Carvalho B M, Rangel E F, Vale M M
Laboratório de Vertebrados,Instituto de Biologia,Universidade Federal do Rio de Janeiro,Rio de Janeiro,Brazil.
Laboratório Interdisciplinar de Vigilância Entomológica em Diptera e Hemiptera, Instituto Oswaldo Cruz,Fundação Oswaldo Cruz,Rio de Janeiro,Brazil.
Bull Entomol Res. 2017 Aug;107(4):419-430. doi: 10.1017/S0007485316001097. Epub 2016 Dec 15.
Vector-borne diseases are exceptionally sensitive to climate change. Predicting vector occurrence in specific regions is a challenge that disease control programs must meet in order to plan and execute control interventions and climate change adaptation measures. Recently, an increasing number of scientific articles have applied ecological niche modelling (ENM) to study medically important insects and ticks. With a myriad of available methods, it is challenging to interpret their results. Here we review the future projections of disease vectors produced by ENM, and assess their trends and limitations. Tropical regions are currently occupied by many vector species; but future projections indicate poleward expansions of suitable climates for their occurrence and, therefore, entomological surveillance must be continuously done in areas projected to become suitable. The most commonly applied methods were the maximum entropy algorithm, generalized linear models, the genetic algorithm for rule set prediction, and discriminant analysis. Lack of consideration of the full-known current distribution of the target species on models with future projections has led to questionable predictions. We conclude that there is no ideal 'gold standard' method to model vector distributions; researchers are encouraged to test different methods for the same data. Such practice is becoming common in the field of ENM, but still lags behind in studies of disease vectors.
媒介传播疾病对气候变化异常敏感。预测特定区域内病媒的出现情况是疾病防控项目为规划和实施防控干预措施及气候变化适应措施而必须应对的一项挑战。最近,越来越多的科学文章应用生态位建模(ENM)来研究具有医学重要性的昆虫和蜱虫。由于有大量可用方法,解读其结果具有挑战性。在此,我们综述了由ENM得出的病媒未来预测,并评估其趋势和局限性。热带地区目前有许多病媒物种;但未来预测表明,适合它们出现的气候将向两极扩展,因此,在预计将变得适宜的地区必须持续开展昆虫学监测。最常用的方法是最大熵算法、广义线性模型、规则集预测遗传算法和判别分析。在对未来预测的模型中未考虑目标物种已知的当前完整分布情况,导致预测结果存疑。我们得出结论,不存在用于模拟病媒分布的理想“金标准”方法;鼓励研究人员针对相同数据测试不同方法。这种做法在ENM领域正变得普遍,但在病媒研究中仍较为滞后。