RESUMEN
BackgroundDespite relatively few reports of residential case clusters of COVID-19, building-wide compulsory testing notices on residential apartment blocks are frequently applied in Hong Kong with the aim of identifying cases and reducing transmission. MethodsWe aimed to describe the frequency of residential case clusters and the efficiency of compulsory testing notices in identifying cases. The residences of locally infected COVID-19 cases in Hong Kong were grouped to quantify the number of cases per residence. Buildings targeted in compulsory testing notices were matched with the residence of cases to estimate the number of cases identified. ResultsWe found that most of the residential buildings (4246/7688, 55.2%) with a confirmed COVID-19 case had only one reported case. In the fourth and the fifth epidemic wave in Hong Kong, we estimated that compulsory testing notices detected 29 cases (95% confidence interval: 26, 32) and 46 cases (44, 48) from every 100 buildings tested (each with hundreds of residents), respectively. Approximately 13% of the daily reported cases were identified through compulsory testing notices. ConclusionsCompulsory testing notices can be an essential method when attempting to maintain local elimination ( zero covid) and most impactful early in an epidemic when the benefit remains of stemming a new wave. Compulsory testing therefore appears to be a relatively inefficient control measure in response to sustained community transmission in the community.
RESUMEN
The serial interval distribution is used to approximate the generation time distribution, an essential parameter to predict the effective reproductive number "Rt", a measure of transmissibility. However, serial interval distributions may change as an epidemic progresses rather than remaining constant. Here we show that serial intervals in Hong Kong varied over time, closely associated with the temporal variation in COVID-19 case profiles and public health and social measures that were implemented in response to surges in community transmission. Quantification of the variation over time in serial intervals led to improved estimation of Rt, and provided additional insights into the impact of public health measures on transmission of infections. One-Sentence SummaryReal-time estimates of serial interval distributions can improve assessment of COVID-19 transmission dynamics and control.