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. 2013 Apr;88(4):630-7.
doi: 10.4269/ajtmh.12-0448. Epub 2013 Feb 4.

Ecohealth interventions limit triatomine reinfestation following insecticide spraying in La Brea, Guatemala

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Ecohealth interventions limit triatomine reinfestation following insecticide spraying in La Brea, Guatemala

David E Lucero et al. Am J Trop Med Hyg. 2013 Apr.

Abstract

In this study, we evaluate the effect of participatory Ecohealth interventions on domestic reinfestation of the Chagas disease vector Triatoma dimidiata after village-wide suppression of the vector population using a residual insecticide. The study was conducted in the rural community of La Brea, Guatemala between 2002 and 2009 where vector infestation was analyzed within a spatial data framework based on entomological and socio-economic surveys of homesteads within the village. Participatory interventions focused on community awareness and low-cost home improvements using local materials to limit areas of refuge and alternative blood meals for the vector within the home, and potential shelter for the vector outside the home. As a result, domestic infestation was maintained at ≤ 3% and peridomestic infestation at ≤ 2% for 5 years beyond the last insecticide spraying, in sharp contrast to the rapid reinfestation experienced in earlier insecticide only interventions.

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Figures

Figure 1.
Figure 1.
The La Brea, Guatemala study area. (A) GeoEye satellite image shown as a natural color composite with the study area location shown in the inset map of Guatemala. (B) Houses and roads were digitized from the imagery and saved as separate geographic information system (GIS) data layers. The entomological and socio-economic survey data were then joined with the housing data layer using the survey global positioning system (GPS) coordinates.
Figure 2.
Figure 2.
Best-fit semi-variogram describing the spatial correlation between pairs of homesteads separated by distance. The average variance for each group of binned data is represented by an “X”. Each bin summarizes 369 pairwise comparisons of homesteads weighted by Triatoma dimidiata abundance for 2002 in La Brea, Guatemala with a 95% confidence envelope (dashed lines). After a range of decorrelation (∼100 m in this study) the data are no longer spatially correlated.
Figure 3.
Figure 3.
Triatoma dimidiata infestation in La Brea, Guatemala before and after scheduled interventions. Data represent the fraction of houses surveyed within which the vector was found, summarized by habitat, i.e., domestic (•), peridomestic (□), and total (▴). The overlying shaded bars represent the scheduled interventions: a) insecticide applications (March and September), b) insecticide application (February), c) wall plastering, and d) cement-like flooring, exclusion of chicken coops from houses, and construction of coops using open-mesh wire. Also shown is the number of homesteads surveyed each survey year (grey solid line).
Figure 4.
Figure 4.
Crowding densities (average vector abundance per infested homestead) for domestic (open bar) and peridomestic (shaded bar) Triatoma dimidiata populations in La Brea, Guatemala. The data shown represent the mean ± 1 SE.
Figure 5.
Figure 5.
Spatial and temporal distribution of Triatoma dimidiata infestation within La Brea, Guatemala by survey year (2002–2009). Data represent vector densities in peridomestic (blue diamond) and domestic (red square) habitats. Symbols are sized in proportion to the vector density observed. Non-infested homesteads (black polygons) and homesteads that were not surveyed (grey polygons) are also represented. The geographic center of vector abundance (mean ± 1 SD) for each year is identified by a star and ellipse.
Figure 6.
Figure 6.
Hot Spot analysis of Triatoma dimidiata infested homesteads in La Brea, Guatemala in 2002. Based on the Getis-Ord Gi* statistic, Hot Spots represent 100 m radius neighborhoods (circles) having significantly higher vector crowding densities than the village as a whole. The size (diameter) of the neighborhoods was chosen based on the range of decorrelation from the semi-variogram analysis (Figure 2).

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