An Extended Bayesian Hierarchical Model Predicted SARS-CoV-2 Cases and Reproductions After Vaccination in England

Abstract

In the UK, one of the worst affected countries by the SARS-CoV-2 global pandemic, the UK government has released a comprehensive vaccination plan for SARS-CoV-2 and will set up more vaccination sites in the coming months to expand the service to more people. We built an extended Bayesian hierarchical prediction model to predict the number of cases and breeding situation after vaccination in the nine districts of England. Based on the population of each region, the number of deaths and the IFR (the infection mortality ratio) for each region were predicted. We found that EAST, NORTHWEST and SOUTHEAST had the largest IFR, and the corresponding death numbers were 29,079, 28,734 and 25,201, respectively. Reproduction number ( ) is expected to drop below 1 in all regions on January 7, January 12, January 16, January 13, January 10, January 17, January 10, January 18 and January 14, respectively. Major vaccine interventions have been effective in reducing transmission in the nine areas of England given the mortality rate of the infected people and epidemiological characteristics of SARS-CoV-2. We also found that vaccination among people aged 70 to 80 had made a significant contribution to reducing transmission of the virus. The model can be extended to forecast the effects of certain interventions in public health emergencies, the effect of preventing the spread of disease, and the effect of different interventions in different age groups to find the best way to control the spread of disease. It can also be extended to drug and non-drug interventions to find the best combination of solutions.