Alistair Hayden
Cornell University, NY·Public Health & Epidemiology
Hurricanes, floods and heat waves do not only cause direct injury; they can also change how infectious diseases spread, through standing water that breeds mosquitoes, damaged hospitals and roads, shifts in where animals and people live, and changes in behavior. Tracing that chain from a storm to a disease outbreak means joining fields that rarely share data or methods: weather science, ecology, the biology of disease-carrying insects, human and animal health, infrastructure, economics and policy.
- Fields
Public Health & Epidemiology
Earth & Environmental Science
Computer Science
- Topics
extreme weather events
infectious disease transmission
predictive epidemiological models
- Grants
- 1 known grant, through Aug 2027
What they work on
- Test whether the living-evidence model of systematic review — continuously updated rather than one-time literature synthesis — makes infectious disease research products more applicable to real decisions.
- Test whether artificial intelligence, epidemiology and econometrics together provide a framework for integrating weather, land-use, health and economic data streams into actionable findings.
- Integrate heterogeneous datasets, including remote sensing, geospatial layers, human and wildlife health records, genomic libraries and biobanked samples, to support predictive epidemiological models of post-extreme-weather disease transmission.
- Identify which weather-to-disease relationships generalize across settings and which are context-specific, using geospatial analysis combined with disease and policy modeling.
- Build transdisciplinary capacity through trainings and a collaborative modeling core, so that the data-curation and modeling methods can be reused for other health-impact research.
More about the research
This work builds the data and modeling backbone for that kind of joined-up research.
Why it matters
Communities hit by hurricanes, floods and heat are also exposed to shifting infectious disease risk, yet forecasts rarely connect the two. By merging weather, land-use, genomic, health and economic data into predictive models, this work could give public health agencies and local decision-makers earlier and more usable warning of post-disaster outbreaks, and distinguish risks that generalize across regions from those tied to one setting.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Alexander Travis
Cornell University, NY·Public Health & Epidemiology
Test whether community-engaged research that combines weather, land-use, human and animal health, behavior and pathogen genomic data can produce predictive epidemiological models that forecast infectious disease outbreaks.
Ariane De Bremond
University of Maryland, MD·Earth & Environmental Science
Coordinate land system science worldwide through the Global Land Programme office by setting research agendas, leading synthesis of place-based case studies, and supporting core methods in modeling, monitoring and case study research.
Jiakai Zhang
New Mexico Institute of Mining and Technology, NM·Earth & Environmental Science
Integrate large public spatial, hazard and socioeconomic datasets into a single AI-driven model of regional environmental risk and vulnerability across the United States.
The school
Cornell University: 37 labs on PI Pages, $1.6B a year on research, 537 research doctorates a year.
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