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通过生态代谢理论预测疾病传播的热学和异速生长依赖性。

Predicting the Thermal and Allometric Dependencies of Disease Transmission via the Metabolic Theory of Ecology.

出版信息

Am Nat. 2019 May;193(5):661-676. doi: 10.1086/702846. Epub 2019 Apr 4.

Abstract

The metabolic theory of ecology (MTE) provides a general framework of allometric and thermal dependence that may be useful for predicting how climate change will affect disease spread. Using and a microsporidian gut parasite, we conducted two experiments across a wide thermal range and fitted transmission models that utilize MTE submodels for transmission parameters. We decomposed transmission into contact rate and probability of infection and further decomposed probability of infection into a product of gut residence time (GRT) and per-parasite infection rate of gut cells. Contact rate generally increased with temperature and scaled positively with body size, whereas infection rate had a narrow hump-shaped thermal response and scaled negatively with body size. GRT increased with host size and was longest at extreme temperatures. GRT and infection rate inside the gut combined to create a 3.5 times higher probability of infection for the smallest relative to the largest individuals. Small temperature changes caused large differences in transmission. We also fit several alternative transmission models to data at individual temperatures. The more complex models-parasite antagonism or synergism and host heterogeneity-did not substantially improve the fit to the data. Our results show that transmission rate is the product of several distinct thermal and allometric functions that can be predicted continuously across temperature and host size using the MTE.

摘要

生态代谢理论(MTE)提供了一种能够预测气候变化如何影响疾病传播的种间关系和热依赖性的通用框架。我们使用和一种微孢子虫肠道寄生虫,在广泛的温度范围内进行了两项实验,并拟合了利用 MTE 子模型的传输模型来描述传输参数。我们将传播分解为接触率和感染概率,进一步将感染概率分解为肠道停留时间(GRT)和肠道细胞每寄生虫感染率的乘积。接触率通常随温度升高而增加,并与体型呈正相关,而感染率的热响应呈狭窄的驼峰形,与体型呈负相关。GRT 随宿主体型增大而增加,在极端温度下最长。GRT 和肠道内的感染率相结合,使得最小个体相对于最大个体的感染概率增加了 3.5 倍。微小的温度变化会导致传播产生巨大差异。我们还拟合了几个替代的传输模型,以适应个体温度下的数据。更复杂的模型——寄生虫拮抗或协同作用和宿主异质性——并没有显著提高对数据的拟合程度。我们的研究结果表明,传播率是几个不同的热和种间关系函数的产物,可以使用 MTE 连续预测在温度和宿主体型范围内的传播率。

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