Abstract
Although remotely sensed data have been used in public health studies, these studies are often limited by the critical choice that has to be made in data selection: either using data with high spatial but low temporal resolution, or data with high temporal but low spatial resolution. This choice creates significant limitations for time-dependent epidemiological studies, since it is often essential to have datasets with high spatial and temporal resolution. Effectively synthesizing high temporal resolution imagery with high spatial resolution imagery can potentially ease this limitation. To this end, we conducted an experiment by creating a series of simulated ASTER datasets by fusing ASTER and MODIS data with the STARFM image fusion model. These simulated datasets are then used to derive the following urban environmental variables: normalized difference vegetation index, normalized difference water index, and land surface temperature. These variables are used to quantitatively examine the effects of urban environmental characteristics on West Nile Virus dissemination in Los Angeles County, California, where the epidemic was most prevalent in the United States in 2007. Mosquito surveillance data were collected from the weekly summary reports published in the California West Nile Virus website. A spatial–temporal analysis of WNV dissemination was conducted by synthesizing remote sensing variables and mosquito surveillance records. We focused on assessment of WNV risk areas in July through September due to data sufficiency of tested-positive mosquito pools. Moderate- and high-risk areas of WNV infections in mosquitoes were identified for five selected time windows, i.e., epidemiological weeks 30–31, 32–33, 34–35, 36–37, and 38–39. The results show that elevation and urban built-up conditions were negatively associated with the WNV propagation, while LST positively correlated with viral transmission. NDVI was not significantly associated with WNV transmission during the studied time intervals. San Fernando Valley was found to be the most vulnerable to mosquito infections of WNV within the City of Los Angeles. With the complementation of high-spatial resolution ASTER and high-temporal resolution MODIS images, the fused image datasets allow for estimating environmental parameters at desired epidemiological weeks. This paper provides important insights into how high temporal resolution remote sensing imagery might be used to study time-dependant events in public health, especially in the operational surveillance and control of vector-borne or other epidemic diseases.
Published Version
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