The COVID-19 pandemic is currently generating considerable activity among applied and industrial mathematicians in all European nations.
A number of national task forces and ad-hoc research teams have for weeks been working to provide both the public and the various national authorities with accurate models of the evolution of the pandemic. Each effort adjusted to the local situation, and using data from regional hospitals to examine the effect of strategies and policies implemented at the national level.
This page on the Blog of the European Consortium aims to provide an overview of this spectrum of efforts, providing public web links, and some national contact points.
The page will be updated as more information comes in. ECMI salutes the effort to apply the most advanced mathematical insigts available throughout Europe to help in making the most informed decisions and ultimitaly alleviate this grave threat to populations everywhere.
If you would like to add some information about the situation in your country, please send it to the ECMI BLOG c/o firstname.lastname@example.org.
Poul Hjorth, 1.4.2020
In Germany several groups are developing mathematical models and simulations for the spread of COVID-19. The ECMI centers in Kaiserslautern (Wolfgang Bock), Koblenz (Thomas Götz, email@example.com) and Trier (Jan-Pablo Burgard) joined the MOCOS-group (MOdeling COrona Spread) initiated at the ECMI-center Wroclaw (Tyll Krüger). The aim of this group is to perform microstructure simulations based on official census data involving household composition and age distribution as the main population structure variables. For both countries, Poland and Germany, as well as for two representative cities, Wroclaw and Berlin, we obtained first results indicating that a mitigation and herd immunity strategy is likely to fail. On the basis of a SIR microsimulation for Germany and Poland, we show that the interval for the transmission parameter, for which the COVID-19 epidemic stays overcritical but below the capacity limit of the health care system to reach herd immunity is so narrow that a successful implementation of this strategy is likely to fail.
These finding are avilable in the preprint „Mitigation and herd immunity strategy for COVID-19 is likely to fail“, see https://www.medrxiv.org/content/10.1101/2020.03.25.20043109v1
Currently we are including effects of quarantine measures, contact tracing and how social distancing may be allowed to vary over time in the model.
Stay tuned for more results coming up soon …
Thomas Götz, 1.4.2020
In Spain the Comité Español de Matemáticas, CEMat, is promoting the initiative Mathematics against coronavirus. Its aim is to make the analysis and modelling skills of the Spanish mathematical community more readily available to the administration and to the society in general, in order to get a better understanding of the actual COVID-19 crisis.
This action includes:
- Collecting links and contributions of the Spanish mathematical community about the virus spread, and make them public on the initiative’s website: http://matematicas.uclm.es/cemat/covid19/en/links-and-contributions/.
- Promoting the interaction between different research groups to create new synergies between them.
- Establishing an Expert Committee to review the contributions and, eventually, report conclusions and recommendations to the administration.
- Collecting relevant data sets to make them available to the researchers. They can be found on http://matematicas.uclm.es/cemat/covid19/en/data/.
- In order to build a meta-predictor to provide a short term behaviour of the virus to the authorities, a call for researchers has been made. To this end, the authors’ collaboration will be used to build a meta-predictor or “cooperative predictor”, based on optimized predictions of different methods desegregated by regions.
For further information, see the website http://matematicas.uclm.es/cemat/covid19/en/.
Peregina Quintela on behalf of the committee of experts, April 3, 2020
There are several groups in Portugal studying the evolution of COVID19 and trying to understand this outbreak and develop measures to control it.
1. At national level, the Portuguese Minister of Science, Technology and Higher Education launched a platform for sharing ideias and proposals on this field (see:
https://www.science4covid19.pt/en/) as well as two new funding programmes (see:
2. A group at the University of Coimbra is collecting and analysing data in (see: https://apps.uc.pt/mypage/faculty/bcpaiva/pt/daily_covid19; and https://covid-pt.blogspot.com). First results form this group are available in the preprints:
Estimation of risk factors for COVID-19 mortality – preliminary results and Temperature and humidity role in the doubling time of COVID-19 cases.
3. A group at IST, University of Lisbon, presents simulations using a model fitting to the statistical data of infected people from the novel coronavirus (see: https://sites.google.com/tecnico.ulisboa.pt/fitteia/home/covid-19) . Anyone interested can register in the system and study the data eventually with other models.
4. A group at the University of Porto developed a tool that allows anyone to simulate different COVID-19 testing rates (with different percentages of positive results), so as to estimate the number of avoided hospitalisations (including ICU episodes) and the subsequent economic savings (see: http://simtestcovid.gim.med.up.pt).
A Portuguese mathematician is updating the prediction of the epidemiological curve for a national TV network in a regular basis.
Adérito Araújo, April 5, 2020
In the UK the Royal Society has launched the RAMP, Rapid Assistance in Modelling the Pandemic, initiative https://royalsociety.org/news/2020/03/Urgent-call-epidemic-modelling/ To quote the RAMP website:
This urgent call to action is addressed to the scientific modelling community, and is a scheme to allow those with modelling skills (including data science) to contribute to current UK efforts in modelling the COVID-19 pandemic.
A willingness to work on specified tasks, and to deadlines, is needed. However, no previous experience in epidemic modelling, as such, is required of RAMP participants.
RAMP is chaired by Mike Cates (Chair), the Lucasian Professor of Mathematics at the University of Cambridge, and the steering committee includes the UK’s leading mathematical epidemiologist, Julia Gog.
As might be expected, RAMP has been overwhelmed with offers of support from across the UK modelling community and is currently prioritising areas that can best support the national effort to tackle the pandemic.
A similar call for help from data scientists has been issued by the Alan Turing Institute
Part of the response to these calls has been the formation of the Virtual Forum for Mathematics, led by the INI, ICMS, KTN and a number of UK university groups. This forum aims to collect, triage, and address problems related to COVID-19, for which a mathematical and statistical approach, and the input of mathematicians, statisticians and data scientists can be useful. It is important to note that as well as its direct impact on health, the issues associated to COVID-19 also impact on logistics, food supply, transport, economics, and mental health and mathematics can give insight into all of these. Furthermore mathematics will be important in modelling the exit strategy after the pandemic. As a part of this strategy the forum will be running Virtual Study Groups (VSG) to tackle these problems by using the combined expertise of teams of mathematicians. The VSGs will be based on the highly successful collaborative model used in the European Study Groups with Industry, but will be making full use of virtual technology such as Zoom and HackMD. We are in the process of organising a pilot VSG to test the idea and the technology, with the first full (COVID-19 centred) VSG currently scheduled for early May. However, we expect that other models for collaborative work by mathematicians on COVID-19 problems will emerge during the pandemic, and we are open to new ways of working to tackle the emergency.
In parallel there has been a sustained effort to develop materials to help inform the public about the nature of the mathematical models used to predict the evolution of the pandemic. A good set of these can be found at https://plus.maths.org/content/tags/covid-19
Prof Chris Budd OBE, University of Bath, UK. 5/4/20
In Denmark, several groups at Technical University of Denmark (DTU), University of Copenhagen (KU), and Roskilde University (RUC) are working on modelling and analysis of the epidemic.
An expert group spanning these universities was formed in order to provide consultancy to the authorities. Models pursued include ODE models of SEIR, SST, SSI-types, with additional states, and taking into account age structure of the population, as well as individual-based stochastic Markovian simulation models. The objective of these models is to examine scenarios for governmental interventions and predict the resulting load on the health care system. – Also, models based on time series analysis are pursued in order to nowcast and short-term forecast.
One group spanning Aalborg University and the Technical University of Denmark is pursuing a control-theoretic approach to identify optimal feedback strategies; a critical component in this analysis is the time lag from policy intervention to observed response, as well as the uncertainty in model, parameters, and states of the system.
Contact person: Poul G. Hjorth, DTU firstname.lastname@example.org
In Ireland, the Chief Medical Office of the Department of Health has established an expert group to provide advice and expertise in the area of epidemiology data modelling. The function of the group is in an advisory capacity reporting into the National Public Health Emergency Team (NPHET); the group is known as the COVID-19 Irish Epidemiological Modelling Advisory Group (IEMAG).
Applied mathematicians and statisticians from several Irish universities (including University of Limerick, Maynooth University and University College Dublin) are active members of IEMAG. They are working to develop mathematical and statistical models, with a strong emphasis on calibration of models to data. The community of applied mathematicians and statisticians in Ireland have also been very forthcoming with offers of assistance, and the IEMAG members are working to incorporate the range of ideas and skillsets into the ongoing modelling work.
Prof. James Gleeson, University of Limerick, Ireland