Probabilistic predictions of the impact of vaccines and changes in the US COVID pathway

In a summary of a report published today Thomas McAndrew, a computer scientist and associate professor at Lehigh University College of Health, presents probabilistic predictions about the impact of vaccines and changes on the U.S. COVID route across over the next few weeks. The aim of the report, says McAndrew, is “to support public health officials, infectious disease modeling organizations, and the general public”

Important reports:

  • A consensus of 91 forecasts predicts that B.1.1.7. variability is found in 42% of all genetic sequences with S-gene mutation in the first two weeks of March and in 72% in all sequences between March 29 and April 4, 2021.
  • The consensus among experts in modeling an infectious disease and a learned prognosis from Metaculus is that on February 28, 55,420,000 people will receive at least one dose of vaccine. General predictors from Good Judgment Open (GJO) – an online prediction platform open to anyone with an interest in the public – responded with an average of 52.2 million people receiving one or more vaccine doses. Preliminary data from the CDC show that 49,772,180 people received an initial dose on 28 February.
  • Consensus predictions from both Metaculus and Good Judgment Open predicted a reduction in the number of cases, deaths and hospitalizations for the last week of February (21-27).

The team shares with members of the Centers for Disease Control and Prevention (CDC), the Council of State and Territorial Epidemiologists, and members of MIDAS.

McAndrew’s approach to forecasting is different from the traditional approach. Instead of building a computer model to predict cases, deaths, and hospitals due to COVID, it requires specialists and training forecasters to predict these targets and bring the prediction together. in one consensus prediction.

In addition he and his team make a metaforecast, which is a mix of an ensemble of computer models and their consensus prediction.

The idea behind this approach is to combine computer models with human judgment to more accurately predict the U.S. revolution. “

Thomas McAndrew, Computer Scientist and Associate Professor, Lehigh University College of Health

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