Summary
The main purpose of this project is to create a realistic agent-based model to simulate the spread of infectious diseases such as measles, influenza, etc. in European and neighboring countries with their possibly under-vaccinated refugee populations. The model will be built upon two large-scale modeling platforms Framework for Reconstructing Epidemic Dynamics (FRED) and the Global Epidemic and Mobility Model (GLEAM). First we will create and curate realistic synthetic populations including residents and refugees by using various data sources such as Integrated Public-Use Microdata (IPUMS), Synthetic Populations and Ecosystems of the World (SPEW) for resident populations and World Health Organization, nongovernmental organizations, and country governments for refugees and relocated populations. Our model, with its forecasting capability of outbreaks, will help policy makers to mitigate outbreaks by assessing possible intervention mechanisms such as better handling refugees, vaccinations, school/workplace closures, antivirals, and social distancing methods. This project with its planned training program will help the researcher to transfer his knowledge in network modeling and analysis into a new field of large-scale agent-based modeling and simulation in a new institution in Turkey where there is a great need for these methods in public health.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/797816 |
| Start date: | 01-04-2018 |
| End date: | 31-03-2020 |
| Total budget - Public funding: | 157 845,60 Euro - 157 845,00 Euro |
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Original description
The main purpose of this project is to create a realistic agent-based model to simulate the spread of infectious diseases such as measles, influenza, etc. in European and neighboring countries with their possibly under-vaccinated refugee populations. The model will be built upon two large-scale modeling platforms Framework for Reconstructing Epidemic Dynamics (FRED) and the Global Epidemic and Mobility Model (GLEAM). First we will create and curate realistic synthetic populations including residents and refugees by using various data sources such as Integrated Public-Use Microdata (IPUMS), Synthetic Populations and Ecosystems of the World (SPEW) for resident populations and World Health Organization, nongovernmental organizations, and country governments for refugees and relocated populations. Our model, with its forecasting capability of outbreaks, will help policy makers to mitigate outbreaks by assessing possible intervention mechanisms such as better handling refugees, vaccinations, school/workplace closures, antivirals, and social distancing methods. This project with its planned training program will help the researcher to transfer his knowledge in network modeling and analysis into a new field of large-scale agent-based modeling and simulation in a new institution in Turkey where there is a great need for these methods in public health.Status
CLOSEDCall topic
MSCA-IF-2017Update Date
28-04-2024
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