Number Of Undetected Infections Research Articles

Prevalence of SARS-CoV-2 IgG antibodies in a large prospective cohort study of elite football players in Germany (May–June 2020): implications for a testing protocol in asymptomatic individuals and estimation of the rate of undetected cases

ObjectivesElite professional football players and staff are a unique group that might give insight into the epidemiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in Germany and thus can serve as a model for geographical distribution and an estimation of undetected infections. MethodsIn this prospective cohort study seroprevalence was determined twice in May and June 2020 in players and staff from the German Bundesliga. As screening assays, a commercial ELISA (Euroimmun) and a chemiluminescent immunoassay (CLIA) (Roche) were used, and an in-house neutralization assay (NT) was used as reference standard. Participants were tested twice weekly using PCR from nasopharyngeal and/or oropharyngeal swabs. ResultsSeroprevalence (NT used as confirmation) in 2164 samples from 1184 players and staff was rather similar in May (23/1157, 1.99%) and June (21/1007, 2.09%). All participants were PCR-negative during the study period. Significant regional differences in seroprevalence were not observed. When comparing seroprevalence with the cumulative incidence of infections derived from the German notification system (subgroup matching to cohort; men, age 20–69 years), IgG was found eight to ten times more frequently, pointing to a high rate of undetected infection. ELISA and CLIA correlated only moderately (κ 0.52). ConclusionsSeroprevalence with a high-quality diagnostic in Germany seemed to be around 2%. The number of undetected infections seems to be eight to ten times higher than in notification data. The quality of antibody assays is rather variable, thus results should ideally be confirmed at least by a second assay to prove IgG positivity.

Seroepidemiological study on the spread of SARS-CoV-2 in populations in especially affected areas in Germany - Study protocol of the CORONA-MONITORING lokal study.

At a regional and local level, the COVID-19 pandemic has not spread out uniformly and some German municipalities have been particularly affected. The seroepidemiological data from these areas helps estimate the proportion of the population that has been infected with SARS-CoV-2 (seroprevalence), as well as the number of undetected infections and asymptomatic cases.In four municipalities which were especially affected, 2,000 participants will be tested for an active SARS-CoV-2 infection (oropharyngeal swab) or a past infection (blood specimen IgG antibody test). Participants will also be asked to fill out a short written questionnaire at study centres and complete a follow-up questionnaire either online or by telephone, including information on issues such as possible exposure, susceptability, symptoms and medical history.The CORONA-MONITORING lokal study will allow to determine the proportion of the population with SARS-CoV-2 antibodies in four particularly affected locations. This study will increase the accuracy of estimates regarding the scope of the epidemic, help determine risk and protective factors for an infection and therefore also identify especially exposed groups and, as such, it will be crucial towards planning of prevention measures.

German and international studies on SARS-CoV-2 seroprevalence.

Since the beginning of the year 2020, the SARS-CoV-2 coronavirus has spread globally at a tremendous pace. Studies on the prevalence of SARS-CoV-2 antibodies in the population help estimate the number of people that have already been infected. They also allow an estimate of the number of undetected infections i.e. infections that do not appear in data on officially reported cases. The interpretation of study results needs to consider bias from selective sampling and the diagnostic test properties. To promote networking and co-operation between scientists, the Robert Koch Institute has compiled an overview of the seroepidemiological studies conducted in Germany on its website, which is regularly updated. The RKI conducts searches, for example of press releases, study registry entries or preprint server publications, and contacts the lead investigators of these studies. Of the 40 studies contacted so far, 24 have already provided information (as of 25.06.2020). We can differentiate between studies of the general population, of selected population groups such as healthcare workers, or of ongoing cohorts. This article provides an overview of such studies from Germany, but also of selected international studies. A special focus is set on studies of children and adolescents, which are now of particular interest due to the planned reopening of childcare facilities and schools.

Using Machine Learning to Estimate Unobserved COVID-19 Infections in North America.

Background:The detection of coronavirus disease 2019 (COVID-19) cases remains a huge challenge. As of April 22, 2020, the COVID-19 pandemic continues to take its toll, with >2.6 million confirmed infections and >183,000 deaths. Dire projections are surfacing almost every day, and policymakers worldwide are using projections for critical decisions. Given this background, we modeled unobserved infections to examine the extent to which we might be grossly underestimating COVID-19 infections in North America.Methods:We developed a machine-learning model to uncover hidden patterns based on reported cases and to predict potential infections. First, our model relied on dimensionality reduction to identify parameters that were key to uncovering hidden patterns. Next, our predictive analysis used an unbiased hierarchical Bayesian estimator approach to infer past infections from current fatalities.Results:Our analysis indicates that, when we assumed a 13-day lag time from infection to death, the United States, as of April 22, 2020, likely had at least 1.3 million undetected infections. With a longer lag time—for example, 23 days—there could have been at least 1.7 million undetected infections. Given these assumptions, the number of undetected infections in Canada could have ranged from 60,000 to 80,000. Duarte’s elegant unbiased estimator approach suggested that, as of April 22, 2020, the United States had up to >1.6 million undetected infections and Canada had at least 60,000 to 86,000 undetected infections. However, the Johns Hopkins University Center for Systems Science and Engineering data feed on April 22, 2020, reported only 840,476 and 41,650 confirmed cases for the United States and Canada, respectively.Conclusions:We have identified 2 key findings: (1) as of April 22, 2020, the United States may have had 1.5 to 2.029 times the number of reported infections and Canada may have had 1.44 to 2.06 times the number of reported infections and (2) even if we assume that the fatality and growth rates in the unobservable population (undetected infections) are similar to those in the observable population (confirmed infections), the number of undetected infections may be within ranges similar to those described above. In summary, 2 different approaches indicated similar ranges of undetected infections in North America.Level of Evidence:Prognostic Level V. See Instructions for Authors for a complete description of levels of evidence.

Underestimation of Schistosoma mansoni prevalences

Field methods used for detecting Schistosoma mansoni infection miss a certain proportion of the infections. Prevalences of infection appear to be far under-estimated by faecal screening, with important consequences for control and research. Sake de Vlos and Bruno Gryseels investigate how the number of undetected infections can be statistically inferred from population surveys.