Forecasting Modeling Studies For Predicting New Leprosy Cases: Protocol For A Scoping Review

Abstract Background: Leprosy is a neglected tropical disease caused by Mycobacterium leprae that mainly affects the skin, the peripheral nerves, mucosa of the upper respiratory tract, and the eyes. Mathematical models and statistical methodology could have a role to play in decision-making for maintaining the gains in elimination programs. Diverse forecasting modeling studies of leprosy cases have been reported in the literature, but there are distinct approaches and settings for predicting the cases being proposed. The purpose of this study is to complete a scoping review to identify and synthesize forecasting modeling studies of leprosy cases. Methods: A scoping review methodology will be applied following the Joanna Briggs Institute methodology for scoping reviews and will be reported according to PRISMA-ScR. We will perform a systematic search from inception until June 2021 and we will include the following electronic databases: MEDLINE via PubMed, Embase, Cochrane Library, and Lilacs. Data will be extracted and recorded on a calibrated predefined data form and will be presented in a tabular form accompanied by a descriptive summary. The Prediction model study Risk of Bias Assessment Tool (PROBAST) will be used. Discussion: This scoping review will identify and map the methodological characteristics and further evidence from modeling studies for predicting leprosy cases. Thereby contributing to a scientific basis for researchers to inform, design, and conduct appropriate models for predicting cases of leprosy. This information could be used to enhance national surveillance systems and to target specific policies. Systematic review registration: This scoping review was registered in the Open Science Framework (https://doi.org/10.17605/OSF.IO/W9375).