Etiology-specific incidence and mortality of diarrheal diseases in the African region: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background Diarrheal diseases substantially affect public health impact in low- and middle-income countries (LMIC), particularly in Africa, where previous studies have indicated a lack of comprehensive data. With a growing number of primary studies on enteric infections in Africa, this study aimed to estimate the incidence and mortality of diarrheal pathogens across all ages in Africa in the year 2020. We also explored different methodological assumptions to allow comparison with other approaches. Methods Through a systematic review and meta-analysis of data from African LMICs, we estimated the etiology proportions for diarrheal diseases and deaths. We combined the etiology proportions with incidence data collected from a population survey in Africa from 2020 and mortality data from the Global Health Observatory of WHO. Results We estimated 1,008 billion diarrhea cases (95% UI 447 million-1,4 billion) and 515,031 diarrhea deaths (95% UI 248,983-1,007,641) in the African region in 2020. In children under five, enteroaggregative E. coli (EAEC) (44,073 cases per 100,000 people, 95% UI 18,818 − 60,922) and G. lamblia (36,116 cases per 100,000 people, 95% UI 15,245 − 49,961) were the leading causes of illness. Enteroinvasive E. coli (EIEC) (155 deaths per 100,000 people, 95% UI 106.5-252.9) and rotavirus (61.5 deaths per 100,000 people, 95% UI 42.3-100.3) were the primary causes of deaths. For children over five and adults, Salmonella spp. caused the largest number of diarrheal cases in the population of children ≥ 5 and adults (122,090 cases per 100,000 people, 95% UI 51,833 − 168,822), while rotavirus (16.4 deaths per 100,000 people, 95% UI 4.2–36.7) and enteroaggregative E. coli (EAEC) (14.6 deaths per 100,000 people, 95% UI 3.9–32.9) causing the most deaths. Geographically, the highest incidence of diarrhea was in Eastern Africa for children under five (114,389 cases per 100,000 people, 95% UI 34,771 − 172,884) and Central Africa for children over five and adults (117,820 cases per 100,000 people, 95% UI 75,111–157,584). Diarrheal mortality was highest in Western Africa for both children below five and above (children < 5: 194.5 deaths per 100,000 people, 95% UI 120-325.4; children ≥ 5 and above: 33.5 deaths per 100,000 people, 95% UI 12.9–75.1). Conclusion These findings provide new information on the incidence and mortality of sixteen pathogens and highlight the need for surveillance and control of diarrheal infectious diseases in Africa. The cause-specific estimates are crucial for prioritizing diarrheal disease prevention in the region.
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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 | 0.012 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.042 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 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".