Association between SARS-CoV-2 Seroprevalence in Nursing Home Staff and Resident COVID-19 Cases and Mortality: A Cross-Sectional Study.
Ania WisniakLakshmi Krishna MenonRoxane DumontNick PullenSimon RegardRichard DubosMaría-Eugenia ZaballaHélène BayssonDelphine Sophie CourvoisierLaurent KaiserDidier PittetAndrew S AzmanSilvia StringhiniIdris GuessousJean-François BalavoineOmar Kheradnull The SEROCoV-Work Study GroupPublished in: Viruses (2021)
The burden of COVID-19 has disproportionately impacted the elderly, who are at increased risk of severe disease, hospitalization, and death. This cross-sectional study aimed to assess the association between SARS-CoV-2 seroprevalence among nursing home staff, and cumulative incidence rates of COVID-19 cases, hospitalizations, and deaths among residents. Staff seroprevalence was estimated within the SEROCoV-WORK+ study between May and September 2020 across 29 nursing homes in Geneva, Switzerland. Data on nursing home residents were obtained from the canton of Geneva for the period between March and August 2020. Associations were assessed using Spearman's correlation coefficient and quasi-Poisson regression models. Overall, seroprevalence among staff ranged between 0 and 31.4%, with a median of 8.3%. A positive association was found between staff seroprevalence and resident cumulative incidence of COVID-19 cases (correlation coefficient R = 0.72, 95%CI 0.45-0.87; incidence rate ratio [IRR] = 1.10, 95%CI 1.07-1.17), hospitalizations (R = 0.59, 95%CI 0.25-0.80; IRR = 1.09, 95%CI 1.05-1.13), and deaths (R = 0.71, 95%CI 0.44-0.86; IRR = 1.12, 95%CI 1.07-1.18). Our results suggest that SARS-CoV-2 transmission between staff and residents may contribute to the spread of the virus within nursing homes. Awareness among nursing home professionals of their likely role in the spread of SARS-CoV-2 has the potential to increase vaccination coverage and prevent unnecessary deaths due to COVID-19.
Keyphrases
- sars cov
- respiratory syndrome coronavirus
- risk factors
- coronavirus disease
- long term care
- patient safety
- magnetic resonance imaging
- physical activity
- healthcare
- quality improvement
- type diabetes
- machine learning
- magnetic resonance
- early onset
- electronic health record
- cardiovascular events
- diffusion weighted imaging