Gender characteristics, social determinants, and seasonal patterns of malaria incidence, relapse, and mortality in Sistan and Baluchistan province and other province of Iran: A systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Introduction Malaria is a climate-dependent disease influenced by gender, social determination, seasonal patterns, and relapse incidence This study reviews these characteristics of malaria in the Sistan and Baluchistan (S&B) province and another province of Iran. Methods This systematic review and meta-analysis was conducted through systematic and manual searches in electronic databases such as PubMed, Web of Science, Scopus, Science Direct, Google Scholar, and the Scientific Information Database. Studies from the S&B province, published from 1990 to 2024, written in Farsi and English, and reporting incidence, relapse, or death were included in this study. The quality of the studies was evaluated using the Newcastle–Ottawa Scale. Results Out of 1941 studies initially identified, 43 were included in the systematic review, with 12 studies on relapse and 43 on incidence included in the meta-analysis. The combined results of the 43 primary studies using the random effect model showed that the frequency of malaria among infected women is 32% in S&B, 22% in other parts of Iran and 24% in the whole of Iran. This is 68%, 77% and 75% in men respectively. Among the primary studies, 8 deaths were reported in two studies, all of which were men. The incidence rate of malaria relapse varied from 0.30% to 46%. Based on the random effect model, the malaria relapse rate in Iran was estimated at 9%. The highest incidence of malaria in Iran was between spring and summer, and the lowest incidence was winter and spring. Most studies showed a downward trend in malaria incidence of malaria between 1986 to 2019. In term of socio-demographic status, malaria was more common in rural areas (82%). Although 28% were employed, and in term of age, young and old individuals (15 to 50 years) had the highest rate of infection. Conclusion This systematic review and meta-analysis revealed a lower incidence of malaria in women compared to men. The findings highlight the need for health care and the importance of targeted malaria control interventions, especially for men, rural areas, hot weather conditions, and young to middle-aged age groups, particularly in the S&B province.
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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 | 0.011 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.031 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".