# Estimating behavioural relaxation induced by COVID-19 vaccines in the first months of their rollout

**Authors:** Yuhan Li, Nicolò Gozzi, Nicola Perra, Roger Dimitri Kouyos, Brittany Rife Magalis, Roger Dimitri Kouyos, Brittany Rife Magalis, Roger Dimitri Kouyos, Brittany Rife Magalis

PMC · DOI: 10.1371/journal.pcbi.1013266 · PLOS Computational Biology · 2025-07-07

## TL;DR

This study examines whether people relaxed their protective behaviors after receiving COVID-19 vaccines, using epidemic models in four regions.

## Contribution

The paper provides a retrospective validation of epidemic models with behavioral relaxation mechanisms during the early vaccine rollout.

## Key findings

- Vaccinations and NPIs significantly reduced infection and mortality rates.
- Adding behavioral relaxation mechanisms improved model fit slightly but increased complexity.
- Little evidence of widespread behavioral relaxation induced by vaccines was found.

## Abstract

The initial rollout of COVID-19 vaccines has been challenged by logistical issues, limited availability of doses, scarce healthcare capacity, spotty acceptance, and the emergence of variants of concern. Non-pharmaceutical interventions (NPIs) have been critical to support these phases. However, vaccines may have prompted behavioural relaxation, potentially reducing NPIs adherence. Epidemic models have explored this phenomenon, but they have not been validated against data. Moreover, recent surveys provide conflicting results on the matter. The extent of behavioural relaxation induced by COVID-19 vaccines is still unclear. Here, we aim to study this phenomenon in four regions. We implement five realistic epidemic models which include age structure, multiple virus strains, NPIs, and vaccinations. One of the models acts as a baseline, while the others extend it including different behavioural relaxation mechanisms. First, we calibrate the baseline model and run counterfactual scenarios to quantify the impact of vaccinations and NPIs. Our results confirm the critical role of both in reducing infection and mortality rates. Second, using different metrics, we calibrate the behavioural models and compare them to each other and to the baseline. Including behavioural relaxation leads to a better fit of weekly deaths in three regions. However, the improvements are limited to a 2−10% reduction in weighted mean absolute percentage errors and these gains are generally offset by models’ increased complexity. Overall, we do not find clear signs of behavioural relaxation induced by COVID-19 vaccines on weekly deaths. Furthermore, our results suggest that if this phenomenon occurred, it generally involved only a minority of the population. Our work contributes to the retrospective validation of epidemic models developed amid the COVID-19 Pandemic and underscores the issue of non-identifiability of complex social mechanisms.

The COVID-19 vaccines rollout initially faced significant challenges. Non-pharmaceutical interventions (NPIs) complemented vaccinations in addressing these issues. However, the interplay between vaccines and NPIs is complex and still unclear. While some surveys suggest that the arrival of vaccines induced people to relax their protective behaviours, others found little support for this phenomenon. Furthermore, the epidemic models developed so far to study these processes lack empirical validation. We aim to quantify the extent of behavioural relaxation studying five compartmental models in four regions. All models integrate age-structure, multiple virus strains, NPIs, and vaccinations. Four also include vaccine induced behavioural relaxation mechanisms. Our findings confirm that both vaccinations and NPIs significantly reduced infection and mortality rates. Furthermore, although adding behavioural relaxation mechanisms improve the overall goodness of fit, the gains are limited and offset by increased models’ complexity. Overall, we found little evidence of behavioural relaxation induced by vaccines on weekly deaths. Even if this phenomenon occurred, our results suggest that it generally involved only a minority of the population. Our work contributes to the efforts devoted to retrospectively validating epidemic models developed during the COVID-19 Pandemic and highlights the issue of non-identifiability of social mechanisms.

## Linked entities

- **Diseases:** COVID-19 (MONDO:0100096)

## Full-text entities

- **Diseases:** deaths (MESH:D003643), infection (MESH:D007239), COVID-19 (MESH:D000086382)

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/PMC12258572/full.md

## Figures

5 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12258572/full.md

## References

87 references — full list in the complete paper: https://tomesphere.com/paper/PMC12258572/full.md

---
Source: https://tomesphere.com/paper/PMC12258572