Spatial patterns and eco-epidemiological systems – part II: characterising spatial patterns of the occurrence of the insect vectors of Chagas disease based on remote sensing and field data

Abstract

While the former part of this back-to-back paper dealt with the identification of multi-scale spatial patterns associated with the presence, abundance and dispersion of the insect vectors (Triatominae) of Chagas disease, this latter part examines the need for pattern characterisation by means of detailed data on environmental, residential, peri-domiciliary and human behaviour. The study site was, in both cases, a single village situated in Bahia, Brazil, wherefrom the data were collected through field observation and a standardised questionnaire, while the environmental characteristics were derived from satellite images and landscape characterisation. Following this, factorial analysis of mixed group (FAMG), an exploratory data analysis method, was applied to “mine” the huge dataset in a hierarchical way and to evaluate the relative impact of different factors such as the surrounding environment, the domiciliary/peri-domiciliary space properties and the presence of domestic animals. In the study village, five principal “districts” associated with different possible causes of infestation were identified. The results favour the role of depressions of the ground surface due to collapse of karstic subsoil (dolines) and open rock faces as infestation sources, vector attraction by outdoor lighting, risk of insect domiciliation in dwellings constructed without finishing materials and associated with apparent disorder. Ultimately, this study not only provides the basic information needed for decision-making and specification of vector control in the study village, but offers also a knowledge-base for more general control strategies in the region.

Keywords

• principal coordinate of neighbourhood matrices, factorial analysis of mixed groups, remote sensing, landscape characterisation, Chagas disease insect vectors, Triatomines, Brazil.