Howard Chang
Professor
Faculty, Biostatistics and Bioinformatics
Jointly Appointed, Environmental Health
My primary research interest is in the development and application of statistical methods for analyzing complex spatial-temporal exposure and health data. Our current projects focus on two broad areas of population health: (1) exposure assessment for air quality and extreme weather events, especially under a changing climate, and (2) health effect estimation and impact assessment leveraging large databases, such as birth/death certificates, hospital billing records, electronic health records, and disease surveilleince systems. I also have collaborative experience in ecology, infectious disease, social epidemiology, and community intervention trials.
[Google Scholar] [CV]
Current Projects:
1. Data Integration Methods for Environmental Exposures with Applications to Air Pollution and Asthma Morbidity.
2. Extreme Heat Events and Pregnancy Duration: a National Study
3. Dust Storms and Emergency Department Visits in Four Southwestern US States
4. Spatio-temporal Data Integration Methods for Infectious Disease Surveillance.
5. Neighborhood transportation vulnerability and geographic patterns of diabetes-related limb loss.
Contact Information
1518 Clifton Rd., NE ,
Atlanta , GA 30322
Mailstop: 1518-002-3AA
Phone: (404) 712-4627
Fax: (404)727-1370
Email: howard.chang@emory.edu
Areas of Interest
- Air Pollution
- Biostatistics
- Climate and Health
- Environmental Health
- Epidemiology
- Exposure Assessment
- Infectious Disease
- Spatial Analysis/GIS
Education
- PhD 2009, Johns Hopkins University
- BSc 2004, University of British Columbia
Courses Taught
- BIOS 525: Longitudinal Data Analysis
Publications
- Comess S, Chang HH, Warren JL, 2022, A Bayesian framework for incorporating exposure uncertainty into health analyses with application to air pollution and stillbirth., Biostatistics, ,
- Zhang Y, Chang HH, Cheng Q, Collender PA, Li T, He J, Remais JV., 2022, A hierarchical model for analyzing multisite individual-level disease surveillance data from multiple systems, Biometrics, ,
- Thomas N, Ebelt ST, Newman AJ, Scovronick N, D’Souza RR, Moss SE, Warren JL, Strickland MJ, Darrow LA, Chang HH., 2021, Time-series analysis of daily ambient temperature and emergency department visits in five US cities with a comparison of exposure metrics derived from 1-km meteorology products, Environmental Health, 20,
- Berrocal VJ, Guan Y, Muyskens A, Wang H, Reich BJ, Mulholland JA, Chang HH., 2020, A comparison of statistical and machine learning methods for creating national daily maps of ambient PM2.5 concentration., Atmospheric Environment, 222,
- Li X, Chang HH, Cheng Q, Collender PA, Li T, He J, Waller LA, Lopman BA, Remais JV, 2020, A spatial hierarchical model for integrating and bias-correcting data from passive and active disease surveillance systems, Spatial and Spatio-Temporal Epidemiology, 35,
- Murray NL, Holmes HA, Liu Y, Chang HH, 2019, A Bayesian ensemble approach to combine PM2.5 estimates from statistical models using satellite imagery and numerical model simulation, Environmental Research, 178,
- Pan A, Sarnat SE, Chang HH., 2018, Time-Series Analysis of Air Pollution and Health Accounting for Covariate-Dependent Overdispersion, American Journal of Epidemiology, 187,
- Chang HH, Sarnat SE, Liu Y, 2017, Projecting health impacts of climate change: embracing an uncertain future., Chance, 30, 55-61
- Chen T, Sarnat SE, Grundstein AJ, Winquist A, Chang HH, 2017, Time-series Analysis of Heat Waves and Emergency Department Visits in Atlanta, 1993 to 2012, Environmental Health Perspectives, 125, 057009
- Chang HH, Warren JL, Darrow LA, Reich BJ, Waller LA, 2015, Assessment of critical exposure and outcome windows in time-to-event analysis with application to air pollution and preterm birth study., Biostatistics, 16, 509-521
- Chang HH, Hao H, Sarnat SE., 2014, A statistical modeling framework for projecting future ambient ozone and its health impact due to climate change., Atmospheric Environment, 89, 290–297
- Chang HH, Hu X, Liu Y, 2014, Calibrating MODIS aerosol optical depth for predicting daily PM2.5 concentrations via statistical downscaling., Journal of Exposure Science and Environmental Epidemiology, 24, 398-404
- Chang HH, Reich BJ, Miranda ML, 2013, A spatial time-to-event approach for estimating associations between air pollution and preterm birth., Journal of the Royal Statistical Society: Series C, 62, 167-179
- Chang HH, Reich BJ, Miranda ML, 2012, Time-to-event analysis of fine particle air pollution and preterm birth: results from North Carolina, 2001-2005 (with invited commentary)., American Journal of Epidemiology, 175, 91-98
- Chang HH, Peng RD, Dominici F, 2011, Estimating the acute health effects of coarse particulate matter accounting for exposure measurement error., Biostatistics, 12, 637-652