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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 | 2022 Jul

REPOSITORIES: biostudies-literature

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

Robert Thomas T Lano Guillaume G Resseguier Noémie N Bobot Mickaël M Bouchouareb Dammar D Burtey Stéphane S de Lamballerie Xavier X Dhorne Jean J Dussol Bertrand B Duval Ariane A Faraut Julien J Fourié Toscane T Giaime Philippe P Hallah Mourad M Jaubert Dominique D Jéhel Océane O Legris Tristan T Liotatis Stéphane S Moal Valérie V Ninove Laetitia L Pedinielli Nathalie N Pelletier Marion M Romeu-Giannoli Manon M Saba Mariela M Sallée Marion M Samson Laurent L Saveanu Adriana A Scarfoglière Violaine V Sebahoun Pascale P Vial Romain R Von Kotze Clarissa C Brunet Philippe P Lebrun Gaëtan G Bataille Stanislas S Jourde-Chiche Noémie N

Scientific reports 20220713 1

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 d ...[more]

PMID: 35831388

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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.

Project description:Background: Attempts to quantify effect sizes of non-pharmaceutical interventions (NPI) to control COVID-19 in the US have not accounted for heterogeneity in social or environmental factors that may influence NPI effectiveness. This study quantifies national and sub-national effect sizes of NPIs during the early months of the pandemic in the US. Methods: Daily county-level COVID-19 cases and deaths during the first wave (January 2020 through phased removal of interventions) were obtained. County-level cases, doubling times, and death rates were compared to four increasingly restrictive NPI levels. Socio-demographic, climate and mobility factors were analyzed to explain and evaluate NPI heterogeneity, with mobility used to approximate NPI compliance. Analyses were conducted separately for the US and for each Census regions (Pacific, Mountain, east/West North Central, East/West South Central, South Atlantic, Middle Atlantic and New England). A stepped-wedge cluster-randomized trial analysis was used, leveraging the phased implementation of policies. Results: Aggressive (level 4) NPIs were associated with slower COVID-19 propagation, particularly in high compliance counties. Longer duration of level 4 NPIs was associated with lower case rates (log beta -0.028, 95% CI -0.04 to -0.02) and longer doubling times (log beta 0.02, 95% CI 0.01-0.03). Effects varied by Census region, for example, level 4 effects on doubling time in Pacific states were opposite to those in Middle Atlantic and New England states. NPI heterogeneity can be explained by differential timing of policy initiation and by variable socio-demographic county characteristics that predict compliance, particularly poverty and racial/ethnic population. Climate exhibits relatively consistent relationships across Census regions, for example, higher minimum temperature and specific humidity were associated with lower doubling times and higher death rates for this period of analysis in South Central, South Atlantic, Middle Atlantic, and New England states. Conclusion and Relevance: Heterogeneity exists in both the effectiveness of NPIs across US Census regions and policy compliance. This county-level variability indicates that control strategies are best designed at community-levels where policies can be tuned based on knowledge of local disparities and compliance with public health ordinances.

Dataset Information

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

Publications

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

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