Evidence map›Paper›PMID 42021812›Full record

ArticleMedical journal of the Islamic Republic of Iran2025

Predicting the Incidence Rate of Tuberculosis in Western Iran Using Time Series Models Before and After COVID-19.

Nasrollah Veisi, Farshid Sharifi, Naser Nasiri, Mojtaba Norouzi, Ghobad Moradi, Shoboo Rahmati

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Article in Medical journal of the Islamic Republic of Iran, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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Authors and funding

6 authors.

Nasrollah VeisiZoonoses Research Center, Research Institute for Health Development, Kurdistan University of Medical Sciences, Sanandaj, Iran.
Farshid SharifiModeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.
Naser NasiriSchool of Health, Jiroft University of Medical Sciences, Jiroft, Iran.
Mojtaba NorouziDepartment of Epidemiology and Biostatistics, School of Health, Shahrekord University of Medical Sciences, Shahrekord, Iran.
Ghobad MoradiSocial Determinants of Health Research Center, Research Institute for Health Development, Kurdistan University of Medical Sciences, Sanandaj, Iran.
Shoboo RahmatiSocial Determinants of Health Research Center, Research Institute for Health Development, Kurdistan University of Medical Sciences, Sanandaj, Iran.ORCID https://orcid.org/0000-0002-2465-395X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Understanding the temporal variation and forecasting the incidence rate of smear-positive tuberculosis may be very helpful in promoting tuberculosis (TB) control initiatives. Therefore, predicting the incidence rate of TB before and after coronavirus disease 2019 (COVID-19) was the aim of this study. Methods: This retrospective study was carried out utilizing data from Iran's National TB Control Program and the monthly TB incidence statistics from April 2005 to March 2021 in Kurdistan Province. There were 192 time points in total cases that were registered each month. Autoregressive Integrated Moving Average (ARIMA) models and interrupted time series were used in the study. Results: The findings demonstrated that TB incidence was declining before the COVID-19 pandemic. However, despite the COVID-19 pandemic, the number of TB diagnoses has unexpectedly declined. During the 26 months of the pandemic, 8 cases of total TB cases, 6 cases of pulmonary TB cases, and 3 cases of extrapulmonary TB cases were detected, while predicted an average number of TB cases during the 26 months of the pandemic is 15 cases per 100,000 for total TB cases, 10 cases per 100,000 for pulmonary TB cases, and 3 cases per 100,000 people for extrapulmonary TB. Conclusion: Our results show that TB patient detection in the Kurdistan region has become significantly more challenging because of the COVID-19 epidemic. In the event that the pandemic persists or recurs in the future, guidelines should be developed to protect these essential services.

Indexed as

COVID-19 PandemicPredictingTime Series ModelsTuberculosis

Identifiers

PMID42021812
PMCPMC13097228

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