Periodic Reporting for period 1 - DEFOG (Data science tool for Epidemic FOrecastinG)
Okres sprawozdawczy: 2019-10-01 do 2022-03-31
Several organisations active in the health care market make decisions based on an estimation of the number of individuals infected with an infectious disease. These organisations benefit from a timely and trust worthy prediction of the number of infected individuals. To date, infectious disease prediction tools are inadequate because they typically include limited and domain-specific data and because the translation to impact for specific stakeholders in the healthcare market is lacking.
DEFOG proposes a data science solution by integrating classical surveillance data, pharmacy sales data, out-of-hours general practitioners’ data, social contact data and possibly other data sets in a novel real-time forecasting tool that will yield better and more rapid warning signals of the number of infected cases.
DEFOG builds on recent advances in mathematical modelling for infectious diseases as part of the original ERC-TransMID project. The team offers a vast amount of expertise in mathematical and infectious disease modelling, computational processing, business development and has an extensive collaborative network with research centres, regulatory agencies and companies, of which 4 entities already expressed interest in exploring the use and/or sharing data for of the proposed innovative real-time disease forecasting tool.
Due to the COVID-19 pandemic, we focused on the spread of SARS-CoV-2 and on the deployment of Infectieradar as an additional valuable source of surveillance data collection.
Infectieradar.be collects syndromic surveillance data and allows us to monitor how health complaints are distributed in Belgium and how the situation develops over time. In comparison with traditional surveillance (e.g. general practitioner, hospital records, etc.) Infectieradar can give more early warnings of increase in infection, in accordance with the project’s objectives. Moreover, the platform not only captures SARS-CoV-2 spread and outbreaks but also other ILI pathogens like RSV, influenza also supporting the original focus of the project.
DEFOG resulted in output in the form of a manuscript ready for peer review, a website with weekly/monthly results reporting, media coverage and recognition by the Belgium's Health institution.
DEFOG proposes a data science solution by integrating classical surveillance data, pharmacy sales data, out-of-hours general practitioners’ data, social contact data and possibly other data sets in a novel real-time forecasting tool that will yield better and more rapid warning signals of the number of infected cases.
DEFOG builds on recent advances in mathematical modelling for infectious diseases as part of the original ERC-TransMID project. The team offers a vast amount of expertise in mathematical and infectious disease modelling, computational processing, business development and has an extensive collaborative network with research centres, regulatory agencies and companies, of which 4 entities already expressed interest in exploring the use and/or sharing data for of the proposed innovative real-time disease forecasting tool.
Due to the COVID-19 pandemic, we focused on the spread of SARS-CoV-2 and on the deployment of Infectieradar as an additional valuable source of surveillance data collection.
Infectieradar.be collects syndromic surveillance data and allows us to monitor how health complaints are distributed in Belgium and how the situation develops over time. In comparison with traditional surveillance (e.g. general practitioner, hospital records, etc.) Infectieradar can give more early warnings of increase in infection, in accordance with the project’s objectives. Moreover, the platform not only captures SARS-CoV-2 spread and outbreaks but also other ILI pathogens like RSV, influenza also supporting the original focus of the project.
DEFOG resulted in output in the form of a manuscript ready for peer review, a website with weekly/monthly results reporting, media coverage and recognition by the Belgium's Health institution.