• A quick overview of a few recent projects related to COVID-19.
• A more in-depth discussion of a recent influenza project.
• Slides here: https://www.andreashandel.com/presentations/

• We wanted to know if/how one could safely re-open college campuses.
• Emory University approached my colleague Ben Lopman. We built a somewhat general model.

• Simulation model for COVID-19 spread and screening/testing based control.

• https://epimodel.shinyapps.io/covid-university/

• Collaborators: Ben Lopman, Carol Y. Liu, Adrien Le Guillou, Timothy L. Lash, Alexander P. Isakov, Samuel M. Jenness.
• More information: https://doi.org/10.1038/s41598-021-85252-z

• Does the severity of COVID infection in an index case impact COVID outcomes in infected contacts?

• Collaborators: Yang Ge, Leonardo Martinez, Shengzhi Sun, Zhiping Chen, Feng Zhang, Fangyu Li, Wanwan Sun, Enfu Chen, Jinren Pan, Changwei Li, Jimin Sun, Feng Ling, Ye Shen.
• More information: https://doi.org/10.1001/jamainternmed.2021.4686

• Use a model, calibrated to COVID-19 case data, to determine the effectiveness of social distancing, contact tracing, and case isolation.

• Collaborators: Yang Ge, Zhiping Chen, Leonardo Martinez, Qian Xiao, Changwei Li, Enfu Chen, Jinren Pan, Yang Li, Feng Ling, Ye Shen.
• More information: https://doi.org/10.1016/j.epidem.2021.100483

• Inoculum dose is an important determinant of infection and vaccination outcomes.
• For infection, higher dose is often associated with greater risk of infection (ID50) and more severe outcomes (LD50).
• For vaccines, dose is thought to impact both immunogenicity/efficacy and side effects (morbidity).

https://xkcd.com/

• Trade-offs between availability/safety and efficacy likely exist.
• Impact of dose on vaccine efficacy might not be monotone.

• Impact of dose on homologous or heterologous protection might not be monotone.

• A few doses are explored in phase 1 and 2 trials.
• Based on those data, one of the doses is chosen for phase 3 trials (and beyond) in a non-rigorous manner.

Example of BioNTech/Pfizer COVID Vaccine

Claim: Knowing in more detail how dose impacts host response following vaccination might help optimize vaccines.

• Open cohort of individuals who were vaccinated (some repeatedly) during the 2014/15 - 2018/19 flu seasons.
• The default vaccine was the trivalent or quadrivalent standard dose (SD, 15µg) Fluzone vaccine.
• Individuals >=65 years were offered the high-dose (HD, 60µg) trivalent vaccine.
• We evaluated immune response following vaccination, specifically antibodies as measured by hemagglutination inhibition assay (HAI).

Question: What is the impact of standard dose (SD) versus high dose (HD) vaccine on HAI antibodies?

We investigate 4 antibody titer outcomes for each strain:

• Titer increase following vaccination
• Post-vaccination titer
• Seroconversion, defined as pre-vaccination HAI titer <1:10 (limit of detection) and post-vaccination titer >= 1:40 OR a >=4-fold increase
• Seroprotection, defined as post-vaccination HAI >= 1:40

All HAI titer dilution values are converted to a scale from 0 - N with limit of detection = 0, lowest dilution (1:10) = 1, etc. up to highest dilution (1:20480) = 12.

Same 4 outcomes as before, but now computed per overall vaccine:

• For Seroprotection/Seroconversion: Sum across all strains, standardized (fraction from 0-1).
• For post-vaccination titer and titer increase: The average across all vaccine strains.

• Linear or logistic multivariable regression
  • Outcomes as just explained
  • Main predictor/exposure is dose
  • Covariates are age, pre-existing HAI titer, sex and race
• Hierarchical Bayesian framework
  • Vaccine level
  • Strain level
• Accounted for repeaters indirectly through pre-vaccination antibody titers
• Looked at difference or odds ratio between doses

• HD seems to induce overall better homologous and heterologous responses.
• Difference between HD and SD is not that large.
• A good bit of variability is noticeable.
• Only 2 dose levels do not allow for deeper analysis.
• This is a secondary analysis of an observational cohort study.

• Collaborators:
  • Prior work: See published papers
  • Ongoing work: Yang Ge, Zane Billings, Ye Shen, Ted Ross, others
• Funding:
  • NIH

https://phdcomics.com/

• Slides: https://www.andreashandel.com/presentations/
• Contact: https://www.andreashandel.com