PLoS neglected tropical diseases · 2026
Seasonal dynamic modeling for real-time prediction of human brucellosis epidemiological trends in Gansu, Guangdong and Sichuan Provinces, China.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Lou Pengwei, Huang Yuting, Yang Jiandong, Chen Nannan, Zhao Feng, Xu Jiabo, Wang Kai
Аннотация
OBJECTIVES: Construct a seasonal dynamic model that captures the transmission characteristics of brucellosis in Gansu, Guangdong and Sichuan provinces of China, in order to fit and predict the epidemic trends of new human brucellosis, and further formulate scientific and targeted prevention and control strategies.
METHODS: Based on the number of new human brucellosis cases reported by the Centers for Disease Control and Prevention in Gansu, Guangdong and Sichuan provinces from 2021 to 2024, a seasonal SEIV dynamic model of brucellosis transmission between sheep/cattle and humans was constructed, with parameters estimated by using the nonlinear least squares method and the Markov Chain Monte Carlo method. The model fitted the epidemic trends of new human brucellosis and estimated the basic reproduction number R0. Through parameter sensitivity analysis, effective prevention and control measures can be proposed.
RESULTS: The established seasonal SEIV dynamic model can well fit the number of new human brucellosis cases and cumulative new human brucellosis cases in Gansu, Guangdong and Sichuan provinces, respectively. The calculated mean absolute percentage error (MAPE) values were approximately 20% and 6%, respectively, indicating a good agreement between the fitted and actual values. It is projected that Gansu and Sichuan provinces will reach peak values of 146,310 and 157,903 cases in July and May 2038, respectively, followed by a gradual declines toward a stable state. The epidemic in Guangdong province will reach a relatively stable, sustained prevalence by 2038. The estimated basic reproduction number R0 for brucellosis transmission in Gansu, Guangdong and Sichuan provinces were 2.2510 (95%CI: 2.2160 - 2.2859), 2.7937 (95%CI: 2.7592 - 2.8283) and 2.9499 (95%CI: 2.9007 - 2.9992), respectively. These findings indicate that brucellosis will continue to spread under the current prevention and control measures. Finally, sensitivity analyses of the number of new human brucellosis cases and R0 were conducted based on specific parameters, it is demonstrated that increasing the culling rate of infected sheep/cattle, raising the vaccination rate of susceptible sheep/cattle, and reducing the immune loss rate of vaccinated sheep/cattle can effectively suppress the spread of brucellosis.
CONCLUSION: The constructed seasonal SEIV dynamic model can accurately simulates the epidemic trends of new human brucellosis cases in Gansu, Guangdong and Sichuan provinces, quantitatively proposes effective prevention and control measures, and lay a theoretical foundation for combating the spread of brucellosis.
METHODS: Based on the number of new human brucellosis cases reported by the Centers for Disease Control and Prevention in Gansu, Guangdong and Sichuan provinces from 2021 to 2024, a seasonal SEIV dynamic model of brucellosis transmission between sheep/cattle and humans was constructed, with parameters estimated by using the nonlinear least squares method and the Markov Chain Monte Carlo method. The model fitted the epidemic trends of new human brucellosis and estimated the basic reproduction number R0. Through parameter sensitivity analysis, effective prevention and control measures can be proposed.
RESULTS: The established seasonal SEIV dynamic model can well fit the number of new human brucellosis cases and cumulative new human brucellosis cases in Gansu, Guangdong and Sichuan provinces, respectively. The calculated mean absolute percentage error (MAPE) values were approximately 20% and 6%, respectively, indicating a good agreement between the fitted and actual values. It is projected that Gansu and Sichuan provinces will reach peak values of 146,310 and 157,903 cases in July and May 2038, respectively, followed by a gradual declines toward a stable state. The epidemic in Guangdong province will reach a relatively stable, sustained prevalence by 2038. The estimated basic reproduction number R0 for brucellosis transmission in Gansu, Guangdong and Sichuan provinces were 2.2510 (95%CI: 2.2160 - 2.2859), 2.7937 (95%CI: 2.7592 - 2.8283) and 2.9499 (95%CI: 2.9007 - 2.9992), respectively. These findings indicate that brucellosis will continue to spread under the current prevention and control measures. Finally, sensitivity analyses of the number of new human brucellosis cases and R0 were conducted based on specific parameters, it is demonstrated that increasing the culling rate of infected sheep/cattle, raising the vaccination rate of susceptible sheep/cattle, and reducing the immune loss rate of vaccinated sheep/cattle can effectively suppress the spread of brucellosis.
CONCLUSION: The constructed seasonal SEIV dynamic model can accurately simulates the epidemic trends of new human brucellosis cases in Gansu, Guangdong and Sichuan provinces, quantitatively proposes effective prevention and control measures, and lay a theoretical foundation for combating the spread of brucellosis.