Assessment of the Benefits of Targeted Interventions for Pandemic Control in China Based on Machine Learning Method and Web Service for COVID-19 Policy Simulation / 生物医学与环境科学（英文）

Taking the Chinese city of Xiamen as an example, simulation and quantitative analysis were performed on the transmissions of the Coronavirus Disease 2019 (COVID-19) and the influence of intervention combinations to assist policymakers in the preparation of targeted response measures. A machine learning model was built to estimate the effectiveness of interventions and simulate transmission in different scenarios. The comparison was conducted between simulated and real cases in Xiamen. A web interface with adjustable parameters, including choice of intervention measures, intervention weights, vaccination, and viral variants, was designed for users to run the simulation. The total case number was set as the outcome. The cumulative number was 4,614,641 without restrictions and 78 under the strictest intervention set. Simulation with the parameters closest to the real situation of the Xiamen outbreak was performed to verify the accuracy and reliability of the model. The simulation model generated a duration of 52 days before the daily cases dropped to zero and the final cumulative case number of 200, which were 25 more days and 36 fewer cases than the real situation, respectively. Targeted interventions could benefit the prevention and control of COVID-19 outbreak while safeguarding public health and mitigating impacts on people's livelihood.

Conceptual model for automatic early warning information system of infectious diseases based on internet reporting surveillance system / 生物医学与环境科学（英文）

<p><b>OBJECTIVE</b>To establish a conceptual model of automatic early warning of infectious diseases based on internet reporting surveillance system, with a view to realizing an automated warning system on a daily basis and timely identifying potential outbreaks of infectious diseases.</p><p><b>METHODS</b>The statistic conceptual model was established using historic surveillance data with movable percentile method.</p><p><b>RESULTS</b>Based on the infectious disease surveillance information platform, the conceptual model for early warning was established. The parameter, threshold, and revised sensitivity and specificity of early warning value were changed to realize dynamic alert of infectious diseases on a daily basis.</p><p><b>CONCLUSION</b>The instructive conceptual model of dynamic alert can be used as a validating tool in institutions of infectious disease surveillance in different districts.</p>