The coronavirus disease 2019 (COVID-19) Epidemiology Forecaster is a fully customizable SEIR(susceptible, exposed, infectious, recovered) model that allows users to develop scenario-based global COVID-19 forecasts for up to two years from initial outbreak. Base assumptions used in this model have been tested and developed by DRG’s Epidemiology team using a semi-mechanistic methodology, running thousands of simulations with plausible parameter ranges set out by the current literature and benchmarked using daily reported COVID-19-related mortality data from the European Centre for Disease Prevention and Control (ECDC) using goodness-of-fit analysis.

Forecasting COVID-19 is challenging for several reasons, including the uncertainty in effect size and duration of local nonpharmaceutical interventions and the timing and efficacy of different treatments entering the market. Therefore, DRG’s COVID-19 Epidemiology Forecaster is flexible by design. Each variable used in the model is fully adjustable, and the tool allows the addition of up to five interventions. The COVID-19 Epidemiology Forecaster reports the following metrics in a tabular form, as well as in a variety of data visualization graphics:

  • Total case estimates (everyone infected with the virus, including laboratory-confirmed and -unconfirmed cases).
  • Mortality associated with COVID-19.
  • Adjusted infection fatality rate to allow cross-country comparisons.
  • Incident and cumulative hospitalizations.
  • Incident and cumulative intensive care unit (ICU) admissions.
  • Available in both total and age-stratified formats.

The COVID-19 Epidemiology Forecaster allows users to export diagrams and charts as image files that can easily be incorporated into internal or investor/shareholder material.

Table of contents

  • Coronavirus COVID-19 Forecaster
    • Introduction
      • COVID-19 Global Epidemiology Forecaster

Author(s): Oliver Blandy; Nishant Kumar, MPH; Alexandre Vo Dupuy (PhamD, MSc)

Oliver Blandy, BSc PGCE MSc, joined Decision Resources Group (DRG) as an Associate Epidemiologist in 2017. He focuses on the epidemiology of cancer. Oliver holds an MSc from the University of Bristol where he specialized in Nutrition, Physical Activity and Public Health. He also holds a BSc in Chemistry and has a Post Graduate Certificate in Education (PGCE), both from the University of Bristol and taught general science and Advanced Chemistry in high school for two years. Before joining the team at DRG, Oliver worked as a Research Assistant for Imperial College London where he was the lead for several studies within an NIRH funded research group that investigated healthcare associated infections and antimicrobial resistance.

Nishant is a senior epidemiologist and head of oncology within the epidemiology team at Decision Resources Group. He also covers some CNS diseases, including Alzheimer’s disease and dementia. His key interests are developing interactive patient flows, and modelling disease progression to forecast commercially relevant drug-treatable incident and prevalent populations. Nishant also spends a lot of time collaborating with clients to help answer more specific questions through custom work and consulting projects. His qualifications include an MSc in Public Health with specialization in epidemiology and statistics from King’s College London, and a BSc in Medical Studies from the University of Birmingham.

Alexandre joined Decision Resources Group in 2017 as an Associate Epidemiologist. He holds a PharmD from Paris Descartes University as well as a Master in pharmacoepidemiology from the University of Bordeaux.   Prior to joining Decision Resources Group, he worked within the fields of Consulting and Real World Evidence ,   and as an intern within the Global Epidemiology department of   one of the top pharmaceutical company . As an associate epidemiologist, Alexandre works across multiple disease areas estimating and forecasting incidence and prevalence, with a focus on cancer epidemiology.