Serial Testing: An Important Tool to Reduce COVID19 Transmission in Communal Settings

BACKGROUND: The COVID19 pandemic continues to pose difficult challenges for Infection Preventionists globally include limiting asymptomatic spread and exposures within challenging physical environments. An academic healthcare system with 4 hospitals with over 1000 inpatient beds, identified that safe patient placement in communal settings to minimize the risk of COVID19 transmission was important to maintain vital services. Communal settings include multibed rooms (semi-private to quads) and rehabilitation and behavioral health units. During the fall of 2020, earlier detection of asymptomatic cases was identified as an opportunity to ensure services would remain operational. METHODS: To minimize COVID19 transmission, prevent outbreaks and service closures, serial testing was implemented for patients in communal settings. By repeating testing at different points in time, the likelihood to detect infection with COVID19 as compared to testing done at one point in time was more comprehensive. An alert was developed in the electronic health record to identify patients who met the criteria for serial testing. The rapid identification of asymptomatic positive COVID19 patients allowed timely implementation of mitigation plans that included patient placement and isolation, rapid contact tracing, strict adherence to social distancing and at times enhanced masking requirements among other strategies. RESULTS: Serial testing of patients in communal settings led to a reduced number of days a treatment area was closed by having the early identification of potential transmission and real time interventions. The addition of an electronic alert proved valuable to ensure timely testing. While unable to calculate the true benefit beyond offering needed services to patients, the use of serial testing limited transmission to patients and staff. Ultimately, this helped alleviate the impact to the stretched workforce. CONCLUSIONS: Serial testing in defined populations was beneficial in the early waves of COVID19. Modifications continue based on the rapidly changing backdrop of the pandemic and evaluation of current data.