Vijay Dhanasekaran’s team investigated the surge of SARS-CoV-2 infections in Hong Kong in early 2022 and the efficiency of the estimates of transmission used by the SAR government, suggesting that those may need to be improved.
Abstract
After keeping infections at bay for two years, Hong Kong experienced a surge of Omicron BA.2 infections in early 2022 that overwhelmed the health care system, isolation facilities, and contact tracing capacity, leading to one of the highest per-capita death rates of COVID-19 in early 2022. The outbreak occurred against a backdrop of a dense population with low immunity towards natural SARS-CoV-2 infection, high vaccine hesitancy in vulnerable populations, comprehensive disease surveillance and the capacity for stringent public health and social measures. Using genome sequences and epidemiological data from this time, we reconstruct the epidemic trajectory of the BA.2 wave, estimate transmission and incidence rates, and evaluate the effectiveness of policy changes. We identify an increase in the effective reproductive rate (Re) to 9.5 in mid-January 2022, which preceded real-time estimates of transmission (Rt), revealing that BA.2 community transmission was under-ascertained weeks before the epidemic appeared to surge in mid-February 2022. Due to this, public health measures were relaxed in early February (Spring Festival) while Re increased and remained > 1 throughout February. An independent estimation of point prevalence and incidence using phylodynamics also indicates extensive superspreading at this time, which likely contributed to the rapid expansion of the epidemic. This study demonstrates that relying on Rt estimation methods dependent on case reporting can misinform epidemic response planning, sometimes with substantial consequences. There is a need for future research and implementation of improved estimates of epidemic growth in near real-time that combine multiple disparate data sources to better inform outbreak response policy.