: Discrepancies were found between seroprevalence and confirmed case counts. High seroprevalence rates found among Black African donors can be ascribed to historical inequities. Our IFR estimates were useful in refining previous large disagreements about the severity of the epidemic in South Africa. Blood donor-based serosurveys provided a valuable and efficient way to provide near real-time monitoring of the ongoing SARS-CoV-2 outbreak.

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.

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.

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".

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.

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.

The risk of COVID-19 death is much greater and age dependent with type I IFN autoantibodies.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection fatality rate (IFR) doubles with every 5 y of age from childhood onward. Circulating autoantibodies neutralizing IFN-α, IFN-ω, and/or IFN-ß are found in ∼20% of deceased patients across age groups, and in ∼1% of individuals aged <70 y and in >4% of those >70 y old in the general population. With a sample of 1,261 unvaccinated deceased patients and 34,159 individuals of the general population sampled before the pandemic, we estimated both IFR and relative risk of death (RRD) across age groups for individuals carrying autoantibodies neutralizing type I IFNs, relative to noncarriers. The RRD associated with any combination of autoantibodies was higher in subjects under 70 y old. For autoantibodies neutralizing IFN-α2 or IFN-ω, the RRDs were 17.0 (95% CI: 11.7 to 24.7) and 5.8 (4.5 to 7.4) for individuals <70 y and ≥70 y old, respectively, whereas, for autoantibodies neutralizing both molecules, the RRDs were 188.3 (44.8 to 774.4) and 7.2 (5.0 to 10.3), respectively. In contrast, IFRs increased with age, ranging from 0.17% (0.12 to 0.31) for individuals <40 y old to 26.7% (20.3 to 35.2) for those ≥80 y old for autoantibodies neutralizing IFN-α2 or IFN-ω, and from 0.84% (0.31 to 8.28) to 40.5% (27.82 to 61.20) for autoantibodies neutralizing both. Autoantibodies against type I IFNs increase IFRs, and are associated with high RRDs, especially when neutralizing both IFN-α2 and IFN-ω. Remarkably, IFRs increase with age, whereas RRDs decrease with age. Autoimmunity to type I IFNs is a strong and common predictor of COVID-19 death.

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.

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.

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 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.

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.

SARS-CoV-2 infection fatality rate after the first epidemic wave in Mexico.

BACKGROUND: Estimates of SARS-CoV-2 infection fatality rates (IFRs) in developing countries remain poorly characterized. Mexico has one of the highest reported COVID-19 case-fatality rates worldwide, although available estimates do not consider serologic assessment of prior exposure nor all SARS-CoV-2-related deaths. We aimed to estimate sex- and age-specific IFRs for SARS-CoV-2 in Mexico. METHODS: The total number of people in Mexico with evidence of prior SARS-CoV-2 infection was derived from National Survey of Health and Nutrition-COVID-19 (ENSANUT 2020 Covid-19)-a nationally representative serosurvey conducted from August to November 2020. COVID-19 mortality data matched to ENSANUT's dates were retrieved from the death-certificate registry, which captures the majority of COVID-19 deaths in Mexico, and from the national surveillance system, which covers the subset of COVID-19 deaths that were identified by the health system and were confirmed through a positive polymerase chain reaction test. We analysed differences in IFRs by urbanization and region. RESULTS: The national SARS-CoV-2 IFR was 0.47% (95% CI 0.44, 0.50) using death certificates and 0.30% (95% CI 0.28, 0.33) using surveillance-based deaths. The IFR increased with age, being close to zero at age <30 years, but increasing to 1% at ages 50-59 years in men and 60-69 years in women, and being the highest at ≥80 years for men (5.88%) and women (6.23%). Across Mexico's nine regions, Mexico City (0.99%) had the highest and the Peninsula (0.26%) the lowest certificate-based IFRs. Metropolitan areas had higher certificate-based IFR (0.63%) than rural areas (0.17%). CONCLUSION: After the first wave of the COVID-19 pandemic, the overall IFR in Mexico was comparable with those of European countries. The IFR in Mexico increased with age and was higher in men than in women. The variations in IFRs across regions and places of residence within the country suggest that structural factors related to population characteristics, pandemic containment and healthcare capabilities could have influenced lethality at the local level.

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

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.

Trends in seroprevalence of SARS-CoV-2 and infection fatality rate in the Norwegian population through the first year of the COVID-19 pandemic.

BACKGROUND: Infection with the novel coronavirus SARS-CoV-2 induces antibodies that can be used as a proxy for COVID-19. We present a repeated nationwide cross-sectional study assessing the seroprevalence of SARS-CoV-2, the infection fatality rate (IFR), and infection hospitalization rate (IHR) during the first year of the pandemic in Norway. METHODS: Residual serum samples were solicited in April/May 2020 (Round 1), in July/August 2020 (Round 2) and in January 2021 (Round 3). Antibodies against SARS-CoV-2 were measured using a flow cytometer-based assay. Aggregate data on confirmed cases, COVID-19-associated deaths and hospitalizations were obtained from the Emergency preparedness registry for COVID-19 (Beredt C19), and the seroprevalence estimates were used to estimate IFR and IHR. RESULTS: Antibodies against SARS-CoV-2 were measured in 4840 samples. The estimated seroprevalence increased from 0.8% (95% credible interval [CrI] 0.4%-1.3%) after the first wave of the pandemic (Rounds 1 and 2 combined) to 3.2% (95% CrI 2.3%-4.2%) (Round 3). The IFR and IHR were higher in the first wave than in the second wave and increased with age. The IFR was 0.2% (95% CrI 0.1%-0.3%), and IHR was 0.9% (95% CrI 0.6%-1.5%) for the second wave. CONCLUSIONS: The seroprevalence estimates show a cumulative increase of SARS-CoV-2 infections over time in the Norwegian population and suggest some under-recording of confirmed cases. The IFR and IHR were low, corresponding to the relatively low number of COVID-19-associated deaths and hospitalizations in Norway. Most of the Norwegian population was still susceptible to SARS-CoV-2 infection after the first year of the pandemic.

Underdetection in a stochastic SIR model for the analysis of the COVID-19 Italian epidemic.

We propose a way to model the underdetection of infected and removed individuals in a compartmental model for estimating the COVID-19 epidemic. The proposed approach is demonstrated on a stochastic SIR model, specified as a system of stochastic differential equations, to analyse data from the Italian COVID-19 epidemic. We find that a correct assessment of the amount of underdetection is important to obtain reliable estimates of the critical model parameters. The adaptation of the model in each time interval between relevant government decrees implementing contagion mitigation measures provides short-term predictions and a continuously updated assessment of the basic reproduction number.

Estimation of SARS-CoV-2 Infection Fatality Rate by Age and Comorbidity Status Using Antibody Screening of Blood Donors During the COVID-19 Epidemic in Denmark.

BACKGROUND: Studies presenting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection fatality rate (IFR) for healthy individuals are warranted. We estimate IFR by age and comorbidity status using data from a large serosurvey among Danish blood donors and nationwide data on coronavirus disease 2019 (COVID-19) mortality. METHODS: Danish blood donors aged 17-69 years donating blood October 2020-February 2021 were tested with a commercial SARS-CoV-2 total antibody assay. IFR was estimated for weeks 11 to 42, 2020 and week 43, 2020 to week 6, 2021, representing the first 2 waves of COVID-19 epidemic in Denmark. RESULTS: In total, 84944 blood donors were tested for antibodies. The seroprevalence was 2% in October 2020 and 7% in February 2021. Among 3898039 Danish residents aged 17-69 years, 249 deaths were recorded. The IFR was low for people <51 years without comorbidity during the 2 waves (combined IFR=3.36 per 100000 infections). The IFR was below 3‰ for people aged 61-69 years without comorbidity. IFR increased with age and comorbidity but declined from the first to second wave. CONCLUSIONS: In this nationwide study, the IFR was very low among people <51 years without comorbidity.

COVID-19 lockdown - Blessing or disaster?

Despite the dubious results of the nationwide lockdown in India state after state continue to clamp lockdowns indiscriminately and claim that it is a panacea for all their ills. Unverified claims abound and myths are perpetuated without any basis. It is time to take a close look at the hard data and come to logical conclusions regarding the utility of prolonged open-ended lockdowns. Unfortunately, the evidence does not support the use of prolonged lockdowns as a useful strategy to combat the COVID-19 pandemic.