A Systematic Review and Meta-Analysis on the Presence of Escherichia coli O157:H7 in Africa from a One Health Perspective
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design
2.2. Study Eligibility Criteria
2.3. Screening and Data Extraction
2.4. Study Quality
2.5. Data Analysis
3. Results
3.1. Characteristics of the Included Research Articles
3.2. Distribution of Samples, the Sampling Sources, and E. coli O157:H7 Identification Methods Used
3.3. Meta-Analysis
3.3.1. Distribution of E. coli O157:H7 Prevalence by Country
3.3.2. Distribution of E. coli O157:H7 Prevalence According to Combination of Sample Sources
- Combination human–animal–environment sources: Figure 4A shows the distribution of the pooled prevalence of E. coli O157:H7 from the 26 articles reviewed having human–animal–environment samples. According to the random effects analysis, this prevalence was 3.7% (95% CI: 2.0–6.8; I2 = 98.1%; p < 0.05). Figure 4B shows a funnel plot showing the distribution bias in effect estimates among studies examining the prevalence of E. coli O157:H7 in Africa. Among these 26 articles, the pooled prevalence of E. coli O157:H7 was 4.3% (95% CI: 1.3–13.4; I2 = 97.8%; p < 0.05) from animal samples (Figure 5A,B), followed by 3.1% (95% CI: 1.5–6.3; I2 = 66.4%; p < 0.05) from environment samples (Figure 6A,B), and 2.3% (95% CI: 1.0–4.9; I2 = 73.6%; p < 0.05) from human samples (Figure 7A,B). These publications were found in 6 countries from which the pooled prevalence of E. coli O157:H7 was 13.8% (n = 6; 95% CI: 4.4–35.8; I2 = 98.8%; p < 0.05) in South Africa, 4.1% (n = 5; 95% CI: 1.8–8.9; I2 = 93.3%; p < 0.05) in Nigeria, 2.8% (n = 11, 95% CI: 1.7–4.5; I2 = 96.2%; p < 0.05) in Ethiopia, 0.9% (n = 2; 95% CI: 0.5–1.8; I2 = 0%; p < 0.05) in Egypt, 4.1% (n = 1) in Namibia, and 0.4% (n = 1) in Tanzania.
- Combination of human–animal sources: In this review, 12 studies described concrete information on E. coli O157:H7 from human and animal sources. The average pooled prevalence was 4.0% (95% CI: 2.3–7.0; I2 = 96.9%; p < 0.05) (Figure 8A). The asymmetrical distribution of the effect estimates, shown by a funnel plot of the study distribution, allowed us to examine the data according to the countries and sample sources (Figure 8B). Specifically, the pooled prevalence of E. coli O157:H7 was 3.6% (95% CI: 1.8–6.9; I2 = 94.1%; p < 0.05) from the human samples and 6.7% (95% CI: 3.5–12.3; I2 = 95.6%; p < 0.05) from the animal samples. In this review, these publications were from 5 countries including Egypt (n = 5; 2.2% (95% CI: 0.6–8.1; I2 = 94.6%; p < 0.05), Ethiopia (n = 3; 7.1% (95% CI: 3.9–12.6; I2 = 93.9%; p < 0.05), Nigeria (n = 2; 4.8% (95% CI: 0.2–54.9; I2 = 98.7%; p < 0.05), Tanzania (n = 1; 9.8%), and Senegal (n = 1; 1.7%).
- Combination of human–environment sources: Our study highlighted 6 publications in this area, of which the pooled prevalence of E. coli O157:H7 was 6.0% (95% CI: 2.5–14.0; I2 = 97.2%; p < 0.05) (Figure 8C). The asymmetrical distribution of the effect estimates, which is shown by a funnel plot of the study distribution, led us to further examine the data according to countries and sample sources (Figure 8D). These research articles were described in 2 countries such as in South Africa (n = 4), where the pooled prevalence of E. coli O157:H7 was 10.9% (95% CI: 4.6–23.6; I2 = 97.3%; p < 0.05), and in Nigeria (n = 2), it was 1.9% (95% CI: 0.4–8.2; I2 = 60.6%; p > 0.05). The pooled prevalence of E. coli O157:H7 from the human samples was 2.7% (95% CI: 0.4–15.8; I2 = 94.3%; p < 0.05), and it was 3.7% (95% CI: 1.2–10.7; I2 = 94.2%; p < 0.05) from the environment samples.
- Combination of animal–environment sources: For this combination, the pooled prevalence of E. coli O157:H7 was 8.5% (95% CI: 6.5–11.0; I2 = 94.7%; p < 0.05) in the 5 publications reviewed (Figure 8E). Figure 8F is a funnel plot showing the distribution bias in the effect estimates among studies that examined the prevalence of E. coli O157:H7 in the animal–environment samples. Specifically, the pooled prevalence of E. coli O157:H7 from the animal samples in this combination was 5.7% (95% CI: 1.0–26.9; I2 = 94.1%; p < 0.05), and it was 3.6% (95% CI: 1.4–8.9; I2 = 69.9%; p < 0.05) in the environment samples. The prevalence of E. coli O157:H7 was 38% (n = 1) in Nigeria, 8.8% (n = 1) in Benin, 4.7% (n = 1) in Ethiopia, 2.2% (n = 1) in Egypt, and 0.02% (n = 1) in Ghana.
3.3.3. Pooled Antimicrobial Resistance (AMR) Prevalence of E. coli O157:H7 Across the Human, Animal, and Environmental Studies in Africa
3.4. Risk of Bias
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Authors | Countries | Sources | Samples Numbers | Human Samples | Animal/Livestock Samples | Environment Samples | Number of Isolates | Clinical Isolates | Animal Isolates | Environment Isolates | Methods |
---|---|---|---|---|---|---|---|---|---|---|---|
[23] | Egypt | Bulk tank milk, milking utensils, knife swabs, wall swabs, workers’ hands swabs. | 200 | N/A | N/A | N/A | 52 | 14 | 18 | 20 | Culture, biochemical tests |
[24] | Egypt | Chicken, beef, cutting board, and cutting knife, food handler (positive hand swabs) | 648 | 108 | 432 | 108 | 7 | 1 | 5 | 1 | Culture, biochemical tests, PCR, antisera anti-E. coli O157 |
[25] | Egypt | Fresh water, human stools and urine, animal stools, meat products, poultry products, seafood, dairy products | 384 | 254 | 99 | 31 | 2 | 2 | 0 | 0 | Culture, biochemical tests, PCR, genomics |
[19] | Egypt | Chicken paneer, chicken burger, chicken luncheon, minced meat, beef burger, and Kariesh cheese, stools | 550 | 100 | 450 | 0 | 11 | 1 | 10 | 0 | Culture, biochemical tests, serotyping, PCR |
[26] | Egypt | Minced beef, chicken fillet, chicken legs, children stools. | 103 | 28 | 75 | 0 | 2 | 0 | 2 | 0 | Culture, biochemical tests, serotyping |
[27] | Egypt | Milk products and stools samples | 300 | 150 | 150 | 0 | 39 | 22 | 17 | 0 | culture, biochemical tests, serotyping |
[28] | Egypt | Meat, luncheon, sausage, and beef burger, Karish cheese samples, and human stool | 310 | 50 | 260 | 0 | 2 | 1 | 1 | 0 | Culture, biochemical tests, PCR |
[29] | Egypt | Meat samples, human stool samples | 700 | 150 | 550 | 0 | 8 | 1 | 7 | 0 | Culture, biochemical tests, ERIC-PCR |
[30] | Egypt | Cattle carcasses, floors, doors, walls, knives, swivels, stamps, water gourds | 230 | 0 | 110 | 120 | 5 | 0 | 1 | 4 | Culture, biochemical tests, PCR |
[20] | Namibia | Meat, equipment, hand swabs | 270 | 29 | 204 | 37 | 11 | 0 | 9 | 2 | Culture, biochemical tests, PCR |
[31] | Tanzania | Human stool, soil, water, andfecal samples from cattle | 1046 | 200 | 446 | 400 | 4 | 0 | 4 | 0 | Culture, biochemical tests, PCR |
[32] | Tanzania | Cattle and humans | 307 | 107 | 200 | 0 | 30 | 10 | 20 | 0 | Culture, biochemical tests, PCR |
[33] | Nigeria | Cow carcass swabs, cecal content samples, water samples, hand swabs, and knife swabs | 415 | 25 | 360 | 30 | 16 | 0 | 14 | 2 | Culture, biochemical tests, latex kit |
[17] | Nigeria | Stool, water samples, meat, skin and visceral organs from sheep, cattle, goat, and poultry | 508 | 227 | 154 | 127 | 65 | 37 | 16 | 12 | Culture, biochemical tests, PCR |
[34] | Nigeria | Raw meat, fish, samples retailed, butchers’ processing tables, and utensils used in retailing meat and fish | 823 | 394 | 429 | 0 | 8 | 2 | 6 | 0 | Culture, biochemical tests, PCR |
[35] | Nigeria | Stool specimens from undergraduates, food vendors, and specimens from non-human sources | 366 | 180 | 100 | 86 | 4 | 1 | 2 | 1 | Culture, biochemical tests, latex agglutination |
[36] | Nigeria | Beef samples, processing water samples, table swabs and entrails samples | 50 | 0 | 30 | 20 | 19 | 0 | 19 | 0 | Culture, biochemical tests, serological test |
[37] | Nigeria | Abattoir meat, abattoir waste water, roadside butchers’ meat, patients’ stool sample, food sellers’ stool | 349 | 159 | 126 | 64 | 29 | 11 | 16 | 2 | Culture, biochemical tests, serotyping |
[38] | Nigeria | Slaughter floor, meat hooks, butchers’ hands, butchers’ knives, meat sellers’ table, meat sellers’ hands, meat sellers’ knives | 406 | 116 | 58 | 232 | 6 | 0 | 0 | 6 | Culture, biochemical tests |
[39] | Nigeria | Diarrheal stools and surface waters | 340 | 112 | 0 | 228 | 11 | 6 | 0 | 5 | Culture, biochemical tests, agglutination test |
[40] | Nigeria | Nurses’ hand swab, nurses’ table top, door knob/handle, toilet seat, operation table, sink, stretcher, floor, bedrail, and cupboard | 160 | 20 | 0 | 140 | 1 | 0 | 0 | 1 | Culture, biochemical tests, latex agglutination |
[41] | Nigeria | Children stool and raw bovine meat | 726 | 366 | 360 | 0 | 146 | 70 | 76 | 0 | Culture, biochemical tests, latex agglutination |
[42] | South Africa | Drinking water, meat and vegetables, andstools | 900 | 360 | 180 | 360 | 29 | 14 | 5 | 10 | Culture, biochemical tests, PCR |
[43] | South Africa | Beef, pork, water, human, and animal species | 220 | 20 | 160 | 40 | 130 | 1 | 124 | 5 | Culture, biochemical tests, PCR |
[44] | South Africa | Pigs, cattle, pork, beef, humans, and water samples | 220 | 20 | 160 | 40 | 95 | 1 | 89 | 5 | Culture, biochemical tests, REP, and ERIC PCR, ISR and BOXAIR PCR |
[45] | South Africa | Cattle, pigs and humans, water samples | 220 | 20 | 160 | 40 | 94 | 1 | 88 | 5 | Culture, biochemical tests, ERIC PCR |
[18] | South Africa | Run-off water, sewage water, surface water, wastewater, bloody, loose, mucoid, watery | 520 | 250 | 0 | 270 | 132 | 1 | 0 | 11 | Culture, biochemical tests, PCR, Sequencing, PFGE |
[46] | South Africa | Water, fruit, hands | 428 | 57 | 0 | 371 | 25 | 1 | 0 | 24 | Bacteriological culture, biochemical tests, PCR |
[47] | South Africa | Raw milk, cattle udder, milking machines, and worker’s hand swabs | 252 | N/A | N/A | N/A | 27 | N/A | N/A | N/A | Culture, biochemical tests, PCR |
[48] | South Africa | Water samples, cattle and pig fecal samples, human fecal samples | 403 | 6 | 62 | 335 | 32 | 0 | 29 | 3 | Culture, PCR immunomagnetic separation (IMS), sequencing |
[49] | South Africa | Poultry, swine, human hand swabs, and abattoir/farms run-off water | 537 | 108 | 418 | 11 | 1 | 0 | 1 | 0 | Culture, biochemical tests, PCR, sequencing |
[50] | South Africa | Cattle, pigs, and humans | 800 | N/A | N/A | 0 | 76 | 3 | 73 | 0 | Culture, biochemical tests, serotyping |
[51] | South Africa | Water samples and stool swabs | 540 | 360 | 0 | 180 | 177 | 131 | 0 | 46 | Culture, biochemical tests, PCR |
[52] | South Africa | Drinking water, dairy wastewater and irrigation water, rectal samples from cattle | 288 | 0 | 180 | 108 | 47 | 0 | N/A | N/A | Culture, biochemical tests, PCR |
[53] | South Africa | River samples were collected, and diarrheic stool samples | 480 | 252 | 0 | 228 | 1 | 1 | 0 | 0 | Culture, biochemical tests, PCR |
[54] | Ethiopia | Fecal sample, skin swab, intestinal mucosal swab, carcass internal swab, carcass external swab, environmental swabs, carcass, hands, cutting board, knife, stool | 2482 | 195 | 1975 | 312 | 16 | 0 | 15 | 1 | Culture, biochemical tests, PCR |
[16] | Ethiopia | Carcass surface, abattoir worker’s hand, knives, carcass wash water, cattle feces, abattoir effluent | 384 | 30 | 280 | 74 | 1 | 1 | Culture, biochemical tests, PCR | ||
[55] | Ethiopia | Fecal, carcass swab, knife swabs, hand swabs, water/wastewater | 352 | 12 | 92 | 248 | 14 | 1 | 8 | 5 | Culture, biochemical tests, PCR |
[56] | Ethiopia | Filleted fish swab, filleted fish muscle (tissue, whole fish (skin) swab, knife and cutting, board swab, ready to eat fish, workers’ hand swab, container swab | 410 | 24 | 352 | 34 | 6 | 0 | 6 | 0 | Culture, biochemical tests, PCR |
[57] | Ethiopia | Fecal sample, carcass swab, knife swab, personnel hand swab, meat transporters cloth swab, meat sample, butcher men hand swab, cutting board swab, knife swab | 630 | 90 | 450 | 90 | 15 | 0 | 14 | 1 | Culture, biochemical tests |
[58] | Ethiopia | Carcass swab, hand swab, knife swab, cutting board swab, minced beef | 525 | 110 | 195 | 220 | 9 | 0 | 5 | 4 | Culture, biochemical tests |
[59] | Ethiopia | Milk, water, milker hand swab | 450 | 65 | 294 | 91 | 27 | 6 | 12 | 9 | Culture, biochemical tests, serological test |
[60] | Ethiopia | Slaughtered cattle feces, carcass swabs, tap water, butcher hand, and knife swabs | 516 | 93 | 300 | 123 | 14 | 1 | 12 | 1 | Culture, biochemical tests, latex agglutination kit, PCR |
[61] | Ethiopia | Raw beef meat, Environmental sample, Equipment, Workers hand, Contact surface, Balance, Vehicle, Cutting board and table Respondents | 370 | 30 | 290 | 50 | 8 | 0 | 6 | 2 | Culture, biochemical tests |
[62] | Ethiopia | Meat sample, cecal content, hand swabs, knife swabs, protective cloth swabs, transport vehicles swab | 502 | 70 | 270 | 165 | 27 | 1 | 18 | 8 | Culture, biochemical tests, latex agglutination test |
[63] | Ethiopia | Carcass, hand, knife, hook | 248 | 62 | 62 | 124 | 22 | 2 | 13 | 7 | Bacteriological culture, biochemical tests, andlatex agglutination tests |
[64] | Ethiopia | Raw beef meat, environmental sample, equipment, workers’ hand, contact surface, balance, vehicle, cutting board, and table respondents | 370 | 40 | 290 | 76 | 8 | 0 | 6 | 2 | Bacteriological culture, biochemical tests |
[65] | Ethiopia | Milk samples, feces samples, water, and manure samples | 408 | 0 | 208 | 100 | 19 | 0 | 13 | 6 | Bacteriological culture, biochemical tests |
[66] | Ethiopia | Cattle, beef, and humans | 793 | 216 | 507 | 0 | 44 | 6 | 38 | 0 | Bacteriological culture, biochemical tests, whole-genome sequencing (WGS), MLST |
[67] | Ethiopia | Cattle, beef, and humans | 583 | 216 | 367 | 0 | 31 | 6 | 25 | 0 | Bacteriological culture, biochemical tests, PFGE |
[68] | Ethiopia | Samples included livestock fecal samples and soil samples | 539 | 0 | 462 | 77 | 42 | 0 | N/A | N/A | Culture, biochemical tests |
[69] | Ethiopia | (Stools) diarrheic patients and cattle | 1378 | 1149 | 229 | 0 | 161 | 128 | 33 | 0 | Culture, latex agglutination test, PCR |
[70] | Ghana | 22 rinse water samples, 33 fecal matter samples, 33 bench top samples, and 60 freshly dressed chicken carcasses | 148 | 0 | 60 | 88 | 71 | 0 | N/A | N/A | Bacteriological culture, biochemical tests, PCR |
[71] | Ghana | Vegetables, irrigation water, manure soil samples, stools of livestock | 642 | 0 | 250 | 392 | 1 | 0 | 0 | 1 | Bacteriological culture, biochemical tests |
[72] | Senegal | Beef, pork, mouton, stools | 1777 | 1667 | 110 | 0 | 31 | 13 | 18 | Bacteriological culture, biochemical tests | |
[73] | Benin | Cattle, pigs, tables, knives, dropping of poultry, vegetable, irrigation water | 148 | 0 | 74 | 74 | 13 | 0 | 6 | 7 | Bacteriological culture, biochemical tests, serological test |
Antibiotics | Human Samples | Animal Samples | Environment Samples | Total |
---|---|---|---|---|
Ciprofloxacin | ||||
Pooled prevalence % | 25.1 | 40.2 | 33.3 | 35.9 |
95% CI; I2; p | 7.7–57.4; I2 = 88.2; p = 0.123 | 17.9–67.5; I2 = 85.6; p = 0.492 | 16.7–61.0; I2 = 91.6; p = 0.269 | |
Number of studies | 3 | 4 | 1 | 5 |
Amoxiclav | ||||
Pooled prevalence % | 43.8 | 50.4 | 16.7 | 43.1 |
95% CI; I2; p | 22.0–68.3; I2 = 87.6; p = 0.63 | 28.4–72.2; I2 = 65.5; p = 0.75 | 28.3–59.3; I2 = 81.3; p = 0.408 | |
Number of studies | 7 | 4 | 1 | 7 |
Ampicillin | ||||
Pooled prevalence % | 72.6 | 82.8 | 72.6 | 77.4 |
95% CI; I2; p | 63.2–80.4; I2 = 0; p = 0 | 55.9–94.8; I2 = 79.9; p = 0.021 | 47.9–88.5; I2 = 27.8; p = 0.072 | 59.4–88.9; I2 = 75.0; p = 0.004 |
Number of studies | 7 | 9 | 6 | 11 |
Gentamicin | ||||
Pooled prevalence % | 71.9 | 65.9 | 72.6 | 66.9 |
95% CI; I2; p | 52.1–85.7; I2 = 0; p = 0.031 | 54.1–77.9; I2 = 44.8; p = 0.032 | 47.9–88.5; I2 = 27.8; p = 0.072 | 56.6–75.8; I2 = 26.9; p = 0.002 |
Number of studies | 3 | 5 | 6 | 12 |
Imipenem | ||||
Pooled prevalence % | 83.3 | N/A | N/A | 83.3 |
95% CI; I2; p | N/A | N/A | ||
Number of studies | 1 | N/A | N/A | 1 |
Ceftriaxone | ||||
Pooled prevalence % | 45.7 | 35.9 | N/A | 43.5 |
95% CI; I2; p | 0.254–0.676; I2 = 60.2; p = 0.7 | 23.8–50.2; I2 = 30.9; p = 0.053 | N/A | 25.6–63.4; I2 = 70.0; p = 0.528 |
Number of study | 3 | 2 | N/A | 3 |
Nitrofurantoin | ||||
Pooled prevalence % | 35.9 | 70.7 | 62.1 | 53.4 |
95% CI; I2; p | 26.2–47.0; I2 = 14.2; p = 0.014 | 49.6–85.5; I2 = 50.5; p = 0.054 | 35.9–82.8; I2 = 0; p = 0.366 | 37.8–68.4; I2 = 59.6; p = 0.674 |
Number of studies | 3 | 3 | 2 | 4 |
Tetracycline | ||||
Pooled prevalence % | 80.7 | 70.3 | 66.7 | 73.2 |
95% CI; I2; p | 62.9–91.1; I2 = 79.8; p = 0.002 | 46.7–86.5; I2 = 79.0; p = 0.089 | 13.0–96.4; I2 = 66.2; p = 0.60 | 55.3–85.7; I2 = 86.1; p = 0.013 |
Number of studies | 7 | 7 | 2 | 8 |
Ceftazidime | ||||
Pooled prevalence % | 48.7 | 40.3 | 47.4 | 44.5 |
95% CI; I2; p | 33.6–64.0; I2 = 0; p = 0.873 | 3.7–92.2; I2 = 85.5; p = 0.788 | 6.5–92.1; I2 = 61.2; p = 0.935 | 9.3–86.3; I2 = 79.8; p = 0.833 |
Number of studies | 2 | 3 | 2 | 4 |
Cefuroxime | ||||
Pooled prevalence % | 53.8 | 76.8 | 36.4 | 51.7 |
95% CI; I2; p | 38.3–68.6; I2 = 0; p = 0.631 | 7.1–99.3; I2 = 84.5; p = 0.534 | 8.9–77.2; I2 = 58.9; p = 0.539 | 15.4–86.3; I2 = 71.9; p = 0.941 |
Number of studies | 2 | 2 | 3 | 4 |
Trimethoprim/sulfamethoxazole | ||||
Pooled prevalence % | 82.9 | 67.9 | 66.7 | 67.9 |
95% CI; I2; p | 53.7–95.3; I2 = 34.9; p = 0.215 | 12.0–97.1; I2 = 86.5; p = 0.592 | 13.0–96.4; I2 = 66.2; p = 0.6 | 31.1–90.9; I2 = 82.4; p = 0.342 |
Number of studies | 2 | 3 | 2 | 5 |
Cefoxitin | ||||
Pooled prevalence % | 49.2 | 96.5 | 65.1 | 63.5 |
95% CI; I2; p | 0.01–0.99; I2 = 88.6; p = 0.989 | 79.1–99.5; I2 = 0; p = 0.001 | 5.9–98.2; I2 = 80.0; p = 0.72 | 6.4–97.8; I2 = 88.7; p = 0.737 |
Number of studies | 2 | 2 | 3 | 4 |
Nalidixic acid | ||||
Pooled prevalence % | 83.3 | 20.0 | 83.3 | 25.5 |
95% CI; I2; p | 19.4–99.0; I2 = 0; p = 0.299 | 2.4–71.7; I2 = 46.2; p = 0.241 | 19.4–99.0; I2 = 0; p = 0.299 | 9.7–52.2; I2 = 0; p = 0.07 |
Number of studies | 1 | 2 | 1 | 2 |
Amikacin | ||||
Pooled prevalence % | 23.8 | 62.1 | N/A | 45.8 |
95% CI; I2; p | 8.1–52.5; I2 = 35.9; p = 0.071 | 22.9–90.0; I2 = 81.7; p = 0.57 | N/A | 26.9–65.9; I2 = 65.6; p = 0.688 |
Number of studies | 2 | 2 | N/A | 2 |
Chloramphenicol | ||||
Pooled prevalence % | 26.4 | 16.2 | N/A | 23.9 |
95% CI; I2; p | 8.4–58.4; I2 = 93.0; p = 0.141 | 1.2–75.1; I2 = 87.9; p = 0.241 | N/A | 7.7–54.2; I2 = 93.3; p = 0.09 |
Number of studies | 3 | 3 | N/A | 4 |
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Somda, N.S.; Adesoji, T.O.; Tetteh-Quarcoo, P.B.; Donkor, E.S. A Systematic Review and Meta-Analysis on the Presence of Escherichia coli O157:H7 in Africa from a One Health Perspective. Microorganisms 2025, 13, 902. https://doi.org/10.3390/microorganisms13040902
Somda NS, Adesoji TO, Tetteh-Quarcoo PB, Donkor ES. A Systematic Review and Meta-Analysis on the Presence of Escherichia coli O157:H7 in Africa from a One Health Perspective. Microorganisms. 2025; 13(4):902. https://doi.org/10.3390/microorganisms13040902
Chicago/Turabian StyleSomda, Namwin Siourimè, Tomiwa Olumide Adesoji, Patience B. Tetteh-Quarcoo, and Eric S. Donkor. 2025. "A Systematic Review and Meta-Analysis on the Presence of Escherichia coli O157:H7 in Africa from a One Health Perspective" Microorganisms 13, no. 4: 902. https://doi.org/10.3390/microorganisms13040902
APA StyleSomda, N. S., Adesoji, T. O., Tetteh-Quarcoo, P. B., & Donkor, E. S. (2025). A Systematic Review and Meta-Analysis on the Presence of Escherichia coli O157:H7 in Africa from a One Health Perspective. Microorganisms, 13(4), 902. https://doi.org/10.3390/microorganisms13040902