Biomedical subjects

Chris Swalm

Publications and source records attributed to Chris Swalm.

3 recordsLinked to original sources

PubMed2003

Linking field-based ecological data with remotely sensed data using a geographic information system in two malaria endemic urban areas of Kenya.

BACKGROUND: Remote sensing technology provides detailed spectral and thermal images of the earth's surface from which surrogate ecological indicators of complex processes can be measured. METHODS: Remote sensing data were overlaid onto georeferenced entomological and human ecological data randomly sampled during April and May 2001 in the cities of Kisumu (population asymptotically equal to 320,000) and Malindi (population asymptotically equal to 81,000), Kenya. Grid cells of 270 meters x 270 meters were used to generate spatial sampling units for each city for the collection of entomological and human ecological field-based data. Multispectral Thermal Imager (MTI) satellite data in the visible spectrum at five meter resolution were acquired for Kisumu and Malindi during February and March 2001, respectively. The MTI data were fit and aggregated to the 270 meter x 270 meter grid cells used in field-based sampling using a geographic information system. The normalized difference vegetation index (NDVI) was calculated and scaled from MTI data for selected grid cells. Regression analysis was used to assess associations between NDVI values and entomological and human ecological variables at the grid cell level. RESULTS: Multivariate linear regression showed that as household density increased, mean grid cell NDVI decreased (global F-test = 9.81, df 3,72, P-value = <0.01; adjusted R2 = 0.26). Given household density, the number of potential anopheline larval habitats per grid cell also increased with increasing values of mean grid cell NDVI (global F-test = 14.29, df 3,36, P-value = <0.01; adjusted R2 = 0.51). CONCLUSIONS: NDVI values obtained from MTI data were successfully overlaid onto georeferenced entomological and human ecological data spatially sampled at a scale of 270 meters x 270 meters. Results demonstrate that NDVI at such a scale was sufficient to describe variations in entomological and human ecological parameters across both cities.

Journal Article↗

PubMed2003

A geographic sampling strategy for studying relationships between human activity and malaria vectors in urban Africa.

This paper describes a geographic sampling strategy for ecologic studies and describes the relationship between human activities and anopheline larval ecology in urban areas. Kisumu and Malindi, Kenya were mapped using global positioning systems, and a geographic information system was used to overlay a measured grid, which served as a sampling frame. Grid cells were stratified and randomly selected according to levels of planning and drainage. A cross-sectional survey was conducted in April and May 2001 to collect entomologic and human ecologic data. Multivariate regression analysis was used to test the relationship between the abundance of potential larval habitats, and house density, socioeconomic status, and planning and drainage. In Kisumu, 98 aquatic habitats were identified, 65% of which were human made and 39% were positive for anopheline larvae. In Malindi, 91 aquatic habitats were identified, of which, 93% were human made and 65% were harboring anopheline larvae. The regression model explains 82% of the variance associated with the abundance of potential larval habitats in Kisumu. In Malindi, 59% of the variance was explained. As the number of households increased, the number of larval habitats increased correspondingly to a point. Beyond a critical threshold, the density of households appeared to suppress the development of aquatic habitats. The proportion of high-income households and the planning and drainage variables tested insignificant in both locations. The integration of social and biologic sciences will allow local mosquito and malaria control groups an opportunity to assess the risk of encountering potentially infectious mosquitoes in a given area, and concentrate resources accordingly.

Africa↗

PubMed2003

Spatial and temporal heterogeneity of Anopheles mosquitoes and Plasmodium falciparum transmission along the Kenyan coast.

The seasonal dynamics and spatial distributions of Anopheles mosquitoes and Plasmodium falciparum parasites were studied for one year at 30 villages in Malindi, Kilifi, and Kwale Districts along the coast of Kenya. Anopheline mosquitoes were sampled inside houses at each site once every two months and malaria parasite prevalence in local school children was determined at the end of the entomologic survey. A total of 5,476 Anopheles gambiae s.l. and 3,461 An. funestus were collected. Species in the An. gambiae complex, identified by a polymerase chain reaction, included 81.9% An. gambiae s.s., 12.8% An. arabiensis, and 5.3% An. merus. Anopheles gambiae s.s. contributed most to the transmission of P. falciparum along the coast as a whole, while An. funestus accounted for more than 50% of all transmission in Kwale District. Large spatial heterogeneity of transmission intensity (< 1 up to 120 infective bites per person per year) resulted in correspondingly large and significantly related variations in parasite prevalence (range = 38-83%). Thirty-two percent of the sites (7 of 22 sites) with malaria prevalences ranging from 38% to 70% had annual entomologic inoculation rates (EIR) less than five infective bites per person per year. Anopheles gambiae s.l. and An. funestus densities in Kwale were not significantly influenced by rainfall. However, both were positively correlated with rainfall one and three months previously in Malindi and Kilifi Districts, respectively. These unexpected variations in the relationship between mosquito populations and rainfall suggest environmental heterogeneity in the predominant aquatic habitats in each district. One important conclusion is that the highly non-linear relationship between EIRs and prevalence indicates that the consistent pattern of high prevalence might be governed by substantial variation in transmission intensity measured by entomologic surveys. The field-based estimate of entomologic parameters on a district level does not provide a sensitive indicator of transmission intensity in this study.

Animals↗