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Background Local authorities in England currently receive ring-fenced funding to provide essential public health and preventive services, known as the public health grant (PHG). However, the real value of this grant has decreased since 2015, with increased costs making it difficult for local authorities to sustain services to meet their population needs. The aim of this project was to explore the feasibility of generating agreed definitions of unmet need for the service areas covered by the PHG, as a first step to identifying potential data sources and methodologies for generating and monetizing estimates of unmet need.Methods A range of potential theoretical methods for defining ‘unmet need’ for different types of service were initially generated by the research team and then explored in interviews with public health staff at three local authorities (both unitary and upper tier). Data on PHG spending across the different categories of services (mandatory, non-mandatory and miscellaneous) and the decision-making processes for the allocation of the PHG locally were provided by two contrasting local authorities.Results A definition of unmet need as the gap between current provision and the level of provision required to meet current population needs led to the development of three potentially quantifiable measures of unmet need: 1. Current Provision versus Guidelines/Best Practice/Targets 2. Current Provision versus Prevalence 3. Current Provision versus Peak Provision.The first was considered the preferred method of estimating unmet need where evidence base guidelines were available. The second has been used effectively for determining need for drug and alcohol services but relies on availability of national and local prevalence data. The third was considered to be the least preferred option, and generates the most conservative estimate of need, given peak provision was not considered to have generally been sufficient to address need for services comprehensively. All three definitions can be supplemented by adjusting for changes in size of the relevant population, prevalence of risk factors or levels of needs for specific services.Conclusion Whilst the concept of quantifiable ‘unmet need’ in the context of prevention may be contested, it is potentially feasible to derive operational definitions of practical value in determining the allocation of funding and addressing inequalities. In the second phase of this project, additional data is being collected from local authorities and models developed for estimating unmet needs to inform national and local policy making and potentially to provide monetized estimates for the return on investment if unmet need is addressed.