COVID-19 Vaccine Acceptance, Attitude and Perception among Slum and Underserved Communities: A Systematic Review and Meta-Analysis
Abstract
:1. Introduction
- (i)
- What is the prevalence of COVID-19 vaccine acceptance, hesitancy and uptake among slum and underserved communities?
- (ii)
- What are the factors associated with COVID-19 vaccine acceptance and hesitancy among slum and underserved communities?
- (iii)
- What are the attitudes and perceptions regarding COVID-19 vaccines among slum and underserved communities?
2. Materials and Methods
2.1. Study Design
2.2. Search Strategy
2.3. Inclusion Criteria
2.4. Exclusion Criteria
2.5. Data Extraction
2.6. Quality Assessment and Data Analysis
3. Results
3.1. Study Selection and Search Results
3.2. Characteristics of the Included Studies
3.3. Primary Findings
3.3.1. COVID-19 Vaccine Acceptance and Hesitancy
3.3.2. COVID-19 Vaccine Uptake
3.3.3. Factors Associated with COVID-19 Vaccination
3.3.4. Qualitative Reasons for COVID-19 Vaccine Hesitancy
3.3.5. Attitudes and Perceptions about COVID-19 Vaccination
4. Discussion
4.1. Primary Findings
4.2. Limitations and Future Research
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Search | Search Terms (Boolean Operators) |
---|---|
1 | “COVID-19 vaccine” OR “COVID-19 vaccination” OR “COVID-19 immunisation” OR “COVID-19 immunisation AND “slum” OR “urban poor” OR “disadvantaged” OR “underserved” OR “slum-dwellers” OR “informal settlement” OR “poor housing” |
2 | “SARS-CoV-2 vaccine” OR “SARS-CoV-2 vaccination” OR “SARS-CoV-2 immunisation” OR “SARS-CoV-2 immunisation AND “slum” OR “urban poor” OR “disadvantaged” OR “underserved” OR “slum-dwellers” OR “informal settlement” OR “poor housing” |
3 | “Coronavirus vaccine” OR “Coronavirus vaccination” OR “Coronavirus immunisation” OR “Coronavirus immunisation AND “slum” OR “urban poor” OR “disadvantaged” OR “underserved” OR “slum-dwellers” OR “informal settlement” OR “poor housing” |
4 | “COVID-19 vaccine acceptance” OR “COVID-19 vaccine hesitancy” OR “COVID-19 vaccine acceptability” AND “slum” OR “urban poor” OR “disadvantaged” OR “underserved” OR “slum-dwellers” OR “informal settlement” OR “poor housing” |
5 | “COVID-19 vaccine attitude” OR “COVID-19 vaccine knowledge” OR “COVID-19 vaccine perception” AND “slum” OR “urban poor” OR “disadvantaged” OR “underserved” OR “slum-dwellers” OR “slum dwellers” OR “informal settlement” OR “poor housing” |
Author, Year | Study Setting /Country | Study Type and Key Measures | Study Population | Sample Size | Vaccine Acceptance/Hesitancy/Uptake Rates | Relevant Findings |
---|---|---|---|---|---|---|
Lennon et al., 2022 [25] | USA | Cross-sectional -Acceptance of COVID-19 booster, influenza and combination influenza-COVID-19 booster vaccines | Underserved communities | 12,887 | Acceptance: 45% for a COVID-19 booster alone; 58% for an influenza vaccine alone; 50% for a combination vaccine. |
|
Alam et al., 2022 [26] | Bangladesh(Dhaka) | -Qualitative study -Perceptions and attitudes | Urban slum dwellers | 36 | N/A |
|
Kusuma et al., 2022 [27] | India (Delhi) | -Cross-sectional -Acceptance and determinants | Urban slum communities | 1539 | Acceptance: 64.9%; hesitancy: 17.7%; not sure: 17.4% |
|
Hasan et al., 2022 [28] | Bangladesh (Dhaka) | -Cross-sectional -Acceptance and determinants | Urban slum dwellers | 318 | -Uptake: 5%; acceptance: 62.6% |
|
Sunil et al., 2021 [29] | India (Bengaluru) | Cross-sectional -Uptake and associated factors | Urban slum dwellers | 1638 | -Uptake: 35.5% |
|
Aguilar et al. 2021 [30] | Brazil (Salvador) | Cross-sectional -Acceptance and determinants | Urban slum dwellers | 985 | Acceptance: 66.0%; hesitancy: 26.1%; not sure: 7.9% -Parental acceptance for children: 67%; hesitancy: 18%; 15% unsure |
|
Cohrs et al., 2022 [31] | USA (Ohio) | Cross-sectional, hospital-based -Barriers and experience | Underserved patients | 189 | N/A |
|
Nasimiyu et al., 2022 [32] | Kenya (Kibera and Asembo) | Cross-sectional -Acceptance and determinants | Urban slum dwellers | 856 | Acceptance: 83.6% in Asembo and 59.8% in Kibera |
|
Doherty et al., 2021 [33] | USA (North Carolina) | Cross-sectional -Hesitancy and correlates | Underserved communities | 948 | Overall hesitancy was 68.9%—Whites: 62.7%; Blacks: 74%; Latinx: 59.5% |
|
Patwary et al., 2022 [34] | Bangladesh (Dhaka and Khulna) | Cross-sectional -Acceptance determinants (antecedents) | Urban slum dwellers | 400 | Acceptance: 82% |
|
Crozier et al., 2022 [35] | USA (Alabama) | Cross-sectional -Acceptance and correlates | Underserved communities | 3721 | Acceptance: 38.7%; hesitancy: 24.1%; not sure: 37.2% |
|
Tamysetty et al., 2021 [36] | India (Mumbai, Bengaluru, Kolkata and Delhi) | Cross-sectional Mixed methods -Facilitators and barriers to vaccination | Urban slum dwellers | 296 | N/A |
|
Qasim et al., 2022 [37] | Pakistan (Karachi) | Cross-sectional -Qualitative study -Perceptions and experience of vaccination | Urban slum dwellers | 46 | N/A |
|
Bhartiya et al., 2021 [38] | India (Mumbai) | Cross-sectional -Knowledge, attitude and perception | Urban slum dwellers | 1342 | Acceptance: 79%; hesitancy: 2%; unsure: 19% |
|
Kazmi et al., 2022 [39] | Pakistan (Islamabad and Rawalpindi) | Cross-sectional -Uptake, acceptance and determinants | Urban slum dwellers | 1760 | Uptake: 16% partially; 6% fully vaccinated; acceptance: 67% |
|
Coman et al., 2022 [40] | USA | Cross-sectional -Attitude and perception | Underserved communities | 795 | Uptake: 20.6%; hesitancy: 79.4% |
|
Kawuki et al., 2023 [41] | Uganda | Cross-sectional -Comparative study -Uptake and determinants | Urban slum dwellers and estate residents | 1025 | Uptake: 43.8% fully vaccinated in slums compared to 39.9% in estate |
|
Abedin et al., 2021 [42] | Bangladesh | Cross-sectional -Acceptance and correlates | Urban slum dwellers | 253 | Acceptance: 58.1%; hesitancy 17%; not sure: 24.9% |
|
Nabirye et al. 2021 [43] | Uganda | Cross-sectional -Acceptance, knowledge and perceptions | Urban slum dwellers | 367 | Acceptance: 58.3% |
|
Mamun et al., 2021 [44] | Bangladesh (Dhaka) | Cross-sectional -Perceptions | Urban slum dwellers | 434 | N/A |
|
Wang et al., 2021 [45] | USA (Delaware) | Cross-sectional -Uptake and determinants | Underserved communities | 293 | Uptake: 30%; hesitancy: 60% |
|
Garcini et al., 2022 [46] | USA (South Texas) | Cross-sectional -Mixed methods -Barriers and facilitators | Community Health Workers in Underserved Communities | 64 | Acceptance: 70.7%; Hesitancy: 8.6%; unsure: 20.7% |
|
Campagnoli et al., 2022 [47] | USA (Chicago) | Cross-sectional, Hospital-based -Acceptance and drivers | Underserved Patients | 97 | Acceptance: 57.8%; hesitancy: 27% |
|
Robinson et al., 2022 [48] | USA (Alaska and Idaho) | Cross-sectional, Qualitative study -Factors for hesitancy | Underserved communities | 34 | N/A |
|
Author | Year | Country | Study Design | Population | Sample Size | Acceptance (%) | Hesitancy (%) | Uptake (%) |
---|---|---|---|---|---|---|---|---|
Lennon et al. [25] | 2022 | USA | Quantitative | General | 12,887 | 54 | 46 | -- |
Alam et al. [26] | 2022 | Bangladesh | Qualitative | General | 36 | -- | -- | -- |
Kusuma et al. [27] | 2022 | India | Quantitative | General | 1539 | 64.9 | 17.7 | -- |
Hasan et al. [28] | 2022 | Bangladesh | Quantitative | General | 318 | 62.6 | 37.4 | 5 |
Sunil et al. [29] | 2021 | India | Quantitative | General | 1638 | -- | -- | 35.5 |
Aguilar et al. [30] | 2021 | Brazil | Quantitative | Parents | 985 | 66.5 | 22.1 | -- |
Cohrs et al. [31] | 2022 | USA | Quantitative | General | 189 | -- | -- | -- |
Nasimiyu et al. [32] | 2022 | Kenya | Quantitative | General | 856 | 71.1 | 28.3 | -- |
Doherty et al. [33] | 2021 | USA | Quantitative | General | 948 | 31.1 | 68.9 | -- |
Patwary et al. [34] | 2022 | Bangladesh | Quantitative | General | 400 | 82 | 18 | -- |
Crozier et al. [35] | 2022 | USA | Quantitative | General | 3721 | 38.7 | 24.1 | -- |
Tamysetty et al. [36] | 2021 | India | Mixed-method | General | 296 | -- | -- | -- |
Qasim et al. [37] | 2022 | Pakistan | Qualitative | General | 46 | -- | -- | -- |
Bhartiya et al. [38] | 2021 | India | Quantitative | General | 1342 | 79 | 2 | -- |
Kazmi et al. [39] | 2022 | Pakistan | Quantitative | General | 1760 | 67 | 33 | 22 |
Coman et al. [40] | 2022 | USA | Quantitative | General | 795 | 20.6 | 79.4 | 20.6 |
Kawuki et al. [41] | 2023 | Uganda | Quantitative | General | 1025 | -- | -- | 43.8 |
Abedin et al. [42] | 2021 | Bangladesh | Quantitative | General | 253 | 58.1 | 17 | -- |
Nabirye et al. [43] | 2021 | Uganda | Quantitative | General | 367 | 58.3 | 41.7 | -- |
Mamun et al. [44] | 2021 | Bangladesh | Quantitative | General | 434 | -- | -- | -- |
Wang et al. [45] | 2021 | USA | Quantitative | General | 293 | 40 | 60 | 30 |
Garcini et al. [46] | 2022 | USA | Mixed-method | Healthcare workers | 64 | 70.7 | 8.6 | -- |
Campagnoli et al. [47] | 2022 | USA | Cross-sectional | Hospital patients | 97 | 57.8 | 27 | -- |
Robinson et al. [48] | 2022 | USA | Qualitative | General | 34 | -- | -- | -- |
2021: 9 2022: 14 2023: 1 | USA: 9 Bangladesh: 5 India: 4 Brazil: 2 Uganda: 2 Pakistan: 1 Kenya: 1 | Quantitative: 19 Qualitative: 3 Mixed methods: 2 | General: 21 Healthcare workers: 1 Hospital patients: 1 | N = 30,323 x = 1263.5 SD = 2610.3 |
Moderator | Number of Studies | Proportion of Outcome (95% CI) | Heterogeneity | Moderator Effect (Meta-Regression) | ||||
---|---|---|---|---|---|---|---|---|
Univariate | Multivariate | |||||||
I2 Within | p-Value | Coefficient | p-Value | Coefficient | p-Value | |||
Acceptance studies | ||||||||
Study year | 0.03 | 0.75 | -- | -- | ||||
2021 | 6 | 0.56 (0.41–0.70) | 99% | <0.01 | ||||
2022 | 10 | 0.59 (0.47–0.71) | 99% | <0.01 | ||||
2023 | -- | -- | -- | -- | ||||
Region | 0.08 | 0.01 | 0.09 | 0.29 | ||||
Africa | 2 | 0.65 (0.52–0.76) | 95% | <0.01 | ||||
Americas | 8 | 0.47 (0.34–0.60) | 99% | <0.01 | ||||
Asia | 6 | 0.70 (0.61–0.77) | 96% | <0.01 | ||||
Slum population | 0.09 | <0.01 | 0.12 | 0.03 | ||||
General | 13 | 0.56 (0.45–0.67) | 99% | <0.01 | ||||
Non-general | 3 | 0.65 (0.59–0.70) | 45% | 0.16 | ||||
Sample size | 0.04 | 0.59 | -- | -- | ||||
Below 1000 | 11 | 0.56 (0.44–0.68) | 99% | <0.01 | ||||
Above 1000 | 5 | 0.61 (0.47–0.74) | 100% | <0.01 | ||||
Hesitancy studies | ||||||||
Study year | −0.03 | 0.84 | -- | -- | ||||
2021 | 6 | 0.27 (0.09- 0.59) | 99% | <0.01 | ||||
2022 | 10 | 0.31 (0.19–0.44) | 99% | <0.01 | ||||
2023 | -- | -- | -- | -- | ||||
Region | −0.11 | 0.01 | −0.13 | 0.13 | ||||
Africa | 2 | 0.35 (0.23–0.49) | 95% | <0.01 | ||||
Americas | 8 | 0.40 (0.23–0.61) | 99% | <0.01 | ||||
Asia | 6 | 0.17 (0.07–0.34) | 99% | <0.01 | ||||
Slum population | −0.17 | 0.01 | −0.21 | 0.17 | ||||
General | 13 | 0.32 (0.19–0.49) | 99% | <0.01 | ||||
Non-general | 3 | 0.19 (0.11–0.32) | 73% | 0.02 | ||||
Sample size | −0.13 | 0.22 | -- | -- | ||||
Below 1000 | 11 | 0.35 (0.22–0.51) | 99% | <0.01 | ||||
Above 1000 | 5 | 0.19 (0.06–0.44) | 100% | <0.01 | ||||
Uptake studies | ||||||||
Study year | 0.02 | <0.01 | −0.06 | 0.04 | ||||
2021 | 2 | 0.33 (0.28–0.39) | 70% | 0.07 | ||||
2022 | 3 | 0.14 (0.05–0.31) | 95% | <0.01 | ||||
2023 | 1 | 0.44 (0.41–0.47) | -- | -- | ||||
Region | ||||||||
Africa | 1 | 0.44 (0.41–0.47) | -- | -- | −0.10 | <0.01 | −0.13 | 0.31 |
Americas | 2 | 0.25 (0.17–0.35) | 90% | <0.01 | ||||
Asia | 3 | 0.17 (0.05–0.44) | 99% | <0.01 | ||||
Slum population | -- | -- | -- | -- | ||||
General | 6 | 0.23 (0.13–0.39) | 98% | <0.01 | ||||
Non-general | 0 | -- | -- | -- | ||||
Sample size | 0.15 | 0.15 | -- | -- | ||||
Below 1000 | 3 | 0.16 (0.05–0.38) | 96% | <0.01 | ||||
Above 1000 | 3 | 0.33 (0.22–0.47) | 99% | <0.01 |
Author | Country | Associates Factors | Qualitative Reasons for Hesitancy |
---|---|---|---|
Lennon et al., 2022 [25] | USA | Acceptance: Gender; female (−) Ethnicity; non-white (−), residence; rural (−) Education; college and post-graduate (+) | N/A |
Kusuma et al., 2022 [27] | India (Delhi) | Hesitancy: Older age (+), low perceived susceptibility and severity of COVID-19 (+), low self-efficacy to protect against COVID-19 (+), awareness and use of Aarogya Setu App (−) | A belief that they had immunity; COVID-19 was a hoax; the vaccine was not necessary; did not want to disturb the natural bodily systems by the vaccine. |
Hasan et al., 2022 [28] | Bangladesh | Acceptance: Older age (+), Adequate knowledge of COVID-19 (+), comorbid patients in the households (+), religious misconceptions (−), doubt on safety of the vaccine (−) | N/A |
Sunil et al., 2021 [29] | India (Bengaluru) | Uptake: Young age (+), gender; males (+), religion; Christians (+), Education; graduates (+), Occupation: clerical and skilled workers (+), SES; upper middle (+). | Mild or serious adverse effects were more reported among women than men across all age groups. |
Aguilar et al. 2021 [30] | Brazil | Hesitancy: Younger age (+), low perceived benefit vaccination (+) Parental acceptance: acceptance among parents themselves (+) | Concerns about vaccine efficacy, potential side effects, low incidence of COVID-19 cases and low perceived susceptibility |
Cohrs et al., 2022 [31] | USA | N/A | Adverse effects and cost of COVID-19 vaccine |
Nasimiyu et al., 2022 [32] | Kenya (Kibera and Asembo) | Acceptance: Education; post-secondary (−) | Safety concerns, insufficient information to decide, low-risk perception and lack of belief in vaccine |
Doherty et al., 2021 [33] | USA (North Carolina) | Hesitancy: Gender; female (+), Ethnicity; Black (+), calendar month (+), safety concerns and government distrust (+) | Safety and efficacy concerns and government mistrust |
Patwary et al., 2022 [34] | Bangladesh | Acceptance: being confident (+), complacent (+), calculative (+), and responsible (+) Anti-vaccine attitudes (−), Information sources; newspaper (+) | N/A |
Crozier et al., 2022 [35] | USA (Alabama) | Acceptance: Gender; male (+), ethnicity; non-Hispanic (+), older age (+), residence; urban (+) | N/A |
Tamysetty et al., 2021 [36] | India (Mumbai, Bengaluru, Kolkata and Delhi) | N/A | Possible side effects, the uncertainty of getting the vaccine, safety concerns, long distance to vaccination centre, and inability to spare a day from work |
Qasim et al., 2022 [37] | Pakistan (Karachi) | Acceptance: Knowledge and awareness of vaccine (+), trusted sources of information (+), good health literacy (+), Occupation; healthcare (+) Negative personal beliefs (−), vaccine mistrust (−), negative public perceptions (−) | N/A |
Bhartiya et al., 2021 [38] | India (Mumbai) | Acceptance: Older age (+), gender; male (+), Education; post-graduate (−), and occupation; blue collar (+) | N/A |
Kazmi et al., 2022 [39] | Pakistan (Islamabad and Rawalpindi) | Uptake and acceptance: Higher education (+), being employed (+), prior infection in the family (+), family vaccination (+), knowing of and living close to a vaccination centre (+) and being worried about COVID-19 (+) | N/A |
Kawuki et al., 2023 [41] | Uganda | Uptake: Older age (+) and Ethnicity/Tribe; Batooro (+), Knowledge level (+), perceived benefits (+) and cues to action (+). Depressive symptoms (−), perceived barriers; serious side effects and long distances (−), Unemployment (−), Religion; Moslem (+) and Tribe; Basoga (−) | N/A |
Abedin et al., 2021 [42] | Bangladesh | Hesitancy: Older age (+), low education (+), Occupation; day-laborers (+), having chronic diseases (+), low confidence in the country’s healthcare system (+), residence: slum (+) | N/A |
Wang et al., 2021 [45] | USA (Delaware) | Acceptance: Ethnicity; Black (−), COVID test history (+) | N/A |
Garcini et al., 2022 [46] | USA (South Texas) | N/A | Mistrust of manufacturers and administrators, concerns about vaccine safety, fear of discrimination/stigmatisation, fear of exploitation/ manipulation by the government or health authorities, and having personal information mishandled. Being undocumented, fear-inducing myths and beliefs, limited information and logistics of vaccination access |
Campagnoli et al., 2022 [47] | USA (Chicago) | Acceptance: older age (+), Ethnicity; white (−), big household size (+), and trust in healthcare workers (+) | Missed opportunity (not having access to a doctor or not seen a doctor lately), fear of short- and long-term side effects, not enough research on the COVID-19 vaccines, concerns about vaccine effectiveness, and government mistrust |
Robinson et al., 2022 [48] | USA (Alaska and Idaho) | Uptake: Vaccine confidence (+), high perceived susceptibility (+), severity (+), and benefits (+), convenient access (+), availability (+) and cues to action; SMS (+) | N/A |
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Kawuki, J.; Chen, S.; Fang, Y.; Liang, X.; Chan, P.S.-f.; Wang, Z. COVID-19 Vaccine Acceptance, Attitude and Perception among Slum and Underserved Communities: A Systematic Review and Meta-Analysis. Vaccines 2023, 11, 886. https://doi.org/10.3390/vaccines11050886
Kawuki J, Chen S, Fang Y, Liang X, Chan PS-f, Wang Z. COVID-19 Vaccine Acceptance, Attitude and Perception among Slum and Underserved Communities: A Systematic Review and Meta-Analysis. Vaccines. 2023; 11(5):886. https://doi.org/10.3390/vaccines11050886
Chicago/Turabian StyleKawuki, Joseph, Siyu Chen, Yuan Fang, Xue Liang, Paul Shing-fong Chan, and Zixin Wang. 2023. "COVID-19 Vaccine Acceptance, Attitude and Perception among Slum and Underserved Communities: A Systematic Review and Meta-Analysis" Vaccines 11, no. 5: 886. https://doi.org/10.3390/vaccines11050886
APA StyleKawuki, J., Chen, S., Fang, Y., Liang, X., Chan, P. S. -f., & Wang, Z. (2023). COVID-19 Vaccine Acceptance, Attitude and Perception among Slum and Underserved Communities: A Systematic Review and Meta-Analysis. Vaccines, 11(5), 886. https://doi.org/10.3390/vaccines11050886