Evidence map›Paper›PMID 38218860›Full record

ArticleMalaria journal2024

Evaluation of malaria outbreak detection methods, Uganda, 2022.

Marie Gorreti Zalwango, Jane F Zalwango, Daniel Kadobera, Lilian Bulage, Carol Nanziri, Richard Migisha, Bosco B Agaba, Benon Kwesiga, Jimmy Opigo, Alex Riolexus Ario and 1 more

Open access · goldAbstract read
In one paragraph

Article in Malaria journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
5.4field-weighted citation impact, top 4% of its field
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

10 citing papers in PubMed, 10 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Marie Gorreti ZalwangoUganda Public Health Fellowship Programme-Uganda National Institute of Public Health, Kampala, Uganda. mzalwango@musph.ac.ug.
Jane F ZalwangoUganda Public Health Fellowship Programme-Uganda National Institute of Public Health, Kampala, Uganda.
Daniel KadoberaUganda Public Health Fellowship Programme-Uganda National Institute of Public Health, Kampala, Uganda.
Lilian BulageUganda Public Health Fellowship Programme-Uganda National Institute of Public Health, Kampala, Uganda.
Carol NanziriUganda Public Health Fellowship Programme-Uganda National Institute of Public Health, Kampala, Uganda.
Richard MigishaUganda Public Health Fellowship Programme-Uganda National Institute of Public Health, Kampala, Uganda.
Bosco B AgabaNational Malaria Control Division, Ministry of Health, Kampala, Uganda.
Benon KwesigaUganda Public Health Fellowship Programme-Uganda National Institute of Public Health, Kampala, Uganda.
Jimmy OpigoNational Malaria Control Division, Ministry of Health, Kampala, Uganda.
Alex Riolexus ArioUganda Public Health Fellowship Programme-Uganda National Institute of Public Health, Kampala, Uganda.
Julie R HarrisDivision of Global Health Protection, US Centers for Disease Control and Prevention, Kampala, Uganda.
Ministry of Health · UGCenters for Disease Control and Prevention · UG

Funding

President's Emergency Plan for AIDS Relief (PEPFAR) through the US Centers for Disease Control and Prevention GH001353
6 · The paper itself

Abstract

backgroundMalaria outbreaks are detected by applying the World Health Organization (WHO)-recommended thresholds (the less sensitive 75th percentile or mean + 2 standard deviations [2SD] for medium-to high-transmission areas, and the more sensitive cumulative sum [C-SUM] method for low and very low-transmission areas). During 2022, > 50% of districts in Uganda were in an epidemic mode according to the 75th percentile method used, resulting in a need to restrict national response to districts with the highest rates of complicated malaria. The three threshold approaches were evaluated to compare their outbreak-signaling outputs and help identify prioritization approaches and method appropriateness across Uganda.

methodsThe three methods were applied as well as adjusted approaches (85th percentile and C-SUM + 2SD) for all weeks in 2022 for 16 districts with good reporting rates ( ≥ 80%). Districts were selected from regions originally categorized as very low, low, medium, and high transmission; district thresholds were calculated based on 2017-2021 data and re-categorized them for this analysis.

resultsUsing district-level data to categorize transmission levels resulted in re-categorization of 8/16 districts from their original transmission level categories. In all districts, more outbreak weeks were detected by the 75th percentile than the mean + 2SD method (p < 0.001). For all 9 very low or low-transmission districts, the number of outbreak weeks detected by C-SUM were similar to those detected by the 75th percentile. On adjustment of the 75th percentile method to the 85th percentile, there was no significant difference in the number of outbreak weeks detected for medium and low transmission districts. The number of outbreak weeks detected by C-SUM + 2SD was similar to those detected by the mean + 2SD method for all districts across all transmission intensities.

conclusionDistrict data may be more appropriate than regional data to categorize malaria transmission and choose epidemic threshold approaches. The 75th percentile method, meant for medium- to high-transmission areas, was as sensitive as C-SUM for low- and very low-transmission areas. For medium and high-transmission areas, more outbreak weeks were detected with the 75th percentile than the mean + 2SD method. Using the 75th percentile method for outbreak detection in all areas and the mean + 2SD for prioritization of medium- and high-transmission areas in response may be helpful.

Indexed as

EpidemicsMalariaDisease OutbreaksHumansUgandaEpidemic thresholdsMalariaMalaria outbreakUganda

Identifiers

PMID38218860
PMCPMC10787982
OpenAlexW4390838291

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.