Developing a Data Set for Mpox Disease: A Scoping Review and Consensus-based Classification.

Authors

Azam Sabahi, Hamideh Ehtesham, Leila Ahmadian, Fatemeh Bahador, Somayeh Paydar, Farzaneh Behnam

Published in

Journal of infection in developing countries. Volume 20. Issue 6. Pages 792-801. Jun 30, 2026. Epub Jun 30, 2026.

Abstract

The emergence of Mpox as a major public health problem has drawn attention toward comprehensive data that could inform effective disease management and control efforts. This study aims to create a standardized data set for Mpox, which will be useful for purposes of collecting, analyzing, and reporting critical data elements.
The scoping review was done in accordance with Arksey and O'Malley's framework and under the PRISMA-ScR guidelines. Searches for the terms "minimum data set" and "Monkeypox" were conducted without time limitation until June 9, 2024, in the PubMed, Scopus, and Web of Science databases. Two researchers independently screened the titles, abstracts, and full texts. Data extraction was carried out in Excel.
670 studies were identified, although the inclusion criteria was met by 16. Most studies were conducted in the Democratic Republic of the Congo. Data elements were divided into administrative (10 core and 15 extended data elements) and clinical (26 core and 51 extended data elements). Patient demographics, socioeconomic factors, residence, and healthcare providers appear in administrative data. Disease exposure, symptoms, medical history, diagnostics, treatments, follow-up, and vaccination form part of the clinical data. A total data set with 104 elements was created.
Identifying the data set is crucial to improving the public health responses to Mpox outbreaks. It will enable healthcare professionals and researchers to enhance disease monitoring and control efforts globally. Future studies should validate the data set in diverse settings, adapt it to the disease's evolving nature, and integrate it into health information systems for real-time data utilization.

PMID:
42430531
Bibliographic data and abstract were imported from PubMed on 11 Jul 2026.

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