International Research Center, Hospital Alemão Oswaldo Cruz, Sao Paulo, Brazil.
The Disease Surveillance and Elimination Coordinating Committee, Department of Chronic Conditions and Sexually Transmitted Infections, Health Surveillance Secretariat, Ministry of Health, Brasília, Brazil.
BMJ Open. 2022 Jul 28;12(7):e062828. doi: 10.1136/bmjopen-2022-062828.
Leprosy is a neglected tropical disease caused by that mainly affects the skin, the peripheral nerves, the mucosa of the upper respiratory tract and the eyes. Mathematical models and statistical methodologies could play an important role in decision-making and help maintain the gains in elimination programmes. Various models for predicting leprosy cases have been reported in the literature, but they have different settings and distinct approaches to predicting the cases. This study describes the protocol for a scoping review to identify and synthesise information from studies using models to forecast leprosy cases.
A scoping review methodology will be applied following the Joanna Briggs Institute methodology for scoping reviews and will be reported according to Preferred Reporting Items for Systematic Reviews and Meta-analysis Extension for Scoping Reviews. We will perform a systematic search from when each database started until April 2022 and we will include the following electronic databases: MEDLINE via PubMed, Embase, Cochrane Library and Latin American and Caribbean Health Science Literature Database. 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.
No ethical approval is required for this study. This scoping review will identify and map the methodological and other characteristics of modelling studies predicting leprosy cases. We hope that the review will contribute to scientific knowledge in this area and act as a basis for researchers designing and conducting leprosy models. This information can also be used to enhance national surveillance systems and to target specific policies. The protocol and consequent publications of this scoping review will be disseminated through peer-reviewed publications and policy briefs.
This scoping review was registered in the Open Science Framework (https://doi.org/10.17605/OSF.IO/W9375).
麻风病是一种被忽视的热带病，由 引起，主要影响皮肤、外周神经、上呼吸道黏膜和眼睛。数学模型和统计方法可以在决策中发挥重要作用，并有助于维持消除规划的成果。文献中已经报道了各种预测麻风病病例的模型，但它们的设置不同，预测病例的方法也不同。本研究描述了一项范围综述的方案，旨在识别和综合使用模型预测麻风病病例的研究信息。
将采用乔安娜·布里格斯研究所（Joanna Briggs Institute）的范围综述方法，并根据系统评价和荟萃分析扩展的首选报告项目（Preferred Reporting Items for Systematic Reviews and Meta-analysis Extension）进行报告。我们将从每个数据库开始的时间进行系统搜索，直到 2022 年 4 月，并将包括以下电子数据库：通过 PubMed 的 MEDLINE、Embase、Cochrane 图书馆和拉丁美洲及加勒比健康科学文献数据库。数据将在经过校准的预定义数据表格中提取和记录，并以表格形式呈现，辅以描述性摘要。将使用预测模型研究偏倚风险评估工具（PROBAST）。
本研究不需要伦理批准。这项范围综述将确定和绘制预测麻风病病例的建模研究的方法学和其他特征。我们希望该综述将有助于该领域的科学知识，并为研究人员设计和进行麻风病模型提供基础。这些信息也可以用于加强国家监测系统，并针对特定政策。该范围综述的方案和随后的出版物将通过同行评议的出版物和政策简报进行传播。
该范围综述在开放科学框架（Open Science Framework）中注册（https://doi.org/10.17605/OSF.IO/W9375）。
