Incorporating social determinants of health into agent-based models of HIV transmission: methodological challenges and future directions
There is much focus in the field of HIV prevention research on understanding the impact of social determinants of health (e.g., housing, employment, incarceration) on HIV transmission and developing interventions to address underlying structural drivers of HIV risk. However, such interventions are r...
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Frontiers Media S.A.
2025-02-01
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| Series: | Frontiers in Epidemiology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fepid.2025.1533119/full |
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| author | Anna L. Hotton Pedro Nascimento de Lima Arindam Fadikar Nicholson T. Collier Aditya S. Khanna Darnell N. Motley Eric Tatara Sara Rimer Ellen Almirol Harold A. Pollack John A. Schneider John A. Schneider John A. Schneider Robert J. Lempert Robert J. Lempert Jonathan Ozik |
| author_facet | Anna L. Hotton Pedro Nascimento de Lima Arindam Fadikar Nicholson T. Collier Aditya S. Khanna Darnell N. Motley Eric Tatara Sara Rimer Ellen Almirol Harold A. Pollack John A. Schneider John A. Schneider John A. Schneider Robert J. Lempert Robert J. Lempert Jonathan Ozik |
| author_sort | Anna L. Hotton |
| collection | DOAJ |
| description | There is much focus in the field of HIV prevention research on understanding the impact of social determinants of health (e.g., housing, employment, incarceration) on HIV transmission and developing interventions to address underlying structural drivers of HIV risk. However, such interventions are resource-intensive and logistically challenging, and their evaluation is often limited by small sample sizes and short duration of follow-up. Because they allow for both detailed and large-scale simulations of counterfactual experiments, agent-based models (ABMs) can demonstrate the potential impact of combinations of interventions that may otherwise be infeasible to evaluate in empirical settings and help plan for efficient use of public health resources. There is a need for computational models that are sufficiently realistic to allow for evaluation of interventions that address socio-structural drivers of HIV transmission, though most HIV models to date have focused on more proximal influences on transmission dynamics. Modeling the complex social causes of infectious diseases is particularly challenging due to the complexity of the relationships and limitations in the measurement and quantification of causal relationships linking social determinants of health to HIV risk. Uncertainty exists in the magnitude and direction of associations among the variables used to parameterize the models, the representation of sexual transmission networks, and the model structure (i.e. the causal pathways representing the system of HIV transmission) itself. This paper will review the state of the literature on incorporating social determinants of health into epidemiological models of HIV transmission. Using examples from our ongoing work, we will discuss Uncertainty Quantification and Robust Decision Making methods to address some of the above-mentioned challenges and suggest directions for future methodological work in this area. |
| format | Article |
| id | doaj-art-608f18ad2ea447afb4b25ca1da0dda60 |
| institution | OA Journals |
| issn | 2674-1199 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Epidemiology |
| spelling | doaj-art-608f18ad2ea447afb4b25ca1da0dda602025-08-20T02:04:20ZengFrontiers Media S.A.Frontiers in Epidemiology2674-11992025-02-01510.3389/fepid.2025.15331191533119Incorporating social determinants of health into agent-based models of HIV transmission: methodological challenges and future directionsAnna L. Hotton0Pedro Nascimento de Lima1Arindam Fadikar2Nicholson T. Collier3Aditya S. Khanna4Darnell N. Motley5Eric Tatara6Sara Rimer7Ellen Almirol8Harold A. Pollack9John A. Schneider10John A. Schneider11John A. Schneider12Robert J. Lempert13Robert J. Lempert14Jonathan Ozik15Department of Medicine, University of Chicago, Chicago, IL, United StatesEngineering & Applied Sciences, RAND, Arlington, VA, United StatesConsortium for Advanced Science and Engineering, University of Chicago, Chicago, IL, United StatesConsortium for Advanced Science and Engineering, University of Chicago, Chicago, IL, United StatesDepartment of Behavioral and Social Sciences, Brown University School of Public Health, Providence, RI, United StatesDepartment of Medicine, University of Chicago, Chicago, IL, United StatesConsortium for Advanced Science and Engineering, University of Chicago, Chicago, IL, United StatesConsortium for Advanced Science and Engineering, University of Chicago, Chicago, IL, United StatesDepartment of Medicine, University of Chicago, Chicago, IL, United StatesCrown Family School of Social Work, Policy, and Practice, University of Chicago, Chicago, IL, United StatesDepartment of Medicine, University of Chicago, Chicago, IL, United StatesCrown Family School of Social Work, Policy, and Practice, University of Chicago, Chicago, IL, United StatesDepartment of Public Health Sciences, University of Chicago, Chicago, IL, United StatesPardee RAND Graduate School, RAND, Santa Monica, CA, United StatesFrederick S. Pardee Center for Longer Range Global Policy and the Future Human Condition, RAND, Santa Monica, CA, United StatesConsortium for Advanced Science and Engineering, University of Chicago, Chicago, IL, United StatesThere is much focus in the field of HIV prevention research on understanding the impact of social determinants of health (e.g., housing, employment, incarceration) on HIV transmission and developing interventions to address underlying structural drivers of HIV risk. However, such interventions are resource-intensive and logistically challenging, and their evaluation is often limited by small sample sizes and short duration of follow-up. Because they allow for both detailed and large-scale simulations of counterfactual experiments, agent-based models (ABMs) can demonstrate the potential impact of combinations of interventions that may otherwise be infeasible to evaluate in empirical settings and help plan for efficient use of public health resources. There is a need for computational models that are sufficiently realistic to allow for evaluation of interventions that address socio-structural drivers of HIV transmission, though most HIV models to date have focused on more proximal influences on transmission dynamics. Modeling the complex social causes of infectious diseases is particularly challenging due to the complexity of the relationships and limitations in the measurement and quantification of causal relationships linking social determinants of health to HIV risk. Uncertainty exists in the magnitude and direction of associations among the variables used to parameterize the models, the representation of sexual transmission networks, and the model structure (i.e. the causal pathways representing the system of HIV transmission) itself. This paper will review the state of the literature on incorporating social determinants of health into epidemiological models of HIV transmission. Using examples from our ongoing work, we will discuss Uncertainty Quantification and Robust Decision Making methods to address some of the above-mentioned challenges and suggest directions for future methodological work in this area.https://www.frontiersin.org/articles/10.3389/fepid.2025.1533119/fullsocial determinants of healthagent-based modelsHIVinfectious disease modelingnetwork modelsuncertainty quantification |
| spellingShingle | Anna L. Hotton Pedro Nascimento de Lima Arindam Fadikar Nicholson T. Collier Aditya S. Khanna Darnell N. Motley Eric Tatara Sara Rimer Ellen Almirol Harold A. Pollack John A. Schneider John A. Schneider John A. Schneider Robert J. Lempert Robert J. Lempert Jonathan Ozik Incorporating social determinants of health into agent-based models of HIV transmission: methodological challenges and future directions Frontiers in Epidemiology social determinants of health agent-based models HIV infectious disease modeling network models uncertainty quantification |
| title | Incorporating social determinants of health into agent-based models of HIV transmission: methodological challenges and future directions |
| title_full | Incorporating social determinants of health into agent-based models of HIV transmission: methodological challenges and future directions |
| title_fullStr | Incorporating social determinants of health into agent-based models of HIV transmission: methodological challenges and future directions |
| title_full_unstemmed | Incorporating social determinants of health into agent-based models of HIV transmission: methodological challenges and future directions |
| title_short | Incorporating social determinants of health into agent-based models of HIV transmission: methodological challenges and future directions |
| title_sort | incorporating social determinants of health into agent based models of hiv transmission methodological challenges and future directions |
| topic | social determinants of health agent-based models HIV infectious disease modeling network models uncertainty quantification |
| url | https://www.frontiersin.org/articles/10.3389/fepid.2025.1533119/full |
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