Abstract
Previous research on Dengue Fever have involved laboratory tests or study areas with less diverse temperature and elevation ranges than is found in Colombia; therefore, preliminary research was needed to identify location specific attributes of Dengue Fever transmission. Environmental variables derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Tropical Rainfall Measuring Mission (TRMM) satellites were combined with population variables to be statistically compared against reported cases of Dengue Fever in the Río Magdalena watershed, Colombia. Three-factor analysis models were investigated to analyze variable patterns, including a population, population density, and empirical Bayesian estimation model. Results identified varying levels of Dengue Fever transmission risk, and environmental characteristics which support, and advance, the research literature. Multiple temperature metrics, elevation, and vegetation composition were among the more contributory variables found to identify future potential outbreak locations.
Highlights
The resurgence of tropical diseases in the Americas, including Dengue Fever (DF), may be related to the suspension of vector eradication programs, such as those conducted by the Pan American HealthOrganization (PAHO) programs until the 1970s [1]
The Stage 2 categorical Principal component analysis (PCA) reduced the list of 150 independent variables to 14 variables which were able to more efficiently explain the variance in the dataset without extraneous variable noise
Mean cell-min zone and daytime land surface temperature (LST) max cell-range zone were highly loaded in the first or second component, supporting previous documentation on the influence of temperature range, or diurnal temperature, on mosquito survivability and their use for DF modeling [26,27,28,52]. Since both warmer daytime and cooler nighttime temperatures were found to be highly influential in the results, it demonstrates the variability of temperature within an area may influence DF transmission
Summary
The resurgence of tropical diseases in the Americas, including Dengue Fever (DF), may be related to the suspension of vector eradication programs, such as those conducted by the Pan American HealthOrganization (PAHO) programs until the 1970s [1]. Implementation of new control programs require ongoing data collection. Cost limitation of in situ data collection has increased the use of remote sensing (RS) and Geographic Information Science (GIS) applications to estimate disease spread and population vulnerability [2,3]. Public health agencies can use such tools to implement monitoring and surveillance programs for multiple purposes, including the estimation of vector abundance, implement prevention strategies, or to control for further dispersion of the disease and vector [4,5]. Local metrics and research are needed to improve current vector disease monitoring practices before cost effective predictive or forewarning systems can be studied or implemented [6,7,8,9]. The outputs of this study identified variables capable of inclusion in such studies, but the statistical methods used here are not designed for predictive purposes
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