metadata: authors: 0: author: Wollburg,Philip Randolph
1: author: Markhof,Yannick Valentin
2: author: Kanyanda,Shelton Sofiel Elisa
3: author: Zezza,Alberto
count: Africa,Burkina Faso,Kenya,Malawi,Nigeria,Tanzania
docna: 0: docna: Turning COVID-19 Vaccines into Vaccinations
            : New Evidence from Sub-Saharan Africa
docty: Policy Research Working Paper
abstracts: cdata!: As COVID-19 vaccines have become more
            widely available in Sub-Saharan Africa, vaccination
            campaigns in the region have struggled to pick up pace and
            trail the rest of the world. This paper presents new
            evidence on vaccine hesitancy, uptake, last-mile delivery
            barriers, and potential strategies to reach those who remain
            unvaccinated. The data come from high-frequency phone
            surveys in five countries in East and West Africa (Burkina
            Faso, Kenya, Malawi, Nigeria, and Tanzania). The surveys
            were conducted by countries&#x2019; national statistical
            agencies, have national scope, are cross-country comparable,
            and draw their samples from nationally representative
            sampling frames. The findings show that across the study
            countries, a majority is willing to get vaccinated. Still,
            vaccine hesitancy is non-negligible among those pending
            vaccination. Concerns about side effects of the vaccine are
            the primary reason for hesitancy. At the same time, many who
            are willing to get vaccinated are deterred by a lack of easy
            access to vaccines at the local level. Radio broadcasts have
            widespread reach and medical professionals have good rapport
            among the unvaccinated population. Furthermore, social ties
            and perceptions as well as intrahousehold power relations
            matter for vaccine take-up. Based on the findings, the paper
            elaborates policy options to boost vaccination campaigns in
            Sub-Saharan Africa.
display_title: Turning COVID-19 Vaccines into
            Vaccinations : New Evidence from Sub-Saharan Africa
listing_relative_url: /research/2022/08/33886756/turning-covid-19-vaccines-vaccinations-new-evidence-sub-saharan-africa
topicv3: Health Equity m1326151 1288,Information and Communication Technologies
            m1326624 133,Immunizations m1327505 1459,Health Policy and Planning m1327535 1401,Coronavirus (COVID-19) m1939478 4828
publishtoextweb_dt: 2022-08-23T00:00:00Z
dois: 10.1596/1813-9450-10152
origu: Off of Sr VP Dev Econ/Chief Econ (DECVP)
author_keys: 0: author_key: 1464872
1: author_key: 1974294
2: author_key: 805742
3: author_key: 635976
model_extractions: Policy Research Working Paper 10152 Turning COVID-19 Vaccines into Vaccinations New Evidence from Sub-Saharan Africa _Philip Wollburg Yannick Markhof Shelton Kanyanda Alberto Zezza_ Development Economics Development Data Group August 2022
Policy Research Working Paper 10152

# **Abstract**

As COVID-19 vaccines have become more widely available in Sub-Saharan Africa, vaccination campaigns in the region have struggled to pick up pace and trail the rest of the world. This paper presents new evidence on vaccine hesitancy, uptake, last-mile delivery barriers, and potential strategies to reach those who remain unvaccinated. The data come from high-frequency phone surveys in five countries in East and West Africa (Burkina Faso, Kenya, Malawi, Nigeria, and Tanzania). The surveys were conducted by countries’ national statistical agencies, have national scope, are cross-country comparable, and draw their samples from nationally representative sampling frames. The findings show that across the study countries, a majority is willing to get vaccinated. Still, vaccine hesitancy is non-negligible among those pending vaccination. Concerns about side effects of the vaccine are the primary reason for hesitancy. At the same time, many who are willing to get vaccinated are deterred by a lack of easy access to vaccines at the local level. Radio broadcasts have widespread reach and medical professionals have good rapport among the unvaccinated population. Furthermore, social ties and perceptions as well as intrahousehold power relations matter for vaccine take-up. Based on the findings, the paper elaborates policy options to boost vaccination campaigns in Sub-Saharan Africa.

This paper is a product of the Development Data Group, Development Economics. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at pwollburg@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **Turning COVID-19 Vaccines into Vaccinations: New Evidence from SubSaharan Africa**

Philip Wollburg<sup>1</sup> Yannick Markhof<sup>1,2</sup> Shelton Kanyanda<sup>1</sup> Alberto Zezza<sup>1</sup>

## **JEL codes: I14, I18, I100, O55**

## **Keywords: COVID-19, vaccination, Africa, vaccine access**

1Development Data Group, World Bank. 2UNU-MERIT, United Nations University. The authors are grateful for support in designing the survey instrument and collecting the data by the country teams: Marco Tiberti for Burkina Faso; Wilbert Drazi Vundru for Malawi; Akiko Sagesaka, Amparo Palacios-Lopez, Ivette Contreras Gonzalez, and Gbemisola Oseni for Nigeria; and Akuffo Amankwah for Tanzania; Antonia Delius and Caleb Leseine Gitau for Kenya. We are furthermore grateful for comments and support by Gero Carletto and Kevin McGee and comments and feedback in the development of the survey instruments by the members of the World Bank Development Data Group’s HFPS Questionnaire Working Group. This paper received funding support from the World Bank Research Support Budget grant “Understanding and estimating COVID-19 vaccination attitudes, uptake, and barriers in Sub-Saharan Africa” and the Global Financing Facility.
# **Introduction**

Since the availability of the first COVID-19 vaccines in late 2020, the world has witnessed the largest vaccination effort in history.<sup>1</sup> In early June 2022, 60 percent of the world population had been fully vaccinated for COVID-19. However, large regional disparities in COVID-19 vaccine coverage remain (Figure 1). Sub-Saharan Africa (SSA), in particular, is lagging in its vaccination efforts. As of July 1, 2022, less than 17 percent of the population had received at least two doses. Consequently, all but two countries (the small island states of the Seychelles and Mauritius) in SSA remain adrift of the World Health Organization’s (WHO) goal to fully vaccinate over 70 percent of the African population by June 2022.<sup>2</sup> _Figure 1: Share of the population fully vaccinated over time._ <!-- Start of picture text --> 60<br>Burkina Faso<br>40 Kenya<br>Malawi<br>Nigeria<br>Tanzania<br>Low income<br>Lower middle income<br>20 Sub-Saharan Africa<br>World<br>0<br>1/1/2021 7/1/2021 1/1/2022 7/1/2022<br>Date<br>Source: Our World In Data<br>Percent<br><!-- End of picture text --> A variety of reasons have been cited for why vaccination efforts in SSA are trailing their targets.<sup>3–12</sup> Shortages in vaccine supplies, the accessibility of vaccination sites, and vaccine hesitancy are the main hypotheses discussed to explain the low coverage.<sup>3,13</sup> However, there is a conspicuous lack of systematic, cross-country comparable, and up-to-date evidence on these issues. Using data from five national phone surveys, we provide new evidence on vaccine hesitancy, uptake, last-mile delivery barriers, and possible promoters of vaccine demand in SSA. Our contributions are fourfold. First, unlike many existing studies that examine specific population groups or regions within countries, our data is national in scope and was collected by the respective national statistical agency of each country we study (Burkina Faso, Kenya, Malawi, Nigeria, and Tanzania) with samples drawn from large, nationally representative sampling frames. Second, data collection efforts were harmonized to a high degree between countries. Our insights are therefore cross-country comparable and representative of a population of approximately 369 million people, 2
32% of the population of SSA. Third, the evidence we present is timely and supersedes potentially outdated information on issues such as vaccine hesitancy from before the start of vaccination for the general population in SSA.<sup>14–16</sup> Fourth, our analysis is comprehensive and provides microlevel evidence on all five dimensions of vaccine hesitancy, _confidence, complacency, convenience, communication,_ and _context,_ lastmile delivery barriers, and potential strategies to reach those who remain unvaccinated.<sup>17</sup> These insights come at a crucial moment for vaccination campaigns which have struggled to pick up pace.

Based on our findings, we elaborate policy options to turn vaccines into vaccinations in Sub-Saharan Africa.

# **Methods**

## **Data**

We use data from High Frequency Phone Surveys (HFPS) in five countries in East and West Africa – Burkina Faso, Kenya, Malawi, Nigeria, and Tanzania. The surveys were conducted by countries’ national statistical agencies in collaboration with the World Bank. Since 2020, the HFPS have collected crosscountry comparable longitudinal data on a wide range of topics, including the impacts of COVID-19 on households and individuals.

Some rounds of the HFPS include a module on COVID-19 vaccination. The data we use in this study was collected between November 2021 and May 2022: Burkina Faso (April-May 2022), Kenya (November 2021-March 2022), Malawi (February 2022), Nigeria (December 2021 – January 2022), and Tanzania (December 2021).

## **Sampling and sample representativeness**

The HFPS are re-contact surveys with national scope whose samples are drawn from nationally representative samples of households interviewed in recent in-person surveys. In Kenya, an additional sample of households was drawn via random digit dialing. Phone survey samples may not be fully representative of the general population, because of limited mobile phone coverage, non-response, and attrition, especially in lower-income contexts. To mitigate these concerns, sampling weights were recalibrated using propensity score and post-stratification methods, which were shown to mitigate sample selection biases in the HFPS.<sup>18–20</sup> In each household, one main respondent over the age of 15 was interviewed, who was selected to be knowledgeable of the affairs of the household and its members to provide reliable responses, though this selection overrepresents certain population groups.<sup>20</sup> Table A1 in the supplementary files summarizes the resulting sample sizes for each country included in our study.

## **Survey instrument and variables**

A harmonized survey module on COVID-19 vaccination was implemented in all five study countries. To study vaccine hesitancy and uptake in a systematic and comprehensive manner, we distinguish three groups in the population: (i) those already vaccinated, (ii) those who are willing to get vaccinated but are yet unvaccinated, and (iii) those who are hesitant to get vaccinated. We define hesitancy in our data as those 3
respondents who are either unwilling to get vaccinated or uncertain about their decision. Analogously, we categorize as willing those who have either already been vaccinated or are willing to do so.

|**Question**<br>**Table**|**Respondent group**<br>**1: Summary of survey questions**|**Answer options**|**Availability**|
|---|---|---|---|
|**(1) Vaccine uptake**||||
|Have you been vaccinated for COVID-19?|all who know of start of vaccination campaigns|Yes, No, Not sure|all countries|
|Where did you get vaccinated?|all vaccinated|One location per jab received|all countries|
|What are your main reasons for getting vaccinated for COVID-19<br>[apart from protecting your health]?|all vaccinated|Up to two reasons (3 in Kenya)|all countries|
|**(2) Vaccine acceptance among the unvaccinated**||||
|Are you planning to be vaccinated for COVID-19?|all who know of start of vaccination campaigns|Yes, No, Not sure|all countries|
|When a vaccine to protect you from COVID-19 is available to you,<br>are you planning to be vaccinated?|all who do not know of start of vaccination<br>campaigns|Yes, No, Not sure|BFA, MWI, NGA, TZN|
|If an approved vaccine to prevent coronavirus was available right now<br>at no cost, would you agree to be vaccinated?|all who do not know of start of vaccination<br>campaigns|Yes, No, Not sure|KEN|
|What are the main reasons why you want to get vaccinated for<br>COVID-19 [apart from protecting your health]?|all willing but unvaccinated|Up to two reasons (3 in Kenya)|all countries|
|Why are you not sure or not planning to get vaccinated?|all hesitant|List of reasons for hesitancy|all countries|
|**(3) Barriers of access**||||
|Do you know if your country has started COVID-19 vaccination?|all|Yes, No|BFA, MWI, NGA, TZN|
|Do you know if a vaccine for COVID-19 is available in Kenya?|all|Yes, No|KEN|
|Why have you not received the COVID-19 vaccine yet?|all willing but unvaccinated who know of start of<br>vaccination campaigns|Up to two reasons|MWI, NGA, TZN|
|What do you think are the main difficulties that you will/would<br>encounter to get the vaccine?|all willing but unvaccinated|List of barriers|KEN|
|**(4) Information sources and channels**||||
|Who/what (institution/body/entity) are your sources of information<br>regarding COVID-19 vaccines?|all who know of start of vaccination campaigns|List of information sources|BFA, MWI, NGA|
|Which source of information do you trust the most for reliable<br>information on COVID-19 vaccines?|all who know of start of vaccination campaigns|Select one among mentioned info<br>sources|BFA, MWI, NGA|
|Through what channels do you receive the information from the<br>source you trust the most?|all who know of start of vaccination campaigns|Select one info channel|BFA, MWI, NGA|
|**(5) Ambassadors of vaccination**||||
|Would you be more likely to receive the COVID-19 vaccine if any of<br>the following individuals/authorities receive or recommend the<br>vaccine?|all hesitant|Select yes or no for list of<br>individuals/authorities|all countries|
|Whose recommendation to get vaccinated for COVID-19 would you<br>trust the most?|all hesitant that had named at least one<br>individual/authority that could encourage them|Select one among previously<br>selected potential ambassadors|BFA, MWI, NGA, TZN|
|How likely are you to encourage others to get the COVID-19 vaccine?|all willing to get vaccinated or already vaccinated|Five point Likert scale|BFA, MWI, NGA, TZN|
|**(6) Social factors in vaccine attitude formation and uptake**||||
|Out of 10 people in your community, how many do you think have<br>been vaccinated or are willing to be vaccinated for COVID-19?|all|Number from 0-10|BFA, MWI, NGA, TZN|
|Who in your household mainly decides whether the adult household<br>members will get vaccinated for COVID-19?|all who know of start of vaccination campaigns|Each for themselves; All adults<br>together; Household head; Name<br>other household member|BFA, MWI, NGA, TZN|

Our analysis draws on the questions summarized in Table 1. These questions group into six broad themes. First, we ask about vaccine uptake among respondents and ask those who have already been vaccinated about the vaccination process. The second theme relates to vaccine acceptance among those who have not been vaccinated yet. These questions gauge the extent of vaccine hesitancy among respondents and the main reasons for their vaccine attitudes. The third theme covers the barriers that keep respondents from getting vaccinated with a particular focus on those who have not been vaccinated yet despite being willing to. Fourth, we ask respondents about their main sources and channels of information on COVID-19 vaccines to identify possible communication strategies for national vaccination campaigns. Theme five is devoted to potential ambassadors that could promote vaccination among respondents. Finally, the sixth theme turns to the social context in which vaccine attitudes are formed and looks at the transmission of vaccine attitudes and uptake decisions within communities and households.

In the analysis we present population-weighted means at the country-level for each variable, computed using the recalibrated phone survey weights. The full results are presented in the supplementary files.

4
## **Role of the funding source**

The funding sources for this paper had no involvement in study design; collection, analysis, and interpretation of the vaccination-related data; in the writing of the report; nor in the decision to submit the paper for publication.

# **Results**

## **A majority is willing to get vaccinated, but COVID-19 vaccine hesitancy should not be dismissed**

Overall, we find that estimated acceptance rates for COVID-19 vaccines in SSA have dropped below the initially high levels of acceptance reported in late 2020 _._<sup>14–16</sup> An exception is Kenya where vaccine acceptance is near universal (95.1%), likely reflecting the issuance of vaccination requirements for public services and places by the Kenyan government in December 2021. Further, we estimate high vaccine acceptance in Nigeria where almost four in five people (78.4%) would accept or have already accepted to be vaccinated for COVID-19. Vaccine acceptance is also above the WHO’s envisioned 70% threshold in Malawi (75.1%) and Burkina Faso (74.4%). At the same time, vaccine hesitancy is notably higher in Tanzania where less than two-thirds of the population (63.3%) are willing to get vaccinated. This is consistent with the COVID-19-sceptic stance the Tanzanian government took during much of the pandemic.<sup>21</sup> Our estimates point to higher hesitancy among women and in urban areas (Table A2).

_Figure 2: Vaccine acceptance among the unvaccinated._ Burkina Faso(57.3%) Kenya(86.4%) Malawi(59.1%) Nigeria(70.5%) Tanzania(56.5%) Willing Unwilling Unsure Among those who are still unvaccinated, the main group for vaccination campaigns to reach out to, vaccine hesitancy is expectedly higher (Figure 2). In Kenya and Nigeria, reported vaccine acceptance still stands at 5
86.4% and 70.5% among the unvaccinated, but this figure is lower in Malawi (59.1%), Burkina Faso (57.3%), and Tanzania (56.5%). Furthermore, in all countries the majority of those we classify as hesitant report being unwilling to be vaccinated rather than uncertain of their decision.

# **Ease of access to vaccines remains a key barrier**

Our data confirms that self-reported knowledge about the start of vaccination campaigns is very high and does not seem to prevent vaccine uptake. Among those currently unvaccinated, knowledge about the start of vaccination campaigns in their country is almost universal in Kenya (99.9%), Malawi (99.3%) and Tanzania (96.3%), very high in Burkina Faso (92.5%), and slightly lower in Nigeria (82.2%).

What is preventing those who are willing to be vaccinated from doing so? Reasons vary between countries but typically relate to the ease of access to vaccinations (Figure 3). In Nigeria, almost four in ten unvaccinated people (39.6%) do not know how to get vaccinated. In Malawi, Nigeria, and Tanzania, a substantial share reports prohibitively long distances to the nearest vaccination point (Malawi: 13.6%; Tanzania: 12.2%; Nigeria: 12.0%) or a lack of available vaccines (Malawi: 18.6%; Nigeria: 9.6%; Tanzania: 9.1%). In Tanzania and Nigeria, traveling to the vaccination site also commonly clashes with work commitments (Tanzania 28.0%; Nigeria 11.7%). In contrast, fear of potential side effects of the vaccine is only a widespread concern in Malawi (35.2%). Structural issues such as the availability of vaccines and distance to the nearest vaccination point are more frequently reported in rural areas whereas in urban areas, work commitments more commonly stand in the way of getting vaccinated. There is a gender divide, with women citing domestic commitments and medical reasons more commonly while men mention work commitments more frequently (Table A4 and A5).

_<mark>Figure 3: Reasons for pending vaccination despite being willing to get vaccinated.</mark>_ <!-- Start of picture text --> Malawi<br>Currently ineligible<br>Don't know how to get<br>Too crowded at vaccination site<br>Facility not disability friendly<br>Too far away<br>Not enough vaccines<br>Unable to register<br>Nigeria<br>Work commitments<br>Domestic commitments<br>Religious reasons<br>Medical reasons<br>Waiting for appointment<br>Afraid of side effects<br>Other reason<br>Tanzania<br>0 .1 .2 .3 .4<br><!-- End of picture text --> 6
In Kenya, a similar question on the anticipated barriers of access was asked. While the largest group cites no barriers of access (37.9%), substantial shares are deterred by crowded vaccination sites (27.8%), a lack of vaccines in sufficient numbers (25.8%), and long distances to the nearest vaccination point (23.5%).

Insufficient ease of access to COVID-19 vaccines is also reflected in the vaccination points used. The majority of respondents was vaccinated at a medical site such as a health center (Burkina Faso: 45.4%; Tanzania: 45.1%; Nigeria: 30.7%; Malawi: 23.4%; Kenya: 18.3%) or hospital (Kenya: 59.9%; Malawi: 43.6%; Tanzania: 31.8%; Nigeria: 29.5%; Burkina Faso: 13.7%). Somewhat fewer people were vaccinated at mass vaccination sites (Burkina Faso: 35.1%; Malawi: 20.0%; Nigeria: 12.6%; Tanzania: 11.9%; Kenya: 8.9%) and smaller, local vaccination sites such as pharmacies, clinics, religious centers, senior homes, or people’s work location play only a minor role.

# **Beliefs about the health benefits and risks of vaccines drive vaccine acceptance and uptake**

A large share of the vaccinated population reports that protecting their own health was the primary and only reason to get vaccinated (Malawi: 89.9%; Tanzania: 76.8%; Nigeria: 64.1%; Burkina Faso: 60.8%; Kenya: 22.7%). This makes a strong case for vaccination campaigns to emphasize the health benefits of vaccination when aiming to increase COVID-19 vaccine take-up. Other motivations commonly cited for getting vaccinated are to protect the health of others in Kenya (68.8%) and Burkina Faso (26.7) and government mandates in Nigeria (18.7%) where a law requiring everyone working in a public institution to get vaccinated took effect in December 2021 - shortly before the start of our data collection. In Kenya, substantial numbers also got vaccinated because they considered it “the right thing to do” (29.7%).

Consistent with the importance of health considerations when deciding to take up the vaccine, concerns about the vaccine’s side effects are the main reason for vaccine hesitancy in all countries studied (Kenya: 86.0%; Malawi: 45.8%; Tanzania: 41.3%; Burkina Faso: 36.2%; Nigeria: 20.8%). In Kenya, concerns about the safety of vaccines are also common (45.2%). Other reasons for hesitancy reflect a lack of confidence, either in vaccines in general or the COVID-19 vaccines in particular: Among vaccine hesitant individuals, one in three in Burkina Faso (33.2%), 15.1% in Malawi, 10.5% in Tanzania, 9.5% in Kenya, and 4.7% in Nigeria say they do not think the vaccine works. In Tanzania and Malawi, around one in five say that they generally do not trust vaccines. Finally, a non-negligible share of the hesitant also simply do not regard getting vaccinated as a high enough priority (Malawi: 21.6%; Tanzania: 10.9%; Nigeria: 10.7%; Burkina Faso: 8.4%).

# **Medical professionals are widely trusted as vaccine ambassadors**

The most common information sources on COVID-19 vaccination are medical professionals (doctors, nurses, pharmacists, and other health workers) and the media. Medical professionals are the most trusted information source in Burkina Faso (45.2%) and Nigeria (28.7%) and also highly trusted in Malawi (34.3%). Notably, trust in medical professionals is higher among those willing to be vaccinated than among the vaccine hesitant population. The hesitant are relatively more likely to cite the media over medical professionals as the most trusted source of information on COVID-19 vaccines (Figure 4). This may relate to an association between vaccine hesitancy and misinformation spread through media channels that previous studies found.<sup>4,12,22</sup> Leveraging trusted figures as ambassadors of COVID-19 vaccination could be a viable strategy to promote vaccine uptake. Across the countries we study, a large but varying share of the hesitant report that they 7
would be more likely to get vaccinated if it was recommended to them by a “vaccine ambassador” (Tanzania: 77.3%; Nigeria: 58.2%; Kenya: 44.0%; Burkina Faso: 42.1%; Malawi: 36.1%). Most frequently, the hesitant mention medical professionals (Nigeria: 40.1%; Kenya: 34.8%; Burkina Faso: 34.5%; Tanzania: 31.9%; Malawi: 26.6%) and family and other community members (Nigeria: 42.7%; Malawi: 29.9%; Burkina Faso: 28.2%; Kenya: 17.6%; Tanzania: 12.1%) among the people that could encourage them to get vaccinated.

_Figure 4: Most trusted information source on COVID-19 vaccines by vaccine acceptance._ <!-- Start of picture text --> Willing<br>Burkina Faso<br>Hesitant<br>Willing<br>Malawi<br>Hesitant<br>Willing<br>Nigeria<br>Hesitant<br>0 .1 .2 .3 .4 .5<br>Medical Professionals Media<br><!-- End of picture text -->

# **Media outlets such as radio and television reach large shares of the population with information on COVID-19 vaccines**

Across countries, we estimate that more than half of the population rely on radios to receive their most trusted information on COVID-19 vaccines (Burkina Faso: 67.0%; Nigeria: 58.8%; Malawi: 51.1%). This emphasizes the role of radio broadcasting as an effective medium of information transmission that has wide dissemination across SSA and among different population groups. Other important channels of vaccine information transmission are in-person interactions (Malawi: 61.7%; Burkina Faso: 44.9%; Nigeria: 42.9%) and, to a lesser extent, television (Burkina Faso: 36.1%; Nigeria: 25.3%; Malawi: 4.5%).

# **The social context informs vaccine attitudes**

Beliefs about the attitudes and norms prevalent in one’s social circle have been shown to influence individual attitudes and behavior.<sup>23,24</sup> Notably, people are found to often misperceive the true attitudes of 8
# ~~<u>bas a</u>~~
vaccination. There is overwhelming willingness among those vaccinated to do so: In Malawi (80.7%), Tanzania (76.4%), and Nigeria (72.1%), more than 7 out of 10 vaccinated individuals would be “very likely” to encourage others to get vaccinated. In Burkina Faso, most are either very likely (22.9%) or somewhat likely (58.4%).

_Figure 6: Decisionmaker about vaccine uptake among adult household members._ <!-- Start of picture text --> Burkina Faso Malawi<br>0.1% 0.6%<br>42.3% 39.4% 42.0%<br>50.9%<br>17.9%<br>6.6%<br>Nigeria Tanzania<br>0.3%<br>6.0%<br>18.3%<br>37.1%<br>6.6% 44.4%<br>69.0%<br>18.2%<br>Each adult for themselves All adults together Household head Other household member<br><!-- End of picture text -->

# **Discussion**

## **Contribution**

Since the start of efforts to vaccinate the world population for COVID-19, vaccine coverage in Sub-Saharan Africa has trailed the rest of the world. In this study, we use data from five national phone surveys conducted by each country’s national statistical agency to provide comprehensive, cross-country comparable, and timely insights into the factors that hold back the progress of vaccination campaigns. Our findings on vaccine hesitancy, uptake, last-mile delivery barriers, and possible promoters of vaccine demand come at a critical moment for vaccination campaigns: vaccines are now more widely available in the region but have generally failed to reach beyond a fraction of the population.

Our findings supersede potentially outdated results from previous studies that were conducted before the wider availability of vaccines<sup>14–16,25,26</sup> and add an up-to-date empirical basis to recent discussions of vaccine hesitancy and last-mile delivery barriers in the uptake of vaccines.<sup>3–8,10,12,13,27,28</sup> The analysis spans all five dimensions of vaccine hesitancy that have been hypothesized to underly the low take-up of vaccines in SSA and elsewhere<sup>17</sup> : Trust in the safety and efficacy of vaccines ( _confidence_ ), perceived severity of COVID19 and risk to fall ill ( _complacency_ ), access to COVID-19 vaccines ( _convenience_ ), the level and sources of information ( _communications_ ), and sociodemographic characteristics ( _context_ ). Furthermore, we provide insights into the last-mile delivery barriers that have kept vaccine-willing people from getting vaccinated 10
and opportunities to reach out to those who are hesitant. As such, our data can inform strategies that national vaccination campaigns may pursue to turn vaccines into vaccinations in Africa.

# **Limitations**

While our data stands out in its informational richness, national scope, and robust survey methodology, it is still subject to the challenges and limitations of (phone) survey data collection on vaccination. These include sample selection at the household level due to under-coverage, non-response, and attrition, as well as within the household arising from the purposive selection of respondents.<sup>19,20</sup> The implications of these issues for findings on vaccine hesitancy should be the subject of future research as should be the reliability of survey data on vaccination in the context of COVID-19.<sup>29–31</sup> Survey data, regardless of mode, necessarily relies on respondent self-reporting which is susceptible to respondents’ incentives, misreporting, and misperceptions.

# **Main findings and policy recommendations**

We find that in our study countries a majority remains willing to get vaccinated but that hesitancy among those unvaccinated is a non-negligible issue. As vaccine coverage in much of SSA is still below 20 percent, vaccination campaigns should focus first on getting those who are willing but yet unvaccinated to take up the vaccine. The main barriers keeping this group away from the vaccination sites are country-specific but commonly relate to the ease with which vaccines can be accessed within communities. Therefore, it is indispensable that vaccination sites become more widespread at the local level.<sup>28</sup> Furthermore, a continuation of communication campaigns about the ongoing risk of COVID-19 and safety of vaccines will be pivotal: We find that the protection vaccines afford to one’s own health is the main reason why people take up the vaccine and that hesitancy mostly relates to concerns about the vaccine’s side effects.<sup>24</sup> As this was already the main concern among the hesitant in 2020<sup>14–16</sup> , national vaccination campaigns should double-down on their efforts to assure the population of the safety of COVID-19 vaccines.

Concerning the means through which the population acquires information on COVID-19 vaccination, we find radio broadcasting to have widespread reach. Radio broadcasts are therefore a promising avenue through which mass communication campaigns could reach their target population. Our results also suggest that medical professionals have good rapport with both the willing and hesitant. Vaccination campaigns could employ endorsements by this group in order to sway the opinions of the hesitant.

Lastly, we find that the social context informs vaccine attitudes, as perceptions about the general acceptance of COVID-19 and within-household power dynamics matter. Changing public perceptions about the true support for vaccines in the country and creating a positive social norm around vaccination could be effective measures. Those already vaccinated could be mobilized as ambassadors that can promote vaccine demand at the community level. Furthermore, convincing key members of the household, mostly the household head, of the need for vaccination may positively affect the take-up of vaccines by the remaining household members. These findings are in line with recent experimental evidence from Zambia.<sup>24</sup>

# **Concluding remarks**

With COVID-19 vaccines becoming more widely available but a large majority of African countries far off the WHO’s target to fully vaccinate 70 percent of the population by June 2022, now is the time to push for 11
increased vaccine take-up in Sub-Saharan Africa. With a renewed focus on creating a positive social norm around COVID-19 vaccination, messaging that leverages trusted and accessible information sources and channels, and more easily accessible vaccination sites at the community level, countries can speed up this process and successfully turn vaccines into vaccinations.

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- 2 WHO Regional Office for Africa. COVID-19 Vaccination in the WHO African Region. Brazzaville: World Health Organization, 2022 https://apps.who.int/iris/bitstream/handle/10665/356373/CV20220615-eng.pdf (accessed July 7, 2022).

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14
# **Supplementary files**

||**Tabl**|**e A1: Sample Siz**|**e**||||
|---|---|---|---|---|---|---|
||**Burkina Faso**|**Kenya (KIHBS)**|**Kenya (RDD)**|**Malawi **|**Nigeria**|**Tanzania**|
|Pre-COVID F2F Survey / RDD frame|7,010||92,999,970|3,181|4,976|12,812|
|With phone numbers|6,877|9,007|92,999,970|2,337|4,934||
|Attempted to contact|2,199|9,007|5,000|2,337|4,440|5,750|
|Reached|1,951||4,075|1,729|3,152|2,251|
|Phone interviews completed|1,847|4,561|1,075|1,447|2,922|2,193|

Note: Sampling frame in Kenya consisted of re-contact sample from the Kenya Integrated Household Budget Survey 2015/16 (KIHBS) and a sample obtained from random digit dialing (RDD).

||**Tab**<br>|**le A2: Estimated**<br>|**vaccine acceptanc**<br>|**e**<br>||
|---|---|---|---|---|---|
||BurkinaFaso|Kenya|Malawi|Nigeria|Tanzania|
|Overall|74.4|95.1|75.1|78.4|63.3|
||(71.5 to 77.2)|(93.4 to 96.9)|(71.1 to 79.1)|(75.8 to 80.9)|(60.2 to 66.3)|
|Unvaccinated|57.3|86.4|59.1|70.5|56.5|
||(53.0 to 61.5)|(81.8 to 91.0)|(53.5 to 64.7)|(67.3 to 73.8)|(53.1 to 59.8)|
|Men|74.9|95.6|77.6|81.1|65.3|
||(71.8 to 78.0)|(93.5 to 97.7)|(73.0 to 82.1)|(78.1 to 84.0)|(61.7 to 68.8)|
|Women|72.3|94.7|71.8|71.4|59.1|
||(65.7 to 78.8)|(92.0 to 97.4)|(65.5 to 78.1)|(67.1 to 75.7)|(53.9 to 64.4)|
|Urban|58.8|95.6|69.9|75.3|59.8|
||(54.6 to 62.9)|(93.5 to 97.7)|(63.0 to 76.8)|(71.5 to 79.1)|(54.7 to 64.9)|
|Rural|81.8|94.8|76.4|79.7|65.0|
||(78.3 to 85.2)|(92.4 to 97.3)|(71.7 to 81.0)|(76.5 to 83.0)|(61.2 to 68.7)|
|_N (overall)_|1,847|5,633|1,447|2,934|2,196|
|_N (unvaccinated)_|1,157|2,018|863|2,010|1,791|
|_N (male)_|1,415|2,605|853|2,053|1,523|
|_N (female)_|432|3,019|594|881|670|
|_N (urban)_|1,141|3,020|547|1,181|809|
|_N(rural)_|706|2,613|900|1,753|1,387|

Note: The table compares estimated acceptance rates for COVID-19 vaccines. The breakdown for different demographics includes those already vaccinated. All values in percent. 95% confidence intervals in parentheses.

15
|**Table A3: Reasons for pendin**<br>**Reasons**<br>**Malawi **|**g vaccination**<br>**Nigeria**|**Tanzania**|
|---|---|---|
|Currently ineligible<br>1.9|3.5|1.7|
|(-0.0 to 3.8)|(1.9 to 5.1)|(0.5 to 3.0)|
|Don't know how to get<br>3.2|39.6|7.8|
|(0.4 to 6.0)|(34.8 to 44.5)|(5.1 to 10.5)|
|Too crowded at vax site<br>3.8|6.7|0.8|
|(1.2 to 6.4)|(4.6 to 8.9)|(0.1 to 1.5)|
|Facility not disability friendly|0.8|0.9|
||(0.2 to 1.3)|(0.2 to 1.7)|
|Too far away<br>13.6|12.0|12.2|
|(8.8 to 18.4)|(9.2 to 14.7)|(9.3 to 15.1)|
|Not enough vaccines<br>18.6|9.6|9.1|
|(12.5 to 24.7)|(7.0 to 12.3)|(6.7 to 11.6)|
|Unable to register<br>0.2|2.0|1.4|
|(-0.1 to 0.4)|(0.8 to 3.3)|(0.4 to 2.4)|
|Work commitments<br>5.3|11.7|28.0|
|(2.3 to 8.3)|(8.4 to 15.0)|(24.1 to 32.0)|
|Domestic commitments<br>5.0|1.5|7.2|
|(2.0 to 8.0)|(0.4 to 2.6)|(5.0 to 9.4)|
|Religious reasons<br>0.5|0.2|0.4|
|(-0.2 to 1.2)|(-0.0 to 0.4)|(0.0 to 0.7)|
|Medical reasons<br>8.0|3.6|6.9|
|(3.5 to 12.5)|(1.9 to 5.3)|(4.8 to 8.9)|
|Waiting for appointment<br>2.0|9.0|3.3|
|(0.6 to 3.5)|(6.4 to 11.6)|(1.8 to 4.7)|
|Afraid of side effects<br>35.2|5.8|0.0|
|(28.0 to 42.4)|(3.6 to 7.9)||
|Other reason<br>8.4|7.8|26.1|
|(4.0 to 12.8)|(5.5 to 10.1)|(22.3 to 29.9)|
|_N_<br>493<br>Note: Reasons for pending vaccination despite<br>vaccinated. All values in percent. 95% confide|1,098<br>being willing to<br>nce intervals in p|992<br>get<br>arentheses.|

16
||**Table A4: Reaso**<br>**Mal**|**ns for pendi**<br>**awi**|**ng vaccinatio**<br>**Nig **|**n by residenc**<br>**eria**|**e**<br>**Tan**|**zania**|
|---|---|---|---|---|---|---|
|**Reasons**|||||||
||**Rural **|**Urban **|**Rural **|**Urban **|**Rural **|**Urban **|
|Currently ineligible|1.9|1.7|3.4|3.6|2.0|1.2|
||(-0.2 to 4.1)|(-1.7 to 5.0)|(1.8 to 5.1)|(-0.1 to 7.2)|(0.3 to 3.7)|(0.2 to 2.3)|
|Don't know how to get|3.8|0.3|41.9|34.8|8.6|6.1|
||(0.4 to 7.2)|(-0.3 to 1.0)|(35.8 to 48.0)|(26.6 to 43.0)|(5.3 to 11.8)|(1.3 to 10.9)|
|Too crowded at vax site|3.6|5.1|5.7|9.0|0.8|0.8|
||(0.5 to 6.6)|(0.8 to 9.4)|(3.1 to 8.2)|(5.1 to 12.9)|(-0.0 to 1.7)|(-0.3 to 1.8)|
|Facility not disability friendly|||0.7|0.8|1.1|0.6|
||(0.5 to 6.6)|(0.8 to 9.4)|(0.0 to 1.4)|(-0.2 to 1.9)|(0.1 to 2.0)|(-0.5 to 1.7)|
|Too far away|15.1|6.4|13.6|8.4|14.4|7.1|
||(9.6 to 20.6)|(-1.8 to 14.6)|(10.0 to 17.2)|(4.9 to 11.9)|(10.6 to 18.2)|(3.2 to 10.9)|
|Not enough vaccines|20.7|8.4|9.3|10.4|11.6|3.4|
||(13.4 to 28.1)|(3.5 to 13.3)|(6.0 to 12.5)|(5.7 to 15.1)|(8.2 to 15.0)|(1.5 to 5.4)|
|Unable to register|0.2|0.0|2.1|1.8|1.6|0.9|
||(-0.1 to 0.5)||(0.4 to 3.9)|(0.4 to 3.2)|(0.2 to 3.0)|(0.0 to 1.8)|
|Work commitments|3.5|13.5|9.5|16.4|24.0|37.2|
||(1.1 to 5.9)|(2.7 to 24.3)|(5.8 to 13.2)|(9.8 to 22.9)|(19.3 to 28.7)|(30.1 to 44.3)|
|Domestic commitments|4.9|5.9|0.7|3.2|7.1|7.3|
||(1.4 to 8.3)|(0.7 to 11.0)|(-0.1 to 1.5)|(0.3 to 6.2)|(4.4 to 9.9)|(3.7 to 10.8)|
|Religious reasons|0.6|0.0|0.0|0.5|0.3|0.4|
||(-0.3 to 1.4)||(-0.0 to 0.1)|(-0.1 to 1.1)|(-0.0 to 0.7)|(-0.3 to 1.2)|
|Medical reasons|7.4|10.5|2.8|5.3|5.8|9.4|
||(2.5 to 12.3)|(-0.7 to 21.6)|(0.8 to 4.7)|(1.9 to 8.8)|(3.4 to 8.1)|(5.2 to 13.6)|
|Waiting for appointment|2.0|2.0|10.6|5.6|3.2|3.4|
||(0.4 to 3.7)|(-1.1 to 5.1)|(7.2 to 13.9)|(2.1 to 9.1)|(1.3 to 5.1)|(1.1 to 5.6)|
|Afraid of side effects|32.8|46.3|4.4|8.6|0.0|0.0|
||(24.9 to 40.8)|(31.2 to 61.4)|(2.1 to 6.8)|(4.3 to 13.0)|||
|Other reason|8.2|9.6|8.1|7.2|25.5|27.4|
||(3.5 to 12.8)|(-2.3 to 21.5)|(5.2 to 11.0)|(3.6 to 10.8)|(20.8 to 30.2)|(21.0 to 33.9)|
|_N_<br>Note: Reasons for pendin<br>percent. 95% confidence|333<br>g vaccination des<br>intervals in paren|160<br>pite being wil<br>theses.|653<br>ling to get va|447<br>ccinated, by u|660<br>rban/rural. All|332<br>values in|

17
|**Reasons**|**Table A5: Rea**<br>**Ma**|**sons for pend**<br>**lawi**|**ing vaccinati**<br>**Nig**|**on by gender**<br>**eria**|**Tan**|**zania**|
|---|---|---|---|---|---|---|
||**Female**|**Male**|**Female**|**Male**|**Female**|**Male**|
|Currently ineligible|1.6|2.1|3.1|3.6|0.8|2.1|
||(-0.5 to 3.6)|(-0.7 to 4.8)|(-1.2 to 7.4)|(1.9 to 5.3)|(-0.2 to 1.7)|(0.5 to 3.8)|
|Don't know how to get|2.1|3.9|39.5|39.7|10.1|7.0|
||(-0.7 to 4.9)|(-0.2 to 8.0)|(30.0 to 49.0)|(34.4 to 45.0)|(4.1 to 16.0)|(4.0 to 9.9)|
|Too crowded at vax site|1.4|5.3|8.5|6.2|1.5|0.5|
||(-0.4 to 3.2)|(1.1 to 9.5)|(3.4 to 13.5)|(3.8 to 8.6)|(-0.6 to 3.6)|(0.0 to 1.0)|
|Facility not disability friendly|||1.2|0.6|0.6|1.0|
||||(-0.2 to 2.6)|(0.0 to 1.2)|(-0.6 to 1.9)|(0.1 to 1.9)|
|Too far away|12.4|14.3|8.0|13.2|8.1|13.7|
||(4.5 to 20.3)|(8.3 to 20.3)|(2.8 to 13.3)|(10.0 to 16.4)|(3.4 to 12.9)|(10.1 to 17.3)|
|Not enough vaccines|12.6|22.3|10.6|9.4|6.4|10.1|
||(4.9 to 20.2)|(14.7 to 29.9)|(4.6 to 16.5)|(6.3 to 12.4)|(2.3 to 10.6)|(7.2 to 13.1)|
|Unable to register|0.0|0.3|0.5|2.5|1.2|1.4|
|||(-0.2 to 0.7)|(-0.1 to 1.2)|(0.9 to 4.1)|(-0.3 to 2.7)|(0.1 to 2.7)|
|Work commitments|0.7|8.1|8.1|12.8|20.1|31.0|
||(0.0 to 1.4)|(3.4 to 12.9)|(2.6 to 13.6)|(9.1 to 16.4)|(13.7 to 26.5)|(26.2 to 35.8)|
|Domestic commitments|6.4|4.2|2.2|1.3|12.0|5.4|
||(2.0 to 10.8)|(0.1 to 8.3)|(-0.1 to 4.4)|(0.0 to 2.6)|(6.2 to 17.8)|(3.3 to 7.5)|
|Religious reasons|0.0|0.8|0.5|0.1|0.8|0.2|
|||(-0.4 to 1.9)|(-0.3 to 1.2)|(-0.0 to 0.2)|(-0.2 to 1.7)|(-0.1 to 0.5)|
|Medical reasons|17.0|2.4|9.4|1.8|13.4|4.4|
||(7.4 to 26.5)|(-1.0 to 5.7)|(3.3 to 15.5)|(0.5 to 3.1)|(7.4 to 19.5)|(2.7 to 6.1)|
|Waiting for appointment|1.7|2.3|3.8|10.6|2.4|3.6|
||(-0.1 to 3.4)|(0.1 to 4.5)|(1.5 to 6.1)|(7.4 to 13.9)|(0.6 to 4.2)|(1.6 to 5.5)|
|Afraid of side effects|42.9|30.4|7.0|5.4|0.0|0.0|
||(30.6 to 55.2)|(22.2 to 38.5)|(3.2 to 10.8)|(2.9 to 7.9)|||
|Other reason|9.5|7.7|10.8|6.9|28.0|25.4|
||(0.7 to 18.3)|(3.1 to 12.4)|(4.4 to 17.2)|(4.7 to 9.1)|(20.5 to 35.5)|(20.8 to 30.0)|
|_N_<br>Note: Reasons for pending<br>95% confidence intervals i|177<br>vaccination despi<br>n parentheses.|316<br>te being willin|270<br>g to get vaccin|830<br>ated, by gende|277<br>r. All values i|715<br>n percent.|

18
|**Barriers**|**Table A6:**<br>**Overall**|**Barriers of acce**<br>**Rural **|**ss (Kenya)**<br>**Urban **|**Female**|**Male**|
|---|---|---|---|---|---|
|Currently ineligible|7.4|6.1|10.0|7.4|7.3|
||(3.1 to 11.6)|(0.8 to 11.3)|(2.8 to 17.1)|(2.3 to 12.5)|(0.6 to 14.1)|
|Too far away|23.5|24.8|20.9|22.1|24.8|
||(17.7 to 29.2)|(17.1 to 32.5)|(13.1 to 28.7)|(14.8 to 29.5)|(16.0 to 33.6)|
|Don't know how to get|2.6|2.6|2.7|1.7|3.5|
||(0.1 to 5.1)|(-1.0 to 6.1)|(0.4 to 4.9)|(0.2 to 3.2)|(-1.1 to 8.1)|
|Too crowded at vax site|27.8|28.0|27.3|30.2|25.4|
||(21.6 to 33.9)|(19.5 to 36.5)|(20.2 to 34.4)|(21.7 to 38.7)|(16.6 to 34.2)|
|Facility not disability friendly|0.1|0.1|0.2|0.1|0.1|
||(0.0 to 0.2)|(-0.0 to 0.1)|(-0.0 to 0.3)|(-0.0 to 0.1)|(-0.0 to 0.3)|
|No transport|5.3|4.9|6.0|8.4|2.3|
||(2.3 to 8.3)|(1.4 to 8.5)|(0.4 to 11.5)|(2.7 to 14.1)|(0.6 to 3.9)|
|Not enough vaccines|25.8|26.6|24.4|25.1|26.5|
||(20.0 to 31.6)|(18.5 to 34.6)|(17.8 to 31.0)|(18.0 to 32.2)|(17.4 to 35.6)|
|Unable to register|0.8|0.9|0.5|1.1|0.5|
||(-0.0 to 1.6)|(-0.2 to 2.1)|(0.1 to 0.8)|(-0.5 to 2.7)|(0.2 to 0.8)|
|Too expensive to obtain|0.5|0.3|1.1|0.2|0.8|
||(-0.1 to 1.1)|(0.0 to 0.5)|(-0.7 to 2.9)|(-0.0 to 0.4)|(-0.4 to 2.0)|
|Discouraged in community|0.4|0.4|0.3|0.3|0.5|
||(0.1 to 0.7)|(-0.0 to 0.9)|(0.0 to 0.6)|(-0.1 to 0.7)|(-0.0 to 1.0)|
|No barriers|37.9|38.7|36.4|34.7|41.0|
||(31.4 to 44.5)|(29.9 to 47.6)|(27.8 to 45.0)|(26.7 to 42.7)|(30.9 to 51.2)|
|Other barrier|0.0|0.0|0.0|0.1|0.0|
||(-0.0 to 0.1)|(-0.0 to 0.1)|(-0.0 to 0.1)|(-0.0 to 0.1)|(-0.0 to 0.0)|
|_N_<br>Note: Main anticipated diffic<br>parentheses.|1,732<br>ulties to get vaccin|839<br>ated. All values i|893<br>n percent. 95% c|952<br>onfidence interva|777<br>ls in|

19
|**Location **|**Table**<br>BurkinaFaso|**A7: Vaccina**<br>Kenya|**tion location**<br>Malawi|Nigeria|Tanzania|
|---|---|---|---|---|---|
|Hospital|13.7|59.9|43.6|29.5|31.8|
||(9.3 to 18.2)|(55.2 to 64.6)|(37.1 to 50.1)|(24.8 to 34.2)|(25.4 to 38.2)|
|Clinic|0.4|6.1|11.5|14.7|1.6|
||(0.0 to 0.7)|(2.8 to 9.5)|(7.7 to 15.4)|(10.9 to 18.5)|(0.0 to 3.6)|
|Health center|45.4|18.3|23.4|30.7|45.1|
||(39.2 to 51.7)|(14.5 to 22.1)|(17.6 to 29.2)|(25.6 to 35.8)|(38.2 to 52.1)|
|Pharmacy|0.1|0.0|0.0|0.5|0.1|
||(0.0 to 0.3)|(-0.0 to 0.1)||(0.0 to 1.3)|(0.0 to 0.2)|
|Senior home|0.2|0.0|0.0|1.2|0.0|
||(0.0 to 0.5)|(-0.0 to 0.0)||(0.0 to 2.7)|(0.0 to 0.1)|
|Mass vaccination site|35.1|8.9|20.0|12.6|11.9|
||(29.2 to 40.9)|(6.7 to 11.1)|(13.8 to 26.3)|(9.3 to 15.9)|(7.5 to 16.3)|
|At work|1.6||1.7|3.1|1.2|
||(0.4 to 2.8)||(0.3 to 3.0)|(1.5 to 4.8)|(0.2 to 2.2)|
|Religious center|0.8||0.3|1.8|3.5|
||(0.0 to 1.6)||(0.0 to 0.6)|(0.0 to 3.7)|(0.6 to 6.5)|
|Other location|3.1|6.7|0.0|5.5|6.3|
||(1.6 to 4.7)|(4.7 to 8.8)||(3.1 to 7.9)|(2.8 to 9.8)|
|_N_|690|3586|584|921|403|

Note: Vaccination location. All values in percent. 95% confidence intervals in parentheses.

20
|**Reason **|**Table A8**<br>BurkinaFaso|**: Reasons for va**<br>Kenya|**ccination**<br>Malawi|Nigeria|Tanzania|
|---|---|---|---|---|---|
|Protecting own health only|60.8|22.7|89.9|64.1|76.8|
||(55.1 to 66.5)|(18.4 to 26.9)|(86.5 to 93.3)|(59.5 to 68.7)|(70.8 to 82.9)|
|Protecting other's health|26.7|68.6|5.0|9.3|16.0|
||(21.4 to 31.9)|(64.1 to 73.1)|(2.7 to 7.2)|(6.4 to 12.2)|(10.8 to 21.2)|
|Government mandate|6.9||1.1|18.7|4.0|
||(4.0 to 9.8)||(0.0 to 2.4)|(14.8 to 22.5)|(1.5 to 6.5)|
|Attend school|0.3|0.4|0.0|0.2|0.0|
||(0.0 to 0.8)|(0.0 to 0.8)|(0.0 to 0.0)|(0.0 to 0.5)||
|Employer mandate|0.7|12.1|1.4|1.6|0.9|
||(0.0 to 1.4)|(9.5 to 14.6)|(0.4 to 2.3)|(0.2 to 2.9)|(0.0 to 2.0)|
|Avoid public health measures|4.4||0.9|3.2|0.5|
||(2.1 to 6.7)||(0.0 to 2.0)|(0.6 to 5.9)|(0.0 to 1.2)|
|Take part in social life|2.1|0.2|1.3|3.1|2.6|
||(0.6 to 3.6)|(0.1 to 0.3)|(0.0 to 2.7)|(1.3 to 5.0)|(0.3 to 4.9)|
|Be able to travel|10.7||1.3|10.4|3.1|
||(7.6 to 13.8)||(0.0 to 2.6)|(7.6 to 13.2)|(0.4 to 5.8)|
|People in community did it too|4.4||0.1|2.3|0.1|
||(2.0 to 6.8)||(0.0 to 0.2)|(1.2 to 3.3)|(0.0 to 0.2)|
|Received material incentive|0.0||0.0|0.0|0.0|
|||||(0.0 to 0.1)||
|Other reason|1.4|29.7|0.2|1.3|4.1|
||(0.0 to 2.9)|(25.8 to 33.7)|(0.0 to 0.4)|(0.1 to 2.5)|(0.7 to 7.5)|
|_N_<br>Note: Reasons for getting vac<br>in Kenya (29.2%). All values|690<br>cinated. 'Other' mai<br>in percent. 95% co|3,586<br>nly comprises of<br>nfidence interva|584<br>people citing ethi<br>ls in parentheses.|921<br>cal reasons as t|403<br>heir motivation|

21
|**Reason **|**Table A9:**<br>BurkinaFaso|**Reasons for h**<br>Kenya|**esitancy**<br>Malawi|Nigeria|Tanzania|
|---|---|---|---|---|---|
|Do not think vax works|33.2|9.5|15.1|4.7|10.5|
||(25.8 to 40.6)|(3.3 to 15.8)|(9.6 to 20.6)|(2.6 to 6.8)|(7.5 to 13.5)|
|Worried about side effects|36.5|86.0|45.8|20.8|41.3|
||(29.9 to 43.2)|(77.8 to 94.1)|(38.3 to 53.2)|(15.7 to 26.0)|(36.4 to 46.2)|
|Already had COVID-19|0.3|||0.3|0.1|
||(0.0 to 0.8)|||(0.0 to 0.6)|(0.0 to 0.3)|
|Not enough at risk|3.9|6.1|4.8|18.7|2.8|
||(1.5 to 6.3)|(1.4 to 10.8)|(1.0 to 8.5)|(14.0 to 23.3)|(1.1 to 4.6)|
|Don't trust vaccines generally|4.8|5.0|18.4|11.6|19.5|
||(1.7 to 7.9)|(1.8 to 8.2)|(11.9 to 24.8)|(7.7 to 15.5)|(15.6 to 23.3)|
|Against my religion|0.4|1.9|4.9|3.1|1.4|
||(0.0 to 1.3)|(-0.2 to 4.1)|(1.6 to 8.3)|(1.4 to 4.7)|(0.5 to 2.3)|
|Infection risk at facility|0.3|1.7|0.2|1.7|0.1|
||(0.0 to 0.6)|(0.2 to 3.1)|(-0.2 to 0.5)|(0.3 to 3.1)|(0.0 to 0.3)|
|Facility too hard to reach|0.0|7.5|0.8|1.5|2.1|
|||(-1.8 to 16.8)|(-0.3 to 1.9)|(0.0 to 3.4)|(0.7 to 3.5)|
|Do not have time|2.2|0.4|2.9|1.9|2.2|
||(0.7 to 3.6)|(-0.3 to 1.0)|(-0.7 to 6.4)|(0.0 to 4.0)|(0.8 to 3.7)|
|Vax available here not effective|10.3||1.7|3.0|0.4|
||(6.7 to 14.0)||(-0.6 to 3.9)|(1.3 to 4.6)|(0.0 to 0.9)|
|Unsure if I get the vax I want|2.6||6.9|1.5|2.2|
||(1.0 to 4.2)||(2.5 to 11.3)|(0.5 to 2.5)|(0.8 to 3.6)|
|Not a priority|8.7||21.6|11.0|10.9|
||(5.3 to 12.1)||(15.0 to 28.3)|(6.8 to 15.3)|(7.9 to 13.9)|
|COVID-19 does not exist|8.9|||16.3|2.6|
||(5.2 to 12.7)|||(9.9 to 22.7)|(1.0 to 4.1)|
|Medical reasons|0.6||0.2|2.3|2.2|
||(0.0 to 1.2)||(-0.1 to 0.5)|(0.8 to 3.7)|(0.8 to 3.5)|
|Do not trust the government|6.1||1.8|5.0|1.7|
||(3.3 to 9.0)||(-0.4 to 4.0)|(2.6 to 7.3)|(0.3 to 3.2)|
|Other reason|5.5|0.0|1.7|13.7|16.0|
||(2.0 to 9.1)|(-0.0 to 0.1)|(0.2 to 3.2)|(9.8 to 17.6)|(12.2 to 19.7)|
|Do not think it is safe||45.2||||
|||(27.2 to 63.2)||||
|_N_<br>Note: Reasons for being hesita<br>parentheses.|526<br>nt to get vaccinated.|<br>313<br>All values in p|366<br>ercent. 95% con|609<br>fidence interval|769<br>s in|

22
|**Information Source**|**Table A10: Most trusted inform**<br>BurkinaFaso|**ation sources**<br>Malawi|Nigeria|
|---|---|---|---|
|Medical professional|45.2|34.3|28.7|
||(41.0 to 49.4)|(30.1 to 38.6)|(25.7 to 31.7)|
|Scientists and epidemiologists|0.1|0.0|0.3|
||(0.0 to 0.3)||(0.1 to 0.6)|
|Celebrities and influencers|0.0|0.9|2.3|
||(0.0 to 0.1)|(0.3 to 1.6)|(1.3 to 3.3)|
|NGO outreach programs|0.4|1.4|1.0|
||(0.1 to 0.7)|(0.3 to 2.6)|(0.4 to 1.6)|
|Other outreach programs|0.3|2.3|1.0|
||(0.0 to 0.7)|(0.9 to 3.6)|(0.5 to 1.6)|
|Local government|5.7|0.5|10.1|
||(4.0 to 7.4)|(0.0 to 1.3)|(8.2 to 12.1)|
|Federal government|0.3|0.0|8.8|
||(0.0 to 0.7)||(7.2 to 10.4)|
|State government|6.2|0.0|6.4|
||(4.4 to 8.0)||(5.0 to 7.8)|
|Family and neighbors|5.6|4.1|12.8|
||(3.9 to 7.2)|(2.2 to 6.0)|(10.7 to 14.8)|
|Religious organizations|0.9|2.3|3.7|
||(0.1 to 1.7)|(0.6 to 4.0)|(2.7 to 4.7)|
|Traditional healer|0.4|0.0|0.0|
||(0.0 to 0.9)|||
|Traditional ruler|1.8|2.0|1.5|
||(0.7 to 2.9)|(0.9 to 3.1)|(0.7 to 2.4)|
|Media|26.5|34.4|10.9|
||(22.9 to 30.0)|(30.3 to 38.4)|(9.1 to 12.7)|
|Other info source|0.4|0.4|2.1|
||(0.0 to 0.7)|(0.0 to 0.9)|(1.1 to 3.2)|
|None|1.7|4.1|5.1|
||(1.0 to 2.4)|(2.5 to 5.6)|(3.8 to 6.4)|
|Trust all equally|4.6|13.3|5.2|
||(3.2 to 5.9)|(10.6 to 16.0)|(3.8 to 6.5)|
|_N_<br>Note: Most trusted inform|1,744<br>ation sources. All values in percent.|1,443<br>95% confidence inte|2,488<br>rvals in parentheses.|

23
|**Table**<br>**Information Source**|**A11: Most trus**<br>**Burkin**|**ted informatio**<br>**a Faso**|**n sources by**<br>**Ma**|**vaccine accep**<br>**lawi**|**tance**<br>**Nig**|**eria**|
|---|---|---|---|---|---|---|
||**Hesitant**|**Willing**|**Hesitant**|**Willing**|**Hesitant**|**Willing**|
|Medical professional|33.5|49.2|32.5|35.0|18.7|31.2|
||(26.9 to 40.1)|(44.3 to 54.1)|(24.2 to 40.8)|(30.2 to 39.7)|(13.7 to 23.8)|(27.9 to 34.5)|
|Scientists and epidemiologists|0.5|0.0|0.0|0.0|0.0|0.4|
||(0.0 to 1.0)|(0.0 to 0.1)|||(0.0 to 0.1)|(0.1 to 0.7)|
|Celebrities and influencers|0.0|0.0|0.3|1.1|2.9|2.1|
|||(0.0 to 0.1)|(0.0 to 1.0)|(0.2 to 1.9)|(0.2 to 5.7)|(1.1 to 3.2)|
|NGO outreach programs|0.2|0.5|0.1|1.9|0.4|1.1|
||(0.0 to 0.4)|(0.1 to 0.8)|(0.0 to 0.3)|(0.4 to 3.4)|(0.0 to 0.9)|(0.5 to 1.8)|
|Other outreach programs|0.1|0.4|1.8|2.4|1.5|0.9|
||(0.0 to 0.4)|(0.0 to 0.8)|(0.0 to 4.3)|(0.8 to 4.0)|(0.0 to 3.0)|(0.4 to 1.5)|
|Local government|3.0|6.6|0.0|0.7|3.2|11.9|
||(0.8 to 5.2)|(4.5 to 8.8)|(0.0 to 0.1)|(0.0 to 1.7)|(1.0 to 5.3)|(9.5 to 14.2)|
|Federal government|1.0|0.0|0.0|0.0|7.1|9.2|
||(0.0 to 2.8)|(0.0 to 0.0)|||(3.2 to 11.0)|(7.4 to 11.0)|
|State government|8.1|5.6|0.0|0.0|5.7|6.6|
||(4.4 to 11.7)|(3.4 to 7.7)|||(2.6 to 8.8)|(5.0 to 8.2)|
|Family and neighbors|4.5|5.9|3.5|4.3|17.1|11.7|
||(1.9 to 7.0)|(3.9 to 7.9)|(1.4 to 5.6)|(2.0 to 6.7)|(12.4 to 21.7)|(9.5 to 13.9)|
|Religious organizations|0.3|1.1|1.1|2.7|5.4|3.3|
||(0.0 to 0.6)|(0.1 to 2.2)|(0.0 to 2.6)|(0.7 to 4.7)|(2.3 to 8.4)|(2.3 to 4.3)|
|Traditional healer|1.0|0.2|0.0|0.0|0.0|0.0|
||(0.0 to 2.9)|(0.0 to 0.4)|||||
|Traditional ruler|0.8|2.1|1.2|2.2|1.4|1.6|
||(0.0 to 1.9)|(0.7 to 3.6)|(0.0 to 2.3)|(0.8 to 3.6)|(0.0 to 3.2)|(0.6 to 2.5)|
|Media|34.1|23.9|37.6|33.3|12.7|10.5|
||(27.2 to 40.9)|(20.1 to 27.7)|(29.8 to 45.4)|(28.7 to 37.8)|(8.4 to 17.0)|(8.6 to 12.4)|
|Other info source|1.4|0.0|0.4|0.4|4.2|1.6|
||(0.0 to 2.9)||(0.0 to 1.2)|(0.0 to 1.0)|(1.0 to 7.4)|(0.5 to 2.7)|
|None|6.5|0.1|11.4|1.6|14.0|2.8|
||(3.8 to 9.1)|(0.0 to 0.2)|(6.2 to 16.6)|(0.6 to 2.6)|(9.4 to 18.7)|(1.7 to 4.0)|
|Trust all equally|5.3|4.3|10.1|14.3|5.6|5.1|

24
|(3.0 to 7.6)|(2.8 to 5.8)|(6.1 to 14.1)|(10.9 to 17.7)|(2.3 to 8.9)|(3.7 to 6.5)|
|---|---|---|---|---|---|
|_N_<br>483|1,261|366|1,077|477|2,021|

Note: Most trusted information sources by vaccine acceptance. All values in percent. 95% confidence intervals in parentheses.

|**Ambassador**|**Table A12**<br>Burkina Faso|**: Vaccine amba**<br>Kenya|**ssadors**<br>Malawi|Nigeria|Tanzania|
|---|---|---|---|---|---|
|At least some ambassador|42.1|44.0|36.1|58.2|77.3|
||(35.8 to 48.3)|(25.2 to 62.9)|(27.2 to 45.0)|(52.3 to 64.1)|(73.1 to 81.4)|
|Family|28.3|17.6|29.9|42.7|12.1|
||(21.5 to 35.1)|(8.2 to 27.1)|(21.2 to 38.6)|(36.9 to 48.6)|(8.9 to 15.4)|
|Religious leader|23.4|11.2|25.4|44.0|20.4|
||(17.1 to 29.7)|(3.9 to 18.6)|(17.6 to 33.2)|(38.0 to 50.0)|(16.2 to 24.6)|
|Medical professional|34.5|34.8|26.6|40.1|31.9|
||(28.1 to 40.9)|(15.3 to 54.3)|(19.1 to 34.2)|(34.5 to 45.7)|(27.2 to 36.5)|
|Community leader|22.4|7.3|19.3|35.5|9.5|
||(16.1 to 28.7)|(3.2 to 11.4)|(12.4 to 26.2)|(29.9 to 41.1)|(6.4 to 12.6)|
|Traditional healer|19.2|5.8|11.0|24.4|2.8|
||(13.0 to 25.3)|(2.2 to 9.4)|(5.9 to 16.2)|(19.8 to 29.0)|(1.2 to 4.3)|
|Scientist and epidemiologists|21.8|23.1|16.2|32.3|13.4|
||(15.5 to 28.1)|(4.0 to 42.1)|(10.1 to 22.3)|(27.7 to 37.0)|(10.1 to 16.8)|
|Celebrities and influencers|16.9|5.8|13.5|22.6|4.2|
||(10.8 to 23.0)|(2.2 to 9.4)|(8.0 to 19.0)|(18.4 to 26.8)|(2.2 to 6.2)|
|Other ambassador|2.3|5.9|0.0|1.1|37.2|
||(0.5 to 4.2)|(1.9 to 9.8)|(0.0 to 0.1)|(0.1 to 2.2)|(32.3 to 42.2)|
|_N_|526|313|366|609|769|

Note: People whose recommendation would make the hesitant more likely to get vaccinated. All values in percent. 95% confidence intervals in parentheses.

25
|**T**<br>**Channel **|**able A13: Inform**<br>BurkinaFaso|**ation channels**<br>Malawi|Nigeria|
|---|---|---|---|
|In person|44.9|61.7|42.8|
||(40.9 to 48.9)|(57.3 to 66.0)|(39.9 to 45.7)|
|Posters, billboards and flyers|9.5|2.4|3.2|
||(7.3 to 11.6)|(0.8 to 4.1)|(2.0 to 4.3)|
|Radio|67.0|51.1|58.8|
||(63.1 to 70.9)|(47.0 to 55.3)|(55.7 to 61.9)|
|TV|36.1|4.5|25.2|
||(32.3 to 39.9)|(2.8 to 6.2)|(22.2 to 28.3)|
|SMS|2.6|3.0|5.7|
||(1.2 to 4.1)|(1.6 to 4.4)|(4.4 to 7.0)|
|Phone|5.0|2.8|11.1|
||(3.5 to 6.6)|(1.4 to 4.2)|(9.2 to 12.9)|
|Newspaper|6.6|0.7|5.6|
||(4.8 to 8.5)|(0.3 to 1.0)|(4.3 to 6.9)|
|Social media|8.5|2.9|10.3|
||(6.6 to 10.3)|(1.4 to 4.3)|(8.6 to 12.0)|
|Other internet channel|0.7|0.0|3.7|
||(0.0 to 1.3)|(0.0 to 0.1)|(2.5 to 4.9)|
|Other information channel|1.3|2.5|3.0|
||(0.4 to 2.3)|(1.2 to 3.7)|(1.8 to 4.2)|
|_N_<br>Note: Information channel<br>19 was obtained. All value|1,738<br>s through which the<br>s in percent. 95% c|1,442<br>most trusted inform<br>onfidence intervals i|2,493<br>ation on COVID-<br>n parentheses.|

26
**Table A14: Perceived vaccine acceptance**

|**Estimate**|Burkina Faso|Malawi|Nigeria|Tanzania|
|---|---|---|---|---|
|Estimated national acceptance|74.4|75.1|78.4|63.3|
||(71.5 to 77.2)|(71.1 to 79.1)|(75.8 to 80.9)|(60.2 to 66.3)|
|Average perceived acceptance|43.2|47.7|59.1|43.6|
||(40.6 to 45.8)|(45.1 to 50.3)|(56.8 to 61.3)|(40.6 to 46.7)|
|Perceived acceptance (hesitant)|22.7|32.5|25.7|25.6|
||(19.2 to 26.2)|(27.8 to 37.2)|(20.9 to 30.5)|(20.8 to 30.3)|
|Perceived acceptance (willing)|49.3|52.5|64.8|51.5|
||(46.7 to 51.9)|(49.9 to 55.1)|(62.5 to 67.0)|(48.1 to 55.0)|
|_N (national)_|1,847|1,447|2,934|2,196|
|_N (perceived)_|1,551|1,287|1,995|1,416|
|_N (hesitant)_|389|315|280|407|
|_N (willing)_|1,162|972|1,714|1,009|

Note: Average perceived acceptance of COVID-19 vaccines in one's community. All values in percent. 95% confidence intervals in parentheses.

**<u><mark>Table A15: Decisionmaker within the household</mark></u>**

|**Decisionmaker **|BurkinaFaso|Malawi|Nigeria|Tanzania|
|---|---|---|---|---|
|Each adult for themselves|50.9|42.0|18.3|37.1|
||(46.7 to 55.2)|(37.6 to 46.5)|(15.2 to 21.5)|(34.0 to 40.3)|
|All adults together|6.6|17.9|6.6|18.2|
||(4.9 to 8.3)|(15.3 to 20.5)|(5.2 to 8.0)|(15.8 to 20.5)|
|Household head|42.3|39.4|69.0|44.4|
||(37.9 to 46.8)|(35.4 to 43.4)|(65.5 to 72.6)|(41.1 to 47.7)|
|Other household member|0.1|0.6|6.0|0.3|
||(0.0 to 0.3)|(0.0 to 1.4)|(4.3 to 7.8)|(0.1 to 0.6)|
|_N_|1,744|1,343|2,386|2,131|

Note: Decisionmaker within the household about vaccine uptake of adult household members. All values in percent. 95% confidence intervals in parentheses.

27
**<u><mark>Table A16: Likelihood to encourage others</mark></u>**

|**Likelihood**|BurkinaFaso|Malawi|Nigeria|Tanzania|
|---|---|---|---|---|
|1. Very likely|22.9|80.7|72.1|76.4|
||(18.2 to 27.7)|(75.0 to 86.4)|(67.3 to 76.9)|(70.7 to 82.2)|
|2. Somewhat likely|58.4|13.0|23.6|18.4|
||(52.9 to 63.8)|(8.2 to 17.8)|(19.0 to 28.3)|(13.2 to 23.5)|
|3. Neither likely nor unlikely|12.1|3.8|1.8|2.5|
||(8.5 to 15.8)|(1.2 to 6.4)|(0.6 to 3.1)|(0.0 to 5.0)|
|4. Somewhat unlikely|6.5|0.3|1.4|1.4|
||(3.6 to 9.4)|(0.0 to 0.6)|(0.2 to 2.5)|(0.0 to 3.1)|
|5. Very unlikely|0.1|2.2|1.1|1.3|
||(0.0 to 0.2)|(0.3 to 4.0)|(0.3 to 1.8)|(0.0 to 3.4)|
|_N_|690|584|921|402|

Note: Likelihood to encourage others to get vaccinated among those already vaccinated. All values in percent. 95% confidence intervals in parentheses.

28