Background: Dengue fever is one of the most important arboviral diseases. Surface temperature versus dengue burden in tropical environments can provide valuable information that can be adapted in future measurements to improve health policies. Methods: A methodological approach using Daymet-V3 provided estimates of daily weather parameters. A Python code developed by us extracted the median temperature from the urban regions of Colima State (207.3 km2) in Mexico. JointPoint regression models computed the mean temperature-adjusted average annual percentage of change (AAPC) in disability-adjusted life years (DALY) rates (per 100,000) due to dengue in Colima State among school-aged (5–14 years old) children. Results: Primary outcomes were average temperature in urban areas and cumulative dengue burden in DALYs in the school-aged population. A model from 1990 to 2017 medium surface temperature with DALY rates was performed. The increase in DALYs rate was 64% (95% CI, 44–87%), and it seemed to depend on the 2000–2009 estimates (AAPC = 185%, 95% CI 18–588). Conclusion: From our knowledge, this is the first study to evaluate surface temperature and to model it through an extensive period with health economics calculations in a specific subset of the Latin-American endemic population for dengue epidemics.
|Number of pages||10|
|Journal||International Journal of Environmental Research and Public Health|
|Publication status||Published - 16 Apr 2021|
- Health economics
- Remote sensing