Multi-criteria decision analysis and spatial statistic: an approach to determining human vulnerability to vector transmission of Trypanosoma cruzi

Montenegro, Diego; Cunha, Ana Paula; Ladeia‐Andrade, Simone; Vera, Mauricio; Pedroso, Marcel de Moraes; Junqueira, Ângela Cristina Veríssimo

doi:10.1590/0074-02760160523

Cited by 4 publications

(3 citation statements)

References 24 publications

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“…The likelihood of human contact is influenced by short-distance movement (for example, whether the species enters and/or colonises homes) and the larger-scale geographical distribution of that species. Studies assessing vulnerability of individuals to Chagas disease have shown that, while housing, ecotype and socio-economics are all relevant, triatomine presence is the most important indicator [4]. Thus understanding the distribution of these vector species is vital to both target control measures and to assess disease risk.…”

Section: Introductionmentioning

confidence: 99%

Modelling geospatial distributions of the triatomine vectors of Trypanosoma cruzi in Latin America

et al. 2020

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Approximately 150 triatomine species are suspected to be infected with the Chagas parasite, Trypanosoma cruzi, but they differ in the risk they pose to human populations. The largest risk comes from species that have a domestic life cycle and these species have been targeted by indoor residual spraying campaigns, which have been successful in many locations. It is now important to consider residual transmission that may be linked to persistent populations of dominant vectors, or to secondary or minor vectors. The aim of this project was to define the geographical distributions of the community of triatomine species across the Chagas endemic region. Presence-only data with over 12, 000 observations of triatomine vectors were extracted from a public database and target-group background data were generated to account for sampling bias in the presence data. Geostatistical regression was then applied to estimate species distributions and fine-scale distribution maps were generated for thirty triatomine vector species including those found within one or two countries and species that are more widely distributed from northern Argentina to Guatemala, Bolivia to southern Mexico, and Mexico to the southern United States of America. The results for Rhodnius pictipes, Panstrongylus geniculatus, Triatoma dimidiata, Triatoma gerstaeckeri, and Triatoma infestans are presented in detail, including model predictions and uncertainty in these predictions, and the model validation results for each of the 30 species are presented in full. The predictive maps for all species are made publicly available so that they can be used to assess the communities of vectors present within different regions of the endemic zone. The maps are presented alongside key indicators for the capacity of each species to transmit T. cruzi to humans. These indicators include infection prevalence, evidence for human blood meals, and colonisation or invasion of homes. A summary of the published evidence for these indicators shows that the majority of the 30 species mapped by this study have the potential to transmit T. cruzi to humans.

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Section: Introductionmentioning

confidence: 99%

Modelling geospatial distributions of the triatomine vectors of Trypanosoma cruzi in Latin America

et al. 2020

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“…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)(32)(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.…”

Section: Propuesta De Modelo De Atención En El Lugarunclassified

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

Montenegro¹

2020

Revista Panamericana De Salud Pública

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Objetivo. Proponer un modelo de atención en salud que integra tecnologías que pueden emplearse en el lugar de atención (point-of-care) y técnicas de inteligencia artificial. Métodos. Se usó un modelo teórico en el que un millón de personas accedieron a la aplicación móvil CoronApp-Colombia, que recoge datos personales, signos, síntomas y nexos epidemiológicos compatibles con COVID-19. Empleando la información de la app se aplicaron técnicas de inteligencia artificial (ciencias de datos) en una sala situacional virtual. Resultados. Los usuarios compatibles con COVID-19 serían priorizados y sometidos a una prueba de diagnóstico rápido para la búsqueda de anticuerpos anti-SARS-CoV-2. El tamizaje con la prueba de diagnóstico rápido permitiría detectar a las personas serorreactivas, en quienes se llevaría a cabo la confirmación diagnóstica mediante biología molecular (PCR). La información de los casos positivos confirmados por PCR se sometería nuevamente a técnicas de inteligencia artificial y estadística espacial para determinar los focos geográficos de infección. En estos focos se puede hacer búsqueda activa de contactos con los casos índices positivos y activar nuevamente la ruta de diagnóstico con la prueba de diagnóstico rápido y PCR. Conclusión. Este escenario puede ser un camino útil para que los países de la región con plataformas tecnológicas para el diagnóstico por PCR débiles o ausentes puedan maximizar los recursos existentes, estimar el peso epidemiológico de la COVID-19 (infección, morbilidad, mortalidad y letalidad) en sus territorios y definir planes de contención, mitigación y control acordes a sus necesidades.

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“…Multi-criteria decision analysis is a method that approaches a certain object from different characteristics that influence the occurrence of a given problem. The method has become increasingly used for understanding of events of interest in public health [54].…”

Section: Analysis Of Datamentioning

confidence: 99%

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

Montenegro¹,

Cunha²,

Machado³

et al. 2018

Spatial Analysis, Modelling and Planning

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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.

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Multi-criteria decision analysis and spatial statistic: an approach to determining human vulnerability to vector transmission of Trypanosoma cruzi

Cited by 4 publications

References 24 publications

Modelling geospatial distributions of the triatomine vectors of Trypanosoma cruzi in Latin America

Modelling geospatial distributions of the triatomine vectors of Trypanosoma cruzi in Latin America

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

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

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