{"title":"Delays in Tuberculosis Care in the Indian Population: A Systematic Review and Meta-analysis.","authors":"Janmejaya Samal, G S Preetha, Hari Singh","doi":"10.4103/jgid.jgid_203_25","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Being harmful to patients, delayed diagnosis and treatment can spread tuberculosis (TB) in the community, posing a significant challenge to TB elimination efforts. This systematic review and meta-analysis aimed to estimate the median delays of TB care and the proportion of the Indian population experiencing these delays.</p><p><strong>Methods: </strong>Data extraction and screening were conducted from August 1, 2024, to September 30, 2024, using PubMed, Scopus, and DOAJ search engines. The pooled proportion of the Indian population experiencing the total delay in TB care was estimated, at a 95% confidence interval (CI), using a random-effects model that assumed potential heterogeneity.</p><p><strong>Results: </strong>Of the 14 studies, 92.85% (<i>n</i> = 13) focused on drug-sensitive TB cases, and 7.15% (<i>n</i> = 1) focused on drug-resistant cases. Similarly, 64.28% (<i>n</i> = 9) of studies were cross-sectional, followed by 21.42% (<i>n</i> = 3) of retrospective studies. The estimated median patient delay is 20.5 days (interquartile range [IQR]: 15.3-25.0), the median diagnosis delay is 32.5 days (IQR: 30.0-37.0), the median treatment delay is 7.50 days (IQR: 2.75-12.8), and the median total delay is 45.5 days (IQR: 37.1-58.5). The pooled proportion of the Indian population experiencing total delay is estimated at 39% (95% CI: 17%-64%). With the random-effects model, high heterogeneity (I2 = 99%) was observed among the studies. The regression test for funnel plot asymmetry did not show statistical significance (z = 0.204, <i>P</i> = 0.838).</p><p><strong>Conclusion: </strong>The findings of this study can help program managers design strategies that can help in reducing delays in TB care in India.</p>","PeriodicalId":51581,"journal":{"name":"Journal of Global Infectious Diseases","volume":"18 3","pages":"134-145"},"PeriodicalIF":1.3000,"publicationDate":"2026-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13679962/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Global Infectious Diseases","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4103/jgid.jgid_203_25","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/7/1 0:00:00","PubModel":"eCollection","JCR":"Q4","JCRName":"INFECTIOUS DISEASES","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction: Being harmful to patients, delayed diagnosis and treatment can spread tuberculosis (TB) in the community, posing a significant challenge to TB elimination efforts. This systematic review and meta-analysis aimed to estimate the median delays of TB care and the proportion of the Indian population experiencing these delays.
Methods: Data extraction and screening were conducted from August 1, 2024, to September 30, 2024, using PubMed, Scopus, and DOAJ search engines. The pooled proportion of the Indian population experiencing the total delay in TB care was estimated, at a 95% confidence interval (CI), using a random-effects model that assumed potential heterogeneity.
Results: Of the 14 studies, 92.85% (n = 13) focused on drug-sensitive TB cases, and 7.15% (n = 1) focused on drug-resistant cases. Similarly, 64.28% (n = 9) of studies were cross-sectional, followed by 21.42% (n = 3) of retrospective studies. The estimated median patient delay is 20.5 days (interquartile range [IQR]: 15.3-25.0), the median diagnosis delay is 32.5 days (IQR: 30.0-37.0), the median treatment delay is 7.50 days (IQR: 2.75-12.8), and the median total delay is 45.5 days (IQR: 37.1-58.5). The pooled proportion of the Indian population experiencing total delay is estimated at 39% (95% CI: 17%-64%). With the random-effects model, high heterogeneity (I2 = 99%) was observed among the studies. The regression test for funnel plot asymmetry did not show statistical significance (z = 0.204, P = 0.838).
Conclusion: The findings of this study can help program managers design strategies that can help in reducing delays in TB care in India.
期刊介绍:
JGID encourages research, education and dissemination of knowledge in the field of Infectious Diseases across the world thus promoting translational research by striking a synergy between basic science, clinical medicine and public health. The Journal intends to bring together scientists and academicians in Infectious Diseases to promote translational synergy between Laboratory Science, Clinical Medicine and Public Health. The Journal invites Original Articles, Clinical Investigations, Epidemiological Analysis, Data Protocols, Case Reports, Clinical Photographs, review articles and special commentaries. Students, Residents, Academicians, Public Health experts and scientists are all encouraged to be a part of this initiative by contributing, reviewing and promoting scientific works and science.