ArticleParasites & vectors2019
Applying fuzzy logic to assess the biogeographical risk of dengue in South America.
Article in Parasites & vectors, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.
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Who cites it
16 citing papers in PubMed, 2 syntheses or guidelines pooled it, 38 citations in OpenAlex.
- Trends in mosquito species distribution modeling: insights for vector surveillance and disease control.Parasites & vectors · 2023Pooled it
- Data-driven methods for dengue prediction and surveillance using real-world and Big Data: A systematic review.PLoS neglected tropical diseases · 2022Pooled it
- Global risk assessment of Lyme borreliosis transmission.Pathogens and global health · 2026Article
- Review
- Predicting the ecological niches ofFrontiers in tropical diseases · 2025Article
- Current and Future Spatial Distribution of theInsects · 2025Article
- The fuzzy system ensembles entomological, epidemiological, demographic and environmental data to unravel the dengue transmission risk in an endemic city.BMC public health · 2024Article
- Understanding the Geographic Patterns of Closely-Related Species ofPlants (Basel, Switzerland) · 2023Article
- Deciphering the Hantavirus Host Range Combining Virology and Species Distribution Models with an Emphasis on the Yellow Pygmy Rice Rat (Transboundary and emerging diseases · 2023Article
- Report of Mosquito Vectors of Arboviruses from a Federal Conservation Unit in the Atlantic Forest, Rio de Janeiro State, Brazil.Life (Basel, Switzerland) · 2022Article
- The application of geographic information system for dengue epidemic in Southeast Asia: A review on trends and opportunity.Journal of public health research · 2022Article
- Forecasting parasite sharing under climate change.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2021Article
- Worldwide dynamic biogeography of zoonotic and anthroponotic dengue.PLoS neglected tropical diseases · 2021Article
- Dengue risk assessment using multicriteria decision analysis: A case study of Bhutan.PLoS neglected tropical diseases · 2021Article
- [Artificial intelligence and its applications in medicine II: Current importance and practical applications].Atencion primaria · 2021Review
- Predicting the spatio-temporal spread of West Nile virus in Europe.PLoS neglected tropical diseases · 2021Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundOver the last decade, reports about dengue cases have increase worldwide, which is particularly worrisome in South America due to the historic record of dengue outbreaks from the seventeenth century until the first half of the twentieth century. Dengue is a viral disease that involves insect vectors, namely Aedes aegypti and Ae. albopictus, which implies that, to prevent and combat outbreaks, it is necessary to understand the set of ecological and biogeographical factors affecting both the vector species and the virus.
methodsWe contribute with a methodology based on fuzzy logic that is helpful to disentangle the main factors that determine favorable environmental conditions for vectors and diseases. Using favorability functions as fuzzy logic modelling technique and the fuzzy intersection, union and inclusion as fuzzy operators, we were able to specify the territories at biogeographical risk of dengue outbreaks in South America.
resultsOur results indicate that the distribution of Ae. aegypti mostly encompasses the biogeographical framework of dengue in South America, which suggests that this species is the principal vector responsible for the geographical extent of dengue cases in the continent. Nevertheless, the intersection between the favorability for dengue cases and the union of the favorability for any of the vector species provided a comprehensive map of the biogeographical risk for dengue.
conclusionsFuzzy logic is an appropriate conceptual and operational tool to tackle the nuances of the vector-illness biogeographical interaction. The application of fuzzy logic may be useful in decision-making by the public health authorities to prevent, control and mitigate vector-borne diseases.
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