2021-02-22 13:09:50

Introduction

  • Inoculum dose is an important determinant of infection or 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 and side effects (morbidity).

Impact of dose following infection: Some past and current work

Dose and virus load

Dose and virus load

Infectious bronchitis virus (IBV) infections of chickens. (Coronavirus!)

Dose and virus load

Dose and infected cells

Dose and virus load revisited

Dose does not always impact pathogen load

Norovirus infections in humans at 3 doses.

Dose does not always impact pathogen load

Impact of dose following vaccination:
Some past and current work

Current approaches to dose choice

Possible important issues

  • Impact of dose on immunogenicity might not be monotone.
  • Knowing in more detail how dose impacts immunogenicity and morbidity might help optimize dose choice.

Modeling the impact of dose

Modeling the impact of dose

Animals infected with HPIV (let’s pretend it’s a live/replicating vaccine).

Modeling the impact of dose

Finally, some real flu vaccine data

Regular versus high-dose flu vaccine responses

  • 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 were offered the high-dose (HD, 60µg) trivalent vaccine.
  • Analysis of immune response (HAI) for SD vs HD individuals.
  • Focus on individuals >=65 years, only look at B-strains that are in both SD and HD.

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

Study population

Dropped H3N2-Singapore-2016 and B-Colorado-2017 due to small sample size.

The data

Strain-specific analysis

Investigate 4 antibody titer (HAI) outcomes for each strain:

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

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

Strain-specicfic responses, H1N1

Median and 95% Credible Interval

Median and 95% Credible Interval

Multivariate Bayesian model, controlling for age, gender, race, pre-vaccination titer.

Strain-specicfic responses, H3N2

Median and 95% Credible Interval

Median and 95% Credible Interval

Strain-specicfic responses, B

Median and 95% Credible Interval

Median and 95% Credible Interval

Heterologous responses, H1N1

Heterologous responses, H1N1

Heterologous responses, H3N2

Heterologous responses, H3N2

Heterologous responses, B

Heterologous responses, B

Responses by gender, H1N1

Responses by gender, H3N2

Responses by gender, B

Vaccine-specific analysis

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

  • For Seroprotection/Seroconversion sum of each strain, standardized (score from 0-1)
  • For post-vaccination and increase in titer, the average for all vaccine strains

Vaccine-specific responses

Median and 95% Credible Interval

Median and 95% Credible Interval

To be done

  • Vaccine-specific heterologous response
  • Other?

Summary

  • HD vaccine seems to lead generally to more HAI against the vaccine strain, though it depends on strain and year. H3N2 seemed to benefit less from HD.
  • There is a tendency for HD to induce better heterologous protection, but the effect is small and inconsistent.
  • There might be interaction between dose and gender for some vaccine strains.
  • This is an exploratory analysis, further investigation is needed.

Overall

  • Dose is important, impact not that well studied.
  • For a universal influenza (or coronavirus?) vaccine, strength and breadth of protection is important.
  • Combination of data and models could help optimize vaccine dose choice.
  • Getting the right kind of data is tricky.

Thanks!

Discussion points

  • What’s the best way to quantify overall response?
  • How to deal with SD having 2 B-strains?
  • Best scale for HAI titer analysis?
  • Anyone know of accessible data sources for (flu) vaccination/infection at different doses?