Model vaccination

Thinh Ong

2 decisions

To model vaccination, we need to decide 2 things:

  1. What is the vaccine effect? Does it protect against infection, severe disease, transmission, or a combination?

  2. How do we model imperfect protection?

Vaccine effect

Prevent infection

Vaccine prevents the pathogen from establishing an infection in the body. A vaccinated person is less likely to get infected.

Prevent infection

Assuming a perfect vaccine against infection, the model can be designed as follows:

Vaccinated people \(V\) remain uninfected in their lifetime and do not participate in disease transmission.

Prevent infection

You can simplify this model by moving susceptible people to the \(R\) compartment because they also do not participate in disease transmission.

Prevent severe disease

A vaccinated individual still get infected but experiences a much milder form of the disease.

Prevent severe disease

Assuming a perfect vaccine against severe disease, the model can be designed as follows:

Prevent transmission

A vaccinated person still get infected, still get sick, but they are less likely to spread the disease to others.

Prevent transmission

Assuming a perfect vaccine against transmission, the model can be designed as follows:

\(I\) being the only source of infection that contributes to the force of infection. Vaccinated people \(S_v\) still get infected and become \(I_v\), but they do not transmit the disease.

Imperfect protections

What is meant by a vaccine with effectiveness of 80%?

All-or-nothing model

All-or-nothing (AoN, also called the polarized (Park et al. 2023), or take) model assumes that among vaccinated individuals, a proportion \(VE_P\) are completely protected, while the remaining fraction \(1 - VE_P\) remains completely unprotected (Zachreson et al. 2023; Park et al. 2023).

An effectiveness of 80% here implies that among vaccinated people, 80% are completely protected, and 20% receive no protection (World Health Organization 2013).

All-or-nothing model

Figure 1: All-or-nothing vaccination model (Park et al. 2023)

Leaky model

Leaky (or degree) model assumes that all vaccinated individuals are partially protected (Zachreson et al. 2023).

An effectiveness of 80% here implies that all vaccinated people have the endpoint of interest reduced by 80% compared to non-vaccinees.

Leaky model

The assumption that no vaccinated people is totally or permanently protected implies one or both of the following (World Health Organization 2013):

  • No amount (titre) of the immune marker is totally protective or, if it is, no individual can maintain that titre for a long period (because of waning or transient immunosuppression)
  • The degree of protection is a function of the level of the immune marker - the simplest explanation being that protection is a function of both the level of the immune marker and the challenge dose.

Leaky model

Figure 2: Leaky vaccination model (Park et al. 2023)

Mixed effects

Imperfect vaccines often have a combination of effects: they can protect against infection, severe disease, and transmission at the same time.

Mixed effects

Assuming a vaccine with leaky effectiveness \(VE_L\) against infection and severe disease, the model can be designed as follows:

Multiple doses

Some vaccines require multiple doses. Below is the DynaMICE model (Verguet et al. 2015) for the 2-dose measles vaccine, assuming AoN effectiveness for both doses.

References

Park, Sang Woo, Michael Li, C. Jessica E. Metcalf, Bryan T. Grenfell, and Jonathan Dushoff. 2023. “Immune Boosting Bridges Leaky and Polarized Vaccination Models.” medRxiv, July. https://doi.org/10.1101/2023.07.14.23292670.
Verguet, Stéphane, Mira Johri, Shaun K. Morris, Cindy L. Gauvreau, Prabhat Jha, and Mark Jit. 2015. “Controlling Measles Using Supplemental Immunization Activities: A Mathematical Model to Inform Optimal Policy.” Vaccine 33 (10): 1291–96. https://doi.org/10.1016/j.vaccine.2014.11.050.
World Health Organization. 2013. “Correlates of Vaccine-Induced Protection: Methods and Implications.”
Zachreson, Cameron, Ruarai Tobin, Joshua Szanyi, Camelia Walker, Deborah Cromer, Freya M Shearer, Eamon Conway, et al. 2023. “Individual Variation in Vaccine Immune Response Can Produce Bimodal Distributions of Protection.” Vaccine 41 (45): 6630–36. https://doi.org/10.1016/j.vaccine.2023.09.025.