An Optimal Nucleic Acid Testing Strategy for COVID-19 during the Spring Festival Travel Rush in Mainland China: A Modelling Study

Abstract

Western countries are experiencing surges in COVID-19 cases and deaths due to increasing public transportation during holiday seasons. This study aimed to explore whether mainland China will face an epidemic rebound during the Spring Festival holiday, when millions of Chinese people travel across the country, and investigate which nucleic acid testing (NAT) strategy is optimal to contain the epidemic. A microsimulation model was used to simulate SARS-CoV-2 transmission among railway travelers and evaluated the effects of various NAT strategies. An extended susceptible-exposed-infectious-recovered (SEIR) model was built to forecast local transmission during the Spring Festival period under different scenarios of testing strategies. The total number of infections, testing burden, and medical expenditure were calculated to devise an optimal strategy during the Spring Festival travel rush. Assuming the daily incidence of 20 per 10 million persons, our model simulated that there would be 97 active infections on the day of travel among 10 million railway passengers without NAT and symptom screening. Pre-travel testing could reduce the number of active infections. Compared with no NAT, testing passengers from risk tier 2–4 regions 3 days before travelling could significantly reduce the risk of transmission, and it is more economical and efficient than testing for all passengers.

A systematic review of COVID-19 transport policies and mitigation strategies around the globe

“…Another strategy implemented by some governments consists of passenger screening . Pre-travel testing is studied by Zhou et al (2021) with an emphasis on reducing the risk of contagion. The study demonstrates how testing 3 days before traveling could significantly reduce the risk of transmission, and it is more economical and efficient than testing for all passengers.…”

A Chess and Card Room-Induced COVID-19 Outbreak and Its Agent-Based Simulation in Yangzhou, China

“…This model divided the population into five compartments, i.e., the vaccinated population V, the susceptible population S, the exposed population E, the infected population I, and the removed population R. The removed population contained individuals removed from transmission due to death or recovery, as well as individuals that were quarantined. Once the infected persons obtained laboratory confirmation, they would be quarantined and would not cause secondary infection anymore (7). In this model, the age of cases was divided into three parts (younger than 15, 15 to 59, and older than 59) (Supplementary Table 1).…”

International Travel-Related Control Measures to contain The Covid-19 Pandemic: An update to a Cochrane Rapid Review

“…The study does not provide a specific effect measure for an air travel-related control measure Well 2021 (63) The study does not measure the specified interventions Wells 2021 (64) The study does not assess the impact of an air travel-related control measure Yang 2021 (65) No data for analysis Yokota 2021 (66) The study did not incorporate the specified study design Yousif 2020 (67) The study does not assess the impact of an air travel-related control measure Yue 2021 (68) The study does not measure the specified interventions Zhou 2021 (69) The study does not assess the impact of an air travel-related control measure Zhu 2021 (70) The study does not measure the specified interventions Zhu 2021 (71) The study does not measure the specified interventions…”