Advanced modelling of the evolution of an epidemiological outbreak to predict its consequences in terms of health resource utilisation and mortality.

Call for tender for project: Grants for health research and development projects 2019: Promotion of health research

Funding body: Department of Health, Basque Government

Record no.: 2020111078

PI: José María Quintana 

Funding awarded: €75,838

Description: The various epidemics that periodically affect the health system (at least annually for influenza, and currently and with a very high incidence for SARS-CoV-2) require valid and detailed information on their evolution and short, medium and long term predictions in real time that allow the health system to organise itself in advance in order to be able to tackle the health and sanitary problem that this entails. This information also serves to monitor the results that are being obtained globally by different health areas and fields. However, this information must also be easily and quickly understandable by the recipients of the information.

Objective: To study the usefulness of the health system’s information and data storage system as a source for the rapid and efficient collection of data necessary for modelling an epidemiological outbreak; modelling it in order to predict its evolution and presenting results to aid decision-making. The project will build on the experience gained so far during the SARS-CoV-2 pandemic to define semi-automated and flexible criteria for searching, extracting, cleaning and aggregating data. These criteria will be validated with the full pandemic data and will be applied to possible outbreaks of this epidemic during the autumn-winter 2020 or later and to the annual influenza epidemic. 

Study design: Observational study that will develop modelling of the evolution of the epidemiological outbreak. The type of modelling proposed is a SEIR (susceptible-exposed-exposed-infected-recovered) model stratified by age based on ordinary differential equations (ODE), with a distinction between symptomatic and asymptomatic infections and with a Bayesian approach to estimation, incorporating data from the Basque Country as prior information. Incidence and cumulative incidence predictions will be made for the number of infected patients, number of patients (differentiating between those treated in primary care and those in hospital), number of admissions, number of ICU admissions and number of deaths at the Basque Country level and at the level of the Integrated Health Organisation (IHO) and/or hospital. 

Roles: Kronikgune – Project Coordinator