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COVID Vaccine Forecast
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MillionsFauciBakerAssumptions/Comments
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US Population328.2
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Adults only (<16)267.7See Population tab
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For herd immunity214.180%147.255%
See article about Dr. Fauci's Dec-2020 comments
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Shots required per person2.02.0
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Total Vaccines needed428.3294.4
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Batch 1 (mm)
Batch 2 (mm)
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Vaccines orders - Trump Admin.
200as of end-Dec
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Vaccines orders - Biden Admin.
200.0as of Jan. 26
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Vaccines to order28.3
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UM Goal
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Delivered by?15-Jan-2131-Mar-21assume half of Dec/half of Jan
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Herd immunity target date31-Jul-21for school to reopen for F2021
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months34.0130.42avg days/mo.
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Vaccines per month needed66.77.0
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Per day2.2
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Biden's pledge
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Administered100in first 100 days
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Months3.3
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Per month30.4
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Per day1.0
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Months to hit herd immunity7.0
assumes 2 shots per person-month
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From inauguration20-Jan-21
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To Herd immunity implied date
22-Aug-21
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Current Rate
Average Rate
30-day Avg
30-day Baker
Highest Rate
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Average administered (daily)1.440.850.854.63See Actuals tab
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Average Recovered (daily)0.040.16
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Total Immune1.484.79
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Number of days to herd immunity 1
298.4501.8345.092.5excludes recoveries
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Number of days to herd immunity 2
289.789.4
includes recoveries in vaccinations
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Months9.52.9
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Forecast herd immunity date 1
14-Nov-215-Jun-2231-Dec-21excludes recoveries
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Forecast herd immunity date 2
5-Nov-21
includes recoveries in vaccinations
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Notes
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1) Starting on inauguration day, the CDC appears to be updating their data each weekday at various times
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2) On Jan. 23, I added a best case forecast based on the highest daily rate in the CDC data
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3) The fitted trendline based on CDC data does not take into account that the vaccine rate will decline as we get closer to the goal. How best to represent an increasing difficulty factor (an assumption) and convert the trendline to a curve ?
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4) On Feb. 18, I added recovered data into our forecast in blue. From the CTP project (Data for All States download table): https://covidtracking.com/data/download
Recovery data only available from CTP thru Mar. 7, 2021.
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5) We have not yet factored in the state, county and international numbers, which have different sources, but are available. We are looking at the composition of the student body with the potential to create a model that factors the data for home locations in addition to the destination location (Washtenaw)
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