Modelling of COVID-19

About this page

The Model and Algorithms in Transportation Systems (MAT) research group belongs to the University of Castilla la Mancha (Spain). The MAT group develops its research in the field of Operations Research. The aim is to develop new optimization models applied to the planning, design and control of transport systems.

In 2020, with the spread of COVID-19 (coronavirus) disease in Spain, after having appeared in the city of Wuhan (China), the group has decided to apply its experience in mathematical modelling to develop new models capable of predicting the evolution of the virus in a given country. The contribution of the MAT group involves the development of a website for the monitoring, collection and visualisation of COVID-19's disease data. Currently, it is possible to visualize two heat maps, updated every day, which show the current global state of the epidemic. These maps are located under this text in the section "Current global situation of COVID-19 disease". The first map represent the Reproduction number (Rt) of the last day for all the countries in the world using the Wallinga and Tenuis method. The second map represent the number of Acumulated Cases per million of inhabitants. The website also allows the visualization of COVID-19 disease data grouped by country through the "Charts by Country" menu option. In addition, "Data in Spain" option shows the data grouped by Autonomous Communities for the case of Spain.

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For each country, it is possible to view the total number of cases, the active cases, deaths and recoveries. The data for each country is updated daily and has been obtained from a public repository (see references section). In addition, for each of the countries, a one-week view forecast of the number of new cases, recoveries and deaths is provided.

Similarly, the website shows the evolution of the virus at the level of the Autonomous Communities in Spain. The data of each one of the communities is daily obtained from the database provided by the Instituto de Salud Carlos III de Madrid, whose data is used by the Spanish Health Ministry (see the references section). Thus, for each of the Autonomous Communities, the number of total cases, active cases, deaths and recoveries is reported, as well as the number of patients hospitalised or critical (in the ICU). In addition, it is possible to view a one-week view forecast of the number of new cases, recoveries and deaths for each autonomous community.

Finally, the website shows the evolution of the Reproduction Number (R) over time for each country. This value represent the average number of secondary cases that each infected subject can infect during the course of his/her infection. The website currently reports the reproduction number using four different methods:
  • Wallinga and Teunis. Wallinga, J., & Teunis, P. (2004). Different epidemic curves for severe acute respiratory syndrome reveal similar impacts of control measures. American Journal of Epidemiology, 160(6), 509–516.
  • Cori et al. Cori, A., Ferguson, N. M., Fraser, C., & Cauchemez, S. (2013). A new framework and software to estimate time-varying reproduction numbers during epidemics. American Journal of Epidemiology, 178(9), 1505–1512.
  • SIR-based models. Chowell, G., Nishiura, H., & Bettencourt, L. M. A. (2007). Comparative estimation of the reproduction number for pandemic influenza from daily case notification data. Journal of the Royal Society Interface, 4(12), 154–166.
  • Fraser. Fraser, C. (2007). Estimating Individual and Household Reproduction Numbers in an Emerging Epidemic. PLoS ONE, 2(8), e758.
It is also possible to compare each R value with the equilibrium point (the value R=1), which allows to clarify if a country is in an expansion or contraction phase of the epidemic. The aim is to monitor the state of the epidemic and provide information and knowledge to authorities who are working hard on a daily basis to reduce its effects.
Current global situation of COVID-19 disease

Last update 15-07-2020 11:01



Last update 15-07-2020 11:01
References

The world data used on this website is collected daily from the GitHub repository for the 2019 Novel Coronavirus Visual Dashboard operated by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE) with the support of the ESRI Living Atlas Team and the Johns Hopkins University Applied Physics Lab (JHU APL).

The data about Spanish CCAA used on this website is collected daily from the Instituto de Salud Carlos III de Madrid, which is reported directly by the Spanish Health Ministry.

The data obtained from the above sources is presented without any pre-processing or inconsistency removal stage.