Public opinion towards global distribution of COVID-19 vaccines - Data from Germany and the United States

Our nationally representative data indicates that public in wealthier countries are willing to share their doses of vaccines with countries in more dire conditions even if they have to wait longer for their own first shot.
Published in Research Data
Public opinion towards global distribution of COVID-19 vaccines - Data from Germany and the United States
Like

COVID-19 pandemic has thrown multiple waves of shock through all the societies across the world. As such were hearing the news of massive casualties, loss of friends and family, rapid development of new vaccines and medicine, mandatory use of face masks, and lockdowns. In dealing with this global crisis, not everyone had access to the same resources. Wealthier countries had access to better healthcare, infrastructure, and bargaining power to secure doses of vaccines; while many low- and middle-income countries were left behind. It was at the midst of this global confusion that the idea of the present study started to take shape. The question was that "what is the degree of willingness of those who live in these privileged positions to share their resources with others who are less fortunate?" This was at the critical time when the inoculation programs were at their early stages with many still waiting to receive their first shot of the vaccine. In such conditions, sharing the vaccine doses needed a great sense of generosity. In particular, many have criticized the government in high-income countries for hoarding and vaccine nationalism. Our study aimed to assess that whether the public in these countries would oppose if more doses of vaccines were sent to the low-income countries. In particular, we focused on the Unites States and Germany who were pioneering countries in development and production of the vaccines. Our theoretical framework was based on literature from distributive justice that in general distinguishes between equality, need, merit, and entitlement. Moreover, we examined that whether people would change their mind if they were challenged with a scenario where there was a clear self-interest either for themselves or for a loved person having to wait longer so that those living in harder conditions could receive the vaccine doses earlier. Based on the present data that is a nationally representative sample, we were pleased to find that in contrast with politicians, public in these countries well-understood the global nature of the pandemic, and their degree of willingness to share the vaccines with poorer countries was high.

This study, however, was a snapshot of an evolving situation and the results might be temporal also differ across various geographical regions. For that, by sharing our data we hope to open the doors for a wider collaboration to gain a better understanding of public’s mindset and attitude during these unusual times. The medical achievements in dealing with COVID-19 pandemic have been extraordinary. We are, however, far from managing such crises at the human level. Working together and through share of knowledge, hopefully we will be better prepared for the next global crisis that we don’t know when and how it might hit us again.

https://doi.org/10.1016/j.vaccine.2022.02.084

Please sign in or register for FREE

If you are a registered user on Research Communities by Springer Nature, please sign in

Subscribe to the Topic

Research Data
Research Communities > Community > Research Data

Related Collections

With collections, you can get published faster and increase your visibility.

Remote sensing data for changes in land use

This Collection comprises a series of articles presenting data on changes to land use in urban areas, farmland, forests, and natural environments, as determined using remote sensing techniques.

Publishing Model: Open Access

Deadline: Jan 31, 2024

Medical imaging data for digital diagnostics

This Collection presents a series of articles describing annotated datasets of medical images and video. All medical specialities are considered and data can be derived from study participants, tissue samples, electronic health records (EHRs) or other sources.

Publishing Model: Open Access

Deadline: Dec 20, 2023