Joint modeling HIV and HPV using a new hybrid agent-based network and compartmental simulation technique

Area of Science:

• Epidemiology
• Mathematical Modeling
• Public Health

Background:

• Persons living with human immunodeficiency virus (HIV) experience a disproportionately high burden of human papillomavirus (HPV) infection and associated cancers.
• Both behavioral and biological factors contribute to this increased risk.
• Existing interventions primarily address biological risks, while social determinants of behavior necessitate structural interventions.

Purpose of the Study:

• To develop a joint HIV-HPV mathematical model to assess the contribution of behavioral and biological factors to HPV-related cancers.
• To inform the development of targeted intervention strategies for HIV and HPV prevention.

Main Methods:

• Application of a novel mixed agent-based compartmental (MAC) simulation technique.
• Jointly modeling HIV and HPV dynamics across diverse U.S. subpopulations (heterosexual females, heterosexual males, men who have sex with men).
• Evaluating the contribution of behavioral and biological factors to cervical cancer risk among women with HIV.

Main Results:

• Model outputs for HIV, HPV, and cervical cancer incidence aligned with surveillance data.
• Women with HIV showed 1.67 times higher HPV prevalence and 3.6 times higher cervical cancer incidence compared to women without HIV.
• Biological factors accounted for 22-38% of increased HPV prevalence and 80% of increased cervical cancer incidence, with behavioral factors explaining the remainder.

Conclusions:

• Both behavioral and biological factors significantly contribute to increased HPV prevalence and cervical cancer risk in persons with HIV.
• Findings underscore the necessity for integrated behavioral, structural, and pharmaceutical interventions.
• The MAC simulation technique is validated as a proof-of-concept for modeling complex, co-occurring diseases.