Published in the Journal of Population Economics on Thursday, it suggests that more than 1.4 million infections and 56,000 deaths were avoided due to national and provincial measures imposed in late January.
The study, led by Xi Chen, President of the China Health Policy and Management Society, cited local and cross-city transmissions of COVID-19 in the country between January 19 and February 29.
The team implemented a machine learning approach to select instrumental variables that strongly predict virus transmission among the rich exogenous weather characteristics.
They examined the role of various factors, including public health measures that encourage social distancing in local communities.
The study shows that stringent quarantine, city lockdown, and local public health measures imposed since late January significantly decreased the virus transmission rate.
The most effective measure was found to be “city lockdown” first, followed by “closed management of communities” and “family outdoor restrictions,” according to the study.
Population outflow from the outbreak source region posed a higher risk to the destination regions than other factors including geographic proximity and similarity in economic conditions, according to the study.
“The results of the study have rich implications for ongoing global efforts in containment of COVID-19,” Chen, a professor at Yale School of Public Health, told Xinhua in an interview.
Coronavirus has claimed 95,000 lives globally with over 1.6million cases.
The World Health Organisation (WHO) says there are 11,000 cases of in the continent with 558 deaths.