Background: Dengue is one of the important vector-borne diseases in the world today; it infects tens of millions of people each year and has been on the rise since the 1950s. In this study, we develop a set of indicators that help us examine the impact of socio-economic and demographic factors on the occurrence of dengue in regions of the United States and Mexico.
Methods: We assess the relationship between dengue occurrence in humans, climate factors (temperature and minimum quarterly rainfall), socio-economic factors (such as household income, regional rates of education, housing overcrowding, life expectancy, and medical resources), and demographic factors (such as migration flows, age structure of the population, and population density). Areas at risk of dengue are first selected based on the predicted presence of at least one of the two mosquito vectors responsible for dengue’s transmission: Aedes aegypti and Aedes albopictus. In those regions where the vectors had a high probability of presence, we assess the impact of the composite socio-economic indicators (derived through factor analysis to account for collinearity), and three composite demographic indicators (also derived from factor analysis) on the regional distribution of dengue cases, controlling for climate and spatial correlation.
Results: We found that an increase of one unit in one of our socio-economic indicators representing labour force with at least secondary education, better broadband access, and rooms per inhabitant, a higher proportions of active physicians is related to a drop in the occurrence of dengue, whereas the demographic indicators such as population density, age structure of the population and population growth showed no significant impact after taking climate into account. More importantly, our socio-economic indicator can also explain differences in the occurrence of dengue across Mexico, whereas simpler measures, such as regional GDP could not.
Conclusions: These results suggest that the set of indicators developed is a better indicator than GDP at predicting the distribution of dengue, by capturing information that is much more tailored to poverty related conditions which aid dengue transmission. Given that data for these indicators are available at a sub-national scale for OECD countries and selected OECD non-member economies, these indices may help us better understand factors responsible for the global distribution of dengue and also, given a warming climate, may help us to better predict vulnerable populations.