Applying fuzzy logic to assess the biogeographical risk of dengue in South America.
Ae. albopictus
Aedes aegypti
Favorability function
Fuzzy operators
Vector-illness interaction
Journal
Parasites & vectors
ISSN: 1756-3305
Titre abrégé: Parasit Vectors
Pays: England
ID NLM: 101462774
Informations de publication
Date de publication:
05 Sep 2019
05 Sep 2019
Historique:
received:
23
05
2019
accepted:
28
08
2019
entrez:
7
9
2019
pubmed:
7
9
2019
medline:
6
2
2020
Statut:
epublish
Résumé
Over 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. We 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. Our 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. Fuzzy 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.
Sections du résumé
BACKGROUND
BACKGROUND
Over 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.
METHODS
METHODS
We 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.
RESULTS
RESULTS
Our 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.
CONCLUSIONS
CONCLUSIONS
Fuzzy 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.
Identifiants
pubmed: 31488198
doi: 10.1186/s13071-019-3691-5
pii: 10.1186/s13071-019-3691-5
pmc: PMC6727500
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
428Références
J Med Entomol. 2009 Jan;46(1):33-41
pubmed: 19198515
PLoS Negl Trop Dis. 2012;6(8):e1760
pubmed: 22880140
Parasit Vectors. 2013 Dec 12;6:351
pubmed: 24330720
Environ Health Perspect. 2013 Nov-Dec;121(11-12):1264-72
pubmed: 24058050
Biometrics. 1977 Mar;33(1):159-74
pubmed: 843571
Parasit Vectors. 2015 Dec 01;8:610
pubmed: 26627473
Science. 1980 Jun 20;208(4450):1385-7
pubmed: 7375945
ScientificWorldJournal. 2014 Jan 21;2014:519710
pubmed: 24719577
Syst Biol. 2017 May 01;66(3):453-462
pubmed: 27616323
Mem Inst Oswaldo Cruz. 2008 Feb;103(1):66-74
pubmed: 18327504
Ecography. 2018 Sep;41(9):1411-1427
pubmed: 32313369
Science. 2002 Feb 15;295(5558):1245-8
pubmed: 11847328
Trends Microbiol. 2014 Mar;22(3):138-46
pubmed: 24468533
Nat Rev Microbiol. 2015 Apr;13(4):230-9
pubmed: 25730702
Ecohealth. 2012 Dec;9(4):448-54
pubmed: 23408100
Elife. 2015 Jun 30;4:e08347
pubmed: 26126267
Nature. 2013 Apr 25;496(7446):504-7
pubmed: 23563266
Naturwissenschaften. 2012 Jul;99(7):515-22
pubmed: 22660474
Philos Trans R Soc Lond B Biol Sci. 2015 Apr 5;370(1665):
pubmed: 25688023
Am J Trop Med Hyg. 2012 Oct;87(4):584-93
pubmed: 23042846
Indian J Med Res. 2015 Dec;142 Suppl:S79-86
pubmed: 26905247
Parasit Vectors. 2013 Nov 06;6(1):321
pubmed: 24499530
PLoS One. 2015 Aug 10;10(8):e0135489
pubmed: 26258684
Trop Med Int Health. 2015 Jan;20(1):77-88
pubmed: 25328988
Parasit Vectors. 2014 Jul 22;7:338
pubmed: 25052008
Sci Data. 2015 Jul 07;2:150035
pubmed: 26175912
J Infect Dis. 2017 Dec 16;216(suppl_10):S860-S867
pubmed: 29267917
Comp Immunol Microbiol Infect Dis. 2004 Sep;27(5):319-30
pubmed: 15225982
Ecohealth. 2014 Sep;11(3):420-8
pubmed: 24643859
J Infect Dis. 2016 Dec 15;214(suppl 5):S436-S440
pubmed: 27920169
Trends Microbiol. 2002 Feb;10(2):100-3
pubmed: 11827812
Sci Transl Med. 2015 Mar 18;7(279):279ra37
pubmed: 25787763
Evolution. 2014 Feb;68(2):514-25
pubmed: 24111703