The Impact of Climate Change on Vaccine-Preventable Diseases: Insights From Current Research and New Directions

Abstract

Purpose of review: Vaccine-preventable diseases remain a major public health concern globally. Climate is a key driver of the dynamics of many infectious diseases, including those that are vaccine preventable. Understanding the impact of climate change on vaccine-preventable diseases is, thus, an important public health research priority. Here, we summarize the recent literature and highlight promising directions for future research.

Recent findings: Vaccine-preventable enteric diseases, such as cholera, exhibit sensitivity to precipitation and flooding events. The predicted increase in extreme weather events as a result of climate change could exacerbate outbreaks of these pathogens. For airborne pathogens, temperature and specific humidity have been shown to be the most important environmental drivers, although the impact of climate change on disease burden and dynamics remains unclear. Finally, the transmission dynamics of vector-borne diseases are dependent on both temperature and precipitation, and climate change is expected to alter the burden and geographic range of these diseases. However, understanding the interacting effects of multiple factors, including socioeconomic and ecological factors, on the vector-borne disease ecosystem will be a crucial step towards forecasting disease burden under climate change. Recent work has demonstrated associations between climate and transmission of vaccine-preventable diseases. Translating these findings into forecasts under various climate change scenarios will require mechanistic frameworks that account for both intrinsic and extrinsic drivers of transmission, and the non-linear effects on disease burden. Future research should also pay greater attention to uncertainty in both the climate modeling processes as well as disease outcomes in the context of vaccine-preventable diseases.

Keywords: Climate change; Environment; Modeling; Vaccine-preventable diseases.

Fig. 1

Top panel: maps show the CMIP6 multi-model mean projected change in temperature (ΔT) and precipitation (ΔP) in 2100 relative to 2000 under the Shared Socioeconomic Pathway (SSP) 3 “middle of the road” scenario, generated using Worldclim data [6]. Bottom panel: plot shows a summary of climate drivers (temperature or precipitation) for different vaccine-preventable diseases and the “best case” modeling effort reviewed, where we assume the best case is a fully mechanistic model using projection data. Absolute humidity drivers are counted under temperature-driven given the functional dependence of the two variables