Using time-dependent reproduction number to predict turning points of COVID-19 outbreak in Dalian, Liaoning province, China

Abstract

Abstract Objectives To forecast the development trend of current outbreak in Dalian, mainly to predict turning points of COVID-19 outbreak in Dalian, Liaoning province, China, the results can be used to provide a scientific reference for timely adjustment of prevention and control strategies. Methods During the outbreak, Bayesian framework was used to calculated the time-dependent reproduction number ( $${R_{t}}$$ R t ), and then above acquired $${R_{t}}$$ R t and exponential trend equation were used to establish the prediction model, through the model, predict the $${R_{t}}$$ R t value of following data and know when $${R_{t}}$$ R t smaller than 1. Results From July 22 to August 5, 2020, and from March 14 to April 2, 2022, 92 and 632 confirmed cases and asymptomatic infected cases of COVID-19 were reported (324 males and 400 females) in Dalian. The R square for exponential trend equation were 0.982 and 0.980, respectively which fit the $${R_{t}}$$ R t with illness onset between July 19 to July 28, 2020 and between March 5 to March 17, 2022. According to the result of prediction, under the current strength of prevention and control, the $${R_{t}}$$ R t of COVID-19 will drop below 1 till August 2, 2020 and March 26, 2022, respectively in Dalian, one day earlier or later than the actual date. That is, the turning point of the COVID-19 outbreak in Dalian, Liaoning province, China will occur on August 2, 2020 and March 26, 2022. Conclusions Using time-dependent reproduction number values to predict turning points of COVID-19 outbreak in Dalian, Liaoning province, China was effective and reliable on the whole, and the results can be used to establish a sensitive early warning mechanism to guide the timely adjustment of COVID-19 prevention and control strategies.

Keywords

• COVID-19
• $${R_{t}}$$ R t   
• Predict
• Bayesion framework
• Exponential trend equation