HIV/AIDS Transmission based on the SI Infectious Disease Model

Over the past few decades, significant progress has been made in the treatment of HIV infection and AIDS. The earliest anti-HIV drugs were reverse transcriptase inhibitors, followed by protease inhibitors, nucleoside analogs, and many others. The emergence of these drugs has made it possible for HIV-infected patients to control viral replication and slow the progression of the disease through medication, thereby prolonging life and improving quality of life. This paper analyses the transmission of HIV/AIDS by collecting data to build different models. Firstly, the data were collected for visualisation and descriptive statistics and improved on the traditional SI infectious disease model by introducing two unknown variables, the infection rate and the mortality rate, to establish a differential equation. Then the grey prediction model is used to predict the change of the number of AIDS in the next 10 years under no control according to three aspects: age, gender and sexual orientation, and a time series model is established, which predicts that the probability of women suffering from AIDS in the end of the next 10 years is greatly increased. Finally, a multiple linear regression model was set up to find the links between the various indicators of AIDS, and it was found that the HIV-positive rate of gay men is closely related to the knowledge rate of AIDS prevention and having sex with the same sex.