Dengue, chikungunya, Zika and malaria are just a few mosquito-borne diseases that can devastate the health of populations in tropical and subtropical countries.
In a study published in the journal Acta Tropica, Daniel Parker, PhD, corresponding author and assistant professor of population health & disease prevention in UCI’s Program in Public Health and Volodymyr Minin, PhD, professor of statistics in the Donald Bren School of Information and Computer Sciences found that spatially-targeted interventions are a key strategy to controlling vector-based disease spread. Parker and Minin worked with UCI Statistics PhD student Catalina Medina on statistical modeling and data analysis that lead to these scientific findings.
Our findings have the potential to alleviate the long-standing obstacles by creating vector-focused public health interventions.”
– Daniel Parker, PhD, Corresponding Author
The World Health Organization reports that vector-borne diseases cause roughly 700,000 deaths annually despite it being preventable when protective measures and community mobilization are adopted. Vector-borne diseases are diseases that are spread between people through another organism (the “vector”, with mosquitoes being one type of vector). There are many challenges to dealing with these types of diseases. For example, vector control strategies are time consuming and labor intensive. Different diseases are spread by different species and genuses of mosquitoes, and these different types of mosquitoes often live in different ecological habitats and feed at different times of the day. The mosquitoes that spread dengue, chikungunya, and Zika tend to thrive in urban environments and feed in the daytime. This means that vector control strategies such as sleeping under bednets are less effective for these diseases. Such diseases are a growing problem in rapidly urbanizing Southeast Asian countries like Cambodia.
In this research, Parker and team measured peoples’ antibody responses to Aedes mosquito saliva as an indicator of exposure to this important vector of infectious diseases.
“This project was very interesting both scientifically and technically. Making sense of mosquito saliva measurements required non-trivial data integration and sophisticated statistical modeling to take into account spatial dependencies in the observations. This experience inspired us to think about novel data science and statistical tool developments that should help epidemiologists with future data analyses,” says Minin.
The research team controlled for potentially important factors in the analysis, such as gender, age, distance from house to a river, and the land type for an individual’s home. They found that hotspots of exposure to these mosquitoes are stable and small, and that household characteristics are very strong predictors of exposure to these mosquitoes. This means that vector control measures could likely be targeted towards these small and stable hotspots, hopefully leading to a reduction in diseases.
“Our findings point toward the possibility of focusing public health interventions on these hotspots,” says Parker.
