All ETDs from UAB

Advisory Committee Chair

Nalini Sathiakumar

Advisory Committee Members

Leslie McClure

Akhlaque Haque

Jeffery Luvall

Ben Zaitchik

Document Type

Dissertation

Date of Award

2014

Degree Name by School

Doctor of Public Health (DrPH) School of Public Health

Abstract

The incidence of dengue fever has increased exponentially in Sri Lanka, from 24.4 cases per 100,000 in 2003 to 165.3 per 100,000 population in 2013. Despite concerted effort by the Sri Lankan government, dengue control remains a challenge in the country, indicating a need for novel approach for dengue prevention and control. The aim of this research was to identify environmental risk factors that may be associated with dengue incidence rate at the Gram Niladhari Divisions level (smallest administrative unit) in Colombo city, Sri Lanka, using geospatial tools such as remote sensing and geographic information system. These factors included climate variables, land cover classes, population demographics and housing characteristics. Data on potential risk factors were obtained from several sources including remotely sensed data, meteorology department and publicly available census data. Data on dengue cases were obtained from Colombo municipal council, Department of Public Health for period between 2005 and 2011. The analysis was conducted in two parts: part I evaluated the relationship between mean temperature and cumulative rainfall and dengue incidence, using generalized linear regression; part II evaluated the relationship between local environmental factors such as land cover, population and housing characteristics and dengue incidence rate, using spatial (geographic weighted regression) and non-spatial analysis (Poisson regression). The results of the study found that: 1) there is a weak association between weekly temperature and rainfall and increased risk of dengue; 2) determined spatial-temporal risk of dengue incidence rate using the Getis-Ord Gi* statistic; and 3) local environmental factors such as decreased piped-water supply, increased brick-walled housing, decreased housing density and increased vegetation were significantly associated with high incidence of dengue fever cases. Results of the study are in agreement with several other studies conducted previously however, they are novel in Sri Lanka. The application geospatial tools for data management and analysis contributes to the evidence supporting routine use of these tools in dengue research. The study paves way for future work using methods applied in this study to targeted interventions to prevent and control dengue in high risk areas in the country and in the region.

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