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Presence of specific SARS-COV2 antibodies in hemodialysis patients and their caregivers after the first wave of COVID-19.

ABSTRACT: Hemodialysis (HD) patients are at risk for severe COVID-19 and cannot comply with social distancing. SARS-COV2 seroprevalence in French patients and caregivers after the first wave of COVID-19 is unknown. SeroCOVIDial is a prospective study conducted between June and December 2020. SARS-COV2 seroprevalence was evaluated by a rapid serological test (BIOSYNEX) in HD patients and caregivers, and the presence or not of anti-SARS-COV2 neutralizing or non-neutralizing antibodies in patients was also determined by ELISA and seroneutralization. In June 2020, 451 HD patients and 238 caregivers were included. Overall SARS-COV2 seroprevalence was 8.4% (patients) and 6.7% (caregivers), and was 87.1% (patients) and 90.0% (caregivers) in participants with a previously documented SARS-COV2 infection. Overall seroprevalence reached 13.8% (patients) and 12.6% (caregivers) following the second epidemic wave. During the follow-up, 38 (8.4%) patients died (9 of COVID-19). Among the 44 (10.6%) patients who became infected, only two were seropositive at M0. The levels of anti-SARS-COV2 antibodies decreased over time in patients and caregivers. The BIOSYNEX test showed 82.9% sensitivity and 97.7% specificity. Prevalence of anti-SARS-COV2 antibodies was low in HD patients and caregivers after the first epidemic wave but rose after the second wave. A rapid serological test showed good performances and could be useful for future monitoring of anti-SARS-COV2 antibodies.

SUBMITTER: Robert T

PROVIDER: S-EPMC9279503 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Following the rapid dissemination of COVID-19 cases in Colombia in 2020, large-scale non-pharmaceutical interventions (NPIs) were implemented as national emergencies in most of the country's municipalities, starting with a lockdown on March 20th, 2020. Recently, approaches that combine movement data (measured as the number of commuters between units), metapopulation models to describe disease dynamics subdividing the population into Susceptible-Exposed-Asymptomatic-Infected-Recovered-Diseased and statistical inference algorithms have been pointed as a practical approach to both nowcast and forecast the number of cases and deaths. We used an iterated filtering (IF) framework to estimate the model transmission parameters using the reported data across 281 municipalities from March to late October in locations with more than 50 reported deaths and cases in Colombia. Since the model is high dimensional (6 state variables in every municipality), inference on those parameters is highly non-trivial, so we used an Ensemble-Adjustment-Kalman-Filter (EAKF) to estimate time variable system states and parameters. Our results show the model's ability to capture the characteristics of the outbreak in the country and provide estimates of the epidemiological parameters in time at the national level. Importantly, these estimates could become the base for planning future interventions as well as evaluating the impact of NPIs on the effective reproduction number ([Formula: see text]) and the critical epidemiological parameters, such as the contact rate or the reporting rate. However, our forecast presents some inconsistency as it overestimates the deaths for some locations as Medellín. Nevertheless, our approach demonstrates that real-time, publicly available ensemble forecasts can provide short-term predictions of reported COVID-19 deaths in Colombia. Therefore, this model can be used as a forecasting tool to evaluate disease dynamics and aid policymakers in infectious outbreak management and control.

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Presence of specific SARS-COV2 antibodies in hemodialysis patients and their caregivers after the first wave of COVID-19.

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