The effect of natural climate variability on future vector-borne disease suitability: A mathematical modelling study
TL;DR
It is demonstrated that NCV should be routinely incorporated into climate-sensitive epidemiological projections, and a key output of this research is the provision of a methodological framework for this.
Abstract
Climate factors such as temperature and rainfall influence vector-borne disease dynamics. Consequently, climate change is affecting the global distribution of diseases such as dengue. Natural climate variability (NCV), which adds noise to the climate signal, alters the future climate trajectory, but is rarely analysed in climate-health analyses. In this study, extending a published model of climate suitability for Ae. aegypti , we consider a climate-sensitive dengue transmission model. Using 100 climate projections up to 2100 from the Community Earth System Model (a climate model including climate change and NCV), each run under the same shared socioeconomic pathway scenario, we generate 100 equally plausible simulations of the future basic reproduction number of dengue globally and the population at risk. We quantify the difference in transmission suitability between the most-suitable and least-suitable projections (i.e., uncertainty due to NCV) and demonstrate that NCV affects future suitability for transmission, dominating epidemiological parameter uncertainty in many locations. While the global population at risk from dengue (and, as we show, other vector-borne diseases) is expected to increase, NCV affects its precise value. Our findings demonstrate that NCV should be routinely incorporated into climate-sensitive epidemiological projections, and a key output of our research is the provision of a methodological framework for this. Accounting for NCV will enable public health policy decisions to be informed by the range of possible future outcomes.