191 Natural experiments: A Nobel Prize awarded research design heavily on timelines. Studies evaluating policies or interventions that have already been implemented will rely on previously collected data. This may sound like a secure route to minimise unpredictability, but exploratory data analysis is needed to assess whether assumptions and other statistical requirements of the study design are met. Not rarely, evaluations are altered or discontinued if evaluation in a meaningful way is not possible as expected when the natural experiment was identified. To overcome these challenges, researchers should be involved in early phases of intervention and policy planning, ensuring that key requirements to conduct evaluations through natural experiments are not missed. Based on our experience, early career researchers with relatively short contracts may benefit from joining existing collaborations with the fundaments for evaluation already present. Furthermore, research environments need to accommodate the intrinsic uncertainty of these studies. Providing the incentives to swiftly react on societal changes that suddenly occur are key: additional data can often be collected now, or never. For example, quick and flexible sources of funding have become available over the past months to study the COVID-19 pandemic. Similar initiatives are needed to combat big global health challenges that have been around for a while, including the “obesity epidemic”, the persistence of social inequalities, and the climate crisis. Figure 1. Rotterdam, 2020. Natural experiments in cities allow evaluation of exposures that often cannot be randomised (Famke Mölenberg, personal collection, used with permission). 6
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