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Mathematical modeling of the transmission and control of foodborne pathogens and antimicrobial resistance at preharvest.

ABSTRACT: Foodborne diseases are a significant health-care and economic burden. Most foodborne pathogens are enteric pathogens harbored in the gastrointestinal tract of farm animals. Understanding the transmission of foodborne pathogens and the dissemination of antimicrobial resistance at the farm level is necessary to design effective control strategies at preharvest. Mathematical models improve our understanding of pathogen dynamics by providing a theoretical framework in which factors affecting transmission and control of the pathogens can be explicitly considered. In this review, we aim to present the principles underlying the mathematical modeling of foodborne pathogens and antimicrobial resistance at the farm level to a broader audience.

SUBMITTER: Lanzas C

PROVIDER: S-EPMC3123936 | biostudies-literature | 2011 Jan

REPOSITORIES: biostudies-literature

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Mathematical modeling of the transmission and control of foodborne pathogens and antimicrobial resistance at preharvest.

Lanzas Cristina C Lu Zhao Z Gröhn Yrjo T YT

Foodborne pathogens and disease 20101102 1

Foodborne diseases are a significant health-care and economic burden. Most foodborne pathogens are enteric pathogens harbored in the gastrointestinal tract of farm animals. Understanding the transmission of foodborne pathogens and the dissemination of antimicrobial resistance at the farm level is necessary to design effective control strategies at preharvest. Mathematical models improve our understanding of pathogen dynamics by providing a theoretical framework in which factors affecting transmi ...[more]

PMID: 21043837

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Project description:BackgroundMathematical transmission models are increasingly used to guide public health interventions for infectious diseases, particularly in the context of emerging pathogens; however, the contribution of modeling to the growing issue of antimicrobial resistance (AMR) remains unclear. Here, we systematically evaluate publications on population-level transmission models of AMR over a recent period (2006-2016) to gauge the state of research and identify gaps warranting further work.MethodsWe performed a systematic literature search of relevant databases to identify transmission studies of AMR in viral, bacterial, and parasitic disease systems. We analyzed the temporal, geographic, and subject matter trends, described the predominant medical and behavioral interventions studied, and identified central findings relating to key pathogens.ResultsWe identified 273 modeling studies; the majority of which (> 70%) focused on 5 infectious diseases (human immunodeficiency virus (HIV), influenza virus, Plasmodium falciparum (malaria), Mycobacterium tuberculosis (TB), and methicillin-resistant Staphylococcus aureus (MRSA)). AMR studies of influenza and nosocomial pathogens were mainly set in industrialized nations, while HIV, TB, and malaria studies were heavily skewed towards developing countries. The majority of articles focused on AMR exclusively in humans (89%), either in community (58%) or healthcare (27%) settings. Model systems were largely compartmental (76%) and deterministic (66%). Only 43% of models were calibrated against epidemiological data, and few were validated against out-of-sample datasets (14%). The interventions considered were primarily the impact of different drug regimens, hygiene and infection control measures, screening, and diagnostics, while few studies addressed de novo resistance, vaccination strategies, economic, or behavioral changes to reduce antibiotic use in humans and animals.ConclusionsThe AMR modeling literature concentrates on disease systems where resistance has been long-established, while few studies pro-actively address recent rise in resistance in new pathogens or explore upstream strategies to reduce overall antibiotic consumption. Notable gaps include research on emerging resistance in Enterobacteriaceae and Neisseria gonorrhoeae; AMR transmission at the animal-human interface, particularly in agricultural and veterinary settings; transmission between hospitals and the community; the role of environmental factors in AMR transmission; and the potential of vaccines to combat AMR.

Project description:This study was aimed at assessing whether the repeated exposure of 12 strains of Salmonella spp., Escherichia coli, and Listeria monocytogenes to alternative nonthermal decontamination techniques with UV light (UV-C) and nonthermal atmospheric plasma (NTAP) may cause the emergence of variants showing increased resistance to clinically relevant antibiotics (ampicillin, cefotaxime, ciprofloxacin, gentamicin, streptomycin, tetracycline, erythromycin, vancomycin, and colistin). UV-C and NTAP treatments were applied on the surface of inoculated brain heart infusion (BHI) agar plates. Survivors were recovered and after 24?h of growth in BHI broth were again subjected to the decontamination treatment; this was repeated for 10 consecutive cycles. A total of 174 strain/decontamination technique/antibiotic combinations were tested, and 12 variant strains with increased resistance to one of the antibiotics studied were identified, with the increases in the MICs in Mueller-Hinton broth ranging from 2- to 256-fold. The variant strains of Salmonella spp. isolated were further characterized through phenotypic screenings and whole-genome sequencing (WGS) analyses. Most changes in susceptibility were observed for antibiotics that act at the level of protein synthesis (aminoglycosides, tetracyclines, and glycylcyclines) or DNA replication (fluoroquinolones), as well as for polymyxins. No changes in resistance to ?-lactams were detected. WGS analyses showed the occurrence of sequence alterations in some antibiotic cellular targets (e.g., gyrA for ciprofloxacin-resistant variants, rpsL for a streptomycin-resistant variant), accompanied by variations in stress response regulators and membrane transporters likely involved in the nonselective efflux of antibiotics, which altogether resulted in a low- to medium-level increase in microbial resistance to several antibiotics.IMPORTANCE The emergence and spread of antibiotic resistance along the food chain can be influenced by the different antimicrobial strategies used from farm to fork. This study evidences that two novel, not yet widely used, nonthermal microbial decontamination techniques, UV light and nonthermal atmospheric plasma, can select variants with increased resistance to various clinically relevant antibiotics, such as ciprofloxacin, streptomycin, tetracycline, and erythromycin. Whole-genome analysis of the resistant variants obtained for Salmonella spp. allowed identification of the genetic changes responsible for the observed phenotypes and suggested that some antimicrobial classes are more susceptible to the cross-resistance phenomena observed. This information is relevant, since these novel decontamination techniques are being proposed as possible alternative green techniques for the decontamination of environments and equipment in food and clinical settings.

Dataset Information

Mathematical modeling of the transmission and control of foodborne pathogens and antimicrobial resistance at preharvest.

Publications

Mathematical modeling of the transmission and control of foodborne pathogens and antimicrobial resistance at preharvest.

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