Trust and COVID-19 vaccine hesitancy.

This article uses novel data collected on a weekly basis covering more than 35,000 individuals in the EU to analyze the relationship between trust in various dimensions and COVID-19 vaccine hesitancy. We found that trust in science is negatively correlated, while trust in social media and the use of social media as the main source of information are positively associated with vaccine hesitancy. High trust in social media is found among adults aged 65+, financially distressed and unemployed individuals, and hesitancy is largely explained by conspiracy beliefs among them. Finally, we found that the temporary suspension of the AstraZeneca vaccine in March 2021 significantly increased vaccine hesitancy and especially among people with low trust in science, living in rural areas, females, and financially distressed. Our findings suggest that trust is a key determinant of vaccine hesitancy and that pro-vaccine campaigns could be successfully targeted toward groups at high risk of hesitancy.

Predicting vaccine hesitancy from area-level indicators: A machine learning approach.

Vaccine hesitancy (VH) might represent a serious threat to the next COVID-19 mass immunization campaign. We use machine learning algorithms to predict communities at a high risk of VH relying on area-level indicators easily available to policymakers. We illustrate our approach on data from child immunization campaigns for seven nonmandatory vaccines carried out in 6062 Italian municipalities in 2016. A battery of machine learning models is compared in terms of area under the receiver operating characteristics curve. We find that the Random Forest algorithm best predicts areas with a high risk of VH improving the unpredictable baseline level by 24% in terms of accuracy. Among the area-level indicators, the proportion of waste recycling and the employment rate are found to be the most powerful predictors of high VH. This can support policymakers to target area-level provaccine awareness campaigns.

The health-economy trade-off during the Covid-19 pandemic: Communication matters.

How do people balance concerns for general health and economic outcomes during a pandemic? And, how does the communication of this trade-off affect individual preferences? We address these questions using a field experiment involving around 2000 students enrolled in a large university in Italy. We design four treatments where the trade-off is communicated using different combinations of a positive framing that focuses on protective strategies and a negative framing which refers to potential costs. We find that positive framing on the health side induces students to give greater relevance to the health dimension. The effect is sizeable and highly effective among many different audiences, especially females. Importantly, this triggers a higher level of intention to adhere to social distancing and precautionary behaviors. Moreover, irrespective of the framing, we find a large heterogeneity in students' preferences over the trade-off. Economics students and students who have directly experienced the economic impact of the pandemic are found to give greater value to economic outcomes.