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STUDY PROTOCOL article

Front. Rehabil. Sci.
Sec. Strengthening Rehabilitation in Health Systems
Volume 6 - 2025 | doi: 10.3389/fresc.2025.1419963
This article is part of the Research Topic Post-Acute COVID Rehabilitation View all 7 articles

“Mapping of long COVID conditions in India: A study protocol for systematic review and meta-analysis.”

Provisionally accepted
Nidhi Jain Nidhi Jain Komal Shah Komal Shah *Roshani Chauhan Roshani Chauhan Abhishek Gupta Abhishek Gupta Priyanka Arora Priyanka Arora Deepak Saxena Deepak Saxena Dileep Mavalankar Dileep Mavalankar
  • Indian Institute of Public Health Gandhinagar (IIPHG), Gandhinagar, India

The final, formatted version of the article will be published soon.

    The COVID-19 pandemic has reported significant alarming aftereffects experienced by some individuals following acute sequelae of SARS-CoV-2 infection, commonly referred to as long COVID. Long COVID is a set of symptoms that remain for weeks or months after the initial phase of COVID-19 infection is ended. Objective: This study protocol outlines the methodology of a systematic review followed by a meta-analysis to comprehensively assess the chronic effects of COVID-19 infection on the Indian population and determine the likely risk factors connected to the development and persistence of long COVID.Methodology: This study will employ a comprehensive search through a custom-made search strategy across significant databases (PubMed, MEDLINE, etc.) and grey literature to identify related literature from January 2020 to December 2023. A systematic review and meta-analysis will be conducted to synthesize data from various studies. The data synthesis will involve a comprehensive narrative and tabular presentation of outcome data from included studies, focusing on the long-term effects of COVID-19 infection in the Indian population. A meta-analysis will be conducted contingent upon the availability and suitability of data. Statistical synthesis will be undertaken if sufficient and comparable quantitative data are identified across the included studies. Subgroup and sensitivity analyses will manage confounders, while MedCalc software will facilitate a meta-analysis to assess pooled data. Publication bias will be evaluated using statistical tests to ensure the integrity of the findings. Without adequate data, a narrative synthesis will be performed to summarize the findings systematically and transparently. The anticipated findings will contribute to a refined understanding of this condition and its lingering symptoms, guiding healthcare interventions and future research endeavors to mitigate the impact of long COVID in the Indian population.

    Keywords: COVID-19, Long Covid, systematic review and meta-analysis, Risk factors, Health Outcomes, Chronic symptoms

    Received: 19 Apr 2024; Accepted: 16 Jan 2025.

    Copyright: © 2025 Jain, Shah, Chauhan, Gupta, Arora, Saxena and Mavalankar. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Komal Shah, Indian Institute of Public Health Gandhinagar (IIPHG), Gandhinagar, India

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.