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DOI10.1007/s10393-018-1388-4
Predicting Yellow Fever Through Species Distribution Modeling of Virus, Vector, and Monkeys
de Almeida, Marco A. B.1,4; dos Santos, Edmilson1; Cardoso, Jader da C.1; da Silva, Lucas G.2; Rabelo, Rafael M.3; Bicca-Marques, Julio Cesar4
发表日期2019
ISSN1612-9202
EISSN1612-9210
卷号16期号:1页码:95-108
英文摘要

Mapping yellow fever (YF) risk is often based on place of infection of human cases, whereas the circulation between nonhuman primates (NHP) and vectors is neglected. In 2008/2009, YF devastated NHP at the southern limit of the disease in the Americas. In view of the recent expansion of YF in Brazil, we modeled the environmental suitability for YF with data from 2008/2009 epizootic, the distribution of NHP (Alouatta spp.), and the mosquito (Haemagogus leucocelaenus) using the maximum entropy algorithm (Maxent) to define risk areas for YF and their main environmental predictors. We evaluated points of occurrence of YF based on dates of confirmed deaths of NHP in three periods, from October 2008 to: December 2008, March 2009, and June 2009. Variables with greatest influence on suitability for YF were seasonality in water vapor pressure (36%), distribution of NHP (32%), maximum wind speed (11%), annual mean rainfall (7%), and maximum temperature in the warmest month (5%). Models of early periods of the epizootic identified suitability for YF in localities that recorded NHP deaths only months later, demonstrating usefulness of the approach for predicting the disease spread. Our data supported influence of rainfall, air humidity, and ambient temperature on the distribution of epizootics. Wind was highlighted as a predicting variable, probably due to its influence on the dispersal of vectors infected with YF in fragmented landscapes. Further studies on the role of wind are necessary to improve our understanding of the occurrence of YF and other arboviruses and their dispersal in the landscape.


WOS研究方向Biodiversity & Conservation ; Environmental Sciences & Ecology
来源期刊ECOHEALTH
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/93981
作者单位1.Secretaria Saude Estado Rio Grande do Sul, Ctr Estadual Vigilancia Saude, Div Vigilancia Ambiental Saude, Ave Ipiranga 5400 Sala 95, BR-90610030 Porto Alegre, RS, Brazil;
2.Univ Fed Rural Pernambuco, Recife, PE, Brazil;
3.Inst Nacl de Pesquisas da Amazonia, Manaus, Amazonas, Brazil;
4.Pontificia Univ Catolica Rio Grande do Sul, Escola Ciencias, Porto Alegre, RS, Brazil
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de Almeida, Marco A. B.,dos Santos, Edmilson,Cardoso, Jader da C.,et al. Predicting Yellow Fever Through Species Distribution Modeling of Virus, Vector, and Monkeys[J],2019,16(1):95-108.
APA de Almeida, Marco A. B.,dos Santos, Edmilson,Cardoso, Jader da C.,da Silva, Lucas G.,Rabelo, Rafael M.,&Bicca-Marques, Julio Cesar.(2019).Predicting Yellow Fever Through Species Distribution Modeling of Virus, Vector, and Monkeys.ECOHEALTH,16(1),95-108.
MLA de Almeida, Marco A. B.,et al."Predicting Yellow Fever Through Species Distribution Modeling of Virus, Vector, and Monkeys".ECOHEALTH 16.1(2019):95-108.
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