Probability of Resurgence and Scale of Transmission of COVID-19 in China Depend on Passive Case Detection Capacity

SSRN Electronic Journal(2021)

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摘要
Small-scale outbreaks of COVID-19 recently occurred in some Chinese cities. Our purpose was to develop a branching process model that assesses the scale and risk of transmission from a single confirmed COVID-19 case in each province when vaccine coverage and non-pharmaceutical interventions (NPIs) are maintained. The model predicts that when a case is detected, resurgence is less likely when detection sensitivity and vaccine coverage are greater. In particular, a 30% increase in detection sensitivity reduces the probability of resurgence by 22.6% (p<0.001) and a 30% increase in vaccine coverage reduces the probability of resurgence by 35.5% (p<0.001). When vaccine coverage is 60%, the probability of resurgence and the emergence of a COVID-19-positive patient are low, regardless of detection sensitivity. Increasing vaccine coverage and detection sensitivity reduces the number of undetected cases after detection of the first case. For every 30% increase in detection sensitivity, there are 12.7 fewer undetected cases (p<0.001); for every 30% increase in vaccine coverage, there are 19.8 fewer undetected cases (p<0.001). Prevention and control measures for the next phase of the COVID-19 pandemic should focus on improving the capacity to detect sporadic outbreaks in remote provinces and rural areas by increasing passive detection capacity and public awareness of the importance of treatment. To achieve a better response to the new variant strains, in parallel to maintaining a rigorous quarantine strategy, booster vaccinations will help maintain high antibody titers in the general population and should be considered for populations that had early vaccinations. In addition, rapid and targeted contact tracing, widespread nucleic acid screening, and a rapid increase in vaccine coverage (“spike vaccination”) are most effective in containing transmission when a local case is detected.Funding Information: This work was supported by the Bill & Melinda Gates Foundation, Seattle, WA [Grant No· INV-006277].Declaration of Interests: None.
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