Modelling the impacts of public health interventions and weather on SARS-CoV-2 Omicron outbreak in Hong Kong

Abstract

AbstractBackgroundHong Kong, has operated under a zero-Covid policy in the past few years. As a result, population immunity from natural infections has been low. The ‘fifth wave’ in Hong Kong, caused by the Omicron variant, grew substantially in February 2022 during the transition from winter into spring. The daily number of reported cases began to decline quickly in a few days after social distancing regulations were tightened and rapid antigen test (RAT) kits were largely distributed. How the non-pharmaceutical interventions (NPIs) and seasonal factors (temperature and relative humidity) could affect the spread of Omicron remains unknown.MethodsWe developed a model with stratified immunity, to incorporate antibody responses, together with changes in mobility and seasonal factors. After taking into account the detection rates of PCR test and RAT, we fitted the model to the daily number of reported cases between 1 February and 31 March, and quantified the associated effects of individual NPIs and seasonal factors on infection dynamics.FindingsAlthough NPIs and vaccine boosters were critical in reducing the number of infections, temperature was associated with a larger change in transmissibility. Cold days appeared to drive Re from about 2–3 sharply to 10.6 (95%CI: 9.9–11.4). But this number reduced quickly below one a week later when the temperature got warmer. The model projected that if weather in March maintained as February’s average level, the estimated cumulative incidence could increase double to about 80% of total population.InterpretationTemperature should be taken into account when making public health decisions (e.g. a more relaxed (or tightened) social distancing during a warmer (or colder) season).