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.

Mumps is an acute respiratory infectious disease with obvious regional and seasonal differences. Exploring the impact of climate factors on the incidence of mumps and predicting its incidence trend on this basis could effectively control the outbreak and epidemic of mumps. Considering the great differences of climate in the vast territory of China, this study divided the Chinese mainland into seven regions according to the administrative planning criteria, data of Mumps were collected from the China Disease Prevention and Control Information System, ARIMA model and ARIMAX model with meteorological factors were established to predict the incidence of mumps. In this study, we found that precipitation, air pressure, temperature, and wind speed had an impact on the incidence of mumps in most regions of China and the incidence of mumps in the north and southwest China was more susceptible to climate factors. Considering meteorological factors, the average relative error of ARIMAX model was 10.87%, which was lower than ARIMA model (15.57%). Meteorology factors were the important factors which can affect the incidence of mumps, ARIMAX model with meteorological factors could better simulate and predict the incidence of mumps in China, which has certain reference value for the prevention and control of mumps.

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.

Background: Typhoid fever and paratyphoid fever are one of the most criticial public health issues worldwide, especially in developing countries. The incidence of this disease may be closely related to socio-economic factors, but there is a lack of research on the spatial level of relevant determinants of typhoid fever and paratyphoid fever. Methods: In this study, we took Hunan Province in central China as an example and collected the data on typhoid and paratyphoid incidence and socio-economic factors in 2015–2019. Firstly spatial mapping was made on the disease prevalence, and again using geographical probe model to explore the critical influencing factors of typhoid and paratyphoid, finally employing MGWR model to analysis the spatial heterogeneity of these factors. Results: The results showed that the incidence of typhoid and paratyphoid fever was seasonal and periodic and frequently occurred in summer. In the case of total typhoid and paratyphoid fever, Yongzhou was the most popular, followed by Xiangxi Tujia and Miao Autonomous Prefecture, Huaihua and Chenzhou generally focused on the south and west. And Yueyang, Changde and Loudi had a slight increase trend year by year from 2015 to 2019. Moreover, the significant effects on the incidence of typhoid and paratyphoid fever from strong to weak were as follows: gender ratio(q = 0.4589), students in ordinary institutions of higher learning(q = 0.2040), per capita disposable income of all residents(q = 0.1777), number of foreign tourists received(q = 0.1697), per capita GDP(q = 0.1589), and the P values for these factors were less than 0.001. According to the MGWR model, gender ratio, per capita disposable income of all residents and Number of foreign tourists received had a positive effect on the incidence of typhoid and paratyphoid fever. In contrast, students in ordinary institutions of higher learning had a negative impact, and per capita GDP shows a bipolar change. Conclusions: The incidence of typhoid and paratyphoid fever in Hunan Province from 2015 to 2019 was a marked seasonality, concentrated in the south and west of Hunan Province. Attention should be paid to the prevention and control of critical periods and concentrated areas. Different socio-economic factors may show other directions and degrees of action in other prefecture-level cities. To summarize, health education, entry-exit epidemic prevention and control can be strengthened. This study may be beneficial to carry out targeted, hierarchical and focused prevention and control of typhoid fever and paratyphoid fever, and provide scientific reference for related theoretical research.

Brucellosis has a considerable impact on human health and the economy in developing countries. In China, the biggest developing country, brucellosis shifted spread of the epidemic from northern to southern regions. Understanding the transmission characteristic of brucellosis on Hunan province, located in central China, is of great significance for successful control. We developed a multi-population and multi-route dynamic model (MPMRDM), which is an animal-human-environment coupled model. The model is an extension of the SEIR model, taking into account direct transmission and indirect transmission. We used the model to explore the spread of brucellosis and evaluate the effectiveness of various intervention strategies. The animal-to-animal transmission rate was the highest at 5.14 × 10^-8, while the environment-to-person transmission rate was the lowest at 9.49 × 10^-12. The mean R₀ was 1.51. The most effective intervention was taking personal protection, followed by shortening the infection period. Shortening the infection period combined with personal protection is the most effective two-combined intervention strategy. After any comprehensive intervention strategy was implemented, TAR dropped by 90% or more. The results demonstrate that animal transmission route is essential for controlling human brucellosis. Strengthening personal protection, early detection, and early treatment can effectively control the trend of brucellosis. These results can provide an important reference for optimizing brucellosis intervention plans.