Mahmud Ayesha S, Martinez Pamela P, Baker Rachel E
Department of Demography, University of California, Berkeley, Berkeley, CA, USA.
Department of Microbiology, University of Illinois Urbana-Champaign, Champaign, IL, USA.
PNAS Nexus. 2023 Sep 19;2(9):pgad307. doi: 10.1093/pnasnexus/pgad307. eCollection 2023 Sep.
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.
尽管在温带地区的高收入环境中对流感的驱动因素已有充分研究,但在热带地区,关于流感的负担、季节性以及流感动态的驱动因素仍存在许多未解决的问题。在温带气候中,比湿与传播之间的反比关系可以解释流感爆发所观察到的许多时间和空间模式。然而,这种关系无法解释热带和亚热带国家的季节性或缺乏季节性的情况。在此,我们分析了来自孟加拉国12个地点的八年流感监测数据,以量化气候在一个有明显雨季的热带环境中对疾病动态的驱动作用。我们发现有力证据表明,在孟加拉国,比湿与流感传播之间存在非线性双峰关系,在相对较低和较高的比湿值时传播率最高。我们使用一个湿度与传播之间呈双峰关系且在非常高的温度下传播率降低的数学模型,同时考虑人群免疫力的变化,模拟了孟加拉国当前和未来气候下的流感负担。这个由气候驱动的机制模型能够准确捕捉孟加拉国各地观察到的流感活动的时间和空间变化,突出了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以及公共卫生后果。