MIDIDP · Modeling Infectious Diseases in Dynamic Populations with Relocation and Refugeeism
Horizon 2020 — Marie Skłodowska-Curie Actions
- Duration
- 2018-04-01 → 2020-03-31
- EU contribution
- €157,846
- Participants
- 1
- Scheme
- MSCA-IF-EF-RI
Lines connect the coordinator with its partners.
Results in brief
Modeling Infectious Diseases in Dynamic Populations with Relocation and Refugeeism
Infectious disease outbreaks such as the new coronavirus disease (Covid-19) pandemic brings a great burden on societies in terms of lives lost, economic stagnation lost labor, etc. To better prepare ourselves for these outbreaks, we need to make good planning of our resources such as hospitals, health workers, medical equipment, etc. The modeling and simulation method has a great advantage over other methods in terms of scenario analysis for planning, preparedness, and response. In this project, we propose to create a unified framework to combine different data sources to create realistic simulation software to model the spread of infectious diseases. An important aspect of the population nowadays is the refugees living in camps or cities in many European countries. Any preparedness and response activity against an infectious disease should include them as an important player due to their possibly different culture, vaccination status, immunological history, etc. Overall objectives of MIDIDP project are: 1. To prepare a complete synthetic population as a case study. 2. To simulate infectious diseases by using the synthetic population 3. To calibrate and verify the simulation and to test different containment scenarios and interventions for infectious diseases for different countries and regions with and without refugees The overall conclusions of the project are: We developed an agent-based model to realistically simulate an infectious disease epidemic in a geographic area, which takes many data sets as input including age-sex distributions, family size, local and refugee population density, disease/pathogen information. In doing this we created a generic framework (a protocol) on how to go from input data sets to final simulation results that can provide guidance for public health authorities to respond to infectious diseases. This framework is designed in such a way that anybody with basic knowledge of epidemiology and programming can utilize it to create simulations for their geographic area and population. Our initial results show that among all many input parameters the family size is the most sensitive one in the final size of the epidemic for vaccine-preventable childhood diseases such as measles and population density is an additional sensitive parameter in diseases with no prior immunity such as pandemic influenza and the new coronavirus disease Covid-19.
Data: CORDIS, © European Union
Project objective
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.
Original text from CORDIS.
Participants
- ISTANBUL MEDENIYET UNIVERSITY · Kadikoy, IstanbulCoordinatorTürkiye
Links
Data: CORDIS, © European Union