Evaluation and planning of Chagas control activities using geospatial tools

  • Diego Weinberg | dweinberg@mundosano.org Mundo Sano Foundation, Buenos Aires, Argentina.
  • Mario Lanfri National Commission for Space Activities, Córdoba, Argentina.
  • Carlos M. Scavuzzo National Commission for Space Activities, Córdoba, Argentina.
  • Marcelo Abril Mundo Sano Foundation, Buenos Aires, Argentina.
  • Sofía Lanfri Mundo Sano Foundation, Buenos Aires, Argentina.

Abstract

Chagas continues to be a relevant public health problem in Latin America. In this work, we present a spatiotemporal analysis applied for the evaluation and planning of Chagas vector control strategies. We analysed the spatial distribution of the vector Triatoma infestans infestation related to ongoing control interventions cycles in rural communities near Añatuya, Santiago del Estero, Argentina. A geographical information system was developed for the spatial analysis obtaining, for each house, variables that describe the history of spraying and infestation at each time of interventions. Bi-dimensional histograms were used to describe the spatiotemporal pattern of these activities and peri-domestic infestation at the last intervention was modelled by a neural network model. We qualitatively evaluate control programmes considering the history of infestation and spraying from a spatiotemporal point of view, incorporating new ways of visualising this information. Predictions are based on novel, non-linear models and spatiotemporal indices, which should be useful for strategically allocating Chagas control resources in the future and thus help to better plan spraying strategies.

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Published
2019-11-06
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Section
Original Articles
Keywords:
Chagas vector control, Spatiotemporal analysis, Geographical information systems, Neural network model, Argentina
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How to Cite
Weinberg, D., Lanfri, M., Scavuzzo, C. M., Abril, M., & Lanfri, S. (2019). Evaluation and planning of Chagas control activities using geospatial tools. Geospatial Health, 14(2). https://doi.org/10.4081/gh.2019.786

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