Max Planck Institute for Infection Biology’s Post

I am happy to share our latest paper, “Causal inference concepts can guide research into the effects of climate on infectious diseases,” published yesterday in Nature Ecology & Evolution. A project led by Laura Andrea Barrero Guevara, an outstanding PhD student in my lab, in collaboration with Sarah Kramer and Tobias Kurth. An important question arising from global warming is how climate change will impact the spread of infectious diseases. To make such predictions, it is essential to understand how weather influences these diseases, usually through the analysis of observational data. However, analyzing such data can be perilous, as observational studies may misinterpret causes—a problem commonly referred to as “association does not imply causation.” What can we do? In this paper, we argue that concepts from causal inference can help. We illustrate this by presenting a series of brief case studies based on a simple mathematical model capturing the causal relationships between weather, transmission, and disease. We demonstrate how causal concepts—such as confounders, descendants, and mediators—can guide research in various ways. This includes evaluating study designs, selecting study locations, and interpreting the multifaceted effects of weather on disease transmission. More broadly, we argue that interdisciplinary approaches using explicit causal frameworks will be crucial for predicting the consequences of climate change on infectious diseases. https://lnkd.in/dZC2uYBC