Literature DB >> 27974065

Evaluation of the impacts of climate change on disease vectors through ecological niche modelling.

B M Carvalho1, E F Rangel2, M M Vale1.   

Abstract

Vector-borne diseases are exceptionally sensitive to climate change. Predicting vector occurrence in specific regions is a challenge that disease control programs must meet in order to plan and execute control interventions and climate change adaptation measures. Recently, an increasing number of scientific articles have applied ecological niche modelling (ENM) to study medically important insects and ticks. With a myriad of available methods, it is challenging to interpret their results. Here we review the future projections of disease vectors produced by ENM, and assess their trends and limitations. Tropical regions are currently occupied by many vector species; but future projections indicate poleward expansions of suitable climates for their occurrence and, therefore, entomological surveillance must be continuously done in areas projected to become suitable. The most commonly applied methods were the maximum entropy algorithm, generalized linear models, the genetic algorithm for rule set prediction, and discriminant analysis. Lack of consideration of the full-known current distribution of the target species on models with future projections has led to questionable predictions. We conclude that there is no ideal 'gold standard' method to model vector distributions; researchers are encouraged to test different methods for the same data. Such practice is becoming common in the field of ENM, but still lags behind in studies of disease vectors.

Keywords:  zzm321990 Aedeszzm321990 ; zzm321990 Anopheleszzm321990 ; zzm321990 Culicoideszzm321990 ; zzm321990 Ixodeszzm321990 ; zzm321990 Lutzomyiazzm321990 ; zzm321990 Phlebotomuszzm321990 ; zzm321990 Triatomazzm321990 ; ensemble modelling; spatial distribution; vector-borne diseases

Mesh:

Year:  2016        PMID: 27974065     DOI: 10.1017/S0007485316001097

Source DB:  PubMed          Journal:  Bull Entomol Res        ISSN: 0007-4853            Impact factor:   1.750


  14 in total

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Review 3.  Leishmaniasis Beyond East Africa.

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Journal:  Front Vet Sci       Date:  2021-02-26

4.  Species-specific ecological niche modelling predicts different range contractions for Lutzomyia intermedia and a related vector of Leishmania braziliensis following climate change in South America.

Authors:  Shannon McIntyre; Elizabeth F Rangel; Paul D Ready; Bruno M Carvalho
Journal:  Parasit Vectors       Date:  2017-03-24       Impact factor: 3.876

5.  Ecological niche modelling and predicted geographic distribution of Lutzomyia cruzi, vector of Leishmania infantum in South America.

Authors:  Everton Falcão de Oliveira; Eunice Aparecida Bianchi Galati; Alessandra Gutierrez de Oliveira; Elizabeth Ferreira Rangel; Bruno Moreira de Carvalho
Journal:  PLoS Negl Trop Dis       Date:  2018-07-30

6.  Coinfection With Trypanosoma brucei Confers Protection Against Cutaneous Leishmaniasis.

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Journal:  Front Immunol       Date:  2018-12-11       Impact factor: 7.561

7.  Ecological niche modeling predicting the potential distribution of Leishmania vectors in the Mediterranean basin: impact of climate change.

Authors:  Bilel Chalghaf; Jomâa Chemkhi; Benjamin Mayala; Myriam Harrabi; Goze Bertin Benie; Edwin Michael; Afif Ben Salah
Journal:  Parasit Vectors       Date:  2018-08-09       Impact factor: 3.876

8.  Risk prediction of two types of potential snail habitats in Anhui Province of China: Model-based approaches.

Authors:  Jun Zhang; Ming Yue; Yi Hu; Robert Bergquist; Chuan Su; Fenghua Gao; Zhi-Guo Cao; Zhijie Zhang
Journal:  PLoS Negl Trop Dis       Date:  2020-04-06

9.  High-resolution habitat suitability model for Phlebotomus pedifer, the vector of cutaneous leishmaniasis in southwestern Ethiopia.

Authors:  Myrthe Pareyn; Anneleen Rutten; Behailu Merdekios; Ronja E M Wedegärtner; Nigatu Girma; Leo Regelbrugge; Simon Shibru; Herwig Leirs
Journal:  Parasit Vectors       Date:  2020-09-11       Impact factor: 3.876

10.  Geographic abundance patterns explained by niche centrality hypothesis in two Chagas disease vectors in Latin America.

Authors:  Mariano Altamiranda-Saavedra; Luis Osorio-Olvera; Carlos Yáñez-Arenas; Juan Carlos Marín-Ortiz; Gabriel Parra-Henao
Journal:  PLoS One       Date:  2020-11-04       Impact factor: 3.240

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