Study on the Estimation of the Number of Potential Hiv-infected Individuals and Prevention and Control Strategies Based on Dynamic Model
Year: 2025
Type: article
Abstract: Motivation AIDS is a chronic and fatal infectious disease caused by the human immunodeficiency virus (HIV). According to the Chinese Center for Disease Control and Prevention (CDC), there are currently 689, 000 cases of HIV-infected patients, with 103, 350 new HIV infections in 2019 and the number of HIV cases continues to rise. Therefore, a reasonable estimation of the number of potentially HIV-infected individuals in the population is essential for the prevention and control of AIDS. Method We develop a dynamic model of a compartment containing potential HIV-infected individuals and fitted the parameters of the model using nonlinear least squares based on the data from 2004 to 2019. Results The basic reproduction number of the model is calculated to be $ R_0 $=1.514 and the mean number of potential HIV-infected individuals in the population is estimated by the model to be 16847 (95$ \% $CI [15047, 18846]). In 2004, there are 1.7835 times more potential HIV-infected individuals K than HIV-infected individuals, this then decreases each year. The average ratio of potentially HIV-infected individuals to HIV-infected individuals from 2004 to 2019 is 38.41$ \% $. Conclusions The number of potential HIV-infected individuals has an important impact on the transmission and control of HIV virus and the proportion of changing sexual behavior habits can greatly reduce the number of new potential HIV-infected individuals. The existence of potential HIV-infected individuals should be taken into account in prevention and control strategies and publicity efforts should be intensified so that more people can understand the transmission pathways, pathogenesis and precautions against AIDS, in order to better reduce the number of new HIV infections and the spread of HIV virus in the population.
DOI: 10.11948/20230486
Authors: Chuanqing Xu, Kedeng Cheng, Yu Wang, Yao Wang, Songbai Guo, Qiuqin Wu, Xiaoyu Zhao
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
Awards: G2641968217, G6907671014, G7542654310
OpenAlex ID: W4412414848
