Community-Based Seroprevelance of SARS-CoV-2 in Saudi Arabia.

Introduction  The new coronavirus disease 2019 (COVID-19) is a major global concern. Due to the number of asymptomatic cases that go untested, the actual proportion of those who have been infected is likely to be higher than the reported prevalence. Thus, investigating the exact proportion of those who developed antibodies against the virus through serological surveys is crucial to identify the immune status of the population and direct public health decisions accordingly. Objectives The aim of this study is to estimate the seroprevalence of SARS-CoV-2 in the community and to describe the epidemiological characteristics of the discovered cases. Methods Between July and October 2020, a cross-sectional sero-survey was conducted including a total of 15,873 serum samples collected from seven regions within the kingdom. Using a multistage convenient sampling, people were invited to participate in an interviewer-administrated questionnaire. Afterward, blood samples were collected and seroprevalence was determined using the SARS-CoV-2 virus IgG/IgM antibody detection kits (ELISA). A p-value of <0.05 and 95% CI were used to report the significance. Results The overall seroprevalence of SARS-CoV-2 in the sample was 17.0%, and Makkah region constituted the highest number of reactive cases (33.3%). There was a significant association between all comorbidities and having symptoms except for diabetes. In addition, age, education, nationality, and region were all significant predeterminants of sero-result. Also, contact with a confirmed or suspected case increased the risk of being seropositive by nearly 1.5 times. Conclusion This study estimated the national seroprevalence of SARS-CoV-2 in Saudi Arabia to be 17%. At the time of this study, most of the population did not have the SARS-CoV-2 specific antibodies. This suggests that the population is still below the threshold of herd immunity and emphasizes the importance of mass vaccination programs and abiding by recommended prevention precautions.

Socio-economic determinants of SARS-CoV-2 infection: Results from a population-based cross-sectional serosurvey in Geneva, Switzerland.

Background: SARS-CoV-2 infection and its health consequences have disproportionally affected disadvantaged socio-economic groups globally. This study aimed to analyze the association between socio-economic conditions and having developed antibodies for-SARS-CoV-2 in a population-based sample in the canton of Geneva, Switzerland. Methods: Data was obtained from a population-based serosurvey of adults in Geneva and their household members, between November and December, 2020, toward the end of the second pandemic wave in the canton. Participants were tested for antibodies for-SARS-CoV-2. Socio-economic conditions representing different dimensions were self-reported. Mixed effects logistic regressions were conducted for each predictor to test its association with seropositive status as the main outcome. Results: Two thousand eight hundred and eighty-nine adults completed the study questionnaire and were included in the final analysis. Retired participants and those living in suburban areas had lower odds of a seropositive result when compared to employed participants (OR: 0.42, 95% CI: 0.20-0.87) and those living in urban areas (OR: 0.67, 95% CI: 0.46-0.97), respectively. People facing financial hardship for less than a year had higher odds of a seropositive result compared to those who had never faced them (OR: 2.23, 95% CI: 1.01-4.95). Educational level, occupational position, and household income were not associated with being seropositive, nor were ethnicity or country of birth. Discussion: While conventional measures of socio-economic position did not seem to be related to the risk of being infected in this sample, this study sheds lights on the importance of examining the broader social determinants of health when evaluating the differential impact of the pandemic within the population.

Identifying immunity gaps for measles using Belgian serial serology data.

Vaccine-preventable diseases, such as measles, have been re-emerging in countries with moderate to high vaccine uptake. It is increasingly important to identify and close immunity gaps and increase coverage of routine childhood vaccinations, including two doses of the measles-mumps-rubella vaccine (MMR). Here, we present a simple cohort model relying on a Bayesian approach to evaluate the evolution of measles seroprevalence in Belgium using the three most recent cross-sectional serological survey data collections (2002, 2006 and 2013) and information regarding vaccine properties. We find measles seroprevalence profiles to be similar for the different regions in Belgium. These profiles exhibit a drop in seroprevalence in birth cohorts that were offered vaccination at suboptimal coverages in the first years after routine vaccination has been started up. This immunity gap is observed across all cross-sectional survey years, although it is more pronounced in survey year 2013. At present, the COVID-19 pandemic could negatively impact the immunization coverage worldwide, thereby increasing the need for additional immunization programs in groups of children that are impacted by this. Therefore, it is now even more important to identify existing immunity gaps and to sustain and reach vaccine-derived measles immunity goals.

High Prevalence of Anti-Severe Acute Respiratory Syndrome Coronavirus 2 (Anti-SARS-CoV-2) Antibodies After the First Wave of Coronavirus Disease 2019 (COVID-19) in Kinshasa, Democratic Republic of the Congo: Results of a Cross-sectional Household-Based Survey.

BACKGROUND: In October 2020, after the first wave of coronavirus disease 2019 (COVID-19), only 8290 confirmed cases were reported in Kinshasa, Democratic Republic of the Congo, but the real prevalence remains unknown. To guide public health policies, we aimed to describe the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immunoglobulin G (IgG) antibodies in the general population in Kinshasa. METHODS: We conducted a cross-sectional, household-based serosurvey between 22 October 2020 and 8 November 2020. Participants were interviewed at home and tested for antibodies against SARS-CoV-2 spike and nucleocapsid proteins in a Luminex-based assay. A positive serology was defined as a sample that reacted with both SARS-CoV-2 proteins (100% sensitivity, 99.7% specificity). The overall weighted, age-standardized prevalence was estimated and the infection-to-case ratio was calculated to determine the proportion of undiagnosed SARS-CoV-2 infections. RESULTS: A total of 1233 participants from 292 households were included (mean age, 32.4 years; 764 [61.2%] women). The overall weighted, age-standardized SARS-CoV-2 seroprevalence was 16.6% (95% CI: 14.0-19.5%). The estimated infection-to-case ratio was 292:1. Prevalence was higher among participants ≥40 years than among those <18 years (21.2% vs 14.9%, respectively; P < .05). It was also higher in participants who reported hospitalization than among those who did not (29.8% vs 16.0%, respectively; P < .05). However, differences were not significant in the multivariate model (P = .1). CONCLUSIONS: The prevalence of SARS-CoV-2 is much higher than the number of COVID-19 cases reported. These results justify the organization of a sequential series of serosurveys by public health authorities to adapt response measures to the dynamics of the pandemic.

Infection fatality ratio and case fatality ratio of COVID-19.

The infection fatality ratio (IFR) is the risk of death per infection and is one of the most important epidemiological parameters. Enormous efforts have been undertaken to estimate the IFR for COVID-19. This study examined the pros and cons of several approaches. It is found that the frequently used approaches using serological survey results as the denominator and the number of confirmed deaths as the numerator underestimated the true IFR. The most typical examples are South Africa and Peru (before official correction), where the confirmed deaths are one-third of the excess deaths. We argue that the RT-PCR-based case fatality ratio (CFR) is a reliable indicator of the lethality of COVID-19 in locations where testing is extensive. An accurate IFR is crucial for policymaking and public-risk perception.

Modelling the early phase of the Belgian COVID-19 epidemic using a stochastic compartmental model and studying its implied future trajectories.

Following the onset of the ongoing COVID-19 pandemic throughout the world, a large fraction of the global population is or has been under strict measures of physical distancing and quarantine, with many countries being in partial or full lockdown. These measures are imposed in order to reduce the spread of the disease and to lift the pressure on healthcare systems. Estimating the impact of such interventions as well as monitoring the gradual relaxing of these stringent measures is quintessential to understand how resurgence of the COVID-19 epidemic can be controlled for in the future. In this paper we use a stochastic age-structured discrete time compartmental model to describe the transmission of COVID-19 in Belgium. Our model explicitly accounts for age-structure by integrating data on social contacts to (i) assess the impact of the lockdown as implemented on March 13, 2020 on the number of new hospitalizations in Belgium; (ii) conduct a scenario analysis estimating the impact of possible exit strategies on potential future COVID-19 waves. More specifically, the aforementioned model is fitted to hospital admission data, data on the daily number of COVID-19 deaths and serial serological survey data informing the (sero)prevalence of the disease in the population while relying on a Bayesian MCMC approach. Our age-structured stochastic model describes the observed outbreak data well, both in terms of hospitalizations as well as COVID-19 related deaths in the Belgian population. Despite an extensive exploration of various projections for the future course of the epidemic, based on the impact of adherence to measures of physical distancing and a potential increase in contacts as a result of the relaxation of the stringent lockdown measures, a lot of uncertainty remains about the evolution of the epidemic in the next months.