COVID-19 modeling and prediction

  • all
  • Epidemiology
  • Motivation
  • Method
  • Results
Modelling of disease progression
Nowadays, epidemiology integrates with mathematics, complex system science, sociology, management science and computer science given rise to the rapid development of mathematical and computational epidemiology. Mathematical and computational methods are not only important tools for understanding the epidemic spread but also on evaluating policies of disease control.
Impact on scientific research
The current pandemic situation has motivated all strata of scientific life to devise transdisciplinary approaches against COVID-19. Doctors, epidemiologists, engineers, physicians, and economists are brought together to come up with cool-headed and integrated methods of patient stratification, so as to minimize resources spent on those with low risk and allocate them on those with the highest risk, in such a way that strikes a balance between simply monitoring and providing adequate care for all, even beyond the hospital premises. We are in need to be better prepared towards future waves of COVID-19, or other similar, pandemics and epidemics.
Modelling of COVID-19 pandemic
Towards this direction, our group aims to simulate epidemic progressions, and evaluate conditions and metrics that actually express a high-risk situation that needs our attention for the optimal spatial, temporal, and financial use of health care resources and the avoidance of the loss of human lives.
A complex epidemic model
We study the spread dynamics of COVID-19. The modeling parameters and outputs are constrained and optimized by the publicly available daily reported data. We explore the effect of several intervention scenarios related to the disease spread dynamics. We focus on o accurately follow the pandemic progression and make predictions in a short time frame. The impact of several interventions and transmissibility rates on the spread dynamics in longer time frames is also explored with the aim to assess the time frame and the conditions under which controlling COVID-19 spread and reducing the burden is feasible.