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

作　　者：Chaitra Gopalappa Hari Balasubramanian Peter J.Haas 

机构地区：[1]University of Massachusetts Amherst,160 Governors Drive,Amherst,MA,01003,USA

出　　处：《Infectious Disease Modelling》2023年第1期84-100,共17页传染病建模（英文）

基　　金：supported by the National Science Foundation,United States,under NSF 1915481;the National Institute of Allergy and Infectious Diseases of the National Institutes of Health,United States,under Award Number R01AI127236.

摘　　要：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.Further,causal factors for higher risk of coinfection could be both behavioral(i.e.,compounding effects of individual behaviors,network structures,and care behaviors)and biological(i.e.,presence of one disease can biologically increase the risk of another).However,the data on the fraction attributed to each are limited.Methods:We present a new mixed agent-based compartmental(MAC)framework for jointly modeling STIs.It uses a combination of a new agent-based evolving network modeling(ABENM)technique for lower-prevalence diseases and compartmental modeling for higher-prevalence diseases.As a demonstration,we applied MAC to simulate lower-prevalence HIV in the United States and a higher-prevalence hypothetical Disease 2,using a range of transmission and progression rates to generate burdens replicative of the wide range of STIs.We simulated sexual transmissions among heterosexual males,heterosexual females,and men who have sex with men(men only and men and women).Setting the biological risk of co-infection to zero,we conducted numerical analyses to evaluate the influence of behavioral factors alone on disease dynamics.Results:The contribution of behavioral factors to risk of coinfection was sensitive to disease burden,care access,and population heterogeneity

关 键 词：Joint-modeling diseases Multi-disease modeling Simulation modeling HIV and STIs Diseases and social determinants SDOH 

分 类 号：R511[医药卫生—内科学]