Multi-variate prediction model in infectivity of AIDs and HIV

Yuhao Yang

doi:10.1117/12.2672680

28 March 2023 Multi-variate prediction model in infectivity of AIDs and HIV

Yuhao Yang

Proceedings Volume 12597, Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022); 1259731 (2023) https://doi.org/10.1117/12.2672680
Event: Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022), 2022, Nanjing, China

Abstract

HIV infections was caused by a sort of chimp in Central Africa. AIDS is the last stage of HIV infection. Though there are many methods to defend the infection of HIV, human still have no way to cure it absolutely. There are statistics of HIV infection, main routes of infection of HIV, the process of HIV infection and the prediction of the number of HIV infected. In this research, the deaths of HIV become less in recent years. The main routes of HIV infection are homosexual, heterosexual, and injecting drugs use. The number of HIV infected will be larger in the future by the prediction. According to the analysis, the main routes of HIV infection is sexual. The number of infected people will still increase in five years, and it is important to give more people the chance of ART treatment. The significance of this research is to analysis the main way of HIV infection and the situation of AIDS. These results shed light on the main routes of HIV transmissions are heterosexual, homosexual, bisexual, and injecting drugs abuse. The deaths averted due to ART treatment become more and more from 2010 to 2014, which explained that the decreasing deaths of HIV infections well. The number of HIV infections still grows up in these years. These results can be used to find the main routes of HIV transmissions and predict the infections of HIV, which can remind people to be care of the behavior in their life to avoid infecting HIV. By this results the death of AIDS will decrease.

Citation Download Citation

Yuhao Yang "Multi-variate prediction model in infectivity of AIDs and HIV", Proc. SPIE 12597, Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022), 1259731 (28 March 2023); https://doi.org/10.1117/12.2672680

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KEYWORDS

Data modeling

Autoregressive models

Received signal strength

Analytical research

Mathematical modeling

Autocorrelation

Statistical modeling

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