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As Covid-19 spreads across the world, governments turn a hopeful eye towards research and development of a vaccine against this new disease. But it is one thing to make a vaccine available, and it is quite another to convince the public to take the shot, as the precedent of the 2009 H1N1 flu illustrated. In this paper, we present the results of four online surveys conducted in April 2020 in representative samples of the French population 18 years of age and over (N=5,018). These surveys were conducted during a period when the French population was on lockdown and the daily number of deaths attributed to the virus reached its peak. We found that if a vaccine against the new coronavirus became available, almost a quarter of respondents would not use it. We also found that attitudes to this vaccine were correlated significantly with political partisanship and engagement with the political system. Attitudes towards this future vaccine did not follow the traditional mapping of political attitudes along a Left-Right axis but oppose people who feel close to governing parties (Centre, Left and Right) on the one hand, and, on the other, people who feel close to Far-Left and Far-Right parties as well as people who do not feel close to any party. We draw on the French sociological literature on ordinary attitudes to politics to discuss our results as well as the cultural pathways via which political beliefs can affect perceptions of vaccines during the COVID-19 pandemic.

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The results stress the need to control for age and gender when the survey participants are teenagers. The relationship between drug use and sporting activity also depends on the type of sport.

There is an ongoing debate in the survey research literature about whether and when probability and nonprobability sample surveys produce accurate estimates of a larger population. Statistical theory provides a justification for confidence in probability sampling as a function of the survey design, whereas inferences based on nonprobability sampling are entirely dependent on models for validity. This article reviews the current debate about probability and nonprobability sample surveys. We describe the conditions under which nonprobability sample surveys may provide accurate results in theory and discuss empirical evidence on which types of samples produce the highest accuracy in practice. From these theoretical and empirical considerations, we derive best-practice recommendations and outline paths for future research.