Dataset Information

Estimates and Determinants of SARS-Cov-2 Seroprevalence and Infection Fatality Ratio Using Latent Class Analysis: The Population-Based Tirschenreuth Study in the Hardest-Hit German County in Spring 2020.

ABSTRACT: SARS-CoV-2 infection fatality ratios (IFR) remain controversially discussed with implications for political measures. The German county of Tirschenreuth suffered a severe SARS-CoV-2 outbreak in spring 2020, with particularly high case fatality ratio (CFR). To estimate seroprevalence, underreported infections, and IFR for the Tirschenreuth population aged ≥14 years in June/July 2020, we conducted a population-based study including home visits for the elderly, and analyzed 4203 participants for SARS-CoV-2 antibodies via three antibody tests. Latent class analysis yielded 8.6% standardized county-wide seroprevalence, a factor of underreported infections of 5.0, and 2.5% overall IFR. Seroprevalence was two-fold higher among medical workers and one third among current smokers with similar proportions of registered infections. While seroprevalence did not show an age-trend, the factor of underreported infections was 12.2 in the young versus 1.7 for ≥85-year-old. Age-specific IFRs were <0.5% below 60 years of age, 1.0% for age 60-69, and 13.2% for age 70+. Senior care homes accounted for 45% of COVID-19-related deaths, reflected by an IFR of 7.5% among individuals aged 70+ and an overall IFR of 1.4% when excluding senior care home residents from our computation. Our data underscore senior care home infections as key determinant of IFR additionally to age, insufficient targeted testing in the young, and the need for further investigations on behavioral or molecular causes of the fewer infections among current smokers.

SUBMITTER: Wagner R

PROVIDER: S-EPMC8230374 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:We undertook a comprehensive, systematic review of observational studies to estimate respective seroprevalences of latent and acute Toxoplasma gondii infections in HIV+ people at the global, regional and country levels; related seroprevalence to socio-economic variables and CD4+ cell counts; and assessed temporal changes in prevalence and risk factors for this group. We systematically searched international databases for seroepidemiological surveys between 1 January 1980 and 31 July 2020. We used a random effects model to calculate pooled seroprevalences with 95% confidence intervals (CI), and estimated the numbers of HIV+ people inferred to harbour latent and acute T. gondii infections (LT or AT). We grouped seroprevalence data according to the geographic regions defined by the World Health Organization (WHO) and conducted subgroup and meta-regression analyses of the data. Of a total of 4024 studies identified, 150 and 65 of them met the inclusion criteria for LT and AT in HIV+ people, respectively. The overall, pooled seroprevalences of LT and AT were 37.4% (95% CI, 33.4-41.4) and 1.3% (95% CI, 0.9-1.8%), equating to ~14.2 and 0.5 million HIV+ people, respectively. Most HIV+ people with T. gondii infections originated from Africa, and the highest seroprevalences were in low-income countries with low human development indices. Significant risk factors for toxoplasmosis in HIV+ patients included the consumption of raw/undercooked meat, frequent contact with soil, a low CD4+ T lymphocyte number (<200 cells per μL) and age. Overall, the finding of high seroprevalences of particularly latent T. gondii infection in HIV+ people in underprivileged regions of the world, such as parts of Africa, calls for preventative action. Programs that include routine serological monitoring, counselling, care, animal control and/or prophylactic treatment measures are needed to prevent severe toxoplasmosis from developing in people living with HIV infection. Our study highlights the potential importance of parasite chemoprophylaxis in resource-poor settings, particularly in low-income countries.

Project description:BackgroundSocial vulnerability indices were created to measure resiliency to environmental disasters based on socioeconomic and population characteristics of discrete geographic regions. They are composed of multiple validated constructs that can also potentially identify geographically vulnerable populations after injury. Our objective was to determine if these indices correlate with injury fatality rates in the US.MethodsWe evaluated three social vulnerability indices: The Hazards & Vulnerability Research Institute's Social Vulnerability Index (SoVI), the Center for Disease Control's Social Vulnerability Index (SVI), and the Economic Innovation Group's Distressed Community Index (DCI). We analyzed SVI subindices and common individual census variables as indicators of socioeconomic status. Outcomes included age-adjusted county-level overall, firearm, and motor vehicle collision deaths per 100,000 population. Linear regression determined the association of injury fatality rates with the SoVI, SVI, and DCI. Bivariate choropleth mapping identified geographic variation and spatial autocorrelation of overall fatality, SoVI, and DCI.ResultsA total of 3,137 US counties were included. Only 24.6% of counties fell into the same vulnerability quintile for all three indices. Despite this, all indices were associated with increasing fatality rates for overall, firearm, and motor vehicle collision fatality. The DCI performed best by model fit, explanation of variance, and diagnostic performance on overall injury fatality. There is significant geographic variation in SoVI, DCI, and injury fatality rates at the county level across the United States, with moderate spatial autocorrelation of SoVI (Moran's I, 0.35; p < 0.01) and high autocorrelation of injury fatality rates (Moran's I, 0.77; p < 0.01) and DCI (Moran's I, 0.53; p < 0.01).ConclusionWhile the indices contribute unique information, higher social vulnerability is associated with higher injury fatality across all indices. These indices may be useful in the epidemiologic and geographic assessment of injury-related fatality rates. Further study is warranted to determine if these indices outperform traditional measures of socioeconomic status and related constructs used in trauma research.Level of evidenceEpidemiological, level IV.

Dataset Information

Estimates and Determinants of SARS-Cov-2 Seroprevalence and Infection Fatality Ratio Using Latent Class Analysis: The Population-Based Tirschenreuth Study in the Hardest-Hit German County in Spring 2020.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets