2020-11-04 13:11:44

Introduction

  • SARS-CoV-2/COVID-19 continues to remain a major concern.
  • Non-pharmaceutical interventions (NPI) are currently the main method of control.
  • Hopefully soon vaccines will be available and help to reduce the future impact of COVID.
  • Simulation modeling can be a useful tool to make forecasts and evaluate the impact of different interventions.

Simulation modeling areas

Source: NOAA

Source: NOAA

  • Weather forecasting.
  • Simulations of man-made, engineered system.
  • Predicting the economy.
  • Infectious disease transmission.

Simulation modeling overview

  • Build a model that simulates the process of disease transmission.
  • Include any details that are relevant for the question, omit everything else.

Simulation modeling uses - Understanding

Simulation modeling uses - Forecasting

Simulation modeling uses - Intervention Assessment

A few of my recent COVID modeling projects

Forecasting COVID in the US

Motivation

  • We wanted to know how many cases/hospitalizations/deaths to expect.
  • We were initially asked by the state of Georgia’s governor office.
  • We then extended it to all US states.

Model

  • Model is fit to case and death data for each state, then used to forecast.

Results (state of GA)

Acknowledgments and More Information

Disease surveillance and screening to control COVID on university campuses

Motivation

  • We wanted to know if/how one could safely re-open college campuses.
  • Emory University approached my colleague Ben Lopman. We built a somewhat general model.

Methods

  • Simulation model for COVID-19 spread and screening/testing based control.

Results

Acknowledgments and More Information

Modeling the impact of non-pharmaceutical interventions to suppress COVID spread

Motivation

  • We wanted to assess the impact of different non-pharmaceutical interventions (NPI) on controlling COVID in Zhejiang Province, China.
  • We wanted to determine the impact of NPI on future cases.

Model and fit to data

Results

Acknowledgments and More Information

  • Collaborators: Yang Ge, Zhiping Chen, Leonardo Martinez, Qian Xiao, Changwei Li, Enfu Chen, Jinren Pan, Yang Li, Feng Ling, Ye Shen
  • More information: prepared for submission

Evaluating the impact of future COVID vaccines

Motivation

  • As COVID vaccines become (hopefully soon) available, figuring out how to roll them out in the most efficient way is not easy.
  • We can build simulation models that include vaccination, explore the impact of different vaccination strategies for currently hypothetical, later real vaccine candidates.

Model

Results

Acknowledgments and More Information

Summary