Long Covid: conceptualizing the challenges for public health

Background Long Covid has caused significant disruption to public services, economies and population health worldwide, but no single public health approach has proven effective in its management. This essay was the winning entry for the Faculty of Public Health's Sir John Brotherston Prize 2022. Methods In this essay, I synthesize existing literature on public health policy in long Covid, and discuss the challenges and opportunities posed by long Covid for the public health profession. The utility of specialist clinics and community care, in the UK and internationally, is examined, as well as key outstanding issues relating to evidence generation, health inequality and defining long Covid. I then use this information to inform a simple conceptual model. Results The generated conceptual model integrates community- and population-level interventions; key areas of identified policy need at both levels include ensuring equitable access to long Covid care, developing screening programmes for high-risk populations, co-production of research and clinical services with patients, and using interventions to generate evidence. Conclusions Significant challenges remain in the management of long Covid from a public health policy perspective. Multidisciplinary community-level and population-level interventions should be employed with a view to achieving an equitable and scalable model of care.

Automated summary

Long Covid has had a significant impact on public services, economies, and population health worldwide, but there is no proven effective public health approach for its management. This essay synthesizes existing literature on public health policy in long Covid and discusses the challenges and opportunities it presents for the public health profession. The essay examines the utility of specialist clinics and community care, as well as outstanding issues related to evidence generation, health inequality, and defining long Covid, and proposes a conceptual model based on this information.