Public Health Criteria for the diagnosis of foodborne illness

1986 ◽  
Vol 8 (15) ◽  
pp. 115
2016 ◽  
Vol 4 (5) ◽  
Author(s):  
Arthur W. Pightling ◽  
Hugh Rand ◽  
Errol Strain ◽  
Franco Pagotto

Listeria monocytogenesis a pathogenic bacterium of importance to public health and food safety agencies. We present the genome sequence of the serotype 1/2aL. monocytogenesfood isolate HPB913, which was collected in Canada in 1993 as part of an investigation into a sporadic case of foodborne illness.


2017 ◽  
Vol 145 (8) ◽  
pp. 1535-1544 ◽  
Author(s):  
R. R. HARVEY ◽  
K. E. HEIMAN MARSHALL ◽  
L. BURNWORTH ◽  
M. HAMEL ◽  
J. TATARYN ◽  
...  

SUMMARYSalmonella is a leading cause of bacterial foodborne illness. We report the collaborative investigative efforts of US and Canadian public health officials during the 2013–2014 international outbreak of multiple Salmonella serotype infections linked to sprouted chia seed powder. The investigation included open-ended interviews of ill persons, traceback, product testing, facility inspections, and trace forward. Ninety-four persons infected with outbreak strains from 16 states and four provinces were identified; 21% were hospitalized and none died. Fifty-four (96%) of 56 persons who consumed chia seed powder, reported 13 different brands that traced back to a single Canadian firm, distributed by four US and eight Canadian companies. Laboratory testing yielded outbreak strains from leftover and intact product. Contaminated product was recalled. Although chia seed powder is a novel outbreak vehicle, sprouted seeds are recognized as an important cause of foodborne illness; firms should follow available guidance to reduce the risk of bacterial contamination during sprouting.


2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Anne Arthur ◽  
Effie Gournis ◽  
Kaitlin Bradley

ObjectiveTo describe the use of an online survey tool to rapidly collect data from a large community outbreak of enteric illness in Toronto, Canada.IntroductionIn the early morning of Friday January 20, 2017, Toronto Public Health (TPH) was notified of several reports of acute vomiting, diarrhea, and stomach pain/cramps among students living in residence at a post-secondary institution in Toronto, Canada. A public health investigation was initiated and it was quickly determined that a large number of students and visitors to the campus were affected. Following considerable media coverage, TPH began receiving an overwhelmingly high volume of reports from ill individuals who lived, visited, or worked at the college campus and had experienced gastrointestinal illness.MethodsGastroBusters – an established online foodborne illness reporting tool was quickly adapted to support the outbreak investigation. GastroBusters was rapidly updated to include a screening question allowing ill individuals connected with the outbreak location to self-identify and report their symptoms, onset dates and times, and food histories to TPH securely online. The necessary updates were developed, tested, and implemented in less than one hour. Ill individuals were directed to the GastroBusters website – tph.to/gastrobusters - by college administrators and through media messaging. Those who were ill and reported to TPH through other methods (e.g., by phone) were interviewed by TPH investigators to collect comparable data, which were entered by staff into an online survey that mirrored the structure of the GastroBusters questions. These two data sets were merged and descriptive analyses were conducted using MS Excel and SAS v9.2.ResultsIn total, 354 reports associated with the outbreak were received by TPH - 232 who self-reported through GastroBusters, and 122 reported through other methods who were interviewed by TPH. Use of GastroBusters allowed ill individuals to report at a time convenient to them - 204 (88%) reports were submitted outside of TPH's business hours. As well, by providing ill individuals a method to self-report, TPH was able to rapidly collect, analyze and interpret data over the weekend while minimizing use of TPH staff resources. A summary report was available on Monday January 23, 2017 by 9:00 am, describing 236 confirmed and probable cases whose data were collected via both online surveys (GastroBusters and TPH data collection tool), between Friday and Sunday evenings. These data supported the hypothesis that the source of illness for the outbreak was likely norovirus; this was later confirmed through laboratory results.ConclusionsThis investigation provides a successful example of how an existing online reporting system for foodborne illness can be used for rapid data collection during a large-scale community enteric outbreak, where the exposed population could not be easily defined and the source of illness was unknown. Advantages of using this approach included: 1) rapid and robust data collection resulting in prompt analysis, and 2) efficient use of public health resources given the volume of reports otherwise processed by a public health investigator. Moreover, the investigation coincided with a weekend when there are fewer staff available and large amounts of overtime costs would have been accrued. TPH is currently developing standards for the use of similar tools in the future.References1. Toronto [Internet]. Toronto: City of Toronto; c1998-2017. GastroBusters; [cited October 2, 2017]. Available from: tph.to/gastrobusters


2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Sripriya Rajamani ◽  
Melanie Firestone ◽  
Craig Hedberg

Foodborne illnesses remain an important public health challenge in the United States causing an estimated 48 million illnesses, 128,000 hospitalizations, and 3,000 deaths per year. Restaurants are frequent settings for foodborne illness transmission. Public health surveillance – the continual, systematic collection, analysis, and interpretation of reports of health data to prevent and control illness – is a prerequisite for an effective food control system. While restaurant inspection data are routinely collected, these data are not regularly aggregated like traditional surveillance data. However, there is evidence that these data are a valuable tool for understanding foodborne illness outbreaks and threats to food safety. This article discusses the challenges and opportunities for incorporating routine restaurant inspection data as a surveillance tool for monitoring and improving foodborne illness prevention activities.  The three main challenges are: 1) the need for a national framework; 2) lack of data standards and interoperability; and 3) limited access to restaurant inspection data. Tapping into the power of public health informatics represents an opportunity to address these challenges. Overall, improving restaurant inspection information systems and making restaurant inspection data available to support decision-making represents an opportunity to practice smarter food safety.


Author(s):  
Ian T. Williams ◽  
Laura Whitlock ◽  
Matthew E. Wise

Public health officials investigate outbreaks to control them, to prevent additional illnesses, and to learn how to prevent similar outbreaks in the future. The process the public health community uses to detect, investigate, and control enteric (intestinal) disease outbreaks from food, water, and other sources involves certain procedural steps. These include detecting a possible outbreak, defining and finding cases, generating hypotheses about likely sources, testing the hypotheses and evaluating evidence, finding contamination sources, controlling the outbreak, and determining when the outbreak is over. Investigating outbreaks of acute enteric diseases can be a dynamic and complex undertaking involving multiple public health and regulatory partners in different jurisdictions. This chapter provides an overview of the investigation process with an emphasis on multijurisdictional foodborne illness investigations in the United States.


2001 ◽  
Vol 7 (5) ◽  
pp. 904-905 ◽  
Author(s):  
Timothy F. Jones ◽  
Diane Eigsti Gerber

2020 ◽  
Vol 11 (4) ◽  
pp. 1030-1044
Author(s):  
Nydia Edith Reyes-Rodriguez ◽  
Jeannette Barba-León ◽  
Armando Navarro-Ocaña ◽  
Vicente Vega-Sanchez ◽  
Fabian Ricardo Gómez De Anda ◽  
...  

Shiga toxin E. coli (STEC) is an important pathogen responsible for foodborne illness, this have been related with epidemic outbreaks in the past, mainly because of consumption of bovine meat. The objective of this study was identify the serotypes and Stx2 subtypes and associate them with their possible epidemiology. There were analyzed a total of 65 isolates from the collection of the Centro de Investigación y Estudios Avanzados en Salud Animal, Facultad de Medicina Veterinaria y Zootecnia of the Universidad Autónoma del Estado de México, from carcasses and feces of bovines at three different Municipal slaughterhouses. The identification of Stx2 gene by PCR at final point, sequencing and analyzed with the help of BLAST software. There were found O157:H7, O70:H16, O91:H10, O112ac:H2, O128ac:H26 serotypes, which have been reported to be present at infectious outbreaks previously by foodborne worldwide; 63.07% (41/65) of the Escherichia coli strains got amplified for Stx2 and after BLAS analysis it was confirmed its presence and a hypothetic protein. The presence of this serotypes in combination with different subtype’s, Stx2a, Stx2c, Stx2d, in carcasses and feces of bovine in must be considered as a potential risk for diseases an important problem of the public health.


2019 ◽  
Vol 28 (01) ◽  
pp. 235-235

Arsevska E, Valentin S, Rabatel J, de Goër de Hervé J, Falala S, Lancelot R, Roche M. Web monitoring of emerging animal infectious diseases integrated in the French Animal Health Epidemic Intelligence System. PLoS One 2018 Aug 3;13(8):e0199960 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6075742/ Effland T, Lawson A, Balter S, Devinney K, Reddy V, Waechter H, Gravano L, Hsu D. Discovering foodborne illness in online restaurant reviews. J Am Med Inform Assoc 2018 Dec 1;25(12):1586-92 https://academic.oup.com/jamia/article-abstract/25/12/1586/4725036?redirectedFrom=fulltext Wakamiya S, Kawai Y, Aramaki E. Twitter-Based Influenza Detection After Flu Peak via Tweets With Indirect Information: Text Mining Study. JMIR Public Health Surveill 2018 Sep 25;4(3):e65 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6231889/


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