One of the main challenges in rare diseases is the unavailability of reliable estimates of prevalence and incidence. The lack of epidemiological data makes planning for therapeutic and management options challenging. Methods for estimating the prevalence and incidence of rare and genetic diseases primarily rely on the availability of accurate national patient registries or databases of birth defects. This gap is wider in Low- and Middle-Income countries (LMICs) such as India, where currently, the estimates of prevalence and incidence are either unknown or data from developed countries have to be used as a proxy. Here, we analyzed the current methods used to estimate the prevalence and incidence of rare genetic diseases to provide recommendations in the form of a decision tree to select the most feasible method, particularly in resource-constrained environments such as India. We selected ten rare diseases of shared importance to the Indo US Organization for Rare Diseases (IndoUSrare) and its Patients Alliance members for analysis. Our analysis suggests that retrospective study designs are the most commonly used method to estimate the prevalence and incidence of rare diseases. We propose a generalized decision tree or flowchart to aid epidemiology researchers during the selection of methods for estimating the prevalence and incidence of a rare or genetic disease.
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