A systematic review of factors influencing participation in two types of malaria prevention intervention in Southeast Asia
Bibliographic record
Abstract
BACKGROUND: Multi-pronged malaria elimination strategies are increasingly being considered for accelerating efforts against malaria transmission in Southeast Asia. Two malaria prevention interventions used in in the region are insecticide-treated bed-nets (ITNs) and mass drug administration (MDA). Universal access to ITNs is recommended and high population coverage (e.g. above 80%) is needed during MDA initiatives to maximize the impact of these interventions. However, variability in ITN use and individual MDA participation exists. This systematic review aims to provide a summary and overview of literature discussing factors influencing uptake of these two malaria control strategies in Southeast Asian countries. METHODS: A search of OVID Embase, OVID MEDLINE, Cochrane Central Register of Controlled Trials, Web of Science, OpenGrey, ProQuest, and Google Scholar was undertaken in February 2020. English-language publications with any study design using data from any of the ten member countries of the Association of Southeast Asian Nations were eligible for inclusion. In addition, reference lists of identified articles were manually searched. Websites for relevant international agencies were also searched to identify related grey literature. RESULTS: The review identified thirty publications that met the inclusion and exclusion criteria. Most discussed ITN use (n = 18) and were relevant to populations in Myanmar (n = 14). All MDA studies were published after 2016, whereas included ITN studies spanned from 1998 to 2020. Seven main themes emerged across the studies. Knowledge of malaria and attitudes towards ITNs were emphasized as key factors associated with ITN use. For MDA participation, key factors included the importance of positive attitudes towards the program, the influence of indirect costs and incentives, and the tendency for group decision-making. CONCLUSIONS: As countries in Southeast Asia continue to work towards becoming malaria-free by 2030, the knowledge and attitudes of local population sub-groups should be assessed and incorporated into the planning and implementation of malaria prevention activities. The role of incentives and group decision making should also be considered particularly as they relate to MDA. There is need for ongoing involvement of health educators, the continuation of implementation research and the prioritization of community engagement efforts alongside malaria interventions in the region.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".