## Main

The COVID-19 pandemic is expected to continue to impose enormous burdens of morbidity and mortality while severely disrupting societies and economies worldwide. Governments must be ready to ensure large-scale, equitable access and distribution of a COVID-19 vaccine if and when a safe and effective one becomes available. This will require sufficient health system capacity, as well as strategies to enhance trust in and acceptance of the vaccine and those who deliver it.

In 2015, the World Health Organization (WHO) Strategic Advisory Group of Experts on Immunization defined vaccine hesitancy as a ’delay in acceptance or refusal of vaccination despite availability of vaccination services’1, which can vary in form and intensity based on when and where it occurs and what vaccine is involved, as has been confirmed in multiple studies2,3. Concern about vaccine hesitancy is growing worldwide4; in fact, WHO identified it as one of the top ten global health threats in 2019 (https://www.who.int/news-room/spotlight/ten-threats-to-global-health-in-2019). In many countries, vaccine hesitancy and misinformation present substantial obstacles to achieving coverage and community immunity5,6.

Governments, public health officials and advocacy groups must be prepared to address hesitancy and build vaccine literacy so that the public will accept immunization when appropriate. Anti-vaccination activists are already campaigning in multiple countries against the need for a vaccine, with some denying the existence of COVID-19 altogether7. Misinformation spread through multiple channels could have a considerable effect on the acceptance of a COVID-19 vaccine8. The accelerated pace of vaccine development has further heightened public anxieties and could compromise acceptance9.

Governments and societies must gauge current levels of willingness to receive a potentially safe and effective COVID-19 vaccine and identify correlates of vaccine hesitancy and/or acceptance. We present findings from a survey of the likelihood of vaccine acceptance from a sample of 13,426 respondents in 19 countries.

## Results

### Analysis

We analyzed the distribution of the responses against the different questions for the entire dataset and further examined differences by country. We calculated results for two sets of univariate regressions: one for each of the two questions related to vaccines. We used logistic regression, defining the outcome as 1 if a respondent answered ‘completely agree’ or ‘somewhat agree’ and 0 for any other response. The independent demographic variables included age, gender, income and education. We also examined the relationship between the two regression outcomes and whether someone in the respondent’s family had been sick with COVID-19, as well as existing country-by-country data on COVID-19 cases per million population, COVID-19 mortality per million population and whether a respondent reported that they trusted pandemic information from their government (yes or no).

### Reporting Summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.