Pakdad Kamran, Hanafi-Bojd Ahmad Ali, Vatandoost Hassan, Sedaghat Mohammad Mehdi, Raeisi Ahmad, Moghaddam Abdolreza Salahi, Foroushani Abbas Rahimi
Department of Medical Entomology & Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran; Department of Parasitology and Mycology, Paramedical School, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Department of Medical Entomology & Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran; Department of Environmental Chemical Pollutants and Pesticides, Institute for Environmental Research, Tehran University of Medical Sciences, Tehran, Iran.
Acta Trop. 2017 May;169:93-99. doi: 10.1016/j.actatropica.2017.02.004. Epub 2017 Feb 7.
Malaria is considered as a major public health problem in southern areas of Iran. The goal of this study was to predict best ecological niches of three main malaria vectors of Iran: Anopheles stephensi, Anopheles culicifacies s.l. and Anopheles fluviatilis s.l. A databank was created which included all published data about Anopheles species of Iran from 1961 to 2015. The suitable environmental niches for the three above mentioned Anopheles species were predicted using maximum entropy model (MaxEnt). AUC (area under Roc curve) values were 0.943, 0.974 and 0.956 for An. stephensi, An. culicifacies s.l. and An. fluviatilis s.l respectively, which are considered as high potential power of model in the prediction of species niches. The biggest bioclimatic contributor for An. stephensi and An. fluviatilis s.l. was bio 15 (precipitation seasonality), 25.5% and 36.1% respectively, followed by bio 1 (annual mean temperature), 20.8% for An. stephensi and bio 4 (temperature seasonality) with 49.4% contribution for An. culicifacies s.l. This is the first step in the mapping of the country's malaria vectors. Hence, future weather situation can change the dispersal maps of Anopheles. Iran is under elimination phase of malaria, so that such spatio-temporal studies are essential and could provide guideline for decision makers for IVM strategies in problematic areas.
疟疾被视为伊朗南部地区的一个主要公共卫生问题。本研究的目的是预测伊朗三种主要疟疾传播媒介的最佳生态位：斯氏按蚊、嗜人按蚊复合组和溪流按蚊复合组。创建了一个数据库，其中包含1961年至2015年期间所有已发表的关于伊朗按蚊种类的数据。使用最大熵模型（MaxEnt）预测上述三种按蚊的适宜环境生态位。斯氏按蚊、嗜人按蚊复合组和溪流按蚊复合组的AUC（Roc曲线下面积）值分别为0.943、0.974和0.956，这被认为该模型在预测物种生态位方面具有很高的潜力。对斯氏按蚊和溪流按蚊复合组影响最大的生物气候因素是生物15（降水季节性），分别为25.5%和36.1%，其次是生物1（年平均温度），对斯氏按蚊的影响为20.8%，而对嗜人按蚊复合组影响最大的是生物4（温度季节性），贡献率为49.4%。这是绘制该国疟疾传播媒介分布图的第一步。因此，未来的天气情况可能会改变按蚊的分布地图。伊朗正处于疟疾消除阶段，因此这种时空研究至关重要，可为问题地区的病媒综合管理策略的决策者提供指导。
