Understanding Parental Attitudes toward Vaccination: Comparative Assessment of a New Tool and Its Trial on a Representative Sample in Hungary.

Background: Last year's epidemic experience proved that measurement of vaccine hesitancy is undeniably important. Existing methods for measuring this propensity are still either too specific, concerning a single vaccine, or only describe the general attitude towards vaccination. When a specific, but previously unknown infection and vaccine (such as SARS-CoV2) appear, these limitations are meaningful. Methods: Based on a method used to identify social prejudice, we created a new tool to assess vaccine hesitancy assessment and to study parental attitudes toward existing and non-existing ('Piresian') vaccines. After validating it with traditional tools for the measurement of vaccine hesitancy, we used the new tool for the demographic characterisation of different vaccine hesitant parent groups in Hungary. The data collected in 2017 on 430 parents, sorted by type of settlement and by geographic region, are representative of Hungarian households with children aged 0 to 18 years. Results: Our results show that attitudes towards a non-existing ('Piresian') vaccine have strong correlations with those towards existing vaccines (p < 0.001). No gender differences in vaccine hesitancy were found using either method. Notably, rejection was significantly higher among parents with low educational levels. Conclusion: The Piresian measurement of vaccine hesitancy offers a simple way to detect vaccine-hesitant groups, reliably quantitating vaccine hesitancy as measured for real vaccinations.

Understanding hesitancy with revealed preferences across COVID-19 vaccine types.

Many countries have secured larger quantities of COVID-19 vaccines than their population is willing to take. The abundance and the large variety of vaccines created not only an unprecedented intensity of vaccine related public discourse, but also a historical moment to understand vaccine hesitancy better. Yet, the heterogeneity of hesitancy by vaccine types has been neglected in the existing literature so far. We address this problem by analysing the acceptance and the assessment of five vaccine types. We use information collected with a nationally representative survey at the end of the third wave of the COVID-19 pandemic in Hungary. During the vaccination campaign, individuals could reject the assigned vaccine to wait for a more preferred alternative that enables us to quantify revealed preferences across vaccine types. We find that hesitancy is heterogenous by vaccine types and is driven by individuals' trusted source of information. Believers of conspiracy theories are more likely to evaluate the mRNA vaccines (Pfizer and Moderna) unacceptable. Those who follow the advice of politicians are more likely to evaluate vector-based (AstraZeneca and Sputnik) or whole-virus vaccines (Sinopharm) acceptable. We argue that the greater selection of available vaccine types and the free choice of the individual are desirable conditions to increase the vaccination rate in societies.

Reconstructing social mixing patterns via weighted contact matrices from online and representative surveys.

The unprecedented behavioural responses of societies have been evidently shaping the COVID-19 pandemic, yet it is a significant challenge to accurately monitor the continuously changing social mixing patterns in real-time. Contact matrices, usually stratified by age, summarise interaction motifs efficiently, but their collection relies on conventional representative survey techniques, which are expensive and slow to obtain. Here we report a data collection effort involving over [Formula: see text] of the Hungarian population to simultaneously record contact matrices through a longitudinal online and sequence of representative phone surveys. To correct non-representative biases characterising the online data, by using census data and the representative samples we develop a reconstruction method to provide a scalable, cheap, and flexible way to dynamically obtain closer-to-representative contact matrices. Our results demonstrate that although some conventional socio-demographic characters correlate significantly with the change of contact numbers, the strongest predictors can be collected only via surveys techniques and combined with census data for the best reconstruction performance. We demonstrate the potential of combined online-offline data collections to understand the changing behavioural responses determining the future evolution of the outbreak, and to inform epidemic models with crucial data.