Climate change is postulated to alter the distribution and abundance of species which serve as vectors for pathogens and is thus expected to affect the transmission of infectious, vector-borne diseases such as malaria. The ability to project and therefore, to mitigate the risk of potential expansion of infectious diseases requires an understanding of how vectors respond to environmental change. Here, we used an extensive dataset on the distribution of the mosquito Anopheles sacharovi, a vector of malaria parasites in Greece, southeast Europe, to build a modeling framework that allowed us to project the potential species range within the next decades. In order to account for model uncertainty, we employed a multi-model approach, combining an ensemble of diverse correlative niche models and a mechanistic model to project the potential expansion of species distribution and to delineate hotspots of potential malaria risk areas. The performance of the models was evaluated using official records on autochthonous malaria incidents. Our projections demonstrated a gradual increase in the potential range of the vector distribution and thus, in the malaria receptive areas over time. Linking the model outputs with human population inhabiting the study region, we found that population at risk increases, relative to the baseline period. The methodological framework proposed and applied here, offers a solid basis for a climate change impact assessment on malaria risk, facilitating informed decision making at national and regional scales.

中文翻译：

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气候变化导致疟疾病媒分布的预计变化

据推测，气候变化会改变作为病原体载体的物种的分布和丰度，因此预计会影响疟疾等传染性、媒介传播疾病的传播。预测并因此减轻传染病潜在扩张风险的能力需要了解媒介如何应对环境变化。在这里，我们使用了关于蚊子 Anopheles sacharovi 分布的广泛数据集，该数据集是欧洲东南部希腊疟疾寄生虫的载体，构建了一个建模框架，使我们能够预测未来几十年的潜在物种范围。为了考虑模型的不确定性，我们采用了多模型方法，结合各种相关生态位模型和机械模型的集合，以预测物种分布的潜在扩展并描绘潜在疟疾风险区域的热点。使用本地疟疾事件的官方记录评估模型的性能。我们的预测表明，随着时间的推移，病媒分布的潜在范围逐渐增加，因此在疟疾接收区。将模型输出与居住在研究区域的人口联系起来，我们发现风险人口相对于基线期增加。这里提出和应用的方法框架为气候变化对疟疾风险的影响评估提供了坚实的基础，促进了国家和区域范围内的知情决策。