关键词: climate disease transmission influenza mathematical modeling

来  源:   DOI:10.1093/pnasnexus/pgad307   PDF(Pubmed)

Abstract:
Although the drivers of influenza have been well studied in high-income settings in temperate regions, many open questions remain about the burden, seasonality, and drivers of influenza dynamics in the tropics. In temperate climates, the inverse relationship between specific humidity and transmission can explain much of the observed temporal and spatial patterns of influenza outbreaks. Yet, this relationship fails to explain seasonality, or lack there-of, in tropical and subtropical countries. Here, we analyzed eight years of influenza surveillance data from 12 locations in Bangladesh to quantify the role of climate in driving disease dynamics in a tropical setting with a distinct rainy season. We find strong evidence for a nonlinear bimodal relationship between specific humidity and influenza transmission in Bangladesh, with highest transmission occurring for relatively low and high specific humidity values. We simulated influenza burden under current and future climate in Bangladesh using a mathematical model with a bimodal relationship between humidity and transmission, and decreased transmission at very high temperatures, while accounting for changes in population immunity. The climate-driven mechanistic model can accurately capture both the temporal and spatial variation in influenza activity observed across Bangladesh, highlighting the usefulness of mechanistic models for low-income countries with inadequate surveillance. By using climate model projections, we also highlight the potential impact of climate change on influenza dynamics in the tropics and the public health consequences.
摘要:
尽管在温带地区的高收入环境中已经对流感的驱动因素进行了充分的研究,关于负担仍然存在许多悬而未决的问题,季节性,以及热带地区流感动态的驱动因素。在温带气候下,特定湿度和传播之间的反向关系可以解释许多观察到的流感爆发的时间和空间模式。然而,这种关系无法解释季节性,或者缺乏,在热带和亚热带国家。这里,我们分析了孟加拉国12个地区8年的流感监测数据,以量化在雨季明显的热带地区气候在驱动疾病动态中的作用.我们发现强有力的证据表明,孟加拉国的特定湿度与流感传播之间存在非线性双峰关系,对于相对较低和较高的特定湿度值,具有最高的透射率。我们使用湿度和传播之间的双峰关系的数学模型模拟了孟加拉国当前和未来气候下的流感负担,在非常高的温度下减少了传播,同时考虑人群免疫力的变化。气候驱动的机制模型可以准确地捕获孟加拉国各地观察到的流感活动的时空变化,强调机制模型对监测不足的低收入国家的有用性。通过使用气候模型预测,我们还强调了气候变化对热带地区流感动态的潜在影响和公共卫生后果。
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