Spatio-temporal Modeling Approach to Mapping Geographic and Temporal Variation in Cancer Incidence Rates for U.S. Counties
The resulting estimates and maps could support surveillance, trend analysis, disparity identification, targeted interventions, and broader research efforts.
Authors
- James Cucinelli (ORCID: https://orcid.org/0000-0003-0937-8643)
- Zaria Tatalovich (ORCID: https://orcid.org/0000-0003-2692-7077)
- Benmei Liu (ORCID: https://orcid.org/0000-0003-0096-139X)
- Zhuoqiao Wang
- Recinda Sherman (ORCID: https://orcid.org/0000-0003-0530-1075)
- Li Zhu (ORCID: https://orcid.org/0000-0002-9805-6779)
- Jeremy Lyman
- Eric J. Feuer
Institutions
- National Institutes of Health (US)
- North American Association of Central Cancer Registries (US)
- Information Management Services (US)
- National Cancer Institute (MY)
- National Cancer Institute (US)
- Associated Management Services (United States) (US)
- National Institutes of Health Clinical Center (US)
Publication Details
- Journal
- Cancer Epidemiology Biomarkers & Prevention
- Published
- 2026-03-26
- DOI
- https://doi.org/10.1158/1055-9965.epi-25-1129
- Primary Topic
- Data-Driven Disease Surveillance
- Type
- article
- Field-Weighted Citation Impact
- 0.00