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UBC Researchers Find Small Long-Term Infection Effects Can Change Optimal Vaccination Levels

UBC Researchers Find Small Long-Term Infection Effects Can Change Optimal Vaccination Levels

By Akshay Satija•Editor in Chief•October 6, 2026•Updated October 6, 2026•2 min read
Today
#UBC#University of British Columbia#Canadian Science#Vaccines#Vaccination#Infectious Diseases#Public Health#Medical Research#Health Research#PNAS#Post-Infection Effects#Science

Key Takeaways

  • UBC researchers found that even relatively small post-infection costs can influence the vaccination coverage level that produces the greatest overall benefit.
  • The modelling suggests masking, social distancing and air filtration can complement vaccination by reducing infections and potential long-term disease burden.
  • There is no universal vaccination target because the optimal level depends on disease characteristics, vaccine costs, post-infection effects and vaccination behaviour.

A Small Cost That Could Change the Vaccine Equation

Vaccination decisions are often framed around preventing immediate illness. New modelling from the University of British Columbia suggests that equation can look very different when the longer-term effects of infection are included.

The study, published in the Proceedings of the National Academy of Sciences, examines how post-infection complications can affect the level of vaccination that makes the most sense for a population. Researchers developed mathematical models that combine disease transmission, economic costs and vaccination costs.

Their results show that even relatively small costs associated with post-infection health effects can push the optimal vaccination level higher. In some scenarios, the models suggest coverage could move toward levels needed for disease elimination.

Beyond Vaccination Alone

The researchers also modelled non-pharmaceutical measures, including masking, social distancing and air filtration. These interventions reduced transmission in the model, meaning fewer people became infected and subsequently remained vulnerable to longer-term post-infection effects.

That matters because public health decisions are rarely about one tool. The modelling suggests that vaccination and measures that reduce transmission can work together, particularly when infections carry costs that extend beyond the initial illness.

The study does not identify one universal vaccination target. Instead, the researchers found that the ideal level depends on factors such as the disease involved, vaccine production and delivery costs, the burden of post-infection effects and how easily additional people can be reached.

TwikUp’s Perspective

The most important takeaway is not that every disease requires maximum vaccination. It is that health policy models can miss part of the economic and social picture when they focus mainly on acute infections.

Including longer-term consequences could change how governments compare the cost of prevention with the cost of allowing infections to continue. That makes better long-term data especially valuable, because decisions about coverage ultimately depend on understanding both the medical burden and the real-world cost of reducing it.

For policymakers, the study points toward a broader question: not simply how many infections can be prevented, but how much lasting harm can be avoided.

Sources

There is no universal vaccination target because the optimal level depends on disease characteristics, vaccine costs, post-infection effects and vaccination behaviour.

Frequently Asked Questions

FAQ

What did UBC researchers discover about vaccination levels?

Their modelling found that even relatively small costs associated with post-infection health effects can shift the optimal vaccination level higher, with some scenarios reaching levels consistent with disease elimination.

What factors determine the optimal vaccination level?

The researchers identified factors including the disease involved, vaccine production and delivery costs, post-infection effects and the difficulty of reaching additional people with vaccination.

Can measures such as masking complement vaccination?

Yes. The modelling found that measures such as masking, social distancing and air filtration can reduce transmission and therefore decrease the number of infections that may lead to longer-term effects.

Does the study recommend maximum vaccination for every disease?

No. The research does not propose one universal target. The appropriate level depends on the characteristics and costs associated with a particular disease and vaccination programme.

Where was the UBC research published?

The study, titled Interventions to mitigate post-infection morbidity: Management insights from simple models, was published in the Proceedings of the National Academy of Sciences.

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