Evidence map›Paper›PMID 42657021›Full record

ArticleDialogues in health2026

What can LMICs learn from transition of Bihar's disease surveillance reporting from paper to portal?

Arpan Sharma, Ajay Kumar Shahi, Ragini Mishra, Anup Kumar Bhagat, Anmol Rai, Neha Gupta, Sanchita Mahapatra

Abstract read
In one paragraph

Article in Dialogues in health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Arpan SharmaCentre for Health Policy, Asian Development Research Institute, Patna, Bihar, India.
Ajay Kumar ShahiState Health Society Bihar, Government of Bihar, Patna, Bihar, India.
Ragini MishraState Health Society Bihar, Government of Bihar, Patna, Bihar, India.
Anup Kumar BhagatCentre for Health Policy, Asian Development Research Institute, Patna, Bihar, India.
Anmol RaiCentre for Health Policy, Asian Development Research Institute, Patna, Bihar, India.
Neha GuptaCentre for Health Policy, Asian Development Research Institute, Patna, Bihar, India.
Sanchita MahapatraCentre for Health Policy, Asian Development Research Institute, Patna, Bihar, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study evaluated the transition of disease surveillance in Bihar, India, from paper-based reporting to the digital Integrated Health Information Platform (IHIP) portal. The operational strategies and system-level governance mechanisms deployed to strengthen surveillance performance in a resource-constrained public health setting was examined. Methods: A program implementation evaluation was conducted using routine indicators from the IHIP-IDSP portal between 2021 and 2024. The intervention integrated systematic mapping of reporting units with a "Training of Trainers" cascade for frontline workers, real-time troubleshooting via formalized WhatsApp groups, and robust accountability frameworks. Results: The transition was associated with a fundamental expansion of active surveillance infrastructure. Between 2021 and 2023, the number of active Syndromic (S) form reporting units increased from 2148 to 10,633, while Presumptive (P) form units rose from 93 to 1650. Laboratory (L) form reporting completeness surged from baseline levels of 0.57% to over 90% within the same period. These gains were sustained by state-level governance structures, including weekly block-level performance reviews, daily automated portal checks, and a constant reward mechanism utilizing public recognition and certificates for high-performing units. The overall state reporting score improved from 8.4/100 (2021) to 85.4/100 by late 2023. Conclusion: Bihar's experience demonstrates that combining need-based training with real-time feedback and administrative accountability can significantly modernize surveillance systems. These results suggest that digital transformation in LMICs is achievable when technological tools are paired with strong governance and institutionalized motivation strategies.

Indexed as

BiharCompletenessDigital reportingDisease surveillanceIDSP/IDSRLMICTimeliness

Identifiers

PMID42657021
PMCPMC13507807

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.