The impact of current and future climates on spatiotemporal dynamics of influenza in a tropical setting

Ayesha S Mahmud; Pamela P Martinez; Rachel E Baker

doi:10.1093/pnasnexus/pgad307

The impact of current and future climates on spatiotemporal dynamics of influenza in a tropical setting

PNAS Nexus. 2023 Sep 19;2(9):pgad307. doi: 10.1093/pnasnexus/pgad307. eCollection 2023 Sep.

Authors

Ayesha S Mahmud¹, Pamela P Martinez^{2

3}, Rachel E Baker^{4

5}

Affiliations

¹ Department of Demography, University of California, Berkeley, Berkeley, CA, USA.
² Department of Microbiology, University of Illinois Urbana-Champaign, Champaign, IL, USA.
³ Department of Statistics, University of Illinois Urbana-Champaign, Champaign, IL, USA.
⁴ Department of Epidemiology, School of Public Health, Brown University, Providence, RI, USA.
⁵ Institute at Brown for Environment and Society, Brown University, Providence, RI, USA.

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.

Keywords: climate; disease transmission; influenza; mathematical modeling.