Optimization of Population-Level Testing, Contact Tracing, and Isolation in Emerging COVID-19 Outbreaks: a Mathematical Modeling Study - Tonghua City and Beijing Municipality, China, 2021-2022

China CDC Wkly. 2023 Jan 27;5(4):82-89. doi: 10.46234/ccdcw2023.016.

Abstract

Introduction: The transmissibility of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant poses challenges for the existing measures containing the virus in China. In response, this study investigates the effectiveness of population-level testing (PLT) and contact tracing (CT) to help curb coronavirus disease 2019 (COVID-19) resurgences in China.

Methods: Two transmission dynamic models (i.e. with and without age structure) were developed to evaluate the effectiveness of PLT and CT. Extensive simulations were conducted to optimize PLT and CT strategies for COVID-19 control and surveillance.

Results: Urban Omicron resurgences can be controlled by multiple rounds of PLT, supplemented by CT - as long as testing is frequent. This study also evaluated the time needed to detect COVID-19 cases for surveillance under different routine testing rates. The results show that there is a 90% probability of detecting COVID-19 cases within 3 days through daily testing. Otherwise, it takes around 7 days to detect COVID-19 cases at a 90% probability level if biweekly testing is used. Routine testing applied to the age group 21-60 for COVID-19 surveillance would achieve similar performance to that applied to all populations.

Discussion: Our analysis evaluates potential PLT and CT strategies for COVID-19 control and surveillance.

Keywords: Contact tracing; Optimization; Population-level testing; SARS-CoV-2 variants.

Grants and funding

Provided by the Beijing Science and Technology Planning Project (Z221100007922019, Z201100005420010); Scientific and Technological Innovation 2030 — Major Project of New Generation Artificial Intelligence (2021ZD0111201); National Natural Science Foundation of China (82073616, 82204160); National Key Research and Development Program of China (2022YFC2303803, 2021YFC0863400); Beijing Advanced Innovation Program for Land Surface Science; Research on Key Technologies of Plague Prevention and Control in Inner Mongolia Autonomous Region (2021ZD0006); Fundamental Research Funds for the Central Universities