ReviewFrontiers in microbiology2019
Critical Orientation in the Jungle of Currently Available Methods and Types of Data for Source Attribution of Foodborne Diseases.
Review in Frontiers in microbiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Transmission pathways and risk factors for sporadic salmonellosis and campylobacteriosis: a source attribution meta-analysis of European case-control studies.Epidemiology and infection · 2025Pooled it
- Animal sources of antimicrobial-resistant bacterial infections in humans: a systematic review.Epidemiology and infection · 2023Pooled it
- A statistical modelling approach for source attribution meta-analysis of sporadic infection with foodborne pathogens.Zoonoses and public health · 2022Pooled it
- Review
- A Review on Microbiological Source Attribution Methods of Human Salmonellosis: From Subtyping to Whole-Genome Sequencing.Foodborne pathogens and disease · 2024Review
- Use of whole genome sequencing for surveillance and control of foodborne diseases:Frontiers in microbiology · 2024Review
- Using SNP addresses forEpidemiology and infection · 2023Article
- Comparison of Source Attribution Methodologies for Human Campylobacteriosis.Pathogens (Basel, Switzerland) · 2023Article
- Development and validation of a random forest algorithm for source attribution of animal and humanFrontiers in microbiology · 2023Article
- Genomic insights into zoonotic transmission and antimicrobial resistance in Campylobacter jejuni from farm to fork: a one health perspective.Gut pathogens · 2022Review
- Salmonella enterica subsp. enterica Welikade: guideline for phylogenetic analysis of serovars rarely involved in foodborne outbreaks.BMC genomics · 2022Article
- Clinical Metagenomics Is Increasingly Accurate and Affordable to Detect Enteric Bacterial Pathogens in Stool.Microorganisms · 2022Article
- Polyphyly in widespreadFrontiers in public health · 2022Article
- Editorial: Integrating Whole Genome Sequencing Into Source Attribution and Risk Assessment of Foodborne Bacterial Pathogens.Frontiers in microbiology · 2021Article
- Molecular typing tools for identifying and characterizing lactic acid bacteria: a review.Food science and biotechnology · 2020Review
- AB_SA: Accessory genes-Based Source Attribution - tracing the source ofMicrobial genomics · 2020Article
- Source Attribution Study of SporadicFrontiers in microbiology · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With increased interest in source attribution of foodborne pathogens, there is a need to sort and assess the applicability of currently available methods. Herewith we reviewed the most frequently applied methods for source attribution of foodborne diseases, discussing their main strengths and weaknesses to be considered when choosing the most appropriate methods based on the type, quality, and quantity of data available, the research questions to be addressed, and the (epidemiological and microbiological) characteristics of the pathogens in question. A variety of source attribution approaches have been applied in recent years. These methods can be defined as top-down, bottom-up, or combined. Top-down approaches assign the human cases back to their sources of infection based on epidemiological (e.g., outbreak data analysis, case-control/cohort studies, etc.), microbiological (i.e., microbial subtyping), or combined (e.g., the so-called 'source-assigned case-control study' design) methods. Methods based on microbial subtyping are further differentiable according to the modeling framework adopted as frequency-matching (e.g., the Dutch and Danish models) or population genetics (e.g., Asymmetric Island Models and STRUCTURE) models, relying on the modeling of either phenotyping or genotyping data of pathogen strains from human cases and putative sources. Conversely, bottom-up approaches like comparative exposure assessment start from the level of contamination (prevalence and concentration) of a given pathogen in each source, and then go upwards in the transmission chain incorporating factors related to human exposure to these sources and dose-response relationships. Other approaches are intervention studies, including 'natural experiments,' and expert elicitations. A number of methodological challenges concerning all these approaches are discussed. In absence of an universally agreed upon 'gold' standard, i.e., a single method that satisfies all situations and needs for all pathogens, combining different approaches or applying them in a comparative fashion seems to be a promising way forward.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.