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Pandem-Source, a tool to collect or generate surveillance indicators for pandemic management

A use case with Covid-19 data

Bibliographic Data

ID22076898
AuthorsFrancisco Orchard (0000-0001-5793-3301, corresponding author), Charline Clain, William Madie, Jessica S Hayes (0000-0003-2443-1895, Ollscoil na Gaillimhe – University of Galway), Máire A Connolly (0000-0003-4322-2837, Ollscoil na Gaillimhe – University of Galway), Étienne de Sevin (0000-0001-6302-2192), Etienne Sevin, Alexis Sentís (0000-0002-8132-5645)
Year2024
Volume12
Pages1295117-1295117
Publication date2024-03-20
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2024.1295117
PMID38572005
OpenAlexW4392999965
LanguageEN
References cited15

Introduction: PANDEM-Source (PS) is a tool to collect and integrate openly available public health-related data from heterogeneous data sources to support the surveillance of infectious diseases for pandemic management. The tool may also be used for pandemic preparedness by generating surveillance data for training purposes. It was developed as part of the EU-funded Horizon 2020 PANDEM-2 project during the COVID-19 pandemic as a result of close collaboration in a consortium of 19 partners, including six European public health agencies, one hospital, and three first responder organizations. This manuscript describes PS's features and design to disseminate its characteristics and capabilities to strengthen pandemic preparedness and response. Methods: A requirement-gathering process with EU pandemic managers in the consortium was performed to identify and prioritize a list of variables and indicators useful for surveillance and pandemic management. Using the COVID-19 pandemic as a use case, we developed PS with the purpose of feeding all necessary data to be displayed in the PANDEM-2 dashboard. Results: PS routinely monitors, collects, and standardizes data from open or restricted heterogeneous data sources (users can upload their own data). It supports indicators and health resources related data from traditional data sources reported by national and international agencies, and indicators from non-traditional data sources such as those captured in social and mass media, participatory surveillance, and seroprevalence studies. The tool can also calculate indicators and be used to produce data for training purposes by generating synthetic data from a minimal set of indicators to simulate pandemic scenarios. PS is currently set up for COVID-19 surveillance at the European level but can be adapted to other diseases or threats and regions. Conclusion: With the lessons learnt during the COVID-19 pandemic, it is important to keep building capacity to monitor potential threats and develop tools that can facilitate training in all the necessary aspects to manage future pandemics. PS is open source and its design provides flexibility to collect heterogeneous data from open data sources or to upload end users's own data and customize surveillance indicators. PS is easily adaptable to future threats or different training scenarios. All these features make PS a unique and valuable tool for pandemic management

2019-20 coronavirus outbreak · Outbreak · Pandemic · Pathology · Computer Science · COVID-19 Digital Contact Tracing · COVID-19 epidemiological studies · Data-Driven Disease Surveillance · Medicine · Virology

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    Open Access•Thomas R Frieden, Marine Buissonnière et al.•BMJ Global Health•2021

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