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Webinars » A simplified approach to understanding how mathematical modeling of COVID-19 can help minimize spread

A simplified approach to understanding how mathematical modeling of COVID-19 can help minimize spread

As we practice the strict social distancing guidelines enforced by governments globally, many questions have arisen concerning the mathematical models that are being used to track and predict the outcome of the COVID-19 pandemic. This talk offers a simple examination of the SIR pandemic model and its value in predicting disease outcome under various social conditions. It also demonstrates how specific measures taken by individuals coupled with widespread testing can directly affect the modelling to limit viral transmission and reduce the risk of a second wave of the pandemic.

Learning outcome from this webinar:

  1. A simplified explanation of pandemic modelling.
  2. How the model can offer guidance in practical measures that can be taken to reduce the spread of disease.
  3. Solutions that can bring widespread testing to limit transmission of COVID-19 globally.
  4. The available molecular and serological diagnostics methods and their advantages and disadvantages.

    Niren Murthy
  • Speaker:
    Sean Taylor, MBA, Ph.D. Field Appliction Scientist Manager, GenScript
  • Date: April 16th
  • Time: 1pm EST/ 10am PST
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Speaker Bio

Sean Taylor holds a Ph.D. and an MBA from McGill University and has spent the past ten years publishing articles, providing seminars, workshops and training videos to help the global scientific community achieve excellent data from western blotting, qPCR and digital PCR experiments.