Dataset Information

Towards an integrated food safety surveillance system: a simulation study to explore the potential of combining genomic and epidemiological metadata.

ABSTRACT: Foodborne infection is a result of exposure to complex, dynamic food systems. The efficiency of foodborne infection is driven by ongoing shifts in genetic machinery. Next-generation sequencing technologies can provide high-fidelity data about the genetics of a pathogen. However, food safety surveillance systems do not currently provide similar high-fidelity epidemiological metadata to associate with genetic data. As a consequence, it is rarely possible to transform genetic data into actionable knowledge that can be used to genuinely inform risk assessment or prevent outbreaks. Big data approaches are touted as a revolution in decision support, and pose a potentially attractive method for closing the gap between the fidelity of genetic and epidemiological metadata for food safety surveillance. We therefore developed a simple food chain model to investigate the potential benefits of combining 'big' data sources, including both genetic and high-fidelity epidemiological metadata. Our results suggest that, as for any surveillance system, the collected data must be relevant and characterize the important dynamics of a system if we are to properly understand risk: this suggests the need to carefully consider data curation, rather than the more ambitious claims of big data proponents that unstructured and unrelated data sources can be combined to generate consistent insight. Of interest is that the biggest influencers of foodborne infection risk were contamination load and processing temperature, not genotype. This suggests that understanding food chain dynamics would probably more effectively generate insight into foodborne risk than prescribing the hazard in ever more detail in terms of genotype.

SUBMITTER: Hill AA

PROVIDER: S-EPMC5383817 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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Towards an integrated food safety surveillance system: a simulation study to explore the potential of combining genomic and epidemiological metadata.

Hill A A AA Crotta M M Wall B B Good L L O'Brien S J SJ Guitian J J

Royal Society open science 20170329 3

Foodborne infection is a result of exposure to complex, dynamic food systems. The efficiency of foodborne infection is driven by ongoing shifts in genetic machinery. Next-generation sequencing technologies can provide high-fidelity data about the genetics of a pathogen. However, food safety surveillance systems do not currently provide similar high-fidelity epidemiological metadata to associate with genetic data. As a consequence, it is rarely possible to transform genetic data into actionable k ...[more]

PMID: 28405360

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Project description:BACKGROUND:Wet markets are markets selling fresh meat and produce. Wet markets are critical for food security and sustainable development in their respective regions. Due to their cultural significance, they attract numerous visitors and consequently generate tourist-geared information on the Web (ie, on social networks such as TripAdvisor). These data can be used to create a novel, international wet market inventory to support epidemiological surveillance and control in such settings, which are often associated with negative health outcomes. OBJECTIVE:Using social network data, we aimed to assess the level of wet markets' touristic importance on the Web, produce the first distribution map of wet markets of touristic interest, and identify common diseases facing visitors in these settings. METHODS:A Google search was performed on 31 food market-related keywords, with the first 150 results for each keyword evaluated based on their relevance to tourism. Of all these queries, wet market had the highest number of tourism-related Google Search results; among these, TripAdvisor was the most frequently-occurring travel information aggregator, prompting its selection as the data source for this study. A Web scraping tool (ParseHub) was used to extract wet market names, locations, and reviews from TripAdvisor. The latter were searched for disease-related content, which enabled assignment of GeoSentinel diagnosis codes to each. This syndromic categorization was overlaid onto a mapping of wet market locations. Regional prevalence of the most commonly occurring symptom group - food poisoning - was then determined (ie, by dividing the number of wet markets per continent with more than or equal to 1 review containing this syndrome by the total number of wet markets on that continent with syndromic information). RESULTS:Of the 1090 hits on TripAdvisor for wet market, 36.06% (393/1090) conformed to the query's definition; wet markets were heterogeneously distributed: Asia concentrated 62.6% (246/393) of them, Europe 19.3% (76/393), North America 7.9% (31/393), Oceania 5.1% (20/393), Africa 3.1% (12/393), and South America 2.0% (8/393). Syndromic information was available for 14.5% (57/393) of wet markets. The most frequently occurring syndrome among visitors to these wet markets was food poisoning, accounting for 54% (51/95) of diagnoses. Cases of this syndrome were identified in 56% (22/39) of wet markets with syndromic information in Asia, 71% (5/7) in Europe, and 71% (5/7) in North America. All wet markets in South America and Oceania reported food poisoning cases, but the number of reviews with syndromic information was very limited in these regions (n=2). CONCLUSIONS:The map produced illustrates the potential role of touristically relevant social network data to support global epidemiological surveillance. This includes the possibility to approximate the global distribution of wet markets and to identify diseases (ie, food poisoning) that are most prevalent in such settings.

Project description:IntroductionAs new antiretrovirals (ARVs), including long-acting ARVs for treatment and prevention, are approved and introduced, surveillance during pregnancy must become the safety net for evaluating birth outcomes, especially those that are rare and require large numbers of observations. Historically, drug pharmacovigilance in pregnancy has been limited and fragmented between different data sources, resulting in inadequate data to assess risk. The International Maternal Pediatric Adolescent AIDS Clinical Trials Network and World Health Organization convened a Workshop which reviewed strengths and weaknesses of existing programs and discussed an improved framework to integrate existing safety data sources and promote harmonization and digitalization.DiscussionThis paper highlights that although robust sources of safety data and surveillance programs exist, key challenges remain, including unknown denominators, reporting bias, under-reporting (e.g. in voluntary registries), few data sources from resource-limited settings (most are in North America and Europe), incomplete or inaccurate data (e.g. within routine medical records). However, recent experiences (e.g. with safety signals) and current innovations (e.g. electronic record use in resource-limited settings and defining adverse outcomes) provide momentum and building blocks for a new framework for active surveillance of ARV safety in pregnancy. A public health approach should be taken using data from existing sources, including registries of pregnancy ARV exposure and birth defects; observational surveillance and cohort studies; clinical trials; and real-world databases. Key facilitators are harmonization and standardization of outcomes, sharing of materials and tools, and data linkages between programs. Other key facilitators include the development of guidance to estimate sample size and duration of surveillance, ensuring strategic geographic diversity, bringing partners together to share information and engaging the community of women living with HIV.ConclusionsLooking ahead, critical steps to safely introduce new ARVs include (1) adopting harmonized standards for measuring adverse maternal, birth and infant outcomes; (2) establishing surveillance centres of excellence in areas with high HIV prevalence with harmonized data collection and optimized electronic health records linking maternal/infant data; and (3) creating targets and evaluation goals for reporting progress on implementation and quality of surveillance in pregnancy. The platform will be leveraged to ensure that appropriate contributions and strategic actions by relevant stakeholders are implemented.

Dataset Information

Towards an integrated food safety surveillance system: a simulation study to explore the potential of combining genomic and epidemiological metadata.

Publications

Towards an integrated food safety surveillance system: a simulation study to explore the potential of combining genomic and epidemiological metadata.

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