One World, One Health Challenge: The Holistic Understanding of Rickettsiosis Integrating Multi-Criteria Analysis Techniques and Spatial Statistics

Abstract

Among the human diseases caused by etiological agents transmitted by ticks in Brazil, the most prevalent and public health interest is that one caused by species of Rickettsia-Spotted Fever (SF). We applied the concept "One World, One Health" to achieve a proper understanding of SF and determine risk scenarios for human infection by pathogenic Rickettsia in the state of Rio de Janeiro (RJ). Multi-criteria decision analysis and spatial statistics were performed on data encompassing epidemiology, health care, biotic determents, and socioeconomic and demographic variables. The construction of multi-criteria descriptors used 33 indicators ordered in 12 sub criteria of 5 major categories: public health, environmental health, acarology, veterinary health, and microbiology. SF happened nonrandomly in RJ and the risk was heterogeneous in the weight of indicators contribution mainly associated with the criteria acarology (35.11%), microbiology (33.25%), and veterinary medicine (23.96%). Spatially, and according to the PROMETHEE algorithm, ticks from Amblyomma sculptum class and dogs are determinants for the occurrence of human cases of SF in RJ. To define indicators of SF and plan health actions, the "One World, One Health" concept proved to be applicable at three levels: (i) the local or possible areas of infection, (ii) the population or municipality, and (iii) the ecosystem or state. The model of study is flexible according to the reality of the endemic areas and also demonstrates its applicability from a national to a local (home) scale.

Uso de tecnologías en el lugar de atención para el manejo de la pandemia por COVID-19 en Colombia

“…La información aportada por los usuarios de la app puede ser analizada por técnicas de aprendizaje automático ( machine learning ), análisis de árboles de decisión o redes neurales artificiales, entre otras técnicas de inteligencia artificial ( 30 ). Las técnicas de inteligencia artificial, combinadas con técnicas cartográficas, son herramientas útiles para buscar, predecir, vigilar y controlar focos de infecciones humanas ( 22 , 31 – 33 ). Se propone emplear estas técnicas porque permiten manejar mejor la cantidad de variables y el análisis de datos masivos en comparación con un agente humano.…”