Study population and setting
This study used laboratory-confirmed case reports and human mobility data (mobile phone records) from 34 Chinese provinces to estimate effects of transmission control measures during the first 50 days of the COVID-19 epidemic (December 31, 2019 – February 19, 2020). Authors used a linear regression model to evaluate the association between the Wuhan travel ban and spread of COVID-19 to other Chinese provinces. They then used a Susceptible-Exposed-Infected-Recovered (SEIR) model fitted to the number of newly confirmed cases each day from each province to estimate the effect of implemented control measures on the trajectory of the epidemic outside of Wuhan.
Summary of Main Findings
Authors found that the total number of cases detected in each province was strongly associated with the number of travelers estimated from Wuhan. Banning travel in/out of Wuhan slowed COVID-19 transmission to other cities by an estimated 2.91 days (95% CI: 2.54-3.29). Cities that implemented control measures before having any confirmed cases had 33.3% fewer confirmed cases during the first week of their outbreak (13.0 cases, 95% CI 7.1-18.8) compared to cities that implemented controls after detecting cases (20.6 cases, 95% CI 14.5-26.8). Model results estimated that R (the effective reproductive number) decreased from 3.15 to 0.04 after the Level 1 response measures were 95% implemented. Authors estimated that, implemented alone, the Wuhan travel ban or Level 1 response would not have been enough to result in the observed decrease in incident cases by February 19, 2020. However, when combined, these control measures were estimated to have prevented 96% of COVID-19 cases that could have been expected to occur in the absence of all interventions.
This study leverages mobile phone data for a detailed examination of how travel restrictions affected human mobility. Combining these data with case reports and the timing of control measures allowed multiple approaches to estimating the impact of control measures on transmission. The SEIR model was fitted to empirical case reports, meaning that the model was adapted to be most appropriate for the observed data.
Results were generated from statistical and mathematical models, and strong statistical associations between implementation of control measures and observed delays and decreases in incident cases do not indicate a causal relationship. Multiple containment measures were implemented at once, and so this study is unable to disaggregate the impact of some containment measures (e.g., isolation of patients, closure of schools).
This study adds to the growing evidence regarding the effectiveness of the Wuhan travel ban and other high-level containment and suppression measures implemented in response to the COVID-19 pandemic. As with other studies, this modeling study suggests that these strict mobility interventions delayed the spread of COVID-19 within mainland China, and may have contributed to the observed reduction in cases by mid-February 2020.
This review was posted on: 17 June 2020