Evidence map›Paper›PMID 39591653›Full record

ArticleThe American journal of tropical medicine and hygiene2025

Documenting Trends in Malaria Data Reporting Accuracy Using Routine Data Quality Audits in Zambia, 2015-2022.

Smita Das, Arantxa Roca Feltrer, Marie-Reine I Rutagwera, Christopher Lungu, Prudence Malama, Mathews Monde, Ignatius Banda, Mercy M Ingwe, Busiku Hamainza, Adam Bennett and 1 more

Abstract read
In one paragraph

Article in The American journal of tropical medicine and hygiene, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. Article
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  3. Article
  4. Observational
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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

11 authors.

Smita DasPATH Malaria Control and Elimination Partnership (MACEPA), Seattle, Washington.
Arantxa Roca FeltrerPATH MACEPA, Maputo, Mozambique.
Marie-Reine I RutagweraPATH MACEPA, Lusaka, Zambia.
Christopher LunguPATH MACEPA, Lusaka, Zambia.
Prudence MalamaPATH MACEPA, Lusaka, Zambia.
Mathews MondePATH MACEPA, Lusaka, Zambia.
Ignatius BandaZambia Ministry of Health, National Malaria Elimination Centre, Lusaka, Zambia.
Mercy M IngweZambia Ministry of Health, National Malaria Elimination Centre, Lusaka, Zambia.
Busiku HamainzaZambia Ministry of Health, National Malaria Elimination Centre, Lusaka, Zambia.
Adam BennettPATH Malaria Control and Elimination Partnership (MACEPA), Seattle, Washington.
Michael HainsworthPATH Malaria Control and Elimination Partnership (MACEPA), Seattle, Washington.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since 2015, the Zambia National Malaria Elimination Centre has conducted routine data quality audits in Central, Southern, and Western provinces, but trends in data reporting accuracy have not been examined. Routine data quality audit data collected at health facilities reporting into the monthly health management information system (HMIS) and weekly malaria rapid reporting system (MRRS) were used to measure data reporting accuracy trends from 2015 to 2022 and potential influencing factors using three data elements: outpatient department attendance and rapid diagnostic test (RDT)-tested cases for HMIS and MRRS, total confirmed cases for HMIS only, and RDT-positive cases for MRRS only. Reporting accuracies for HMIS and MRRS data elements and the percentage of facilities reporting with high accuracy (≥85%) improved over this period. Low-accuracy (<70%) health facilities were uncommon, accounting for less than 15% of facilities for HMIS and MRRS. With each successive DQA visit, the proportion of facilities with high accuracy increased from visits 1 to 8: 23% to 56% (HMIS) and 42% to 85% (MRRS). No correlation was observed between facility size or incidence and overall accuracy for HMIS and MRRS. Starting in 2017, about 40-50% of health facilities appeared to be overreporting incidence in comparison with their register-based incidence. The risk stratification determined by register-based and reported incidences matched in more than 70% of facilities. Routine data quality audits conducted between 2015 and 2022 in Central, Southern, and Western provinces showed an improvement in malaria data reporting accuracy.

Indexed as

Data AccuracyMalariaHealth FacilitiesHumansZambia

Identifiers

PMID39591653
PMCPMC11803651

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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.