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1.
Journal of the American Medical Directors Association ; 2023.
Article in English | EuropePMC | ID: covidwho-2302183

ABSTRACT

Objectives Quantify the effects of characteristics of nursing homes and their surrounding on the spread of COVID-19 outbreaks and assess the changes in resident protection between the first two waves (March 1 to July 31 and August 1 to December 31, 2020). Design An observational study was carried out on data on COVID-19 outbreaks extracted from a database that monitored the spread of the virus in nursing homes. Setting and participants The study concerned all 937 nursing homes with > 10 beds in Auvergne-Rhône-Alpes Region, France. Methods The rate of nursing homes with at least one outbreak and the cumulative number of deaths were modeled for each wave. Results During the second (vs. the first wave), the proportion of nursing homes that reported at least one outbreak was higher (70% vs. 56%) and the cumulative number of deaths more than twofold (3348 vs. 1590). The outbreak rate was significantly lower in public hospital-associated nursing homes than in private for-profit ones. During the second wave, it was lower in public and private not-for-profit nursing homes than in private for-profit ones. During the first wave, the probability of outbreak and the mean number of deaths increased with the number of beds (p < 0.001). During the second wave, the probability of outbreak remained stable in > 80-bed institutions and, under proportionality assumption, the mean number of death was less than expected in > 100-bed institutions. The outbreak rate and the cumulative number of deaths increased significantly with the increase in the incidence of hospitalization for COVID-19 in the surrounding populations. Conclusions and implications The outbreak in the nursing homes was stronger during the second than the first wave despite better preparedness and higher availabilities of tests and protective equipment. Insufficient staffing, inadequate rooming, and suboptimal functioning should find solutions before future epidemics.

2.
PLoS One ; 17(1): e0261756, 2022.
Article in English | MEDLINE | ID: covidwho-1613356

ABSTRACT

BACKGROUND: Worldwide, COVID-19 outbreaks in nursing homes have often been sudden and massive. The study investigated the role SARS-CoV-2 virus spread in nearby population plays in introducing the disease in nursing homes. MATERIAL AND METHODS: This was carried out through modelling the occurrences of first cases in each of 943 nursing homes of Auvergne-Rhône-Alpes French Region over the first epidemic wave (March-July, 2020). The cumulative probabilities of COVID-19 outbreak in the nursing homes and those of hospitalization for the disease in the population were modelled in each of the twelve Départements of the Region over period March-July 2020. This allowed estimating the duration of the active outbreak period, the dates and heights of the peaks of outbreak probabilities in nursing homes, and the dates and heights of the peaks of hospitalization probabilities in the population. Spearman coefficient estimated the correlation between the two peak series. RESULTS: The cumulative proportion of nursing homes with COVID-19 outbreaks was 52% (490/943; range: 22-70% acc. Département). The active outbreak period in the nursing homes lasted 11 to 21 days (acc. Département) and ended before lockdown end. Spearman correlation between outbreak probability peaks in nursing homes and hospitalization probability peaks in the population (surrogate of the incidence peaks) was estimated at 0.71 (95% CI: [0.66; 0.78]). CONCLUSION: The modelling highlighted a strong correlation between the outbreak in nursing homes and the external pressure of the disease. It indicated that avoiding disease outbreaks in nursing homes requires a tight control of virus spread in the surrounding populations.


Subject(s)
COVID-19/epidemiology , COVID-19/transmission , Nursing Homes/trends , Communicable Disease Control/methods , Disease Outbreaks/prevention & control , Disease Outbreaks/statistics & numerical data , Epidemiological Models , France/epidemiology , Humans , Pandemics , SARS-CoV-2/pathogenicity
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