The World Health Organization (WHO) expresses vital populated areas as the ones that would be vulnerable towards and at most risk at acquiring HIV. Strategies refer to at most-risk populations as “men who have sex with men, transgender people, people who inject drugs and sex workers. At most-risk populated regions get inexplicably influenced by HIV.” Exposed inhabitants are recognized through aiming a particular social demographic feature for the region. Perception of the crucial populated regions related to epidemical jargon as demarcated through the Joint United Nations Programme on UNAIDS that renders towards “concentrated epidemic” is the one where it would spread promptly among populated areas generally, which stands >5% prevalent. “Generalized epidemic” is the one which gets self-sustained inside regions with populations via heterosexually spreading it. The aim of this study is to contribute towards the analytical preview of mechanism for global epidemiological spread in Asian region, including the influence of its treatment and prevention schemes on epidemiological trends for over a decade.

According to UNAIDS data, an estimation of around 1.8 million first-hand HIV infections have been transmitted universally in 2017, which characterized a 14% waning from 2.1 million newfound contagions in the year 2015 also 22% decline since 2.3 million new contaminations in the year 2012. Sub-Saharan Africa led the approach with 25% decline in newly infected population from 2012 to 2017, which is declining from 1.6 to 1.2 million. Though most of the regions have observed a decline in new annual infections since 2012, growths occur in Latin America from 86,000 towards a lakh plus Caribbean having ranges of 12,000–15,000. The number of newly discovered infections remained at level at eastern side of Europe and Central Asian regions.

Thus, it is need of our generation for understanding the elementary mechanism of infection spread with progression of the epidemic. It effects various immune cells, particularly CD4+ T cells, macrophages, and microglial cells. HIV-1 accesses macrophages plus CD4+ T cells, which is possible because of interface of the virion-sachet glycoproteins within CD4+ molecule on the targeted ones. Virions then pass on a disease to several cellular targets disseminating inside the whole body. Mathematical modeling development of the viral dynamics for HIV has been developed towards studying spread and treatment. Model for this virus infection has three variables: T accounts for the amount of uninfected target cells, I refers to the number of infected cells, and V refers to the amount of virus particles in the blood cells. The nonlinearity of the HIV epidemiology is studied using intelligent analysis. Further, machine-learned regressions consisting of L1-norm, logistic, Poisson, etc. with the uncertainty of prediction help to understand the virion behavior in a better way. It is observed that if the state variables undergo alterations, then the viral dynamics changes the behavior gradually.