EESS talk on "Epidemiological modelling during the COVID-19 pandemic: between Science and Public Health"
Event details
Date | 15.12.2020 |
Hour | 12:15 › 13:00 |
Speaker | Joseph C. Lemaître, Doctoral Assistant, Ecohydrology Laboratory, IIE |
Location |
ZOOM
|
Category | Conferences - Seminars |
Abstract:
Coronavirus disease 2019 (COVID-19) has caused strain on health systems worldwide due to its high mortality rate and the large portion of cases requiring critical care and mechanical ventilation. During these uncertain times, public health decision makers, from city health departments to federal agencies, sought the use of epidemiological models for decision support in allocating resources, developing non-pharmaceutical interventions, and characterizing the dynamics of COVID-19 in their jurisdictions. In response, the IDDynamics group at JHU developed a flexible scenario modelling pipeline that could quickly tailor models for decision makers seeking to compare projections of epidemic trajectories and healthcare impacts from multiple intervention scenarios in different locations.
At the same time, scientists sought to better understand transmission dynamics and general epidemiology of COVID-19. Doing so with available data presents many challenges, with critical implications for the interpretation of the course of the pandemic. One possible approach, used at the Laboratory of Eco-hydrology, is inference on epidemiological models. Using reported data and our knowledge of infectious disease dynamics, it is possible to derive information on e.g, the variations of the reproduction number, the serial interval, the effectiveness of past non pharmaceutical interventions ... These quantities carry scientific interest and, with proper care, may be useful for scenario planning.
This talk explores the feedback loop between epidemiological modelling for inference and for scenario planning to advise decision makers. It focuses on mostly on the first months of the COVID-19 pandemic, when very incomplete information on disease transmission was available.
Short biography:
Joseph Lemaitre is a PhD student working on infectious disease epidemiology in the Laboratory of Eco-hydrology, EPFL. His dissertation focuses on cholera transmission modelling and in optimal allocation of control ressources. From February, he was visiting the Infectious Disease Dynamics group at the Johns Hopkins Bloomberg School of Public Health on a SNF Mobility Grant. There, he has been developing the JHU COVIDScenarioPipeline, used by several countries and states to inform public health decisions for the COVID-19 pandemic. In Switzerland, Joseph Lemaitre has performed work as part of the Modelling group of the Swiss National COVID-19 Science Task Force, and scenario planning work for Canton de Vaud and CHUV.
Coronavirus disease 2019 (COVID-19) has caused strain on health systems worldwide due to its high mortality rate and the large portion of cases requiring critical care and mechanical ventilation. During these uncertain times, public health decision makers, from city health departments to federal agencies, sought the use of epidemiological models for decision support in allocating resources, developing non-pharmaceutical interventions, and characterizing the dynamics of COVID-19 in their jurisdictions. In response, the IDDynamics group at JHU developed a flexible scenario modelling pipeline that could quickly tailor models for decision makers seeking to compare projections of epidemic trajectories and healthcare impacts from multiple intervention scenarios in different locations.
At the same time, scientists sought to better understand transmission dynamics and general epidemiology of COVID-19. Doing so with available data presents many challenges, with critical implications for the interpretation of the course of the pandemic. One possible approach, used at the Laboratory of Eco-hydrology, is inference on epidemiological models. Using reported data and our knowledge of infectious disease dynamics, it is possible to derive information on e.g, the variations of the reproduction number, the serial interval, the effectiveness of past non pharmaceutical interventions ... These quantities carry scientific interest and, with proper care, may be useful for scenario planning.
This talk explores the feedback loop between epidemiological modelling for inference and for scenario planning to advise decision makers. It focuses on mostly on the first months of the COVID-19 pandemic, when very incomplete information on disease transmission was available.
Short biography:
Joseph Lemaitre is a PhD student working on infectious disease epidemiology in the Laboratory of Eco-hydrology, EPFL. His dissertation focuses on cholera transmission modelling and in optimal allocation of control ressources. From February, he was visiting the Infectious Disease Dynamics group at the Johns Hopkins Bloomberg School of Public Health on a SNF Mobility Grant. There, he has been developing the JHU COVIDScenarioPipeline, used by several countries and states to inform public health decisions for the COVID-19 pandemic. In Switzerland, Joseph Lemaitre has performed work as part of the Modelling group of the Swiss National COVID-19 Science Task Force, and scenario planning work for Canton de Vaud and CHUV.
Links
Practical information
- General public
- Free
- This event is internal
Organizer
- EESS - IIE
Contact
- Prof. Andrea Rinaldo, ECHO