A risk-based model for predicting the impact of using condoms on the spread of sexually transmitted infections

作     者：Asma Azizi Karen Ríos-Soto Anuj Mubayi James MHyman 

作者机构：Department of MathematicsTulane UniversityNew OrleansLA70118United States Department of Mathematical SciencesUniversity of Puerto RicoMayaguezPR00610United States School of Human Evolution and Social ChangeArizona State UniversityTempeAZUnited States Simon A.Levin Mathematical Computational Modeling Science CenterArizona State UniversityTempeAZUnited States 

出 版 物：《Infectious Disease Modelling》 (传染病建模（英文）)

年 卷 期：2017年第2卷第1期

页      面：100-112页

学科分类：0303[法学-社会学] 03[法学] 030302[法学-人口学] 

基　　金：This project has been partially supported by National Institute of Child Health and Human Development of the National Institutes of Health under award number R01HD086794 by grants from the National Science Foundation(DMS1263374) the Office of the President of ASU,and the Office of the Provost at ASU.The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health 

主　　题：Mathematical modeling Sexually transmitted infection(STI) Biased(preferential)mixing Random(proportional)mixing Condom-use Risk(number of partners) 

摘      要：We create and analyze a mathematical model to understand the impact of condom-use and sexual behavior on the prevalence and spread of Sexually Transmitted Infections(STIs).STIs remain significant public health challenges globally with a high burden of some Sexually Transmitted Diseases(STDs)in both developed and undeveloped *** condom-use is known to reduce the transmission of STIs,there are a few quantitative population-based studies on the protective role of condom-use in reducing the incidence of *** number of concurrent partners is correlated with their risk of being infectious by an STI such as chlamydia,gonorrhea,or *** develop a Susceptible-Infectious-Susceptible(SIS)model that stratifies the population based on the number of concurrent *** model captures the multi-level heterogeneous mixing through a combination of biased(preferential)and random(proportional)mixing processes between individuals with distinct risk levels,and accounts for differences in condom-use in the low-and high-risk *** use sensitivity analysis to assess the relative impact of high-risk people using condom as a prophylactic intervention to reduce their chance of being infectious,or infecting *** model predicts the STI prevalence as a function of the number of partners of an individual,and quantifies how this distribution of effective partners changes as a function of *** results show that when the mixing is random,then increasing the condom-use in the high-risk population is more effective in reducing the prevalence than when many of the partners of high-risk people have high *** model quantifies how the risk of being infected increases for people who have more partners,and the need for high-risk people to consistently use condoms to reduce their risk of infection.