# **2. Data and Methods**

# _2a. Data_

This analysis describes the levels of vaccine hesitancy and its reasons in 53 developing countries between - October 2020 August 2021 using data from the World Bank’s COVID-19 high <u>frequency phone surveys</u> (HFPS) which were implemented to monitor the impact of COVID-19 on households around the world (World Bank 2020). Data are available for one survey round from 39 countries and two or more survey rounds for 14 countries. The countries in the pooled database represent five out of six regions defined by the World Bank: Latin America and the Caribbean (24 countries), Sub-Saharan Africa (14), East Asia and Pacific (7), Europe and Central Asia (6) and the Middle East and North Africa (2).<sup>3</sup> By income group, the sample includes 12 low-income countries, 13 lower-middle income countries, 23 upper middle-income countries and five high-income countries (Appendix Table 1 provides a list of countries with survey month, sample size, region and country income group).

A global core questionnaire served as the basis for each country’s survey but was then customized to fit the local context. As a result, the exact questions may vary across countries, but topics typically included knowledge and concerns about COVID-19, access to food, health care and education, employment and income loss, and safety nets and coping strategies. The survey data was then harmonized ex-post to enable cross-country comparability. The questionnaire was flexible and adapted over time to the pandemic context. The vaccine module, for example, was included more recently.

The sampling frame was drawn from pre-existing nationally representative household surveys in 19 countries, random digit dialing (RDD) in 29 countries, and a list of phone numbers typically obtained from mobile phone operators in 5 countries. The RDD design samples from all active mobile and landline phone numbers, such that RDD surveys are representative of the population aged 18 and over with an active phone number, conditional on response and survey completion. Sampling weights were then constructed to correct for selection bias due to the inability to contact households that did not participate in the survey either due to non-response or lack of access to a phone, with the goal of obtaining estimates that are as close to being nationally representative as possible. Information was collected from one respondent per household. In the case of countries where the sampling frame was derived from a previous survey, this was typically the household head. In other cases, such as when the sample utilized RDD, the respondent was more representative of individuals within the household. While the non-random selection of individuals in the former cases is not ideal, in an earlier analysis of labor market indicators derived from phone surveys, Kugler et al. (2021) find little evidence of differences in employment outcomes or trends over time being affected by the oversampling of household heads with respect to variables such as level of education, gender or location, the main source of bias being for age comparisons. Within the pooled data set, the household sampling weights are scaled such that countries are weighted equally, such that estimates of vaccine hesitancy reported in this study are averages of country averages.<sup>4</sup>

# _2b. Outcome measures_

<mark>The questions asked about vaccine hesitancy in the surveys varied</mark> depending on whether a vaccine was available in the country at the time of the survey. In surveys that took place before the vaccine rollout had

> 3 South Asia is not represented due to lack of available data. The Middle East and North Africa includes two countries—Iraq and Lebanon.

> 4 Using population weights would have resulted in the results being driven by a small number of large countries.

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