The Planning and Management principle defines that an One Health oriented surveillance organization and management can lead to a more effective One Health coordination, emergency preparedness, data generation and decision making. The resources provided under this principle are meant to support and strengthen the planning and management tasks along the whole surveillance process. This includes the design, development, establishment, implementation, monitoring, evaluation and optimization of surveillance systems with a cross-sector One Health approach.
The methods proposed under this principle were designed to support the activities related to the planning, design, coordination and management of surveillance activities. These methods aim to be applicable to all One Health sectors and adaptable to the OH capacities and capabilities under each country considering their resource settings.
The free and open source software FoodChain-Lab (FCL) allows for fast and reliable tracing of suspicious food items along complex global supply chains during foodborne incidents. It unifies supply chain tracing data collection, cleaning, visualisation, analysis and reporting in one modular framework. FCL is available as desktop version (FCL Desktop) and as web application (FCL Web).
In both tools, tracing data remains completely on the user side without any storage on servers to ensure data protection. FCL is already in use by several EU Member States, EFSA and U.S. FDA. In 2020, it became part of the SISOT tool box of OIE, WHO and FAO.
FCL Desktop and FCL Web are joint outputs of several projects (e.g. SiLeBAT, EFSA-BfR Framework Partnership Agreements, One Health EJP COHESIVE) and will contribute to future projects on traceability together with EFSA e.g. by integrating FCL Web into a European framework of tracing tools and by developing a universal tracing data exchange format.
For more information on FCL, please check https://foodrisklabs.bfr.bund.de/foodchain-lab/. FCL Desktop can be installed via https://foodrisklabs.bfr.bund.de/installation/. FCL Web is available at https://fcl-portal.bfr.berlin. The software code is published at https://github.com/SiLeBAT/BfROpenLab (FCL Desktop), https://github.com/SiLeBAT/fcl-client and https://github.com/SiLeBAT/fcl-server (both FCL Web).
Fig. 3: FCL Web visualising the supply chain network of a fictitious foodborne disease outbreak in the network view, the map view, the reporting view and in the data table.
Surveillance Evaluation Framework (SurF) is a free available online guideline. It was initially developed by P. Muellner, K.D.C. Stärk, and J. Watts1 to provide a fit-for-purpose and efficient surveillance evaluation framework for the Ministry for Primary Industries (MPI) in New Zealand to assess surveillance activities, programmes, systems or portfolios in a structured and adaptable way.
SurF builds upon and adapts previous work conducted nationally and internationally in the context of the evaluation of human and animal health surveillance. This includes in particular the SERVAL Framework 2, the recently published guidelines by the European Centre for Disease Control (ECDC, 2014), as well as the available information describing the preliminary version of the EVA tool (RiskSur Consortium 2013 & 2015), which at the time of writing is still under development. An effort was made to align this framework with the national standards proposed by the Aotearoa New Zealand Evaluation Association (ANZEA, 2015) where possible.
SurF provides a common umbrella for surveillance evaluation in the animal, plant, environment and marine sectors. It consists of four components, each supporting a distinct phase in the evaluation. Each component describes the activities and decisions related to a phase within an evaluation project: (i) Motivation for the evaluation, (ii) Scope of the evaluation, (iii) Evaluation design and implementation, and (iv) Reporting and communication of evaluation outputs. The tool provides users with an Evaluation Template to guide capturing input. Further, SurF provides a visual output that allows for comparison of core performance between systems and within individual systems over time.
Link: https://www.mpi.govt.nz/dmsdocument/18091-Surveillance-Evaluation-Framework-SurF-Main-Document .. rubric:: References
This is an interactive, stand-alone tool to evaluate the capacities and capabilities for the One Health Surveillance of a specific sector and/or pathogen of choice. Additionally, the tool allows the benchmarking of surveillance capacities and capabilities for comparison i) with other countries for the same hazard; ii) between specific hazards within one country. The tool addresses the need for evaluating strengths and weaknesses of multi-sectoral surveillance systems and identifying opportunities for further integration. The tool evaluates 3 dimensions: Organization of One Health (formalization, coverage / transdisciplinary, resources, evaluation and resilience) One Health in operational activities (data collection / methods sharing; data sharing; data analysis and interpretation; communication) Impact of One Health (technical outputs, collaborative added values, immediate and intermediate outcomes, ultimate outcomes)
More information about the OH-EpiCap tool is available here.
OH-EpiCap online application for evaluating the OH capacities of surveillance systems: https://freddietafreeth.shinyapps.io/OH-EpiCap/
The Report on the implementation of the OH-EpiCap evaluation tool on several study cases is available here: https://zenodo.org/record/7375651#.Y5Bw1HbMKUk
This is a guideline that countries can use to develop One Health Surveillance according to their needs and resources. Countries can use it both to build a new One Health Surveillance system or to advance an existing one. The roadmap expands the work of the OHEJP COHESIVE project.
More information about the OHEJP COHESIVE project and roadmap is available here. The roadmap provides step by step instructions on how to work through its different parts. The roadmap also addresses barriers and facilitators between One Health Surveillance sectors, based on the findings of a requirement analysis that is available here.
The website with the roadmap (guidelines) for countries to improve One Health Surveillance is available here: https://www.ohras.eu
The requirement analysis for the Roadmap including a systematic literature review of both peer-reviewed and grey literature is available here: https://zenodo.org/record/6504418#.YmuyAdpByUk
This solution provides practices to operationalize cross-sectorial collaborations with a focus on data collection, data sharing, data analysis, and the dissemination of surveillance results. It is a guideline to the practical implementation of collaboration between the animal health, public health and food safety sectors according to different surveillance purposes: surveillance purposes: i) measuring the levels and temporal trends of exposure and burden of disease; ii) supporting early detection and response to outbreaks; iii) identifying risk factors to implement control measures. This work builds upon a report about the mapping of surveillance chains and cross-sectorial linkages for different hazards.
The report is available here
The best-practice guidelines are available here: https://zenodo.org/record/7053387#.Y5N6A-zMLOR
A guide to design, implement, and evaluate official controls within the food sector using outputbased standards
This is a non-prescriptive guideline for countries, a loose framework to work around the aspects of output-based standards for surveillance in the food sector. The guideline maps out the process, considerations, evaluation strategies etc. depending on what the aims of surveillance are. It can be used i) to assess the current sensitivity of surveillance; ii) to reduce sampling numbers; iii) to implement risk based surveillance; iv) to identify a method to analyse a current surveillance system to ensure it is fit for purpose.
Link to the guideline: https://zenodo.org/record/7390006#.Y5bkJXbMKUk
This exploratory study was to identify barriers and opportunities for an integrated One Health surveillance of food-borne diseases in selected EU countries. The results from these studies can be used to support revision of existing systems, or development of new systems for food-borne disease surveillance from a One Health (OH) perspective. This study was part of One Health EJP NOVA. The study is available on Zenodo: https://zenodo.org/record/5497346#.Y5NcwuzMLOR
Muellner, P, Watts, J, Bingham, P, et al. SurF: an innovative framework in biosecurity and animal health surveillance evaluation. Transbound Emerg Dis. 2018; 65: 1545– 1552. https://doi.org/10.1111/tbed.12898↩
Drewe, J.A., Hoinville, L.J., Cook, A.J.C., Floyd, T., Gunn, G. and Stärk, K.D.C. (2015), SERVAL: A New Framework for the Evaluation of Animal Health Surveillance. Transbound Emerg Dis, 62: 33-45. https://doi.org/10.1111/tbed.12063↩