University of Brescia, Medical School, Department of Biomedical Sciences and Biotechnologies, Viale Europa 11, I-25123 Brescia, Italy.
Malar J. 2011 Oct 10;10:294. doi: 10.1186/1475-2875-10-294.
Mechanistic models play an important role in many biological disciplines, and they can effectively contribute to evaluate the spatial-temporal evolution of mosquito populations, in the light of the increasing knowledge of the crucial driving role on vector dynamics played by meteo-climatic features as well as other physical-biological characteristics of the landscape.
In malaria eco-epidemiology landscape components (atmosphere, water bodies, land use) interact with the epidemiological system (interacting populations of vector, human, and parasite). In the background of the eco-epidemiological approach, a mosquito population model is here proposed to evaluate the sensitivity of An. gambiae s.s. population to some peculiar thermal-pluviometric scenarios. The scenarios are obtained perturbing meteorological time series data referred to four Kenyan sites (Nairobi, Nyabondo, Kibwesi, and Malindi) representing four different eco-epidemiological settings.
Simulations highlight a strong dependence of mosquito population abundance on temperature variation with well-defined site-specific patterns. The upper extreme of thermal perturbation interval (+ 3°C) gives rise to an increase in adult population abundance at Nairobi (+111%) and Nyabondo (+61%), and a decrease at Kibwezi (-2%) and Malindi (-36%). At the lower extreme perturbation (-3°C) is observed a reduction in both immature and adult mosquito population in three sites (Nairobi -74%, Nyabondo -66%, Kibwezi -39%), and an increase in Malindi (+11%). A coherent non-linear pattern of population variation emerges. The maximum rate of variation is +30% population abundance for +1°C of temperature change, but also almost null and negative values are obtained. Mosquitoes are less sensitive to rainfall and both adults and immature populations display a positive quasi-linear response pattern to rainfall variation.
The non-linear temperature-dependent response is in agreement with the non-linear patterns of temperature-response of the basic bio-demographic processes. This non-linearity makes the hypothesized biological amplification of temperature effects valid only for a limited range of temperatures. As a consequence, no simple extrapolations can be done linking temperature rise with increase in mosquito distribution and abundance, and projections of An. gambiae s.s. populations should be produced only in the light of the local meteo-climatic features as well as other physical and biological characteristics of the landscape.
机制模型在许多生物学学科中发挥着重要作用，它们可以有效地帮助评估蚊子种群的时空演变，因为人们越来越了解气象气候特征以及景观的其他物理生物学特征对媒介动态的关键驱动作用。
在疟疾生态流行病学景观成分（大气、水体、土地利用）与流行病学系统（媒介、人类和寄生虫相互作用的种群）相互作用的背景下，本文提出了一个蚊子种群模型，以评估冈比亚按蚊种群对一些特殊热雨情景的敏感性。通过扰动四个肯尼亚地点（内罗毕、尼亚邦多、基布韦西和马林迪）的气象时间序列数据，得到了这些情景。这四个地点代表了四个不同的生态流行病学环境。
模拟结果表明，蚊子种群数量与温度变化有很强的依赖性，具有明确的特定地点模式。热扰区间的上限（+3°C）导致内罗毕（+111%）和尼亚邦多（+61%）的成虫种群数量增加，而基布韦西（-2%）和马林迪（-36%）的成虫种群数量减少。在扰动量下限（-3°C）下，三个地点的未成熟和成虫蚊子种群数量都减少（内罗毕-74%，尼亚邦多-66%，基布韦西-39%），马林迪增加（+11%）。出现了种群变化的一致非线性格式。温度变化 1°C 时，种群数量的最大变化率为+30%，但也得到了接近零和负值。蚊子对降雨的敏感性较低，成虫和未成熟种群对降雨变化表现出正的准线性响应模式。
与基本生物人口统计学过程的温度响应非线性模式一致，温度依赖性的非线性响应表明温度效应的生物放大作用仅在有限的温度范围内有效。因此，不能简单地将温度升高与蚊子分布和数量的增加联系起来进行推断，只有根据当地的气象气候特征以及景观的其他物理和生物特征，才能对冈比亚按蚊种群进行预测。
