A fully integrated real-time detection, diagnosis, and control of community diarrheal disease clusters and outbreaks (the INTEGRATE Project): Protocol for an enhanced surveillance system

Kirsty Marie McIntyre*, Frederick J. Bolton, Rob M. Christley, Paul Cleary, Elizabeth Deja, Ann E. Durie, Peter J. Diggle, Dyfrig A. Hughes, Simon de Lusignan, Lois Orton, Alan D. Radford, Alex Elliot, Gillian Smith, Darlene A. Snape, Debbi Stanistreet, Roberto Vivancos, Craig Winstanley, Sarah J. O’Brien

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


Background: Diarrheal disease, which affects 1 in 4 people in the United Kingdom annually, is the most common cause of outbreaks in community and health care settings. Traditional surveillance methods tend to detect point-source outbreaks of diarrhea and vomiting; they are less effective at identifying low-level and intermittent food supply contamination. Furthermore, it can take up to 9 weeks for infections to be confirmed, reducing slow-burn outbreak recognition, potentially impacting hundreds or thousands of people over wide geographical areas. There is a need to address fundamental problems in traditional diarrheal disease surveillance because of underreporting and subsequent unconfirmed infection by patients and general practitioners (GPs); varying submission practices and selective testing of samples in laboratories; limitations in traditional microbiological diagnostics, meaning that the timeliness of sample testing and etiology of most cases remains unknown; and poorly integrated human and animal surveillance systems, meaning that identification of zoonoses is delayed or missed. Objective: This study aims to detect anomalous patterns in the incidence of gastrointestinal disease in the (human) community; to target sampling; to test traditional diagnostic methods against rapid, modern, and sensitive molecular and genomic microbiology methods that identify and characterize responsible pathogens rapidly and more completely; and to determine the cost-effectiveness of rapid, modern, sensitive molecular and genomic microbiology methods. Methods: Syndromic surveillance will be used to aid identification of anomalous patterns in microbiological events based on temporal associations, demographic similarities among patients and animals, and changes in trends in acute gastroenteritis cases using a point process statistical model. Stool samples will be obtained from patients’ consulting GPs, to improve the timeliness of cluster detection and characterize the pathogens responsible, allowing health protection professionals to investigate and control outbreaks quickly, limiting their size and impact. The cost-effectiveness of the proposed system will be examined using formal cost-utility analysis to inform decisions on national implementation. Results: The project commenced on April 1, 2013. Favorable approval was obtained from the Research Ethics Committee on June 15, 2015, and the first patient was recruited on October 13, 2015, with 1407 patients recruited and samples processed using traditional laboratory techniques as of March 2017. Conclusions: The overall aim of this study is to create a new One Health paradigm for detecting and investigating diarrhea and vomiting in the community in near-real time, shifting from passive human surveillance and management of laboratory-confirmed infection toward an integrated, interdisciplinary enhanced surveillance system including management of people with symptoms.

Original languageEnglish
Article numbere13941
JournalJMIR Research Protocols
Issue number9
Publication statusPublished - Sep 2019

Bibliographical note

Funding Information:
The authors acknowledge the Department of Health and Social Care and the Wellcome Trust for the funding received for this project through the Health Innovation Challenge Fund (grant reference: HICF-T5-354). The authors acknowledge the support of the University of Liverpool Sponsorship Review and Approval Committee, patients registered with RCGP RSC general practices as well as the practices that allowed their data to be shared, Apollo Medical Systems, EMIS, In-Practice Vision, and TPP for support and collaboration with data extraction. The authors would like to thank Simone Nudds, Gillian Byrne, and David Knight from Luminex Corporation for their support. Finally, the authors would also like to thank NHS 111 for providing permission to use the anonymized NHS 111 syndromic surveillance data. SdL has subsequently received funding through the University of Surrey to explore household transmission of acute gastroenteritis.

Publisher Copyright:
© Kirsty Marie McIntyre, Frederick J Bolton, Rob M Christley, Paul Cleary, Elizabeth Deja, Ann E Durie, Peter J Diggle, Dyfrig A Hughes, Simon de Lusignan, Lois Orton, Alan D Radford, Alex J Elliot, Gillian E Smith, Darlene A Snape, Debbi Stanistreet, Roberto Vivancos, Craig Winstanley, Sarah J O’Brien. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 27.09.2019 This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on http://www.researchprotocols.org, as well as this copyright and license information must be included.


  • Diarrhea
  • Gastrointestinal diseases
  • Microbiology
  • Syndromic surveillance
  • Vomiting


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