Continuous risk factors in the twenty included nursing homes (NH).

Continuous risk factors in the twenty included nursing homes (NH).</p

Categorical risk factors in the twenty included nursing homes (NH).

Categorical risk factors in the twenty included nursing homes (NH).</p

Overview of the selected risk factors.

aused in unchanged form bnormalization with the total number of residents cnormalization with the number of questions dcombining two variables into one new variable with new factor levels. (DOCX)</p

Graphical presentation of the distribution of seroprevalence (%) across the 20 nursing homes.

Graphical presentation of the distribution of seroprevalence (%) across the 20 nursing homes.</p

Nursing home specific questionnaire.

In a previous study in Belgian nursing homes (NH) during the first wave of the COVID-19 pandemic, we found a SARS-CoV-2 seroprevalence of 17% with a large variability (0–45%) between NH. The current exploratory study aimed to identify nursing home-specific risk factors for high SARS-CoV-2 seroprevalence. Between October 19th, 2020 and November 13th, 2020, during the second COVID-19 wave in Belgium, capillary blood was collected on dried blood spots from 60 residents and staff in each of the 20 participating NH in Flanders and Brussels. The presence of SARS-CoV-2-specific IgG antibodies was assessed by ELISA. Risk factors were evaluated using a questionnaire, filled in by the director or manager of the NH. Assessed risk factors comprised community-related factors, resident-related factors, management and performance features as well as building-related aspects. The relation between risk factors and seroprevalence was assessed by applying random forest modelling, generalized linear models and Bayesian linear regression. The present analyses showed that the prevalence of residents with dementia, the scarcity of personal protective equipment (surgical masks, FFP2 masks, glasses and face shields), and inadequate PCR test capacity were related to a higher seroprevalence. Generally, our study put forward that the various aspects of infection prevention in NH require more attention and investment. This exploratory study suggests that the ratio of residents with dementia, the availability of test capacity and personal protective equipment may have played a role in the SARS-CoV-2 seroprevalence of NH, after the first wave. It underscores the importance of the availability of PPE and education in infection prevention. Moreover, investments may also yield benefits in the prevention of other respiratory infections (such as influenza).</div

Graphical presentation of the random forest modeling showing the relative importance of the risk factors in relation to seroprevalence (using %MSE).

Graphical presentation of the random forest modeling showing the relative importance of the risk factors in relation to seroprevalence (using %MSE).</p

Overview of the risk factors, with respectively regression coefficient and significance level of the univariable relations with seroprevalence, estimated with generalized linear models (1) and median and 95% credible interval (between squared brackets) of the multivariable relations with seroprevalence, estimated with Bayesian generalized linear regression (2<i>)</i>.

Overview of the risk factors, with respectively regression coefficient and significance level of the univariable relations with seroprevalence, estimated with generalized linear models (1) and median and 95% credible interval (between squared brackets) of the multivariable relations with seroprevalence, estimated with Bayesian generalized linear regression (2).</p

Graphical presentation of the random forest modeling showing the relative importance of the risk factors in relation to seroprevalence (using IncNodePurity).

Graphical presentation of the random forest modeling showing the relative importance of the risk factors in relation to seroprevalence (using IncNodePurity).</p