Evidence map›Paper›PMID 40018582›Full record

ArticleBMJ public health2024

Unraveling the 'community effects' of interventions against malaria endemicity: a systematic scoping review.

Yura K Ko, Wataru Kagaya, Chim W Chan, Mariko Kanamori, Samuel M Mbugua, Alex K Rotich, Bernard N Kanoi, Mtakai Ngara, Jesse Gitaka, Akira Kaneko

Abstract read
In one paragraph

Article in BMJ public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
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

10 authors.

Yura K KoDepartment of Microbiology, Tumor and Cell Biology, Karolinska Institute, Stockholm, Sweden.ORCID 0000-0002-3493-0180
Wataru KagayaDepartment of Ecoepidemiology, Institute of Tropical Medicine (NEKKEN), Nagasaki University, Nagasaki, Japan.
Chim W ChanDepartment of Virology and Parasitology, Osaka Metropolitan University, Osaka, Japan.
Mariko KanamoriDepartment of Public Health Sciences, Stockholm University, Stockholm, Sweden.ORCID 0000-0001-8733-1336
Samuel M MbuguaCenter for Research in Infectious Diseases, Directorate of Research and Innovation, Mount Kenya University, Thika, Kenya.
Alex K RotichCenter for Research in Infectious Diseases, Directorate of Research and Innovation, Mount Kenya University, Thika, Kenya.
Bernard N KanoiCenter for Research in Infectious Diseases, Directorate of Research and Innovation, Mount Kenya University, Thika, Kenya.
Mtakai NgaraDepartment of Microbiology, Tumor and Cell Biology, Karolinska Institute, Stockholm, Sweden.
Jesse GitakaCenter for Research in Infectious Diseases, Directorate of Research and Innovation, Mount Kenya University, Thika, Kenya.
Akira KanekoDepartment of Microbiology, Tumor and Cell Biology, Karolinska Institute, Stockholm, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: There is an urgent need to maximise the effectiveness of existing malaria interventions and optimise the deployment of novel countermeasures. When assessing the effects of interventions against malaria, it is imperative to consider the interdependence of people and the resulting indirect effects. Without proper consideration of the effects, the interventions' impact on health outcomes and their cost-effectiveness may be miscalculated. We aimed to summarise how the indirect effects of malaria interventions were analysed and reported. Design: We conducted a scoping review. Data sources: We searched PubMed, Web of Science and EMBASE. Eligibility criteria: We included studies that were conducted to quantify the indirect effects of any interventions for all species of Data extraction and synthesis: We used a standardised data collection form to obtain the following information from each record: title, name of authors, year of publication, region, country, study type, malaria parasite species, type of interventions, type of outcomes, separate estimated indirect effect for different conditions, pre-specified to measure indirect effect, secondary analysis of previous study, methods of indirect effects estimation, terms of indirect effects, and if positive or negative indirect effects observed. Results: We retrieved 32 articles and observed a recent increase in both the number of reports and the variety of terms used to denote the indirect effects. We further classified nine categories of methods to identify the indirect effects in the existing literature and proposed making comparisons conditional on distance to account for mosquito flight range or intervention density within that range. Furthermore, we proposed using the words community effects or spillover effects as standardised terms for indirect effects and highlighted the potential benefits of mathematical models in estimating indirect effects. Conclusions: Incorporating assessment of indirect effects in future trials and studies may provide insights to optimise the deployment of existing and new interventions, a critical pillar in the current fight against malaria globally.

Indexed as

Disease VectorsEpidemiologyPublic Health

Identifiers

PMID40018582
PMCPMC11816959

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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.