get_allornone_ve_estimands: Time-dependency of variant and vaccine-specific efficacy (VE)...

In anirudhtomer/vess: Vaccine Efficacy Sample Size Calculations in a Multiple Vaccine and Multiple Pathogen Variant Scenario

Description

The function get_allornone_ve_estimands provides the VE estimands based on incidence rate ratio, cumulative-risk ratio, and odds ratio for an all-or-none vaccine given the actual efficacy of the vaccine. The function returns both absolute and relative VE estimands.

Usage

get_allornone_ve_estimands(
  anticipated_VE_for_each_brand_and_variant = matrix(data = c(0.04, 0.1, 0.03, 0.05,
    0.03, 0.07, 0.4, 0.05, 0.18, 0.01, 0.08, 0.04, 0.07, 0.2, 0.08, 0.05, 0.07, 0.01,
    0.02, 0.13, 0.1), nrow = 3, ncol = 7, byrow = T, dimnames = list(paste0("brand",
    1:3), paste0("variant", c("1", "2", "3", "12", "13", "23", "123")))),
  incidence_rate_unvaccinated = c(0.05, 0.1, 0.2),
  study_period = 1
)

Arguments

anticipated_VE_for_each_brand_and_variant	a matrix of proportion of subjects immune to certain combination (column) of variants given a certain vaccine (row). Each value must be a real number between 0 and 1 and sum of each row should not exceed 1.
incidence_rate_unvaccinated	a vector denoting the incidence rates of each variant in the unvaccinated subjects.
study_period	the study period (epochs) should be numeric value greater than 0.

Details

To understand the parameter anticipated_VE_for_each_brand_and_variant and the action of all-or-none vaccines, assume that there are only three variants 1,2, and 3 circulating. The subjects vaccinated with the vaccine 1 are represented in row 1 of the matrix anticipated_VE_for_each_brand_and_variant[1, ]. Specifically, anticipated_VE_for_each_brand_and_variant[1, 1] is the proportion of subjects who become immune to the variant 1 but not to the other two variants. Among these subjects infections occur with the combined incidence rates of the variants 2 and 3. anticipated_VE_for_each_brand_and_variant[1, 2] and anticipated_VE_for_each_brand_and_variant[1, 3] hold similar interpretation. Next, let anticipated_VE_for_each_brand_and_variant[1, 4], be the proportion of subjects who become immune to both variants 1 and 2 but not to variant 3. Among these subjects infection with variant 3 happens with the incidence rate of variant 3. We can define anticipated_VE_for_each_brand_and_variant[1, 5] and anticipated_VE_for_each_brand_and_variant[1, 6], similarly. Lastly, anticipated_VE_for_each_brand_and_variant[1, 7] are the proportion of subjects who become immune to all three variants. The remaining proportion of subjects do not become immune to any variant despite vaccination. For them infections happens as in as in the placebo subjects. This proportion is not entered in the matrix anticipated_VE_for_each_brand_and_variant because this proportion can be obtained as 1 - rowSums(anticipated_VE_for_each_brand_and_variant).

Smith et al. (1984) have shown that when a vaccine has an all-or-none action mechanism (Halloran et al., 2010, page 132), then VE calculated as VE = 1 - incidence rate ratio depends on the length of the study period t. Specifically, when t -> Infinity then 1 - incidence rate ratio -> 1 and thus it does not reflect the biological effect of the vaccine for a given exposure to the pathogen. The aim of this function is to extend upon the findings of Smith et al. (1984) for multiple variant/variants and vaccines. And to help practitioners understand why certain VE measures may not reflect the biological VE. More details can be found in our related paper.

Value

A list with three elements, namely absolute_ve, relative_ve_across_variant_given_vaccine, and relative_ve_across_vaccines_given_variant. The list element absolute_ve pertains to the absolute efficacy of the vaccines. It contains four elements, namely absolute_ve_true, absolute_ve_irr, absolute_ve_crr, and absolute_ve_or. Here absolute_ve_true is same as the input parameter anticipated_VE_for_each_brand_and_variant, and indicates the true biological efficacy of the vaccine. Whereas, the remaining three are the VE estimands based on incidence rate ratio, cumulative-risk ratio, and odds ratio, respectively.

The list element relative_ve_across_variant_given_vaccine pertains to the relative VE of a vaccine against two different variants/variants. It is a matrix with 7 rows and multiple columns. Each column being one of the comparison sets of variants and vaccines. Rows 1 and 2 indicate the two variants of interest for comparison and row 3 has the vaccine. The remaining rows show the true relative VE, and the relative VE based on incidence rate ratio, cumulative-risk ratio, and odds ratio, respectively.

The list element relative_ve_across_vaccines_given_variant pertains to the relative VE of two vaccines against the same variants/variants. It is a matrix with 7 rows and multiple columns. Each column being one of the comparison sets of variants and vaccines. Rows 1 and 2 indicate the two vaccines of interest for comparison and row 3 has the variant. The remaining rows show the true relative VE, and the relative VE based on incidence rate ratio, cumulative-risk ratio, and odds ratio, respectively.

References

1. Halloran, M. E., Longini, I. M., Struchiner, C. J., and Longini, I. M. (2010).Design and analysis of vaccine studies, volume 18. Springer.

2. Smith, P., Rodrigues, L., and Fine, P. (1984). Assessment of the protective efficacy of vaccines against common diseases using case-control and cohort studies.International journal of epidemiology, 13(1):87–93.

Examples

As an example we recommend running the function without passing any parameter to it.
The default scenario is for three vaccines and three pathogen variants.

anirudhtomer/vess documentation built on Feb. 24, 2022, 3 p.m.