Quantitative Assessment of a Dual Epidemic Caused by Tuberculosis and HIV in the Philippines.
Monica TorresJerrold M TubayAurelio A de Los Reyes VPublished in: Bulletin of mathematical biology (2023)
Tuberculosis (TB) and human immunodeficiency virus (HIV) are the two major public health emergencies in the Philippines. The country is ranked fourth worldwide in TB incidence cases despite national efforts and initiatives to mitigate the disease. Concurrently, the Philippines has the fastest-growing HIV epidemic in Asia and the Pacific region. The TB-HIV dual epidemic forms a lethal combination enhancing each other's progress, driving the deterioration of immune responses. In order to understand and describe the transmission dynamics and epidemiological patterns of the co-infection, a compartmental model for TB-HIV is developed. A class of people living with HIV (PLHIV) who did not know their HIV status is incorporated into the model. These unaware PLHIV who do not seek medical treatment are potential sources of new HIV infections that could significantly influence the disease transmission dynamics. Sensitivity analysis using the partial rank correlation coefficient is performed to assess model parameters that are influential to the output of interests. The model is calibrated using available Philippine data on TB, HIV, and TB-HIV. Parameters that are identified include TB and HIV transmission rates, progression rates from exposed to active TB, and from TB-latent with HIV to active infectious TB with HIV in the AIDS stage. Uncertainty analysis is performed to identify the degree of accuracy of the estimates. Simulations predict an alarming increase of 180% and 194% in new HIV and TB-HIV infections in 2025, respectively, relative to 2019 data. These projections underscore an ongoing health crisis in the Philippines that calls for a combined and collective effort by the government and the public to take action against the lethal combination of TB and HIV.
Keyphrases
- human immunodeficiency virus
- antiretroviral therapy
- hiv positive
- hiv infected
- hiv testing
- hepatitis c virus
- hiv aids
- men who have sex with men
- mycobacterium tuberculosis
- public health
- healthcare
- immune response
- south africa
- machine learning
- pulmonary tuberculosis
- quality improvement
- magnetic resonance
- artificial intelligence
- social media
- toll like receptor
- combination therapy