Timing Matters: Rethinking How We Measure Malaria Vaccine Efficacy

Comparing vaccines from different trials can mislead if timing of vaccination and seasonal disease transmission are not considered.

Numerous infectious diseases can be prevented or partially prevented by more than one available vaccine, and comparing these alternatives is common practice. However, conducting head-to-head trials is expensive and logistically challenging. As a result, we often rely on comparing vaccine efficacies estimated from different trials. But how reliable are these comparisons, really? In our recent Personal View article published in The Lancet Infectious Diseases, we argue that this approach can be misleading, especially when the disease in question — like malaria — is strongly influenced by seasonal and regional transmission dynamics.

We often rely on comparing vaccine efficacies estimated from different trials. But how reliable are these comparisons, really?

A case in point: comparing the two approved malaria vaccines

In the last few years, the World Health Organization (WHO) has approved two malaria vaccines: RTS,S/AS01E and R21/Matrix-M. Both target the same malaria parasite protein but are formulated slightly differently. They’ve both gone through large-scale phase 3 trials in Africa and shown encouraging results:

• RTS,S: 55% efficacy in the first year
• R21: 72% efficacy in the first year

So, is R21 clearly the better vaccine by more than 15% VE? Not necessarily.

Sure, those vaccine efficacy estimates come with confidence intervals, but what’s often missed is that they’re time-aggregated — basically, they average out all the ups and downs over a full year. But here’s the thing: malaria doesn’t hit evenly year-round — it spikes during the rainy seasons when mosquitoes are everywhere. Meanwhile, vaccine protection doesn’t stay the same either — it wanes over time.

The Problem with Averages

Imagine testing a raincoat by seeing how often you get soaked over a year. Now, say this raincoat starts to fall apart after a few months. If you start testing it in July — right as the rainy season begins — it’s brand new when you need it most. But if you start in January during the dry season, by the time the rains arrive, the raincoat might already be full of holes. Same raincoat, different results over one year trial. Malaria vaccines work the same way — their protection decreases over time, so whether they’re still strong when malaria season hits makes a big difference in how well they perform overall. And that difference isn’t about the vaccine itself — it’s all about when the vaccination happened during the trial.

What Our Analysis Found

We dug into the data from the RTS,S and R21 trials and ran simulations to see what would happen if vaccinations had occurred at different times of year.

Here's what we found:

• In Burkina Faso, RTS,S efficacy could vary by 20 percentage points depending on the month of vaccination — from 46% to 66%.
• For R21, seasonal trial sites reported higher efficacy (75%) than non-seasonal ones (67%), mostly because vaccination was better timed with malaria peaks.

So, the apparent superiority of R21 in some cases and might not be due to better biology only— but better timing.

The apparent superiority of R21 in some cases and might not be due to better biology only— but better timing

Why This Matters

These findings have important implications for how we:

• Compare vaccines tested in different trials
• Compare vaccine efficacies across different population subgroups in the same trial—whether from various geographic regions or vaccinated at different times, such as before or after an outbreak or peak season
• Interpret trial results critically

If we don’t account for how disease transmission fluctuates during the follow-up period of clinical trials, we risk underestimating the efficacy of a good vaccine — or overestimating one that just had lucky timing.

A Better Way Forward

We propose a few simple fixes:

• Use time-specific vaccine efficacy estimates — not just annual averages or averages over long time spans.
• Highlight intensity and changes in transmission — using data from trial control groups.
• Plan vaccine rollouts according to seasons, especially when efficacy wanes quickly.

These ideas aren’t limited to malaria — they apply to many vaccines, from flu to COVID-19, where timing and waning immunity matter.

Next time you see a vaccine touted as “60% effective,” ask yourself: effective when and where? That question might be more important than we thought

Bottom Line

For many infectious diseases, vaccine trial results aren’t just about how well the vaccine protects people—they’re also influenced by how disease spreads over time. By paying closer attention to how vaccine waning and disease transmission interact we can make fairer comparisons and make sure vaccines are used when they’ll do the most good. So next time you see a vaccine touted as “60% effective,” ask yourself: effective when and where? That question might be more important than we thought. 

Reference

Macià, D., Pons-Salort, M., Moncunill, G., & Dobaño, C. (2025). The effect of disease transmission on time-aggregated treatment efficacy estimates: A critical analysis of factors influencing the RTS,S and R21 malaria vaccine phase 3 trials. The Lancet Infectious Diseases. https://doi.org/10.1016/S1473-3099(25)00090-8