ABSTRACT
BackgroundSARS-CoV-2 outbreaks in nursing homes can be large with high case fatality. Identifying asymptomatic individuals early through serial testing is recommended to control COVID-19 in nursing homes, both in response to an outbreak ("outbreak testing" of residents and healthcare personnel) and in facilities without outbreaks ("non-outbreak testing" of healthcare personnel). The effectiveness of outbreak testing and isolation with or without non-outbreak testing was evaluated. MethodsUsing published SARS-CoV-2 transmission parameters, the fraction of SARS-CoV-2 transmissions prevented through serial testing (weekly, every three days, or daily) and isolation of asymptomatic persons compared to symptom-based testing and isolation was evaluated through mathematical modeling using a Reed-Frost model to estimate the percentage of cases prevented (i.e., "effectiveness") through either outbreak testing alone or outbreak plus non-outbreak testing. The potential effect of simultaneous decreases (by 10%) in the effectiveness of isolating infected individuals when instituting testing strategies was also evaluated. ResultsModeling suggests that outbreak testing could prevent 54% (weekly testing with 48-hour test turnaround) to 92% (daily testing with immediate results and 50% relative sensitivity) of SARS-CoV-2 infections. Adding non-outbreak testing could prevent up to an additional 8% of SARS-CoV-2 infections (depending on test frequency and turnaround time). However, added benefits of non-outbreak testing were mostly negated if accompanied by decreases in infection control practice. ConclusionsWhen combined with high-quality infection control practices, outbreak testing could be an effective approach to preventing COVID-19 in nursing homes, particularly if optimized through increased test frequency and use of tests with rapid turnaround. SummaryMathematical modeling evaluated the effectiveness of serially testing asymptomatic persons in a nursing home in response to a SARS-CoV-2 outbreak with or without serial testing of asymptomatic staff in the absence of known SARS-CoV-2 infections.
ABSTRACT
BackgroundCongregate settings are at risk for coronavirus disease 2019 (COVID-19) outbreaks. Diagnostic testing can be used as a tool in these settings to identify outbreaks and to control transmission. MethodsWe used transmission modeling to estimate the minimum number of persons to test and the optimal frequency to detect small outbreaks of COVID-19 in a congregate facility. We also estimated the frequency of testing needed to interrupt transmission within a facility. ResultsThe number of people to test and frequency of testing needed depended on turnaround time, facility size, and test characteristics. Parameters are calculated for a variety of scenarios. In a facility of 100 people, 26 randomly selected individuals would need to be tested at least every 6 days to identify a true underlying prevalence of at least 5%, with test sensitivity of 85%, and greater than 95% outbreak detection sensitivity. Disease transmission could be interrupted with universal, facility-wide testing with rapid turnaround every three days. ConclusionsTesting a subset of individuals in congregate settings can improve early detection of small outbreaks of COVID-19. Frequent universal diagnostic testing can be used to interrupt transmission within a facility, but its efficacy is reliant on rapid turnaround of results for isolation of infected individuals.
ABSTRACT
Balancing the control of SARS-CoV-2 transmission with the resumption of travel is a global priority. Current recommendations include mitigation measures before, during, and after travel. Pre- and post-travel strategies including symptom monitoring, testing, and quarantine can be combined in multiple ways considering different trade-offs in feasibility, adherence, effectiveness, cost and adverse consequences. Here we use a mathematical model to analyze the expected effectiveness of symptom monitoring, testing, and quarantine under different estimates of the infectious period, test-positivity relative to time of infection, and test sensitivity to reduce the risk of transmission from infected travelers during and after travel. If infection occurs 0-7 days prior to travel, immediate isolation following symptom onset prior to or during travel reduces risk of transmission while traveling by 26-30%. Pre-departure testing can further reduce risk if testing is close to the time of departure. For example, testing on the day of departure can reduce risk while traveling by 37-61%. For transmission risk after travel with infection time up to 7 days prior to arrival at the destination, isolation based on symptom monitoring reduced introduction risk at the destination by 42-56%. A 14-day quarantine after arrival, without symptom monitoring or testing, can reduce risk by 97-100% on its own. However, a shorter quarantine of 7 days combined with symptom monitoring and a test on day 3-4 after arrival is also effective (95-99%) at reducing introduction risk and is less burdensome, which may improve adherence. To reduce the risk of introduction without quarantine, optimal test timing after arrival is close to the time of arrival; with effective quarantine after arrival, testing a few days later optimizes sensitivity to detect those infected immediately before or while traveling. These measures can complement recommendations such as social distancing, using masks, and hand hygiene, to further reduce risk during and after travel.
