Spatio-temporal Prediction of the Malaria Transmission Risk in Minab District (Hormozgan Province, Southern Iran)

被引:4
|
作者
Salahi-Moghaddam, Abdolreza [1 ]
Turki, Habibollah [1 ]
Yeryan, Masoud [2 ]
Fuentes, Marius, V [3 ]
机构
[1] Hormozgan Univ Med Sci, Infect & Trop Dis Res Ctr, Hormozgan Hlth Inst, Bandar Abbas, Hormozgan, Iran
[2] Minab Hlth Ctr, Malaria Vector Unit, 17th Sharivar Ave, Minab, Hormozgan, Iran
[3] Univ Valencia, Fac Farm, Dept Farm & Tecnol Farmaceut & Parasitol, Parasites & Hlth Res Grp, Av Vicent Andres Estelles S-N, Valencia 46100, Spain
关键词
Anopheline larvae; Environmental risk; GIS; Hormozgan province; Iran; Malaria; ANOPHELES-STEPHENSI; SITUATION ANALYSIS; LARVAL HABITATS; ENDEMIC AREA; STRATIFICATION; VECTORS;
D O I
10.1007/s11686-022-00598-2
中图分类号
R38 [医学寄生虫学]; Q [生物科学];
学科分类号
07 ; 0710 ; 09 ; 100103 ;
摘要
Introduction Malaria is the most important parasitic disease in tropical and subtropical regions, with more than 240 million cases reported annually. In Iran, indigenous cases occur in its south-eastern region. The aim of this study is to assess the environmental risk of malaria transmission in an endemic area of southern Iran. Methods The study was carried out in Minab district (Hormozgan province, southern Iran), with the aim to assess the environmental risk of malaria, based on a spatio-temporal study, using Growing Degree Days (GDD)-based predictions, larval habitat ecology, MaxEnt spatial predictions and malaria transmission data. Results The Gradient Model Risk index showed the highest malaria transmission risk period to be during January-April and October-December. The ecological conditions of water bodies of larval habitats of the four vector species (Anopheles culicifacies, A. dthali, A. fluviatilis and A. stephensi) were assessed, with A. stephensi being the most prevalent and the most widely distributed species. Conclusion These findings, together with the MaxEnt Anopheles predictive distribution models, allowed identifying villages in danger of malaria transmission in Minab district. This spatio-temporal prediction of malaria transmission risk should be incorporated in the design of malaria control initiatives towards a local malaria early warning system. Moreover, the proposed transmission risk model can be extrapolated, at local scale, to other malaria endemic areas of tropical and subtropical regions.
引用
收藏
页码:1500 / 1513
页数:14
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