Evidence map›Paper›PMID 38350921›Full record

ArticleMalaria journal2024

Evaluation of the malaria case surveillance system in KwaZulu-Natal Province, South Africa, 2022: a focus on DHIS2.

Maxwell Mabona, Thembekile Zwane, Jaishree Raman, Lazarus Kuonza, Babongile Mhlongo, Poncho Phafane

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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 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 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

6 authors at 1 institution in 1 country.

Maxwell MabonaSouth African Field Epidemiology Training Programme, National Institute for Communicable Diseases, A Division of the National Health Laboratory Service, Johannesburg, Gauteng, South Africa. Maxwellm@nicd.ac.za.
Thembekile ZwaneSouth African Field Epidemiology Training Programme, National Institute for Communicable Diseases, A Division of the National Health Laboratory Service, Johannesburg, Gauteng, South Africa.
Jaishree RamanCentre for Emerging Zoonotic and Parasitic Diseases, National Institute for Communicable Diseases, A Division of the National Health Laboratory Service, Johannesburg, Gauteng, South Africa.
Lazarus KuonzaSouth African Field Epidemiology Training Programme, National Institute for Communicable Diseases, A Division of the National Health Laboratory Service, Johannesburg, Gauteng, South Africa.
Babongile MhlongoKwaZulu-Natal Provincial Department of Health, Pietermaritzburg, KwaZulu-Natal, South Africa.
Poncho PhafaneKwaZulu-Natal Provincial Department of Health, Pietermaritzburg, KwaZulu-Natal, South Africa.
National Health Laboratory Service · ZA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSouth Africa set a target to eliminate malaria by 2023, with KwaZulu-Natal (KZN) Province the malaria-endemic province closest to achieving this goal. Objective two of the National Malaria Elimination Strategic Plan (NMESP) focused on strengthening surveillance systems to support the country's elimination efforts. Regular evaluations of the malaria surveillance systems against the targets of the NMESP objective are crucial in improving their performance and impact. This study aimed to assess whether the malaria surveillance system in KwaZulu-Natal Province meets the NMESP surveillance objective and goals.

methodsA mixed-methods cross-sectional study design was used to evaluate the malaria surveillance system, focusing on the District Health Information System 2 (DHIS2). The study assessed the data quality, timeliness, simplicity, and acceptability of the system. Key personnel from KZN's Provincial malaria control programme were interviewed using self-administered questionnaires to evaluate their perception of the system's simplicity and acceptability. Malaria case data from January 2016 to December 2020 were extracted from the DHIS2 and evaluated for data quality and timeliness.

resultsThe survey respondents generally found the DHIS2-based surveillance system acceptable (79%, 11/14) and easy to use (71%, 10/14), stating that they could readily find, extract, and share data (64%, 9/14). Overall data quality was good (88.9%), although some variables needed for case classification had low completeness and data availability. However, case notifications were not timely, with only 61% (2 622/4 329) of cases notified within 24 h of diagnosis. During the 5-year study period, the DHIS2 captured 4 333 malaria cases. The majority of cases (81%, 3 489/4 330) were categorized as imported, and predominately in males (67%, 2 914/4 333).

conclusionWhile the malaria surveillance system in KZN Province largely met the NMESP surveillance strategic goals, it failed to achieve the overarching surveillance objective of 100% notification of cases within 24 h of diagnosis. The majority of reported cases in KZN Province were classified as imported, emphasizing the importance of complete data for accurate case classification. Engaging with healthcare professionals responsible for case notification and disseminating aggregated data back to them is needed to encourage and improve notification timeliness.

Indexed as

Health Information SystemsMalariaCross-Sectional StudiesHealth PersonnelHumansMaleSouth AfricaDHIS2EliminationEvaluationKwaZulu-NatalMalariaSurveillance system

Identifiers

PMID38350921
PMCPMC10865712
OpenAlexW4391819627

What OpenQuestion holds

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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.