Varicella is an acute respiratory infectious diseases, with high transmissibility and quick dissemination. In this study, an SEIR (susceptible-exposed-infected-recovered) dynamic model was established to explore the optimal prevention and control measures according to the epidemiological characteristics about varicella outbreak in a school in a central city of China. Berkeley Madonna 8.3.18 and Microsoft Office Excel 2010 software were employed for the model simulation and data management, respectively. The result showed that the simulated result of SEIR model agreed well with the reported data when β (infected rate) equal to 0.067. Models showed that the cumulative number of cases was only 13 when isolation adopted when the infected individuals were identified (assuming isolation rate was up to 100%); the cumulative number of cases was only two and the TAR (total attack rate) was 0.56% when the vaccination coefficient reached 50%. The cumulative number of cases did not change significantly with the change of efficiency of ventilation and disinfection, but the peak time was delayed; when δ (vaccination coefficient) = 0.1, m (ventilation efficiency) = 0.7 or δ = 0.2, m = 0.5 or δ = 0.3, m = 0.1 or δ = 0.4 and above, the cumulative number of cases would reduce to one case and TAR would reduce to 0.28% with combined interventions. Varicella outbreak in school could be controlled through strict isolation or vaccination singly; combined interventions have been adopted when the vaccination coefficient was low.

Influenza is a worldwide public health problem which causes a serious economic and health burden. In order to provide a scientific basis for improving the prevention and control level of influenza, using dynamic model to evaluate the infection rates of influenza different subtypes from 2010 to 2019 in China. This article established SEIABR model based on influenza cases reported by China National Influenza Center from 2010 to 2019. And calculated the transmission rate and R_e by combined the natural birth rate, natural death rate, infectious rate, proportion of asymptomatic patients, proportion of untreated patients, recovery rate and fatality rate. The average infection rate of influenza was (2.38 ± 0.59) × 10^-10, and influenza A was (2.24 ± 0.51) × 10^-10, influenza B was (2.21 ± 0.68) × 10^-10. And average R_e were 1.60, 1.51, 1.49. In addition, the infection rates of A /H1N1, A/H3N2, B/Yamagata and B/Victoria were (2.47 ± 0.51) × 10^-10, (2.25 ± 0.48) × 10^-10, (2.15 ± 0.61) × 10^-10, and (2.30 ± 0.66) × 10^-10 and average R_e were 1.67, 1.52, 1.44, 1.56. Between each year, flu transmission capacity had fluctuation. Influenza A was more transmissible than influenza B, and during the major subtypes, influenza A/H1N1 was the most transmissible.

In this study, we quantify and evaluate the transmission capacity of different types of influenza, and evaluate the flu vaccination effect. Taking the influenza cases reported by the National Influenza Center of China from 2010 to 2019 as the research object (http://www.chinaivdc.cn/cnic), we established the SEIABR model to calculate the influenza infection rate and R₀ for each year from 2010 to 2019, and calculate the influenza A and B influenza infection rates. We further added vaccination measures to the SEIABR model, and analysis the impact of different vaccination rates on the spread of influenza. We find that the range of β(infection rate) is $6.03\times {10}^{-10}$ to $9.66\times {10}^{-10}$, and the average is $\left(7.95\pm 1.27\right)\times {10}^{-10}$, the range of R₀ is .98 to 1.47, and the average is 1.21. Simulation result suggest that vaccine coverage needed to reach 60%-80% to control the spread of influenza virus in China when the vaccine effectiveness was 20%-40%. When the vaccine effectiveness is 40%-60%, vaccine coverage needs to reach 40%-60% to control the spread of influenza virus in China. In China, the infection rate of influenza A is higher than influenza B, to better control the spread of the flu virus, we suggest that we also need to increase the number of people vaccinated or improve the efficiency of vaccines(the current vaccination coverage is probably less than 20%).