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Simulation model for productivity, risk and GDP impact forecasting of the COVID-19 portfolio vaccines

Shnaydman, V.

2020-11-04 health economics
10.1101/2020.11.01.20214122 medRxiv
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Executive summaryThe paper presents the methodology and modeling results for COVID-19 vaccines portfolio forecasting, including R&D output (rate and likelihood of approvals at a vaccine technology platform level) and manufacturing production output to meet worldwide demand. In order to minimize the time and risk of global vaccination, scaling up of Operation Warp Speed (OWS) and other programs could be very beneficial, leading to increased financing for additional vaccine development programs, in both Phase III clinical trials and in manufacturing. It would also lead to a reduction of the global production time for world vaccination, from 75 months for a baseline scenario to 36 months, reducing potential global GDP loss by as much as US$4.2 trillion (US [~] $1 trillion) when compared to the baseline scenario.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

1
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Top 0.1%
22.8%
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2
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Top 0.1%
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11
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1.6%
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Top 2%
1.2%
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Top 10%
1.2%
19
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Top 3%
1.2%
20
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Top 4%
1.2%
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Top 5%
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22
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Top 0.2%
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○ 128 papers in training set
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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.