Using DHIS2 routine data for health system preparedness in resource-limited settings: A Bayesian predictive approach in Bangladesh

Toufiq Hassan Shawon, Ema Akter, Bibek Ahamed, Tazreen Ahmed, Romana Afroz Lubna, Animesh Biswas, Tasnu Ara, Ridwana Maher Manna, Pradip Chandra, Nasimul Gani Usmani, Md Alamgir Hossain, Md Shahidul Islam, S M Hasibul Islam, Sultan Mahmud, Abu Bakkar Siddique, Shafiqul Ameen, Shabnam Mostari, Mohammad Sohel Shomik, Emily Wilson, Nadia Akseer, Ahmed Ehsanur Rahman, Shams El Arifeen, Agbessi Amouzou and Aniqa Tasnim Hossain

PLOS Global Public Health, 2026, vol. 6, issue 3, 1-14

Abstract: Health systems in low- and middle-income countries (LMICs) like Bangladesh face persistent challenges in delivering timely and equitable care, often exacerbated by poor planning and inefficient resource allocation. Forecasting service utilization using routine health data can support more responsive and data-driven health system planning, yet such approaches remain under utilized in Bangladesh. By analyzing service utilization trends and projecting future service volume at national and regional levels, we aim to improve region-specific health planning. This can promote more efficient and equitable service provision. We analyzed monthly routine health service data reported into the District Health Information Software 2 (DHIS2) platform between January 2021 and March 2025 in Bangladesh. We examined key indicators across maternal, newborn, child and hospital-based services. Bayesian log-linear Poisson regression models, adjusted for seasonality and autocorrelation, were applied to forecast service utilization for the final nine months of 2025 and all of 2026. Relative changes in 2025 and 2026 were calculated using 2024 as the reference year. The analysis revealed rising trends across most service areas relative to 2024 levels. Kangaroo Mother Care (KMC) has the highest projected expansion, with coverage forecast to rise by over 75% by 2026. Over the same time period, outpatient visits and pneumonia treatment are also expected to increase by about 30%. More moderate increases are seen in low birth weight (LBW) deliveries, cesarean sections, and normal deliveries. Notable regional disparities persist, with Dhaka and Chittagong showing the highest service utilization, while Barishal and Sylhet consistently report the lowest levels. Bangladesh’s health system must prepare for increasing service utilization across all service categories. Forecasting using DHIS2 data supports for proactive planning and equitable resource allocation. Strategic investments in infrastructure, workforce, and data-driven planning are essential for building a resilient health system.

Date: 2026
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/globalpublichealth/artic ... journal.pgph.0005231 (text/html)
https://journals.plos.org/globalpublichealth/artic ... 05231&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pgph00:0005231

DOI: 10.1371/journal.pgph.0005231

Access Statistics for this article

More articles in PLOS Global Public Health from Public Library of Science
Bibliographic data for series maintained by globalpubhealth ().