Ewing D A, Cobbold C A, Purse B V, Nunn M A, White S M
Centre for Ecology & Hydrology, Benson Lane, Wallingford, Oxfordshire OX10 8BB, UK; School of Mathematics and Statistics, College of Science and Engineering, University of Glasgow, Glasgow, United Kingdom.
School of Mathematics and Statistics, College of Science and Engineering, University of Glasgow, Glasgow, United Kingdom; The Boyd Orr Centre for Population and Ecosystem Health, University of Glasgow, Glasgow, UK.
J Theor Biol. 2016 Jul 7;400:65-79. doi: 10.1016/j.jtbi.2016.04.008. Epub 2016 Apr 13.
Mosquito-borne diseases cause substantial mortality and morbidity worldwide. These impacts are widely predicted to increase as temperatures warm and extreme precipitation events become more frequent, since mosquito biology and disease ecology are strongly linked to environmental conditions. However, direct evidence linking environmental change to changes in mosquito-borne disease is rare, and the ecological mechanisms that may underpin such changes are poorly understood. Environmental drivers, such as temperature, can have non-linear, opposing impacts on the demographic rates of different mosquito life cycle stages. As such, model frameworks that can deal with fluctuations in temperature explicitly are required to predict seasonal mosquito abundance, on which the intensity and persistence of disease transmission under different environmental scenarios depends. We present a novel, temperature-dependent, delay-differential equation model, which incorporates diapause and the differential effects of temperature on the duration and mortality of each life stage and demonstrates the sensitivity of seasonal abundance patterns to inter- and intra-annual changes in temperature. Likely changes in seasonal abundance and exposure to mosquitoes under projected changes in UK temperatures are presented, showing an increase in peak vector abundance with warming that potentially increases the risk of disease outbreaks.
蚊媒疾病在全球范围内造成了大量的死亡和发病。随着气温升高和极端降水事件愈发频繁,人们普遍预计这些影响将会加剧,因为蚊子的生物学特性和疾病生态学与环境条件密切相关。然而,将环境变化与蚊媒疾病变化联系起来的直接证据很少,而且对可能支撑此类变化的生态机制也知之甚少。温度等环境驱动因素可能会对不同蚊子生命周期阶段的种群统计学速率产生非线性的、相反的影响。因此,需要能够明确处理温度波动的模型框架来预测季节性蚊子数量,而不同环境情景下疾病传播的强度和持续性取决于此。我们提出了一个新的、依赖温度的延迟微分方程模型,该模型纳入了滞育以及温度对每个生命阶段持续时间和死亡率的不同影响,并证明了季节性数量模式对温度年际和年内变化的敏感性。本文展示了在英国预计的温度变化下,季节性蚊子数量和接触蚊子情况可能发生的变化,表明随着气候变暖,病媒数量峰值增加,这可能会增加疾病爆发的风险。