Association between temperature and malaria (1959-2019): a systematic review and meta-analysis
Bibliographic record
Abstract
Malaria remains a significant global health challenge, with temperature playing a critical role in transmission dynamics by affecting parasite development, mosquito longevity, and vectorial capacity. This systematic review and meta-analysis aimed to quantify the association between ambient temperature and malaria incidence across diverse geographical and ecological contexts, informing climate-informed control strategies. Following PRISMA guidelines, we systematically searched PubMed/MEDLINE, Embase, Scopus, and Web of Science from inception to September 2024. Studies examining correlations between temperature metrics and malaria outcomes with a minimum 12-month follow-up were included. Methodological quality was assessed using a modified version of the Newcastle–Ottawa Scale. Random-effects meta-analysis was conducted to calculate pooled correlation coefficients and 95% confidence intervals. Eleven studies from Africa and Asia spanning 1959–2019 were included, representing diverse transmission ecologies from temperate China to tropical Africa. Mean temperature showed a moderate positive correlation with malaria incidence (r = 0.417, 95% CI: 0.098–0.735, p = 0.01). Minimum temperature demonstrated the strongest and most consistent association with malaria test positivity rates (r = 0.454, 95% CI: 0.358–0.549, p < 0.001), with all 11 studies showing statistically significant positive correlations. Maximum temperature exhibited weaker relationships (r = 0.356, 95% CI: 0.263–0.450 for positivity rates). Substantial heterogeneity was observed across all analyses (I2 > 99%), reflecting regional variations in temperature-malaria dynamics. Temperature, particularly minimum temperature, significantly influences malaria transmission across diverse epidemiological settings. The stronger association with minimum temperature is concerning, given that climate change disproportionately affects nighttime temperatures. The substantial heterogeneity underscores the need for locally tailored climate-informed malaria control strategies. These findings support integrating temperature monitoring, especially minimum temperature thresholds, into malaria surveillance systems and early warning programs as climate change progresses.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.013 | 0.002 |
| 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) | 0.000 | 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".