Laura Andrea Barrero Guevara, Sarah C. Kramer, Tobias Kurth, Matthieu Domenech de Cellès
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Causal inference concepts can guide research into the effects of climate on infectious diseases
A pressing question resulting from global warming is how climate change will affect infectious diseases. Answering this question requires research into the effects of weather on the population dynamics of transmission and infection; elucidating these effects, however, has proved difficult due to the challenges of assessing causality from the predominantly observational data available in epidemiological research. Here we show how concepts from causal inference—the sub-field of statistics aiming at inferring causality from data—can guide that research. Through a series of case studies, we illustrate how such concepts can help assess study design and strategically choose a study’s location, evaluate and reduce the risk of bias, and interpret the multifaceted effects of meteorological variables on transmission. More broadly, we argue that interdisciplinary approaches based on explicit causal frameworks are crucial for reliably estimating the effect of weather and accurately predicting the consequences of climate change.
Nature ecology & evolutionAgricultural and Biological Sciences-Ecology, Evolution, Behavior and Systematics
CiteScore
22.20
自引率
2.40%
发文量
282
期刊介绍:
Nature Ecology & Evolution is interested in the full spectrum of ecological and evolutionary biology, encompassing approaches at the molecular, organismal, population, community and ecosystem levels, as well as relevant parts of the social sciences. Nature Ecology & Evolution provides a place where all researchers and policymakers interested in all aspects of life's diversity can come together to learn about the most accomplished and significant advances in the field and to discuss topical issues. An online-only monthly journal, our broad scope ensures that the research published reaches the widest possible audience of scientists.