Seroprevalence of Severe Acute Respiratory Syndrome Coronavirus 2 Among Skilled Nursing Facility Residents and Staff Members-Los Angeles County, August-September 2020.

BACKGROUND: The prevalence of current or past coronavirus disease 2019 in skilled nursing facility (SNF) residents is unknown because of asymptomatic infection and constrained testing capacity early in the pandemic. We conducted a seroprevalence survey to determine a more comprehensive prevalence of past coronavirus disease 2019 in Los Angeles County SNF residents and staff members. METHODS: We recruited participants from 24 facilities; participants were requested to submit a nasopharyngeal swab sample for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) polymerase chain reaction (PCR) testing and a serum sample for detection of SARS-CoV-2 antibodies. All participants were cross-referenced with our surveillance database to identify persons with prior positive SARS-CoV-2 results. RESULTS: From 18 August to 24 September 2020, we enrolled 3305 participants (1340 residents and 1965 staff members). Among 856 residents providing serum samples, 362 (42%) had current or past SARS-CoV-2 infection. Of the 346 serology-positive residents, 199 (58%) did not have a documented prior positive SARS-CoV-2 PCR result. Among 1806 staff members providing serum, 454 (25%) had current or past SARS-CoV-2 infection. Of the 447 serology-positive staff members, 353 (79%) did not have a documented prior positive SARS-CoV-2 PCR result. CONCLUSIONS: Past testing practices and policies missed a substantial number of SARS-CoV-2 infections in SNF residents and staff members.

Investigation of a Suspect Severe Acute Respiratory Syndrome Coronavirus-2 and Influenza A Mixed Outbreak: Lessons Learned for Long-Term Care Facilities Nationwide.

A suspected outbreak of influenza A and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at a long-term care facility in Los Angeles County was, months later, determined to not involve influenza. To prevent inadvertent transmission of infections, facilities should use highly specific influenza diagnostics and follow Centers for Disease Control and Prevention (CDC) guidelines that specifically address infection control challenges.

Using control charts to understand community variation in COVID-19.

Decision-makers need signals for action as the coronavirus disease 2019 (COVID-19) pandemic progresses. Our aim was to demonstrate a novel use of statistical process control to provide timely and interpretable displays of COVID-19 data that inform local mitigation and containment strategies. Healthcare and other industries use statistical process control to study variation and disaggregate data for purposes of understanding behavior of processes and systems and intervening on them. We developed control charts at the county and city/neighborhood level within one state (California) to illustrate their potential value for decision-makers. We found that COVID-19 rates vary by region and subregion, with periods of exponential and non-exponential growth and decline. Such disaggregation provides granularity that decision-makers can use to respond to the pandemic. The annotated time series presentation connects events and policies with observed data that may help mobilize and direct the actions of residents and other stakeholders. Policy-makers and communities require access to relevant, accurate data to respond to the evolving COVID-19 pandemic. Control charts could prove valuable given their potential ease of use and interpretability in real-time decision-making and for communication about the pandemic at a meaningful level for communities.