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A scoping review of factors associated with antimicrobial-resistant Campylobacter species infections in humans

Published online by Cambridge University Press:  07 June 2023

Christine M. Neustaedter Open the ORCID record for Christine M. Neustaedter [Opens in a new window] ,
Kelsey Robertson Open the ORCID record for Kelsey Robertson [Opens in a new window] ,
Dana Tschritter Open the ORCID record for Dana Tschritter [Opens in a new window] ,
Richard J. Reid-Smith ,
Melissa C. MacKinnon Open the ORCID record for Melissa C. MacKinnon [Opens in a new window] ,
Colleen P. Murphy ,
Brennan Chapman Open the ORCID record for Brennan Chapman [Opens in a new window] ,
Norman F. Neumann Open the ORCID record for Norman F. Neumann [Opens in a new window]  and
Simon J. G. Otto Open the ORCID record for Simon J. G. Otto [Opens in a new window]
Christine M. Neustaedter
Affiliation:
School of Public Health, University of Alberta, Edmonton, AB, Canada HEAT-AMR Research Group, School of Public Health, University of Alberta, Edmonton, AB, Canada Antimicrobial Resistance – One Health Consortium, University of Calgary, Calgary, AB, Canada
Kelsey Robertson
Affiliation:
School of Public Health, University of Alberta, Edmonton, AB, Canada HEAT-AMR Research Group, School of Public Health, University of Alberta, Edmonton, AB, Canada Antimicrobial Resistance – One Health Consortium, University of Calgary, Calgary, AB, Canada
Dana Tschritter
Affiliation:
School of Public Health, University of Alberta, Edmonton, AB, Canada HEAT-AMR Research Group, School of Public Health, University of Alberta, Edmonton, AB, Canada Antimicrobial Resistance – One Health Consortium, University of Calgary, Calgary, AB, Canada Food-Borne Disease and Antimicrobial Resistance Surveillance Division, Centre for Food-Borne, Environmental, and Zoonotic Infectious Diseases, Public Health Agency of Canada, Guelph, ON, Canada
Richard J. Reid-Smith
Affiliation:
Antimicrobial Resistance – One Health Consortium, University of Calgary, Calgary, AB, Canada Food-Borne Disease and Antimicrobial Resistance Surveillance Division, Centre for Food-Borne, Environmental, and Zoonotic Infectious Diseases, Public Health Agency of Canada, Guelph, ON, Canada Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
Melissa C. MacKinnon
Affiliation:
Food-Borne Disease and Antimicrobial Resistance Surveillance Division, Centre for Food-Borne, Environmental, and Zoonotic Infectious Diseases, Public Health Agency of Canada, Guelph, ON, Canada Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
Colleen P. Murphy
Affiliation:
Antimicrobial Resistance – One Health Consortium, University of Calgary, Calgary, AB, Canada Food-Borne Disease and Antimicrobial Resistance Surveillance Division, Centre for Food-Borne, Environmental, and Zoonotic Infectious Diseases, Public Health Agency of Canada, Guelph, ON, Canada
Brennan Chapman
Affiliation:
Food-Borne Disease and Antimicrobial Resistance Surveillance Division, Centre for Food-Borne, Environmental, and Zoonotic Infectious Diseases, Public Health Agency of Canada, Guelph, ON, Canada Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
Norman F. Neumann
Affiliation:
School of Public Health, University of Alberta, Edmonton, AB, Canada Antimicrobial Resistance – One Health Consortium, University of Calgary, Calgary, AB, Canada
Simon J. G. Otto*
Affiliation:
School of Public Health, University of Alberta, Edmonton, AB, Canada HEAT-AMR Research Group, School of Public Health, University of Alberta, Edmonton, AB, Canada Antimicrobial Resistance – One Health Consortium, University of Calgary, Calgary, AB, Canada Healthy Environments Thematic Area Lead, Centre for Healthy Communities, School of Public Health, University of Alberta, Edmonton, AB, Canada
*
Corresponding author: Simon Otto; Email: [email protected]
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Abstract

Human infection with antimicrobial-resistant Campylobacter species is an important public health concern due to the potentially increased severity of illness and risk of death. Our objective was to synthesise the knowledge of factors associated with human infections with antimicrobial-resistant strains of Campylobacter. This scoping review followed systematic methods, including a protocol developed a priori. Comprehensive literature searches were developed in consultation with a research librarian and performed in five primary and three grey literature databases. Criteria for inclusion were analytical and English-language publications investigating human infections with an antimicrobial-resistant (macrolides, tetracyclines, fluoroquinolones, and/or quinolones) Campylobacter that reported factors potentially linked with the infection. The primary and secondary screening were completed by two independent reviewers using Distiller SR®. The search identified 8,527 unique articles and included 27 articles in the review. Factors were broadly categorised into animal contact, prior antimicrobial use, participant characteristics, food consumption and handling, travel, underlying health conditions, and water consumption/exposure. Important factors linked to an increased risk of infection with a fluoroquinolone-resistant strain included foreign travel and prior antimicrobial use. Identifying consistent risk factors was challenging due to the heterogeneity of results, inconsistent analysis, and the lack of data in low- and middle-income countries, highlighting the need for future research.

Keywords

Antimicrobial resistanceantimicrobial drugsCampylobacterfood-borne infectionsrisk factor
Type
Review
Information
Epidemiology & Infection , Volume 151 , 2023 , e100
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This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press

Introduction

Campylobacter species is one of the leading causes of acute diarrheic illness, accounting for 16% of foodborne illnesses globally [1] and 8.42% of foodborne illnesses in Canada [Reference Thomas, Murray, Flockhart, Pintar, Pollari, Fazil, Nesbitt and Marshall2]. Infections are characterised by acute, watery diarrhoea progressing to bloody diarrhoea and often accompanied by abdominal pain, but vomiting is uncommon [Reference Moore, Corcoran, Dooley, Fanning, Lucey, Matsuda, McDowell, Mégraud, Millar, O’Mahony, O’Riordan, O’Rourke, Rao, Rooney, Sails and Whyte3]. Campylobacter infection has an incubation period of 2–4 days and most people recover within 2–5 days [4]. An uncomplicated infection typically only requires supportive care to avoid dehydration [4]; however, some cases develop bacteraemia [Reference Nachamkin, Allos and Ho5]. Although uncommon, complications related to Campylobacter infections include but are not limited to reactive arthritis, irritable bowel syndrome, Guillain–Barré syndrome (GBS), and Miller Fisher Syndrome, a variant of GBS, which are autoimmune disorders characterised by nerve damage, muscle weakness, and sometimes paralysis [Reference Nachamkin, Allos and Ho5, Reference Facciolà, Riso, Avventuroso, Visalli, Delia and Laganà6].

Fluoroquinolone and macrolide antimicrobials can be used in the treatment of complicated Campylobacter infections to reduce the duration of illness [Reference Ternhag, Asikainen, Giesecke and Ekdahl7]. There is evidence that inappropriate antimicrobial prescribing practices occur in Canada for Campylobacter infections, such as prescribing antimicrobials after symptoms have resolved, before the culture results have confirmed the diagnosis of Campylobacter, or treatment before the collection of a sample [Reference Deckert, Reid-Smith, Tamblyn, Morrell, Seliske, Jamieson, Irwin, Dewey, Boerlin and McEwen8]. Furthermore, antimicrobials not suggested by clinical antimicrobial stewardship guidelines have also been prescribed [Reference Dougherty, Finley, Marshall, Dumoulin, Pavletic, Dow, Hluchy, Asplin and Stone9]. Human infections with strains resistant to macrolides, fluoroquinolones/quinolones, and other antimicrobial classes including tetracyclines occur [Reference Luangtongkum, Jeon, Han, Plummer, Logue and Zhang10], and these infections may have an increased risk of an adverse health event such as a longer duration of illness, hospitalisation, invasive illness, or death, than patients with a susceptible infection [Reference Helms, Simonsen, Olsen and Mølbak11–Reference Wassenaar, Kist and de Jong13].

There is a large amount of research on factors associated with human Campylobacter infections, including undercooked meat, especially chicken, contaminated unpasteurised milk, animal contact, and contaminated water [4]. However, despite this wealth of research, searches on 21 January 2020, in Ovid Medline®, Cochrane Library, Joanna Briggs Institute (JBI) Systematic Review Registry, and Google Scholar did not identify any scoping or systematic reviews on factors associated with infections with antimicrobial-resistant Campylobacter. The objective of this scoping review was to synthesise the published literature on factors associated with human infections with antimicrobial-resistant strains of Campylobacter species, with a focus on resistance to macrolides, tetracyclines, fluoroquinolones, and/or quinolones.

Methods

Protocol, search, and information sources

The review followed the systematic search methods outlined in the JBI Reviewer’s Manual [Reference Aromataris and Munn14] and is reported according to the PRISMA Scoping Review reporting guidelines [Reference Tricco, Lillie, Zarin, O’Brien, Colquhoun, Levac, Moher, MDJ, Horsley, Weeks, Hempel, Akl, Chang, McGowan, Stewart, Hartling, Aldcroft, Wilson, Garritty, Lewin, Godfrey, Macdonald, Langlois, Soares-Weiser, Moriarty, Clifford, Tunçalp and Straus15]. The protocol was registered with the JBI Systematic Review Register on 5 February 2020, and is available in the Supplementary Material (S1). The PRISMA-Scoping Review checklist is provided in Supplementary Table S1.

A comprehensive search strategy was developed in consultation with a librarian to identify articles that studied human infections with antimicrobial-resistant Campylobacter. An example search string for MEDLINE® in Ovid® is shown in Supplementary Table S2. The complete search strings (S1) were used to search MEDLINE®, AGRICOLA™ in ProQuest®, Centre for Agriculture and Bioscience abstracts in Web of Science, EMBASE® in Ovid, and Scopus®. Grey literature sources included the World Health Organization’s Global Index Medicus, the Bielefield Academic Search Engine, and the first 250 results from Google Scholar when sorted by relevance. The search was completed on 5 February 2020, and was updated on 7 May 2021. Articles were de-duplicated in three stages in Mendeley (Version 1.19.8, Elsevier, Amsterdam, Netherlands), EndNote (Version X9.2, Clarivate Analytics, London, United Kingdom), and DistillerSR (Version 2.35, Evidence Partners, Ottawa, ON, Canada).

Eligibility criteria

To be included, articles, theses, and dissertations had to be an analytic study that used a comparison group and reported on factors potentially associated with human infections with a strain of Campylobacter resistant to an antimicrobial of interest: macrolides, tetracyclines, and/or fluoroquinolones/quinolones (collectively referred to as fluoroquinolones hereafter). Resistance had to be determined by recognised laboratory antimicrobial susceptibility testing methods such as disc diffusion or broth micro-dilution. Review articles, commentaries, opinion pieces, editorials, newspaper articles, books, book chapters, and conference proceedings were excluded. No limits were applied to language, geographical location, Campylobacter species, or the date of publication. Non-English articles identified during screening were excluded. Included studies had to report human Campylobacter infections confirmed by recognised laboratory methods. Studies on nonhuman research, infections other than Campylobacter, colonisation instead of infection, or that failed to confirm a Campylobacter infection by recognised laboratory methods were excluded.

Factors associated with human infections with a resistant strain of Campylobacter were defined as observations that were measured and quantified, with the potential for identifying a reported statistical relationship to antimicrobial resistance (AMR) [Reference Murphy, Carson, Smith, Chapman, Marrotte, McCann, Primeau, Sharma and Parmley16], which included but were not limited to age, recent travel, or pre-existing medical conditions. The comparator group had to be appropriate for the study design. For example, the comparator group for case–control studies were infections with strains of Campylobacter that were susceptible to the antimicrobials of interest. Inherently, the comparator group had to be Campylobacter isolates from human infections that were susceptible to the antimicrobials of interest, to compare to the resistant isolates from human infections.

Articles were screened for eligibility via a two-stage screening process by two independent reviewers. Article titles, abstracts, and keywords were screened in the first stage, and articles proceeded to secondary screening if both reviewers determined all eligibility criteria were met or unclear (S1). Secondary full-text screening by both reviewers included articles that answered yes to all eligibility criteria. The reasons for exclusion were documented. Reviewers resolved conflicts through discussion.

Data collection and synthesis

Data regarding authorship, publication date, the location of study, study type (defined by the authors or assigned by the reviewers), AMR outcome(s), Campylobacter species, the site of infection, factor description and descriptive data, results of measures of association (if considered), and the type of analysis (univariable vs. multivariable where reported) were extracted by one reviewer in Distiller SR® and analysed in Excel® (Microsoft, Redmond, WA) and using the R Metaphor package (v4.1.1, R Core Team, 2021). Tables and figures present key findings in the results, whereas the Supplementary Material provides comprehensive results from the study. Factors were combined into themed categories for comparison. For relative associations, an odds ratio (OR) with a value of less than 1 is generally interpreted as a protective factor, whereas a value of greater than 1 was interpreted as a risk factor, meaning that either was associated with a decreased or increased risk of infection with a resistant strain of Campylobacter, respectively.

Results

Selection of information sources

Our search identified 8,527 unique articles. Primary and secondary screening excluded 8,089 and 411 articles, respectively, including 12 where we could not locate a full-text document after additional inquiry through library requests (Figure 1). The review included 27 articles that met all inclusion criteria.

Figure 1. PRISMA scoping review flow diagram of the study selection process for the scoping review of human infections with an antimicrobial-resistant strain of Campylobacter species.

Characteristics of information sources

The characteristics of included articles (n = 27) are included in Table 1. Complete extracted data for all studies are included in Supplementary Table S3. All articles were published between 1998 and 2018 except for one in 1988. The most common countries included the United States (n = 6), Denmark (n = 4), Canada (n = 3), and the United Kingdom (n = 3). Study designs included cross-sectional (n = 16), case–control (n = 4), case–case–control (n = 1), and various cohort designs (n = 6). The most commonly reported age range of participants was 20–50 years, but variations in reporting details made summarising age characteristics difficult. Fourteen studies reported the gender or sex of participants, but rarely included it in the analysis, whereas the rest did not report (n = 9) or did not include females in their study (n = 4). Most articles studied gastrointestinal infections (n = 19), and the most common species included was Campylobacter jejuni (n = 22). Six studies reported results for multivariable analyses, whereas the remaining 21 only reported results from univariable analyses if at all. Often, studies reported resistance to different antimicrobials. The most reported factor results were for resistance to fluoroquinolones (n = 20) and quinolones (n = 9), while resistance to macrolides (n = 13) and tetracyclines (n = 7) were also considered.

Table 1. Key characteristics of peer-reviewed references included in the scoping review of factors related to human infections with an antimicrobial-resistant strain of Campylobacter species

a When a study design was not specified by the authors, the study design was determined by the first author during data extraction based on the reported methods.

b Infection type specified or determined during data extraction where possible; BS, blood-stream infection; GI, gastrointestinal infection; NS, not specified/could not be determined.

c Specified or calculated during data extraction where possible; comp., comparisons; cont., controls; IQR, interquartile range; Med., median; NS, not specified.

d Percentage of female versus other, specified in the article or calculated during the data extraction where possible; NS, not specified.

e CSSSC, Campylobacter Sentinel Surveillance Scheme Collaborators.

Information about factors

Reported factors related to resistant Campylobacter infections are summarised in Supplementary Table S4 and were combined into seven themes: animal contact (Figure 2), prior antimicrobial use (Figure 3), food and food preparation (Figure 4a,b), travel (Figure 5), underlying health conditions (Supplementary Table S5), water exposure (Figure 6a,b), and participant characteristics (Supplementary Table S5). Articles reporting factors regarding travel (n = 17) and participant characteristics (n = 14) were the most common. Most of the studies were conducted in a small number of high-income, westernised countries. Studies reported data for unspecified Campylobacter species as well as C. jejuni, Campylobacter coli, Campylobacter fetus, and Campylobacter lari.

Figure 2. Animal contact factors identified in studies included in the scoping review for human infections with antimicrobial-resistant Campylobacter strains compared to infection with susceptible strains, limited to studies reporting odds ratios.

Note: CSSSC, Campylobacter Sentinel Surveillance Scheme Collaborators; F, fluoroquinolone-resistant outcome; MVA, multivariable analysis result; Q, quinolone-resistant outcome; UVA, univariable analysis result

Figure 3. Prior antimicrobial use as factors identified in studies included in the scoping review for human infections with antimicrobial-resistant Campylobacter strains compared to infection with susceptible strains, limited to studies reporting odds ratios.

Note: F, fluoroquinolone-resistant outcome; MVA, multivariable analysis result; Q, quinolone-resistant outcome; UVA, univariable analysis result; UVA*, results from a study that only conducted univariable analysis.

Figure 4. Food consumption (a) and preparation (b) factors identified in studies included in the scoping review for human infections with antimicrobial-resistant Campylobacter strains compared to infection with susceptible strains, limited to studies reporting odds ratios.

Note: CSSSC, Campylobacter Sentinel Surveillance Scheme Collaborators; F, fluoroquinolone-resistant outcome; MVA, multivariable analysis result; UVA, univariable analysis result.

Figure 5. Travel factors identified in studies included in the scoping review for human infections with antimicrobial-resistant Campylobacter strains compared to infection with susceptible strains, limited to studies reporting odds ratios.

Note: CSSSC, Campylobacter Sentinel Surveillance Scheme Collaborators; F, fluoroquinolone-resistant outcome; MVA, multivariable analysis result; Q, quinolone-resistant outcome; UVA, univariable analysis result; UVA*, results from a study that only conducted a univariable analysis.

Figure 6. Key data extracted for drinking water-related (a) and swimming (b) factors identified in studies included in the scoping review for human infections with an antimicrobial-resistant Campylobacter strains compared to infection with susceptible strains, limited to studies reporting odds ratios.

Note: CSSSC, Campylobacter Sentinel Surveillance Scheme Collaborators; F, fluoroquinolone-resistant outcome; MVA, multivariable analysis result; Q, quinolone-resistant outcome; UVA, univariable analysis result; UVA*, results from a study that only conducted a univariable analysis.

Synthesis of results

Animal contact

Five articles reported animal contact as a factor for infection with fluoroquinolone-resistant strains of Campylobacter (Figure 2). Most factors, including unspecified pets, pet rodents, dogs, birds, and other domestic or animal contact, were associated with a decreased risk of infection with resistant Campylobacter [Reference Engberg, Neimann, Nielsen, Aarestrup and Fussing12, Reference Evans, Northey, Sarvotham, Hopkins, Rigby and Thomas17–Reference Cha, Mosci, Wengert, Singh, Newton, Salimnia, Lephart, Khalife, Mansfield, Rudrik and Manning19]. Zoo-animal contact was the only animal factor that was significantly associated with an increased risk [Reference Evans, Northey, Sarvotham, Hopkins, Rigby and Thomas17].

Prior antimicrobial use

Seven articles reported prior antimicrobial use as a factor [Reference Engberg, Neimann, Nielsen, Aarestrup and Fussing12, Reference Evans, Northey, Sarvotham, Hopkins, Rigby and Thomas17, Reference Gallay, Bousquet, Siret, Prouzet-Mauléon, Valk, Vaillant, Simon, Strat, Mégraud and Desenclos20–Reference Smith, Besser, Hedberg, Leano, Bender, Wicklund, Johnson, Moore and Osterholm24], but only five reported the results of the analysis. All studies with speciated isolates found that prior antimicrobial use was associated with an increased risk of infection with fluoroquinolone-resistant Campylobacter, but not all were statistically significant (Figure 3). The study with non-speciated isolates found prior antimicrobial use was associated with a lower risk, but it was not significant. The definition of prior antimicrobial use varied between studies, ranging from possession of non-prescribed antibiotics [Reference Johnson, McMullen, Hasselback, Louie, Jhangri and Saunders21] to the use of an antibiotic before specimen collection [Reference Engberg, Neimann, Nielsen, Aarestrup and Fussing12, Reference Smith, Besser, Hedberg, Leano, Bender, Wicklund, Johnson, Moore and Osterholm24]. In addition, the definition of the interval for prior antimicrobial use was a month (4 weeks) [Reference Engberg, Neimann, Nielsen, Aarestrup and Fussing12, Reference Evans, Northey, Sarvotham, Hopkins, Rigby and Thomas17, Reference Gallay, Bousquet, Siret, Prouzet-Mauléon, Valk, Vaillant, Simon, Strat, Mégraud and Desenclos20, Reference Smith, Besser, Hedberg, Leano, Bender, Wicklund, Johnson, Moore and Osterholm24, Reference Sharma, Unicomb, Forbes, Djordjevic, Valcanis, Dalton and Ferguson25], but when specified, the starting point of this interval also varied from a month prior to the onset of illness [Reference Gallay, Bousquet, Siret, Prouzet-Mauléon, Valk, Vaillant, Simon, Strat, Mégraud and Desenclos20, Reference Smith, Besser, Hedberg, Leano, Bender, Wicklund, Johnson, Moore and Osterholm24], the onset of symptoms [Reference Engberg, Neimann, Nielsen, Aarestrup and Fussing12], infection [Reference Sharma, Unicomb, Forbes, Djordjevic, Valcanis, Dalton and Ferguson25], or stool sample collection [Reference Johnson, McMullen, Hasselback, Louie, Jhangri and Saunders21].

Food and food preparation

Four articles reported many different factors related to food consumption and food handling or associated behaviours, all with fluoroquinolone resistance outcomes (Figure 4a,b) [Reference Engberg, Neimann, Nielsen, Aarestrup and Fussing12, Reference Evans, Northey, Sarvotham, Hopkins, Rigby and Thomas17–Reference Cha, Mosci, Wengert, Singh, Newton, Salimnia, Lephart, Khalife, Mansfield, Rudrik and Manning19]. There were opposing results of varying statistical significance for factors such as consumption of chicken, red meat, and other miscellaneous meats, as well as for handling of raw meat and raw chicken at home [Reference Engberg, Neimann, Nielsen, Aarestrup and Fussing12, Reference Evans, Northey, Sarvotham, Hopkins, Rigby and Thomas17–Reference Cha, Mosci, Wengert, Singh, Newton, Salimnia, Lephart, Khalife, Mansfield, Rudrik and Manning19] without any discernible patterns. When considering multivariable results, one study reported that those eating chicken had decreased risk, but increased risk when eating poultry other than chicken or turkey [Reference Engberg, Neimann, Nielsen, Aarestrup and Fussing12]. Another reported increased risk when eating chicken or pre-cooked cold meats [18]. Interestingly, two studies found that factors linked to handling [Reference Engberg, Neimann, Nielsen, Aarestrup and Fussing12] or storing of raw chicken [Reference Evans, Northey, Sarvotham, Hopkins, Rigby and Thomas17] were significantly associated with a reduced risk for infection with a fluoroquinolone-resistant strain, whereas the latter paper found no association with handling raw chicken, all from univariable analyses.

Travel

Seventeen studies reported travel-related factors related to an infection with resistant Campylobacter (Figure 5) [Reference Helms, Simonsen, Olsen and Mølbak11, Reference Engberg, Neimann, Nielsen, Aarestrup and Fussing12, Reference Evans, Northey, Sarvotham, Hopkins, Rigby and Thomas17–Reference Cha, Mosci, Wengert, Singh, Newton, Salimnia, Lephart, Khalife, Mansfield, Rudrik and Manning19, Reference Johnson, McMullen, Hasselback, Louie, Jhangri and Saunders21, Reference Smith, Besser, Hedberg, Leano, Bender, Wicklund, Johnson, Moore and Osterholm24–Reference Ricotta, Palmer, Wymore, Clogher, Oosmanally, Robinson, Lathrop, Karr, Hatch, Dunn, Ryan and Blythe34], and all found foreign travel, regardless of definition and destination country, to be significantly associated with an increased risk of infection with a fluoroquinolone-resistant strain. Of the articles that reported analysis, domestic study populations were limited to the United Kingdom [18], Wales [Reference Evans, Northey, Sarvotham, Hopkins, Rigby and Thomas17], Denmark [Reference Engberg, Neimann, Nielsen, Aarestrup and Fussing12], Canada [Reference Johnson, McMullen, Hasselback, Louie, Jhangri and Saunders21], and the United States [Reference Cha, Mosci, Wengert, Singh, Newton, Salimnia, Lephart, Khalife, Mansfield, Rudrik and Manning19, Reference Johnson, McMullen, Hasselback, Louie, Jhangri and Saunders21, Reference Smith, Besser, Hedberg, Leano, Bender, Wicklund, Johnson, Moore and Osterholm24, Reference Nelson, Smith, Vugia, Rabatsky-Ehr, Segler, Kassenborg, Zansky, Joyce, Marano, Hoekstra and Angulo30, Reference Patrick, Henao, Robinson, Geissler, Cronquist, Hanna, Hurd, Medalla, Pruckler and Mahon31]. Travel destinations included Africa, Asia, Central and South America, and Europe, but some articles conducted subanalyses on destinations within travel-only cases, which made interpretation challenging [18, Reference Smith, Besser, Hedberg, Leano, Bender, Wicklund, Johnson, Moore and Osterholm24, Reference Hakanen, Jousimies-Somer, Siitonen, Huovinen and Kotilainen29]. One study considered food and water exposure during travel but did not evaluate travel as a possible interaction [Reference Evans, Northey, Sarvotham, Hopkins, Rigby and Thomas17]. Another study compared the rate of fluoroquinolone-resistant C. jejuni infections in Finnish patients that travelled abroad; specifically comparing rates of cases from various travel destinations to those travelling to Thailand [Reference Hakanen, Jousimies-Somer, Siitonen, Huovinen and Kotilainen29]. They found that cases in Finnish residents travelling to Spain (including the Canary Islands) and Portugal had lower case rates of fluoroquinolone-resistant infections (rate ratios of 0.11 (95% CI 0.05–0.24) and 0.11 (0.07–0.16), respectively), whereas those travelling to China and India did not differ significantly from Thailand.

Water

Four articles explored factors related to water exposure, with a focus on water consumption and swimming [Reference Engberg, Neimann, Nielsen, Aarestrup and Fussing12, Reference Evans, Northey, Sarvotham, Hopkins, Rigby and Thomas17, 18, Reference Smith, Besser, Hedberg, Leano, Bender, Wicklund, Johnson, Moore and Osterholm24]. There was a large variety in the definition of water consumption-related factors and their association with increased or decreased risk of infection with fluoroquinolone-resistant strains (Figure 6a). Untreated water was associated with increased risk [Reference Smith, Besser, Hedberg, Leano, Bender, Wicklund, Johnson, Moore and Osterholm24], whereas public, tap, or private domestic water was associated with decreased risk [Reference Engberg, Neimann, Nielsen, Aarestrup and Fussing12, Reference Evans, Northey, Sarvotham, Hopkins, Rigby and Thomas17, 18]. Several bottled water (domestic- or travel-sourced) factors were associated with increased risk [Reference Evans, Northey, Sarvotham, Hopkins, Rigby and Thomas17, 18]. Generally, swimming was reported to increase the risk of infection with a resistant strain (Figure 6b).

Discussion

Summary of evidence

This scoping review identified 27 studies with factors related to human infections with an antimicrobial-resistant strain of Campylobacter and provides insight into the available literature and risks associated with these infections. Many reported specific gastrointestinal infections with C. jejuni, but there was variability in the site of infection (sample source and Campylobacter species), the AMR outcome, and subsequent factor analyses. This review identified key factors associated with infection with resistant strains, such as travel, prior antimicrobial use, animal exposure, and food- and water-related factors, but highlighted the vast heterogeneity of available data and associations with increased or decreased risk of infection with a resistant strain, as well as the gaps that could benefit from further research. Only a small number of studies reported multivariable analysis, and those that did were almost exclusively for fluoroquinolone resistance outcomes. All studies were conducted on cases from a small number of wealthy, westernised countries.

Risk factors

This review identified several important risk factors associated with human infections with resistant Campylobacter. The most consistent was foreign travel, with departure from home countries always being significantly associated with infection with a fluoroquinolone-resistant strain [Reference Engberg, Neimann, Nielsen, Aarestrup and Fussing12, Reference Evans, Northey, Sarvotham, Hopkins, Rigby and Thomas17, Reference Cha, Mosci, Wengert, Singh, Newton, Salimnia, Lephart, Khalife, Mansfield, Rudrik and Manning19, Reference Smith, Besser, Hedberg, Leano, Bender, Wicklund, Johnson, Moore and Osterholm24, Reference Sharma, Unicomb, Forbes, Djordjevic, Valcanis, Dalton and Ferguson25, Reference Nelson, Smith, Vugia, Rabatsky-Ehr, Segler, Kassenborg, Zansky, Joyce, Marano, Hoekstra and Angulo30, Reference Patrick, Henao, Robinson, Geissler, Cronquist, Hanna, Hurd, Medalla, Pruckler and Mahon31, Reference van Hees, Veldman-Ariesen, de Jongh, Tersmette and van Pelt33, Reference Ricotta, Palmer, Wymore, Clogher, Oosmanally, Robinson, Lathrop, Karr, Hatch, Dunn, Ryan and Blythe34]. Care needs to be taken when interpreting these results as only departures from a few wealthy, westernised countries were studied, with highly variable definitions of destinations. Travel is a complex variable that, in this context, is largely a proxy for several different, often unmeasured, factors in the destination country, such as water quality, food/food handling practices and microbial contamination, and potential exposure to different strains of pathogens [Reference Frost, Van Boeckel, Pires, Craig and Laxminarayan42]. Genomics and molecular epidemiology should be employed to better understand the epidemiology of antimicrobial-resistant Campylobacter infections in future observational risk-factor studies.

Antimicrobial use prior to infection was another important reported factor for infection with resistant Campylobacter. While prior antimicrobial use is recognised to select for AMR, especially in Campylobacter [43, 44], only seven of the included studies reported this factor [Reference Engberg, Neimann, Nielsen, Aarestrup and Fussing12, Reference Evans, Northey, Sarvotham, Hopkins, Rigby and Thomas17, Reference Gallay, Bousquet, Siret, Prouzet-Mauléon, Valk, Vaillant, Simon, Strat, Mégraud and Desenclos20–Reference Smith, Besser, Hedberg, Leano, Bender, Wicklund, Johnson, Moore and Osterholm24]. It is possible that many studies did not have access to these data linked to the human cases, which can be difficult to collect/obtain. It is important to note that in these studies, it represents a risk factor for infection with resistant Campylobacter compared to susceptible infection, but these observational studies cannot determine whether prior antimicrobial use is specifically selecting for development of a resistant strain in the human host as opposed to selecting for infection with a resistant over a susceptible strain. In addition to the inconsistent definitions of prior antimicrobial use, no studies reported drug dosing or duration, which would be important for future quantitative dose–response modelling. Prior antimicrobial use has been identified as a risk factor for other antimicrobial-resistant, foodborne bacterial infections, such as Salmonella Heidelberg [Reference Otto, Carson, Finley, Thomas, Reid-Smith and SA45]. Prior antimicrobial use may be due to inappropriate prescribing or over-the-counter drug access, which may represent less than optimal antimicrobial stewardship [44]. Only one included study reported a factor in this realm, possession of non-prescribed antibiotics [Reference Johnson, McMullen, Hasselback, Louie, Jhangri and Saunders21]. It is also surprising that very few medical conditions requiring antimicrobial use were explored as comorbidities in the included studies. Only three articles looked at HIV and Campylobacter and did not analyse their data beyond providing counts [Reference Perlman, Ampel, Schifman, Cohn, Patton, Aguirre, Wang and Blaser23, Reference Jenkin and Tee35, Reference Koningstein, Simonsen, Helms, Hald and Mølbak39].

Animal contact, including contact with seemingly healthy pets, has been implicated as a risk factor for AMR in humans [Reference Lloyd46–Reference Seepersadsingh and Adesiyun48], as well as general human infections with Campylobacter. Resistant Campylobacter has been isolated from cats and dogs, and pet store puppies have been implicated in a large extensively drug-resistant human outbreak of C. jejuni [Reference Joseph, Watkins, Chen, Tagg, Bennett, Caidi, Folster, Laughlin, Koski, Silver, Stevenson, Robertson, Pruckler, Nichols, Pouseele, Carleton, Basler, Friedman, Geissler, Hise and Aubert49, Reference Acke, McGill, Quinn, Jones, Fanning and Whyte50]. Conversely, the included studies found that in most cases, animal contact was associated with a reduced risk of infection with a resistant strain compared to susceptible Campylobacter [Reference Engberg, Neimann, Nielsen, Aarestrup and Fussing12, Reference Evans, Northey, Sarvotham, Hopkins, Rigby and Thomas17–Reference Cha, Mosci, Wengert, Singh, Newton, Salimnia, Lephart, Khalife, Mansfield, Rudrik and Manning19, Reference Smith, Besser, Hedberg, Leano, Bender, Wicklund, Johnson, Moore and Osterholm24], with the one exception being zoo animal contact [Reference Evans, Northey, Sarvotham, Hopkins, Rigby and Thomas17]. It may be that in these studies, the infecting strains from different animal sources have varying antimicrobial susceptibilities, but these observational study designs were not able to distinguish this, pointing to the need for genomics and molecular epidemiology to better understand these identified associations.

Contaminated foods, especially chicken meat, are known risk factors for infection with Campylobacter [4, Reference Olson, Ethelberg, van Pelt, Tauxe, Nachamkin, Szymanski and Blaser51], but only four studies included food-related factors in their analysis [Reference Engberg, Neimann, Nielsen, Aarestrup and Fussing12, Reference Evans, Northey, Sarvotham, Hopkins, Rigby and Thomas17–Reference Cha, Mosci, Wengert, Singh, Newton, Salimnia, Lephart, Khalife, Mansfield, Rudrik and Manning19]. There is evidence of AMR spreading to humans through the food chain, specifically broiler chickens in the case of Campylobacter, where antimicrobial use on farms may initially select for AMR [Reference Murphy, Carson, Smith, Chapman, Marrotte, McCann, Primeau, Sharma and Parmley16, Reference Founou, Founou and Essack52]. However, the results of food-related factors, including chicken, from included studies are mixed and variable. There are several potential reasons for this, including different study populations and potential confounding, intervening, or unmeasured factors, many of which were not considered in studies that did not conduct multivariable analyses. Many studies were cross-sectional, making causal inferences for these relationships challenging. Statistically significant multivariable results for food from two studies were discordant in that one found eating chicken protective while eating other poultry was a risk factor [Reference Engberg, Neimann, Nielsen, Aarestrup and Fussing12]. The other found eating chicken or pre-cooked cold meats to be a risk factor [18]. The food handling results were largely protective, but only from univariable analyses [Reference Engberg, Neimann, Nielsen, Aarestrup and Fussing12, Reference Evans, Northey, Sarvotham, Hopkins, Rigby and Thomas17]. Some risk factors for infection with Campylobacter may be independent of the susceptibility of the strain, and interventions that reduce the overall prevalence or concentration of Campylobacter in food or water could also reduce the risk of infection with a resistant strain, yet these types of factors were not studied [Reference Maillard, Bloomfield, Courvalin, Essack, Gandra, Gerba, Rubino and Scott53–Reference Harris, Karchmer, Carmeli and Samore56]. It is also possible that risk factors for infection with a resistant strain would differ if there was more global representation among the studies included in the review, as different antimicrobials may be used and in some areas, access to these drugs can be over-the-counter for humans and animals [Reference Torres, Chibi, Kuupiel, Solomon, Mashamba-Thompson and Middleton57, Reference Nadimpalli, Delarocque-Astagneau, Love, Price, Huynh, Collard, Lay, Borand, Ndir, Walsh and Guillemot58]. Lastly, while only one study included a factor related to vegetables [18], antimicrobial use in plant agriculture and the use of manure from animals as a fertiliser for crops may increase the risk of resistant organisms on produce [44, Reference Haynes, Ramwell, Griffiths, Walker and Smith59, Reference McCubbin, Anholt, de Jong, Ida, Nóbrega, Kastelic, Conly, Götte, McAllister, Orsel, Lewis, Jackson, Plastow, Wieden, McCoy, Leslie, Robinson, Hardcastle, Hollis, Ashbolt, Checkley, Tyrrell, Buret, Rennert-May, Goddard, Otto and Barkema60].

Water consumption and contact are also recognised as potential risk factors for Campylobacter infection [Reference Olson, Ethelberg, van Pelt, Tauxe, Nachamkin, Szymanski and Blaser51]; however, only four studies reported water-related factors with marked variability in the definition and results [Reference Engberg, Neimann, Nielsen, Aarestrup and Fussing12, Reference Evans, Northey, Sarvotham, Hopkins, Rigby and Thomas17, 18, Reference Smith, Besser, Hedberg, Leano, Bender, Wicklund, Johnson, Moore and Osterholm24]. Water contamination with Campylobacter varies regionally; however, little is known about contamination with fluoroquinolone-resistant versus susceptible Campylobacter. Fluoroquinolone resistance is largely mutational in Campylobacter, rather than by acquisition through mobile genetic elements [Reference Luangtongkum, Jeon, Han, Plummer, Logue and Zhang10], meaning that antimicrobial use in humans or animals and selection for resistant strains that contaminate water is the more likely source compared to acquisition in the environment. None of these studies evaluated this potential linkage, which would require more data about antimicrobial use and genomics.

Overall considerations

Antimicrobial resistance is a complex, population-level issue across One Health sectors that is driven by individual, regional, and global activities [Reference McCubbin, Anholt, de Jong, Ida, Nóbrega, Kastelic, Conly, Götte, McAllister, Orsel, Lewis, Jackson, Plastow, Wieden, McCoy, Leslie, Robinson, Hardcastle, Hollis, Ashbolt, Checkley, Tyrrell, Buret, Rennert-May, Goddard, Otto and Barkema60]. These studies reported factors at the individual level; however, population-level influences such as environmental sources, cleanliness of water, crop and animal agriculture, the spread of resistant organisms, the overall availability of antimicrobials, and the prescribing nature of the physicians and veterinarians are important to consider [44, Reference Founou, Founou and Essack52, Reference McCubbin, Anholt, de Jong, Ida, Nóbrega, Kastelic, Conly, Götte, McAllister, Orsel, Lewis, Jackson, Plastow, Wieden, McCoy, Leslie, Robinson, Hardcastle, Hollis, Ashbolt, Checkley, Tyrrell, Buret, Rennert-May, Goddard, Otto and Barkema60]. Identified factors and associations with risk of infection with resistant Campylobacter were variable, and generalisability was largely limited to wealthy, western countries. Resistance does not recognise borders and AMR surveillance in all countries linked to better patient metadata and genomics are needed to better understand these factors such as travel, prior antimicrobial use, food, and water [Reference Frost, Van Boeckel, Pires, Craig and Laxminarayan42]. In addition to individual patient-level factors, population-level research using a One Health approach that includes water quality, food safety and preparation, and antimicrobial use would expand our knowledge of risk-prevention strategies for infection with resistant Campylobacter [Reference McCubbin, Anholt, de Jong, Ida, Nóbrega, Kastelic, Conly, Götte, McAllister, Orsel, Lewis, Jackson, Plastow, Wieden, McCoy, Leslie, Robinson, Hardcastle, Hollis, Ashbolt, Checkley, Tyrrell, Buret, Rennert-May, Goddard, Otto and Barkema60, Reference Schechner, Temkin, Harbarth, Carmeli and Schwaber61].

Care was taken to state these factors as associations with increased or decreased risk of infection with a resistant strain. The most common study design (cross-sectional) may suffer from reverse causation [Reference Levin62]. Additionally, when evaluating case–control studies, care must be taken when selecting controls to link the factor for AMR and to control for bias [Reference Kaye, Harris, Samore and Carmeli54–Reference Harris, Karchmer, Carmeli and Samore56, Reference Schechner, Temkin, Harbarth, Carmeli and Schwaber61]. The cohort study design controls for the temporality of events and provides the opportunity to measure multiple outcomes, but it is not well suited for the relatively rare incidence of infection with a resistant strain of Campylobacter [Reference Schechner, Temkin, Harbarth, Carmeli and Schwaber61].

We chose patients infected with antimicrobial-susceptible strains as our comparison group, which was appropriate for our research question to identify risk factors for infection with a resistant strain among all infections, but may have different results and interpretations than in comparison to healthy patients [Reference Schechner, Temkin, Harbarth, Carmeli and Schwaber61]. This comparison group may not be advantageous for identifying the strength of association for all risk factors of resistant Campylobacter infections, especially prior antimicrobial use [Reference Harris, Karchmer, Carmeli and Samore56]. Case–case–control studies for infection with resistant organisms compare those infected with a resistant strain to those with a susceptible strain and those who are healthy with a negative test, which allows researchers to better control for bias [Reference Kaye, Harris, Samore and Carmeli54].

Our work yielded less insight into the global understanding of factors associated with human infections with antimicrobial-resistant Campylobacter than expected. The dearth of published studies included in our review in any low- and middle-income countries should be a call to action for research funders and government surveillance programmes alike [Reference Iskandar, Molinier, Hallit, Sartelli, Hardcastle, Haque, Lugova, Dhingra, Sharma, Islam, Mohammed, Mohamed, Hanna, Hajj, NAH, Salameh and Roques63]. Tackling AMR requires a One Health approach at the global level [Reference McCubbin, Anholt, de Jong, Ida, Nóbrega, Kastelic, Conly, Götte, McAllister, Orsel, Lewis, Jackson, Plastow, Wieden, McCoy, Leslie, Robinson, Hardcastle, Hollis, Ashbolt, Checkley, Tyrrell, Buret, Rennert-May, Goddard, Otto and Barkema60], and the lack of investment, for example, in AMR surveillance in all but developed countries speaks to the stark gaps present in global AMR research, surveillance, and understanding with a need for an equity lens to be applied to future surveillance and policy. Future use of case–case–control or case–control–control study designs is preferred to examine factors related to infection with resistant strains [Reference Kaye, Harris, Samore and Carmeli54]. Conducting and reporting multivariable analyses is very important as simple univariable associations fail to account for confounding or identify interactions between related factors. In addition, reporting all factors assessed for association, not just those found to be statistically significant in uni- and multivariable models, would provide the complete picture.

Limitations

We aimed to minimise the possibility of not capturing all eligible articles for our review, a risk inherent in any literature review, by following a rigorous, systematic approach [Reference Pham, Rajić, Greig, Sargeant, Papadopoulos and McEwen64]. The factor list identified in this review is by no means exhaustive; it is likely there are factors that were outside the scope of our search or for which research is likely lacking. Our protocol also excluded articles primarily focused on identifying molecular and genetic similarities between human Campylobacter isolates with AMR with those from other sources such as animals and water. The synthesis of such literature was beyond the scope of this study but would be an important future contribution to the understanding of human infections with resistant Campylobacter. Additionally, excluding non-English articles and publishing bias against null findings has the potential to influence the factors included in our review [Reference Aromataris and Munn14]. There is limited global generalisability because there were no studies from Africa and South America and 24 out of 27 studies were in westernised, high-income countries. The lack of multivariable results for most studies, and, in particular, a seeming lack of identified or assessed interactions between factors, may fail to capture the complicated, interconnected nature of the impact of multiple factors on the risk of infection with resistant strains.

Conclusions

This scoping review mapped the current literature that investigated and quantified risk or protective factors related to a human infection with antimicrobial-resistant Campylobacter compared to susceptible infections. Travel, prior antimicrobial use, food consumption and handling, water consumption and exposure, and animal contact were important factors associated with the risk of infection with a resistant strain. The heterogeneity of the results, focus on fluoroquinolone-resistant outcomes, and lack of multivariable analyses made identifying concrete associations with risk factors challenging but highlighted areas for potential future research. The study of AMR in Campylobacter would benefit from an interdisciplinary, One Health research approach that expands to include research in low- and middle-income countries.

Supplementary material

The supplementary material for this article can be found at http://doi.org/10.1017/S0950268823000742.

Data availability statement

The search protocol and all extracted data are provided in the Supplementary Material. All the Supplementary Material is available on the Cambridge Core website.

Acknowledgements

We thank Sandra Campbell, a research librarian from the University of Alberta, for her assistance in developing the search strings and protocol. We also thank the second reviewers Amreen Babujee, Soumayadita Ghosh, and Julia Grochowski.

Author contribution

See the summary included with co-authors in the submission portal.

Financial support

This study was funded through a grant from the Alberta Ministry of Technology and Innovation, by the Major Innovation Fund Program for the AMR – One Health Consortium, and the Genomics Research and Development Initiative Project on Antimicrobial Resistance.

Competing interest

The authors have no competing interest.

References

World Health Organization (2015) WHO Estimates of the Global Burden of Foodborne Diseases 2007–2015 [Internet]. Geneva, Switzerland: World Health Organization. Available at https://apps.who.int/iris/bitstream/handle/10665/199350/?sequence=1 (accessed 28 June 2022).Google Scholar
Thomas, MK, Murray, R, Flockhart, L, Pintar, K, Pollari, F, Fazil, A, Nesbitt, A and Marshall, B (2013) Estimates of the burden of foodborne illness in Canada for 30 specified pathogens and unspecified agents, circa 2006. Foodborne Pathogens and Disease 10, 639–648. https://doi.org/10.1089/fpd.2012.1389CrossRefGoogle ScholarPubMed
Moore, JE, Corcoran, D, Dooley, JSG, Fanning, S, Lucey, B, Matsuda, M, McDowell, DA, Mégraud, F, Millar, BC, O’Mahony, R, O’Riordan, L, O’Rourke, M, Rao, JR, Rooney, PJ, Sails, A and Whyte, P (2005) Campylobacter. Veterinary Research 36, 351–382. https://doi.org/10.1051/vetres:2005012CrossRefGoogle ScholarPubMed
Centers for Disease Control and Prevention (2017) Campylobacter (Campylobacteriosis) [Internet]. Available at https://www.cdc.gov/campylobacter/technical.html (accessed 28 June 2022).Google Scholar
Nachamkin, I, Allos, BM and Ho, T (1998) Campylobacter species and Guillain–Barré syndrome. Clinical Microbiology Reviews 11, 555–567. https://doi.org/10.1128/cmr.11.3.555CrossRefGoogle ScholarPubMed
Facciolà, A, Riso, R., Avventuroso, E., Visalli, G., Delia, S.A. and Laganà, P. (2017) Campylobacter: From microbiology to prevention. Journal of Preventive Medicine and Hygiene 58, E79–E92.Google ScholarPubMed
Ternhag, A, Asikainen, T, Giesecke, J and Ekdahl, K (2007) A meta-analysis on the effects of antibiotic treatment on duration of symptoms caused by infection with Campylobacter species. Clinical Infectious Diseases 44, 696–700. https://doi.org/10.1086/509924CrossRefGoogle ScholarPubMed
Deckert, AE, Reid-Smith, RJ, Tamblyn, SE, Morrell, L, Seliske, P, Jamieson, FB, Irwin, R, Dewey, CE, Boerlin, P and McEwen, SA (2013) Antimicrobial resistance and antimicrobial use associated with laboratory-confirmed cases of Campylobacter infection in two health units in Ontario. Canadian Journal of Infectious Diseases and Medical Microbiology 24, e16–e21. https://doi.org/10.1155/2013/176494CrossRefGoogle ScholarPubMed
Dougherty, B, Finley, R, Marshall, B, Dumoulin, D, Pavletic, A, Dow, J, Hluchy, T, Asplin, R and Stone, J (2020) An analysis of antibiotic prescribing practices for enteric bacterial infections within FoodNet Canada sentinel sites. Journal of Antimicrobial Chemotherapy 75, 1061–1067. https://doi.org/10.1093/jac/dkz525CrossRefGoogle ScholarPubMed
Luangtongkum, T, Jeon, B, Han, J, Plummer, P, Logue, CM and Zhang, Q (2009) Antibiotic resistance in Campylobacter: Emergence, transmission and persistence. Future Microbiology 4, 189–200. https://doi.org/10.2217/17460913.4.2.189CrossRefGoogle ScholarPubMed
Helms, M, Simonsen, J, Olsen, KEP and Mølbak, K (2005) Adverse health events associated with antimicrobial drug resistance in Campylobacter species: A registry-based cohort study. Journal of Infectious Diseases 191, 1050–1055.CrossRefGoogle ScholarPubMed
Engberg, J, Neimann, J, Nielsen, EM, Aarestrup, FM and Fussing, V (2004) Quinolone-resistant Campylobacter infections: Risk factors and clinical consequences. Emerging Infectious Diseases 10, 1056–1063.CrossRefGoogle ScholarPubMed
Wassenaar, TM, Kist, M and de Jong, A (2007) Re-analysis of the risks attributed to ciprofloxacin-resistant Campylobacter jejuni infections. International Journal of Antimicrobial Agents 30, 195–201. https://doi.org/10.1016/j.ijantimicag.2007.01.019CrossRefGoogle ScholarPubMed
Aromataris, E and Munn, Z (2020) Chapter 11: Scoping reviews [Internet]. In JBI Manual for Evidence Synthesis. Adelaide, SA: Joanna Briggs Institute. Available at https://jbi-global-wiki.refined.site/space/MANUAL/4687342/Chapter+11%3A+Scoping+reviews (accessed 28 June 2022).Google Scholar
Tricco, AC, Lillie, E, Zarin, W, O’Brien, KK, Colquhoun, H, Levac, D, Moher, D, MDJ, Peters, Horsley, T, Weeks, L, Hempel, S, Akl, EA, Chang, C, McGowan, J, Stewart, L, Hartling, L, Aldcroft, A, Wilson, MG, Garritty, C, Lewin, S, Godfrey, CM, Macdonald, MT, Langlois, EV, Soares-Weiser, K, Moriarty, J, Clifford, T, Tunçalp, Ö and Straus, SE (2018) PRISMA extension for scoping reviews (PRISMA-ScR): Checklist and explanation. Annals of Internal Medicine 169, 467–473.CrossRefGoogle ScholarPubMed
Murphy, CP, Carson, C, Smith, BA, Chapman, B, Marrotte, J, McCann, M, Primeau, C, Sharma, P and Parmley, EJ (2018) Factors potentially linked with the occurrence of antimicrobial resistance in selected bacteria from cattle, chickens and pigs: A scoping review of publications for use in modelling of antimicrobial resistance (IAM.AMR Project). Zoonoses and Public Health 65, 957–971. https://doi.org/10.1111/zph.12515CrossRefGoogle ScholarPubMed
Evans, MR, Northey, G, Sarvotham, TS, Hopkins, AL, Rigby, CJ and Thomas, DR (2009) Risk factors for ciprofloxacin-resistant Campylobacter infection in Wales. Journal of Antimicrobial Chemotherapy 64, 424–427. http://doi.org/10.1093/jac/dkp179CrossRefGoogle ScholarPubMed
Campylobacter Sentinel Surveillance Scheme Collaborators (2002) Ciprofloxacin resistance in Campylobacter jejuni: Case–case analysis as a tool for elucidating risks at home and abroad. Journal of Antimicrobial Chemotherapy 50, 561–568.CrossRefGoogle Scholar
Cha, W, Mosci, R, Wengert, SL, Singh, P, Newton, DW, Salimnia, H, Lephart, P, Khalife, W, Mansfield, LS, Rudrik, JT and Manning, SD (2016) Antimicrobial susceptibility profiles of human Campylobacter jejuni isolates and association with phylogenetic lineages. Frontiers in Microbiology 7, 589. https://doi.org/10.3389/fmicb.2016.00589CrossRefGoogle ScholarPubMed
Gallay, A, Bousquet, V, Siret, V, Prouzet-Mauléon, V, Valk, H, Vaillant, V, Simon, F, Strat, YL, Mégraud, F and Desenclos, JC (2008) Risk factors for acquiring sporadic Campylobacter infection in France: Results from a national case–control study. The Journal of Infectious Diseases 197, 1477–1484. https://doi.org/10.1086/587644CrossRefGoogle ScholarPubMed
Johnson, JYM, McMullen, LM, Hasselback, P, Louie, M, Jhangri, G and Saunders, LD (2008) Risk factors for ciprofloxacin resistance in reported Campylobacter infections in southern Alberta. Epidemiology and Infection 136, 903–912. http://doi.org/10.1017/S0950268807009296CrossRefGoogle ScholarPubMed
Lu, PL, Hsueh, PR, Hung, CC, Chang, SC, Luh, KT and Lee, CY (2000) Bacteremia due to Campylobacter species: High rate of resistance to macrolide and quinolone antibiotics. Journal of the Formosan Medical Association 99, 612–617.Google ScholarPubMed
Perlman, DM, Ampel, NM, Schifman, RB, Cohn, DL, Patton, CM, Aguirre, ML, Wang, WL and Blaser, MJ (1988) Persistent Campylobacter jejuni infections in patients infected with human immunodeficiency virus (HIV). Annals of Internal Medicine 108, 540–546.CrossRefGoogle ScholarPubMed
Smith, KE, Besser, JM, Hedberg, CW, Leano, FT, Bender, JB, Wicklund, JH, Johnson, BP, Moore, KA and Osterholm, MT (1999) Quinolone-resistant Campylobacter jejuni infections in Minnesota, 1992–1998. New England Journal of Medicine 340, 1525–1532. http://doi.org/10.1056/NEJM199905203402001CrossRefGoogle ScholarPubMed
Sharma, H, Unicomb, L, Forbes, W, Djordjevic, S, Valcanis, M, Dalton, C and Ferguson, J (2003) Antibiotic resistance in Campylobacter jejuni isolated from humans in the Hunter Region, New South Wales. Communicable Diseases Intelligence 27 Suppl, S80–S88.Google ScholarPubMed
Bottieau, E, Clerinx, J., Vlieghe, E., van Esbroeck, M., Jacobs, J., van Gompel, A. and van den Ende, J. (2011) Epidemiology and outcome of Shigella, Salmonella and Campylobacter infections in travellers returning from the tropics with fever and diarrhoea. Acta Clinica Belgica 66, 191–195. http://doi.org/10.2143/ACB.66.3.2062545Google ScholarPubMed
Feodoroff, B, Ellström, P, Hyytiäinen, H, Sarna, S, Hänninen, M-L and Rautelin, H (2010) Campylobacter jejuni isolates in Finnish patients differ according to the origin of infection. Gut Pathogens 2, 22. https://doi.org/10.1186/1757-4749-2-22CrossRefGoogle Scholar
Ghunaim, H, Behnke, JM, Aigha, I, Sharma, A, Doiphode, SH, Deshmukh, A and Abu-Madi, MM (2015) Analysis of resistance to antimicrobials and presence of virulence/stress response genes in Campylobacter isolates from patients with severe diarrhoea. PLoS One 10, e0119268. http://doi.org/10.1371/journal.pone.0119268CrossRefGoogle ScholarPubMed
Hakanen, A, Jousimies-Somer, H, Siitonen, A, Huovinen, P and Kotilainen, P (2003) Fluoroquinolone resistance in Campylobacter jejuni isolates in travelers returning to Finland: Association of ciprofloxacin resistance to travel destination. Emerging Infectious Diseases 9, 267–270.CrossRefGoogle Scholar
Nelson, JM, Smith, KE, Vugia, DJ, Rabatsky-Ehr, T, Segler, SD, Kassenborg, HD, Zansky, SM, Joyce, K, Marano, N, Hoekstra, RM and Angulo, FJ (2004) Prolonged diarrhea due to ciprofloxacin-resistant Campylobacter infection. The Journal of Infectious Diseases 190, 1150–1157. http://doi.org/10.1086/423282CrossRefGoogle ScholarPubMed
Patrick, ME, Henao, OL, Robinson, T, Geissler, AL, Cronquist, A, Hanna, S, Hurd, S, Medalla, F, Pruckler, J and Mahon, BE (2018) Features of illnesses caused by five species of Campylobacter: Foodborne diseases active surveillance network (FoodNet) – 2010–2015. Epidemiology and Infection 146, 1–10. http://doi.org/10.1017/S0950268817002370CrossRefGoogle ScholarPubMed
Skjot-Rasmussen, L, Ethelberg, S, Emborg, H-D, Agersø, Y, Larsen, LS, Nordentoft, S, Olsen, SS, Ejlertsen, T, Holt, H, Nielsen, EM and Hammerum, AM (2009) Trends in occurrence of antimicrobial resistance in Campylobacter jejuni isolates from broiler chickens, broiler chicken meat, and human domestically acquired cases and travel associated cases in Denmark. International Journal of Food Microbiology 131, 277–279. http://doi.org/10.1016/j.ijfoodmicro.2009.03.006CrossRefGoogle ScholarPubMed
van Hees, BC, Veldman-Ariesen, MJ, de Jongh, BM, Tersmette, M and van Pelt, W (2007) Regional and seasonal differences in incidence and antibiotic resistance of Campylobacter from a nationwide surveillance study in the Netherlands: An overview of 2000–2004. Clinical Microbiology and Infection 13, 305–310. https://doi.org/10.1111/j.1469-0691.2006.01643.xCrossRefGoogle Scholar
Ricotta, EE, Palmer, A, Wymore, K, Clogher, P, Oosmanally, N, Robinson, T, Lathrop, S, Karr, J, Hatch, J, Dunn, J, Ryan, P and Blythe, D (2014) Epidemiology and antimicrobial resistance of international travel-associated Campylobacter infections in the United States, 2005–2011. American Journal of Public Health 104, e108–e114. https://doi.org/10.2105/ajph.2013.301867CrossRefGoogle ScholarPubMed
Jenkin, GA and Tee, W (1998) Campylobacter upsaliensis-associated diarrhea in human immunodeficiency virus-infected patients. Clinical Infectious Diseases 27, 816–821. http://doi.org/10.1086/514957CrossRefGoogle ScholarPubMed
Kownhar, H, Shankar, EM, Rajan, R, Vengatesan, A and Rao, UA (2007) Prevalence of Campylobacter jejuni and enteric bacterial pathogens among hospitalized HIV infected versus non-HIV infected patients with diarrhoea in southern India. Scandinavian Journal of Infectious Diseases 39, 862–866. http://doi.org/10.1080/00365540701393096CrossRefGoogle ScholarPubMed
Gaudreau, C and Michaud, S (2003) Cluster of erythromycin- and ciprofloxacin-resistant Campylobacter jejuni subsp. jejuni from 1999 to 2001 in men who have sex with men, Quebec, Canada. Clinical Infectious Diseases 37, 131–136. http://doi.org/10.1086/375221CrossRefGoogle ScholarPubMed
Gaudreau, C, Rodrigues-Coutlée, S, Pilon, PA, Coutlée, F and Bekal, S (2015) Long-lasting outbreak of erythromycin- and ciprofloxacin-resistant Campylobacter jejuni subspecies jejuni from 2003 to 2013 in men who have sex with men, Quebec, Canada. Clinical Infectious Diseases 61, 1549–1552. http://doi.org/10.1093/cid/civ570CrossRefGoogle ScholarPubMed
Koningstein, M, Simonsen, J, Helms, M, Hald, T and Mølbak, K (2011) Antimicrobial use: A risk factor or a protective factor for acquiring campylobacteriosis? Clinical Infectious Diseases 53, 644–650. https://doi.org/10.1093/cid/cir504CrossRefGoogle ScholarPubMed
Moore, JE, McLernon, P, Xu, J, Murphy, PG and Wareing, D (2002) Characterisation of fluoroquinolone-resistant Campylobacter species isolated from human beings and chickens. The Veterinary Record 150, 518–520. http://doi.org/10.1136/vr.150.16.518CrossRefGoogle ScholarPubMed
Uzunovic-Kamberovic, S, Zorman, T, Berce, I, Herman, L and Možina, SS (2009) Comparison of the frequency and the occurrence of antimicrobial resistance among C. jejuni and C. coli isolated from human infections, retail poultry meat and poultry in Zenica-Doboj Canton, Bosnia and Herzegovina. Medicinski Glasnik 6, 173–180.Google Scholar
Frost, I, Van Boeckel, TP, Pires, J, Craig, J and Laxminarayan, R (2019) Global geographic trends in antimicrobial resistance: The role of international travel. Journal of Travel Medicine 26, taz036. https://doi.org/10.1093/jtm/taz036CrossRefGoogle ScholarPubMed
World Health Organization (2019) Antimicrobial Resistance [Internet]. Geneva, Switzerland: World Health Organization. Available at https://www.who.int/health-topics/antimicrobial-resistance (accessed 28 June 2022).Google Scholar
Council of Canadian Academies (2019) When Antibiotics Fail: The Expert Panel on the Potential Social-Economic Impacts of Antimicrobial Resistance in Canada [Internet]. Ottawa, ON: Council of Canadian Academies. Available at https://cca-reports.ca/reports/the-potential-socio-economic-impacts-of-antimicrobial-resistance-in-canada/ (accessed 28 June 2022).Google Scholar
Otto, SJG, Carson, CA, Finley, RL, Thomas, MK, Reid-Smith, RJ and SA, McEwen (2014) Estimating the number of human cases of ceftiofur-resistant Salmonella enterica serovar Heidelberg in Quebec and Ontario, Canada. Clinical Infectious Diseases 59, 1281–1290. https://doi.org/10.1093/cid/ciu496CrossRefGoogle ScholarPubMed
Lloyd, DH (2007) Reservoirs of antimicrobial resistance in pet animals. Clinical Infectious Diseases 45, S148–S152. https://doi.org/10.1086/519254CrossRefGoogle ScholarPubMed
Pomba, C, Rantala, M, Greko, C, Baptiste, KE, Catry, B, van Duijkeren, E, Mateus, A, Moreno, MA, Pyörälä, S, Ružauskas, M, Sanders, P, Teale, C, Threlfall, EJ, Kunsagi, Z, Torren-Edo, J, Jukes, H and Törneke, K (2016) Public health risk of antimicrobial resistance transfer from companion animals. Journal of Antimicrobial Chemotherapy 72, 957––968. https://doi.org/10.1093/jac/dkw481Google Scholar
Seepersadsingh, N andAdesiyun, AA (2003) Prevalence and antimicrobial resistance of Salmonella spp. in pet mammals, reptiles, fish aquarium water, and birds in Trinidad. Journal of Veterinary Medicine Series B 50, 488–493. https://doi.org/10.1046/j.0931-1793.2003.00710.xCrossRefGoogle ScholarPubMed
Joseph, LA, Watkins, LKF, Chen, J, Tagg, KA, Bennett, C, Caidi, H, Folster, JP, Laughlin, ME, Koski, L, Silver, R, Stevenson, L, Robertson, S, Pruckler, J, Nichols, M, Pouseele, H, Carleton, HA, Basler, C, Friedman, CR, Geissler, A, Hise, KB and Aubert, RD (2020) Comparison of molecular subtyping and antimicrobial resistance detection methods used in a large multistate outbreak of extensively drug-resistant Campylobacter jejuni infections linked to pet store puppies. Journal of Clinical Microbiology 58, e00771-20. https://doi.org/10.1128/jcm.00771-20CrossRefGoogle Scholar
Acke, E, McGill, K, Quinn, T, Jones, BR, Fanning, S and Whyte, P (2009) Antimicrobial resistance profiles and mechanisms of resistance in Campylobacter jejuni isolates from pets. Foodborne Pathogens and Disease 6, 705–710.CrossRefGoogle ScholarPubMed
Olson, CK, Ethelberg, S, van Pelt, W and Tauxe, RV (2008) Epidemiology of Campylobacter jejuni infections in industrialized nations. In Nachamkin, I, Szymanski, CM and Blaser, MJ (eds), Campylobacter, 3rd edn. Washington, DC: ASM Press, pp. 163–189.Google Scholar
Founou, LL, Founou, RC and Essack, SY (2016) Antibiotic resistance in the food chain: A developing country-perspective. Frontiers in Microbiology 7, 1881. https://doi.org/10.3389/fmicb.2016.01881CrossRefGoogle ScholarPubMed
Maillard, J-Y, Bloomfield, SF, Courvalin, P, Essack, SY, Gandra, S, Gerba, CP, Rubino, JR and Scott, EA (2020) Reducing antibiotic prescribing and addressing the global problem of antibiotic resistance by targeted hygiene in the home and everyday life settings: A position paper. American Journal of Infection Control 48, 1090–1099. https://doi.org/10.1016/j.ajic.2020.04.011CrossRefGoogle ScholarPubMed
Kaye, KS, Harris, AD, Samore, M and Carmeli, Y (2005) The case–case–control study design: Addressing the limitations of risk factor studies for antimicrobial resistance. Infection Control & Hospital Epidemiology 26, 346–351. https://doi.org/10.1086/502550CrossRefGoogle ScholarPubMed
Harris, AD, Carmeli, Y, Samore, MH, Kaye, KS and Perencevich, E (2005) Impact of severity of illness bias and control group misclassification bias in case–control studies of antimicrobial-resistant organisms. Infection Control & Hospital Epidemiology 26, 342–345. https://doi.org/10.1086/502549CrossRefGoogle ScholarPubMed
Harris, AD, Karchmer, TB, Carmeli, Y and Samore, MH (2001) Methodological principles of case–control studies that analyzed risk factors for antibiotic resistance: A systematic review. Clinical Infectious Diseases 32, 1055–1061. https://doi.org/10.1086/319600CrossRefGoogle ScholarPubMed
Torres, NF, Chibi, B, Kuupiel, D, Solomon, VP, Mashamba-Thompson, TP and Middleton, LE (2021) The use of non-prescribed antibiotics; prevalence estimates in low-and-middle-income countries. A systematic review and meta-analysis. Archives of Public Health 79, 2. https://doi.org/10.1186/s13690-020-00517-9CrossRefGoogle ScholarPubMed
Nadimpalli, M, Delarocque-Astagneau, E, Love, DC, Price, LB, Huynh, B-T, Collard, J-M, Lay, KS, Borand, L, Ndir, A, Walsh, TR, Guillemot, D and Bacterial Infections and Antibiotic-Resistant Diseases among Young Children in Low-Income Countries (BIRDY) Study Group (2018) Combating global antibiotic resistance: Emerging one health concerns in lower- and middle-income countries. Clinical Infectious Diseases 66, 963–969. https://doi.org/10.1093/cid/cix879CrossRefGoogle ScholarPubMed
Haynes, E, Ramwell, C, Griffiths, T, Walker, D and Smith, J (2020) Review of antibiotic use in crops, associated risk of antimicrobial resistance and research gaps [Internet]. Report to the Department for Environment, Food and Rural Affairs (Defra) and the Food Standards Agency (FSA), FS301082. Available at https://www.food.gov.uk/research/antimicrobial-resistance/review-of-antibiotic-use-in-crops-associated-risk-of-antimicrobial-resistance-and-research-gaps.CrossRefGoogle Scholar
McCubbin, KD, Anholt, RM, de Jong, E, Ida, JA, Nóbrega, DB, Kastelic, JP, Conly, JM, Götte, M, McAllister, TA, Orsel, K, Lewis, I, Jackson, L, Plastow, G, Wieden, HJ, McCoy, K, Leslie, M, Robinson, JL, Hardcastle, L, Hollis, A, Ashbolt, NJ, Checkley, S, Tyrrell, GJ, Buret, AG, Rennert-May, E, Goddard, E, Otto, SJG, Barkema, HW (2021) Knowledge gaps in the understanding of antimicrobial resistance in Canada. Frontiers in Public Health 9, 726484.CrossRefGoogle ScholarPubMed
Schechner, V, Temkin, E, Harbarth, S, Carmeli, Y and Schwaber, MJ (2013) Epidemiological interpretation of studies examining the effect of antibiotic usage on resistance. Clinical Microbiology Reviews 26, 289–307. https://doi.org/10.1128/cmr.00001-13CrossRefGoogle ScholarPubMed
Levin, KA (2006) Study design III: Cross-sectional studies. Evidence-Based Dentistry 7, 24–25. https://doi.org/10.1038/sj.ebd.6400375CrossRefGoogle ScholarPubMed
Iskandar, K, Molinier, L, Hallit, S, Sartelli, M, Hardcastle, TC, Haque, M, Lugova, H, Dhingra, S, Sharma, P, Islam, S, Mohammed, I, Mohamed, IN, Hanna, PA, Hajj, SE, NAH, Jamaluddin, Salameh, P and Roques, C (2021) Surveillance of antimicrobial resistance in low- and middle-income countries: A scattered picture. Antimicrobial Resistance & Infection Control 10, 63. https://doi.org/10.1186/s13756-021-00931-wCrossRefGoogle ScholarPubMed
Pham, MT, Rajić, A, Greig, JD, Sargeant, JM, Papadopoulos, A and McEwen, SA (2014) A scoping review of scoping reviews: Advancing the approach and enhancing the consistency. Research Synthesis Methods 5, 371–385. https://doi.org/10.1002/jrsm.1123CrossRefGoogle ScholarPubMed
Figure 0

Figure 1. PRISMA scoping review flow diagram of the study selection process for the scoping review of human infections with an antimicrobial-resistant strain of Campylobacter species.

Figure 1

Table 1. Key characteristics of peer-reviewed references included in the scoping review of factors related to human infections with an antimicrobial-resistant strain of Campylobacter species

Figure 2

Figure 2. Animal contact factors identified in studies included in the scoping review for human infections with antimicrobial-resistant Campylobacter strains compared to infection with susceptible strains, limited to studies reporting odds ratios.Note: CSSSC, Campylobacter Sentinel Surveillance Scheme Collaborators; F, fluoroquinolone-resistant outcome; MVA, multivariable analysis result; Q, quinolone-resistant outcome; UVA, univariable analysis result

Figure 3

Figure 3. Prior antimicrobial use as factors identified in studies included in the scoping review for human infections with antimicrobial-resistant Campylobacter strains compared to infection with susceptible strains, limited to studies reporting odds ratios.Note: F, fluoroquinolone-resistant outcome; MVA, multivariable analysis result; Q, quinolone-resistant outcome; UVA, univariable analysis result; UVA*, results from a study that only conducted univariable analysis.

Figure 4

Figure 4. Food consumption (a) and preparation (b) factors identified in studies included in the scoping review for human infections with antimicrobial-resistant Campylobacter strains compared to infection with susceptible strains, limited to studies reporting odds ratios.Note: CSSSC, Campylobacter Sentinel Surveillance Scheme Collaborators; F, fluoroquinolone-resistant outcome; MVA, multivariable analysis result; UVA, univariable analysis result.

Figure 5

Figure 5. Travel factors identified in studies included in the scoping review for human infections with antimicrobial-resistant Campylobacter strains compared to infection with susceptible strains, limited to studies reporting odds ratios.Note: CSSSC, Campylobacter Sentinel Surveillance Scheme Collaborators; F, fluoroquinolone-resistant outcome; MVA, multivariable analysis result; Q, quinolone-resistant outcome; UVA, univariable analysis result; UVA*, results from a study that only conducted a univariable analysis.

Figure 6

Figure 6. Key data extracted for drinking water-related (a) and swimming (b) factors identified in studies included in the scoping review for human infections with an antimicrobial-resistant Campylobacter strains compared to infection with susceptible strains, limited to studies reporting odds ratios.Note: CSSSC, Campylobacter Sentinel Surveillance Scheme Collaborators; F, fluoroquinolone-resistant outcome; MVA, multivariable analysis result; Q, quinolone-resistant outcome; UVA, univariable analysis result; UVA*, results from a study that only conducted a univariable analysis.

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