BackgroundEstimating scabies prevalence in communities is crucial for identifying the communities with high scabies prevalence and guiding interventions. There is no standardisation of sampling strategies to estimate scabies prevalence in communities, and a wide range of sampling sizes and methods have been used. The World Health Organization recommends household sampling or, as an alternative, school sampling to estimate community-level prevalence. Due to varying prevalence across populations, there is a need to understand how sampling strategies for estimating scabies prevalence interact with scabies epidemiology to affect accuracy of prevalence estimates.MethodsWe used a simulation-based approach to compare the efficacy of different sampling methods and sizes. First, we generate synthetic populations with Australian Indigenous communities’ characteristics and then, assign a scabies status to individuals to achieve a specified prevalence using different assumptions about scabies epidemiology. Second, we calculate an observed prevalence for different sampling methods and sizes.ResultsThe distribution of prevalence in population groups can vary substantially when the underlying scabies assignment method changes. Across all of the scabies assignment methods combined, the simple random sampling method produces the narrowest 95% confidence interval for all sampling percentages. The household sampling method introduces higher variance compared to simple random sampling when the assignment of scabies includes a household-specific component. The school sampling method overestimates community prevalence when the assignment of scabies includes an age-specific component.DiscussionOur results indicate that there are interactions between transmission assumptions and surveillance strategies, emphasizing the need for understanding scabies transmission dynamics. We suggest using the simple random sampling method for estimating scabies prevalence. Our approach can be adapted to various populations and diseases.Author summaryScabies is a parasitic infestation that is commonly observed in underprivileged populations. A wide range of sampling sizes and methods have been used to estimate scabies prevalence. With differing key drivers of transmission and varying prevalence across populations, it can be challenging to determine an effective sampling strategy. In this study, we propose a simulation approach to compare the efficacy of different sampling methods and sizes. First, we generate synthetic populations and then assign a scabies status to individuals to achieve a specified prevalence using different assumptions about scabies epidemiology. Second, we calculate an observed prevalence for different sampling methods and sizes. Our results indicate that there are interactions between transmission assumptions and surveillance strategies. We suggest using the simple random sampling method for estimating prevalence as it produces the narrowest 95% confidence interval for all sampling sizes. We propose guidelines for determining a sample size to achieve a desired level of precision in 95 out 100 samples, given estimates of the population size and a priori estimates of true prevalence. Our approach can be adapted to various populations, informing an appropriate sampling strategy for estimating scabies prevalence with confidence.