Better data for better public health decision-making: perspectives on quantifying the intended and unintended impacts...

Public services such as healthcare, schools, and transport constitute the infrastructure essential for a functioning and productive society. These services may undergo planned modifications because of interventions intended to manage societal challenges, or experience unplanned disruptions resulting from external shocks. For instance, schools might be closed to mitigate the spread of an infectious disease, or when an external shock, such as a heatwave, renders their continued operation infeasible. These modifications to public services, whether planned or unplanned, have both intended and unintended public health outcomes, as well as wider and longer-term societal consequences. To improve our response to various societal challenges, it is essential to assess the relation between the extent of modifications and the intended outcomes, and identify the full spectrum of unintended consequences, both beneficial and adverse. A central pillar of such an exercise would be timely and granular data on the modifications and outcomes - what was done, what happened, to whom, where, and when? However, these data are rarely, if ever, systematically collected. Instead, research into the evaluation of public service modifications relies on sporadic and bespoke data collection. In this perspective, we highlight a critical data gap in tracking public service availability, adaptations, and interventions, illustrating our arguments through two case studies. We examine the challenges in collecting and integrating such data and propose practical solutions to improve data infrastructure and cross-sectoral coordination.