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COVID-19 Predictive Analytics April 8th, 2020 Predictive Analytics - PowerPoint PPT Presentation

COVID-19 Predictive Analytics April 8th, 2020 Predictive Analytics Focus Areas Health System Clinical Health Case Trajectories Capacity Consequences Forecasting Various projection scenarios are provided to inform COVID-19 management and


  1. COVID-19 Predictive Analytics April 8th, 2020

  2. Predictive Analytics Focus Areas Health System Clinical Health Case Trajectories Capacity Consequences Forecasting Various projection scenarios are provided to inform COVID-19 management and health system planning. Goals: 1) Assess provincial and regional trends of COVID-19. 2) Determine whether public health measures have had an impact on flattening the curve. 3) Forecast health system demand and compare to capacity. 2

  3. Focus of Today’s Presentation • Current Situation • Compare the trajectory of COVID-19 cases in NL to other provinces • Examine local trends and impact of ongoing public health measures • Discuss characteristics of the NL population affected with COVID-19 • Future projections for COVID-19 • Discuss challenges and limitations in projecting cases • Display short term needs for acute and critical care beds • Present projections results from two possible scenarios 3

  4. Current Situation Understanding the Data 4

  5. COVID-19 Positive Cases by Province (Total Number of Cases / 100K population 5

  6. Cumulative NL Cases (All, Funeral Home, Other) 6

  7. Age Distribution for COVID-19 Population, NL 30.0 25.0 20.0 Percent 15.0 10.0 5.0 0.0 Under 20 20-44 45-54 55-64 65-74 75-84 85+ Age 7

  8. Age Distribution for COVID-19 Population, by Hospitalization Status, NL 60 50 40 Percent 30 20 10 0 Under 20 20-44 45-54 55-64 65-74 75-84 85+ Age Hospitalized ICU Non-hospitalized 8

  9. COVID-19 Population with Selected Comorbid Illnesses, by Hospitalization Status, NL 90 80 70 Percent 60 50 40 30 20 10 0 Heart Failure Hypertension IHD AMI Asthma COPD Stroke Diabetes Additional illness Hospitalized ICU only Non-hospitalized 9

  10. Forecasting 10

  11. Projecting COVID-19 Cases • Modelling • Conceptually helpful • Numerous underlying assumptions, frequently misleading • Challenges in NL - Cluster effect, small number of deaths • Our Approach • Let the data drive the model • Short term projections • Look for consistency with other models • Refine model frequently based on the data 11

  12. Current and “worst case” scenarios for acute care hospitalizations till April 30 th 12

  13. Current and “worst case” scenarios for critical care beds till April 30 th 13

  14. Health Care System Capacity for Province (Scenario 1 - 32% of NL Infected with COVID-19) 14

  15. Health Care System Capacity for Province (Scenario 2 – 51 % of NL Infected with COVID-19) 15

  16. Summary • Public Health Measures have clearly had a significant impact in flattening the curve • Need to continue and further improve our efforts to achieve the best possible outcome • Future outcome for COVID-19 is highly dependent on the collective effect of our individual actions to stop its spread. 16

  17. Thank You

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