A new mixed agent-based network and compartmental simulation framework for joint modeling of related infectious diseases- application to sexually transmitted infections.

ABSTRACT:

Background

A model that jointly simulates infectious diseases with common modes of transmission can serve as a decision-analytic tool to identify optimal intervention combinations for overall disease prevention. In the United States, sexually transmitted infections (STIs) are a huge economic burden, with a large fraction of the burden attributed to HIV. Data also show interactions between HIV and other sexually transmitted infections (STIs), such as higher risk of acquisition and progression of co-infections among persons with HIV compared to persons without. However, given the wide range in prevalence and incidence burdens of STIs, current compartmental or agent-based network simulation methods alone are insufficient or computationally burdensome for joint disease modeling. Furthe

SUBMITTER: Gopalappa C 

PROVIDER: S-EPMC9827035 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature