webinar-wave

WEBINAR:
WAVE, a Hybrid Epidemiologic Model for Forecasting the Course of the Pandemic at Highly Local Level

 Date: 30th June 2021

Time: 7.30pm – 8.30pm (SGT)

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Summary

The COVID-19 pandemic has brought many challenges for public health, hospital managers, health care research, and other disciplines. Public health departments need forecasts of the evolving case numbers and the possible effects of interventions, vaccines, and other measures. Hospitals must plan their resources in light of expected surge requirements while those planning clinical trials, either for SARS-COV-2 vaccines and treatments or for unrelated trials have to consider where hot zones will be and for how long. WAVE (Weekly Assessment of coVid Epidemiology) was created to simulate the trajectory of COVID-19 at a highly local level. It consists of three modules to address a wide range of potential uses. In this webinar, the WAVE model will be introduced and its use will be illustrated through several case studies.

Discussion points

In this webinar, we will discuss:

  • The design of the WAVE model
  • Predictions obtained from WAVE
  • Scenario definitions using WAVE
  • Case-studies: a vaccine trial, a hospital resource use planner, and a treatment

Learning outcomes

Attendees of this webinar will understand:

  • The concepts and implementation of a customizable epidemiologic model
  • Its use for forecasting and planning during COVID-19
  • How to specify analyses and scenarios

Speaker

Jaime Caro

Professor in practice, Health Policy, London School of Economics
Professor, Faculty of Medicine and Health Sciences, McGill University
Chief Scientist, Evidera

Dr Caro develops and applies novel techniques in modelling, health economics, comparative effectiveness, epidemiology, and outcomes research. To provide a better alternative to the well-known QALY, he is working on the BADI, a broader approach to valuing health benefits. He continues to develop DICE, the unified approach to health economic modelling that he created. Working with health technology assessment agencies and academic groups, he is formalising this innovation to enable rapid, standardized and less error-prone development of decision-analytic models.

Registration is complimentary!

Please scan the below QR code for registration or click on the link, https://nus-sg.zoom.us/meeting/register/tZYsc-ugpzMoG9OdOEvow36cuugk0DnBPDTp

For more information on this course, please contact us at hiper@nus.edu.sg

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