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Multi-criteria decision analysis and spatial statistic: an approach to determining human vulnerability to vector transmission of Trypanosoma cruzi
Montenegro, Diego; Cunha, Ana Paula da; Ladeia-Andrade, Simone; Vera, Mauricio; Pedroso, Marcel & Junqueira, Angela
Abstract
BACKGROUND Chagas disease (CD), caused by the protozoan Trypanosoma cruzi, is a neglected human disease. It is endemic
to the Americas and is estimated to have an economic impact, including lost productivity and disability, of 7 billion dollars per
year on average.
OBJECTIVES To assess vulnerability to vector-borne transmission of T. cruzi in domiciliary environments within an area
undergoing domiciliary vector interruption of T. cruzi in Colombia.
METHODS Multi-criteria decision analysis [preference ranking method for enrichment evaluation (PROMETHEE) and geometrical
analysis for interactive assistance (GAIA) methods] and spatial statistics were performed on data from a socio-environmental
questionnaire and an entomological survey. In the construction of multi-criteria descriptors, decision-making processes and
indicators of five determinants of the CD vector pathway were summarily defined, including: (1) house indicator (HI); (2) triatominae
indicator (TI); (3) host/reservoir indicator (Ho/RoI); (4) ecotope indicator (EI); and (5) socio-cultural indicator (S-CI).
FINDINGS Determination of vulnerability to CD is mostly influenced by TI, with 44.96% of the total weight in the model, while the
lowest contribution was from S-CI, with 7.15%. The five indicators comprise 17 indices, and include 78 of the original 104 priority
criteria and variables. The PROMETHEE and GAIA methods proved very efficient for prioritisation and quantitative categorisation
of socio-environmental determinants and for better determining which criteria should be considered for interrupting the man-T.
cruzi-vector relationship in endemic areas of the Americas. Through the analysis of spatial autocorrelation it is clear that there is
a spatial dependence in establishing categories of vulnerability, therefore, the effect of neighbors’ setting (border areas) on local
values should be incorporated into disease management for establishing programs of surveillance and control of CD via vector.
CONCLUSIONS The study model proposed here is flexible and can be adapted to various eco-epidemiological profiles and is
suitable for focusing anti-T. cruzi serological surveillance programs in vulnerable human populations.
Keywords
vulnerability; Chagas disease; multi-criteria decision analysis; spatial statistic; PROMETHEE method; GAIA method
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