Department of Entomology, Center for Infectious Disease Dynamics, Penn State University, University Park, PA 16802, USA.
Proc Natl Acad Sci U S A. 2010 Aug 24;107(34):15135-9. doi: 10.1073/pnas.1006422107. Epub 2010 Aug 9.
Malaria transmission is strongly influenced by environmental temperature, but the biological drivers remain poorly quantified. Most studies analyzing malaria-temperature relations, including those investigating malaria risk and the possible impacts of climate change, are based solely on mean temperatures and extrapolate from functions determined under unrealistic laboratory conditions. Here, we present empirical evidence to show that, in addition to mean temperatures, daily fluctuations in temperature affect parasite infection, the rate of parasite development, and the essential elements of mosquito biology that combine to determine malaria transmission intensity. In general, we find that, compared with rates at equivalent constant mean temperatures, temperature fluctuation around low mean temperatures acts to speed up rate processes, whereas fluctuation around high mean temperatures acts to slow processes down. At the extremes (conditions representative of the fringes of malaria transmission, where range expansions or contractions will occur), fluctuation makes transmission possible at lower mean temperatures than currently predicted and can potentially block transmission at higher mean temperatures. If we are to optimize control efforts and develop appropriate adaptation or mitigation strategies for future climates, we need to incorporate into predictive models the effects of daily temperature variation and how that variation is altered by climate change.
疟疾传播受到环境温度的强烈影响，但生物学驱动因素仍未得到充分量化。大多数分析疟疾-温度关系的研究，包括那些调查疟疾风险和气候变化可能影响的研究，都仅基于平均温度，并根据在不现实的实验室条件下确定的函数进行推断。在这里，我们提供了实证证据，表明除了平均温度外，温度的日常波动还会影响寄生虫感染、寄生虫发育速度以及蚊子生物学的基本要素，这些因素共同决定了疟疾传播的强度。总的来说，我们发现与等效恒定平均温度下的速度相比，低温下的温度波动会加速速度过程，而高温下的温度波动则会减缓速度过程。在极端情况下（代表疟疾传播边缘的条件，在这些条件下，范围会扩大或收缩），波动使得在比目前预测的更低的平均温度下传播成为可能，并且在更高的平均温度下可能会阻止传播。如果我们要优化控制工作并为未来气候制定适当的适应或缓解策略，我们需要将每日温度变化的影响以及气候变化如何改变这种变化纳入预测模型中。
