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      Prevalence of Campylobacter and Salmonella in African food animals and meat: A systematic review and meta-analysis

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          Abstract

          Background

          Campylobacter and Salmonella, particularly non-typhoidal Salmonella, are important bacterial enteric pathogens of humans which are often carried asymptomatically in animal reservoirs. Bacterial foodborne infections, including those derived from meat, are associated with illness and death globally but the burden is disproportionately high in Africa. Commercial meat production is increasing and intensifying in many African countries, creating opportunities and threats for food safety.

          Methods

          Following Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines, we searched six databases for English language studies published through June 2016, that reported Campylobacter or Salmonella carriage or infection prevalence in food animals and contamination prevalence in food animal products from African countries. A random effects meta-analysis and multivariable logistic regression were used to estimate the species-specific prevalence of Salmonella and Campylobacter and assess relationships between sample type and region and the detection or isolation of either pathogen.

          Results

          Seventy-three studies reporting Campylobacter and 187 studies reporting Salmonella across 27 African countries were represented. Adjusted prevalence calculations estimate Campylobacter detection in 37.7% (95% CI 31.6–44.3) of 11,828 poultry samples; 24.6% (95% CI 18.0–32.7) of 1975 pig samples; 17.8% (95% CI 12.6–24.5) of 2907 goat samples; 12.6% (95% CI 8.4–18.5) of 2382 sheep samples; and 12.3% (95% CI 9.5–15.8) of 6545 cattle samples. Salmonella were detected in 13.9% (95% CI 11.7–16.4) of 25,430 poultry samples; 13.1% (95% CI 9.3–18.3) of 5467 pig samples; 9.3% (95% CI 7.2–12.1) of 2988 camel samples; 5.3% (95% CI 4.0–6.8) of 72,292 cattle samples; 4.8% (95% CI 3.6–6.3) of 11,335 sheep samples; and 3.4% (95% CI 2.2–5.2) of 4904 goat samples. ‘External’ samples (e.g. hide, feathers) were significantly more likely to be contaminated by both pathogens than ‘gut’ (e.g. faeces, cloaca) while meat and organs were significantly less likely to be contaminated than gut samples.

          Conclusions

          This study demonstrated widespread prevalence of Campylobacter species and Salmonella serovars in African food animals and meat, particularly in samples of poultry and pig origin. Source attribution studies could help ascertain which food animals are contributing to human campylobacteriosis and salmonellosis and direct potential food safety interventions.

          Highlights

          • Campylobacter prevalence data was compiled from 14 African countries.

          • Salmonella prevalence data was compiled from 27 African countries.

          • Campylobacter and Salmonella were most prevalent in poultry and pig samples.

          • C. jejuni was the most predominant Campylobacter species except in pigs where C. coli predominates.

          • S. enterica serovar Typhimurium was the most commonly identified Salmonella serovar.

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          Most cited references280

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          Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement.

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            Meta: An R Package for Meta-Analysis.

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              Risk Factors for Campylobacteriosis of Chicken, Ruminant, and Environmental Origin: A Combined Case-Control and Source Attribution Analysis

              Background Campylobacteriosis contributes strongly to the disease burden of food-borne pathogens. Case-control studies are limited in attributing human infections to the different reservoirs because they can only trace back to the points of exposure, which may not point to the original reservoirs because of cross-contamination. Human Campylobacter infections can be attributed to specific reservoirs by estimating the extent of subtype sharing between strains from humans and reservoirs using multilocus sequence typing (MLST). Methodology/Principal Findings We investigated risk factors for human campylobacteriosis caused by Campylobacter strains attributed to different reservoirs. Sequence types (STs) were determined for 696 C. jejuni and 41 C. coli strains from endemic human cases included in a case-control study. The asymmetric island model, a population genetics approach for modeling Campylobacter evolution and transmission, attributed these cases to four putative animal reservoirs (chicken, cattle, sheep, pig) and to the environment (water, sand, wild birds) considered as a proxy for other unidentified reservoirs. Most cases were attributed to chicken (66%) and cattle (21%), identified as the main reservoirs in The Netherlands. Consuming chicken was a risk factor for campylobacteriosis caused by chicken-associated STs, whereas consuming beef and pork were protective. Risk factors for campylobacteriosis caused by ruminant-associated STs were contact with animals, barbecuing in non-urban areas, consumption of tripe, and never/seldom chicken consumption. Consuming game and swimming in a domestic swimming pool during springtime were risk factors for campylobacteriosis caused by environment-associated STs. Infections with chicken- and ruminant-associated STs were only partially explained by food-borne transmission; direct contact and environmental pathways were also important. Conclusion/Significance This is the first case-control study in which risk factors for campylobacteriosis are investigated in relation to the attributed reservoirs based on MLST profiles. Combining epidemiological and source attribution data improved campylobacteriosis risk factor identification and characterization, generated hypotheses, and showed that genotype-based source attribution is epidemiologically sensible.
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                Author and article information

                Contributors
                Journal
                Int J Food Microbiol
                Int. J. Food Microbiol
                International Journal of Food Microbiology
                Elsevier Science Publishers
                0168-1605
                1879-3460
                16 February 2020
                16 February 2020
                : 315
                : 108382
                Affiliations
                [a ]Centre for International Health, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand
                [b ]Kilimanjaro Clinical Research Institute, Good Samaritan Foundation, Moshi, United Republic of Tanzania
                [c ]Institute of Biodiversity Animal Health and Comparative Medicine, College of Medical Veterinary & Life Sciences, University of Glasgow, Glasgow, United Kingdom
                [d ]Norwich, United Kingdom
                [e ]mEpiLab, Massey University, Palmerston North, New Zealand
                [f ]School of Life Sciences and Bio-Engineering, Nelson Mandela African Institution of Science and Technology, Arusha, United Republic of Tanzania
                [g ]Paul G. Allen School for Global Animal Health, Washington State University, Pullman, WA, United States of America
                [h ]New Zealand Food Safety Science and Research Centre, New Zealand
                [i ]School of People, Environment and Planning, Massey University, Palmerston North, New Zealand
                [j ]State Department of Veterinary Services, Ministry of Livestock and Fisheries, Dodoma, United Republic of Tanzania
                Author notes
                [* ]Corresponding author at: Centre for International Health, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand. k.thomas@ 123456otago.ac.nz
                Article
                S0168-1605(19)30312-5 108382
                10.1016/j.ijfoodmicro.2019.108382
                6985902
                31710971
                6c29ee76-9db2-46aa-9e71-b5ba5d682f5c
                © 2019 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 25 May 2019
                : 20 August 2019
                : 2 October 2019
                Categories
                Article

                africa,campylobacter,food animals,food safety,prevalence,salmonella

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