Prevalence and associated factors of malaria among the displaced population in refugee camps in Africa: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: The increased occurrence of malaria among Africa's displaced communities poses a new humanitarian problem. Understanding malaria epidemiology among the displaced population in African refugee camps is a vital step for implementing effective malaria control and elimination measures. As a result, this study aimed to generate comprehensive and conclusive data from diverse investigations undertaken in Africa. METHODS: This review adhered to PRISMA standards, involving searches across electronic data bases such as Google Scholar, PubMed, Web of Science, Scopus, and Science Direct. In addition, grey literature was retrieved from several professional associations. The quality of selected studies was evaluated using the Newcastle-Ottawa Quality Assessment Scale. Data extraction was executed using Microsoft Excel, and the meta-analysis was performed with STATA 14 software. A random-effects model was used to estimate the pooled prevalence and associated factors of malaria. Meta-regression and subgroup analysis were used to identify heterogeneity, while funnel plots and Egger's statistical tests assessed the publication bias. Furthermore, a sensitivity analysis was performed. RESULTS: The overall random-effects pooled prevalence of malaria infection (comprising symptomatic and asymptomatic cases) across all included studies was 35.93% (95% CI 24.71-47.15). This study showed a high level of heterogeneity between studies (I2 = 97.1; P < 0.001). Of the identified Plasmodium species, Plasmodium falciparum constituted 99.3%. The frost plot indicated that the overall prevalence of P. falciparum was 34.94% (95% CI 24.34-45.53). Subgroup analysis revealed significant variation (P < 0.001) in malaria prevalence between asymptomatic and symptomatic cases, with a prevalence of 4.39% (95% CI 2.57-6.21) and 45.10% (95% CI 27.28-62.92), respectively. Lack of insecticide-treated mosquito net utilization (AOR 2.43; 95% CI 1.01-5.88) and living near mosquito breeding sites (AOR 2.76, 95% CI 1.56-4.87) were risk factors of malaria. CONCLUSION: This study determined that the pooled prevalence of malaria among displaced individuals in refugee camps was high and exhibited variations across different population groups. This signifying there is still a need to improve and recheck existing malaria prevention and control strategies to establish an effective malaria control and elimination programme in Africa.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.042 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".