Assistant ProfessorCore Faculty, Translational Data Analytics
Public health is my life. I get up every morning to carry out the mission of public health in service of all Ohioans. I am passionate about finding solutions to complex public health issues, such as reproductive health, opioid addiction and food insecurity. Currently, public health systems and workforce are in decline due to lack of innovation and systems thinking.
Therefore, we must think anew about how we carry out the mission of public health. I envision a future for public health that is proactive, data-driven, apolitical, equity-based and grounded in community needs. My contribution towards this vision is to build innovative models and data analytics tools for public health practice in Ohio and beyond.
hyder [dot] 22osu [dot] edu
I connect models to action for public health impact. I help communities develop models that reflect their values. This means placing communities at the center of the modeling enterprise. The focal public health issues that I address are birth and infant outcomes, addiction and food insecurity. Common to these outcomes is the role of social determinants of health, the need for multiple stakeholder engagement, and breaking down discipline and data silos to come up with holistic and sustainable interventions.
A novel theme of my research is developing strategies for community-centered modeling where models are co-created, personalized and relevant to community needs, and generalizable to other communities.
Current Research Projects
COVID-19-related research and service projects in close partnerships with several colleagues and community stakeholders include:
1. Guiding the State of Ohio’s response to re-opening Ohio after the stay-at-home order in May 2020,
2. Providing local data for local decision-making (e.g., changes in learning mode, Board approved plans for safe re-opening of schools) to 21 school districts in Central Ohio, including Columbus City Schools.
3. Developing and implementing the Equity Mapping Tool, which is used daily by local health departments and healthcare systems to identify, coordinate and site pop-up/mobile COVID-19 vaccine sites.
Birth Outcomes/Infant mortality
-Systems Modeling of Infant Mortality in Ohio
-Agent-Based Models of Preterm Birth in the US
-Community Based System Dynamics for Reproductive Health Policy in Ohio
-Healing Communities Study (Health Economics and Simulation Modeling)
-Franklin County Opioid Recovery Deserts (FOCAL Map project)
-OpenOD: A Framework for Open-Source Opioid-related Data in Rural Settings
-Systems Models for Opioid Epidemic
-Smart Foodsheds in Ohio and California
-Agent-based model of Food Insecurity and Diet-related Health Outcomes in Franklin County, Ohio
-Smart Columbus Hackathon on food access
-Cost-effectiveness of Food Prescription Programs by Health Care Providers
Funding: OSU Internal Seed Grants (InFACT, Opioid Innovation Fund, IPR), NIH (Healing Communities Study), NSF (Midwest Big Data Hub, EAGER, Smart and Connected Communities), CDC (FOCAL Map), Foundation, and State of Ohio (Infant Mortality Research Partnership).
Systems Science, Agent-Based Modeling, Birth Outcomes/Infant Mortality, Environmental Epidemiology, Air Pollution, Citizen Science, Opioid epidemic, Food insecurity, Smart Cities, Health Economics
2nd Place in Poster Session #2 at Society for Epidemiological Research Conference 2019.
Hyder A, Trinh A, Padmanabhan P, Marschhausen J, Wu A, Evans A, Iyer R, Jones A. COVID-19 Surveillance for Local Decision Making: An Academic, School District, and Public Health Collaboration. Public Health Reports. 2021 May 12:00333549211018203.
Hyder A, Lee J, Dundon A, Southerland LT, All D, Hammond G, Miller HJ. Opioid Treatment Deserts: Concept development and application in a US Midwestern urban county. Plos one. 2021 May 12;16(5):e0250324.
Hyder, A. (2020). Teaching systems science to public health professionals. Public Health, 181, 119-121.
Hyder, A., & May, A. A. (2020). Translational data analytics in exposure science and environmental health: a citizen science approach with high school students. Environmental Health, 19(1), 1-12.
Hyder, A., & Barnett, K. S. (2020). Low Birth Weight and Preterm Birth Among Arab-American Women in Ohio. Maternal and Child Health Journal, 1-10.
Hollander, A. D., Hoy, C., Huber, P. R., Hyder, A., Lange, M. C., Latham, A., ... & Tomich, T. P. (2020). Toward Smart Foodsheds: Using Stakeholder Engagement to Improve Informatics Frameworks for Regional Food Systems. Annals of the American Association of Geographers, 110(2), 535-546.
Koh, K., Kaiser, M. L., Sweeney, G., Samadi, K., & Hyder, A. (2020). Explaining Racial Inequality in Food Security in Columbus, Ohio: A Blinder–Oaxaca Decomposition Analysis. International journal of environmental research and public health, 17(15), 5488.
Hyder, A. (2018). Public Funding for Genomics and the Return on Investment: A Public Health Perspective. Perspectives in Biology and Medicine, 61(4), 572-583.
Reno, R., & Hyder, A. (2018). The evidence base for social determinants of health as risk factors for infant mortality: A systematic scoping review. Journal of health care for the poor and underserved, 29(4), 1188-1208.
Hosseinichimeh, N., MacDonald, R., Hyder, A., Ebrahimvandi, A., Porter, L., Reno, R., ... & Andersen, D. F. (2017). Group model building techniques for rapid elicitation of parameter values, effect sizes, and data sources. System Dynamics Review, 33(1), 71-84.
Milwid, R., Steriu, A., Arino, J., Heffernan, J., Hyder, A., Schanzer, D., ... & Moghadas, S. M. (2016). Toward standardizing a lexicon of infectious disease modeling terms. Frontiers in public health, 4, 213.
Hyder, A., Lee, H. J., Ebisu, K., Koutrakis, P., Belanger, K., & Bell, M. L. (2014). PM2. 5 exposure and birth outcomes: use of satellite-and monitor-based data. Epidemiology (Cambridge, Mass.), 25(1), 58.
Hyder, A., & Leung, B. (2015). Social deprivation and burden of influenza: Testing hypotheses and gaining insights from a simulation model for the spread of influenza. Epidemics, 11, 71-79.
Hyder, A., Buckeridge, D. L., & Leung, B. (2013). Predictive validation of an influenza spread model. PloS one, 8(6), e65459.