Omicron variant a month later: what do we (not) know?

Figure 1. Key questions on the new Omicron variant
  • Numbers are changing almost daily and should be taken as directional. Any incorrect information shared is unintentional. I will attempt to correct or edit anything as soon as I learn about it.
  • Epidemiological modeling is relying on data from different global studies, and each of the analyses comes with different confounding variables at the population level.
  • Given the near-real time of the data, little of what’s cited here is peer reviewed or replicated. Ideally, I would prefer to cite published scientific papers wherever I can.
  • Leading indicators are used to extrapolate information such as severity of disease. As more information comes online, this will be replaced with data that will hopefully provide a more holistic, longitudinal view of disease course and outcomes.
  • Infection status (COVID test data), AND
  • Variant type status (sequencing data) AND
  • Medical history and demographics (to segment different populations based on different factors we’d want to study) AND
  • Outcome data (hospitalization status, recovery rate, mortality data, long-term follow-up data to determine post-acute COVID symptoms)
  • Enough individuals need to get boosters, AND
  • The booster status needs to be tracked appropriately. We need to know the # of vaccine doses each individual has received, what vaccine type they have received, and when their last dose was administered. (In the US, we don’t yet have high accuracy data on the number of people who have received a first and second shot of the vaccine, and data points on boosters are lagging further behind), AND
  • Individuals who show symptoms of disease need to get tested, AND
  • Samples need to be sequenced to determine variant

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Passionate about R&D and healthcare data. Thoughts here are my own.

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Vera Mucaj

Vera Mucaj

Passionate about R&D and healthcare data. Thoughts here are my own.