Submitted:
22 November 2024
Posted:
27 November 2024
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Preprints on COVID-19 and SARS-CoV-2
Abstract
COVID-19 remains a global health emergency, causing thousands of illnesses. This study investigated peoples’ knowledge of COVID-19 in Africa. It highlighted factors impacting acceptance of preventive and vaccination measures. This cross-sectional survey was conducted in Nigeria, and South Africa, from September 2023 to December 2023. It included 1000 participants via convenience sampling. Participants completed the validated survey online or in person. Data was analyzed using t-test, analysis of variance, regression analysis, Pearson Chi-square test, and Fisher's exact test. Most participants (96%) identified COVID-19 as a virus and were aware of its transmission modes. About 60% reported using facemasks and hand hygiene as preventative measures. Education, employment status, and living arrangements significantly influenced knowledge of COVID-19. Despite 88% of participants being aware of vaccines, 21% had received the first vaccine dose, and 81.7% had negative attitudes towards vaccinations. False information was the leading hindrance, especially in younger and less-educated individuals, who believed that the vaccine caused death (26%) or caused COVID-19 itself (17%). Therefore, future interventions should address misconceptions about vaccines and widen access to preventative measures. Further research should examine behavioral interventions to improve compliance with infection control measures.
Keywords:
Africa
; Behavior
; COVID-19
; Infection prevention
; Medical sociology
; Vaccine
Introduction
COVID-19 is an infectious disease caused by the SARS-CoV-2 virus. Most infected people experience mild to moderate respiratory illness and recover without special treatment. However, some people become seriously ill or die [1]. COVID-19 was declared a pandemic by the World Health Organization (WHO) in March 2020 [2,3]. COVID-19 has overwhelmed the health systems of many countries, caused significant deaths, and caused enormous economic losses. To date, COVID-19 has infected millions of people and caused millions of deaths worldwide [3]. Efforts have been made to mitigate the devastating effects of this unprecedented global health crisis. The WHO recommends disease control measures such as personal protective equipment, hand hygiene, physical distancing, and vaccination [3,4,5]. The WHO recommends vaccination to prevent severe disease and reduce the likelihood of new variants emerging [5,6]. However, compliance with vaccination recommendations poses significant challenges in controlling the spread of the disease.
COVID-19 vaccine acceptance rates differ globally, with the highest rates in Ecuador (97%), Malaysia (94%), and Indonesia (93%), and the lowest in Lebanon (21%) [6]. COVID-19 vaccine hesitancy is widespread and influenced by various factors such as perceived infection risk, vaccine safety, vaccine efficacy, doctors' recommendations, and inoculation history [7]. Predictors of COVID-19 vaccine hesitancy include lower perceived risk of infection, institutional mistrust, lack of influenza vaccination, lower perceived severity of COVID-19, beliefs that vaccination will cause side effects, or beliefs that vaccines are unsafe [8].
African studies have demonstrated variability in knowledge and attitudes towards COVID-19 transmission and control. Additionally, studies have shown gaps between knowledge and practice of preventive guidelines and vaccine acceptance [9,10]. Studies in sub-Saharan African countries showed vaccine hesitancy was significantly associated with participant’s gender, educational level, occupational status, attitude towards COVID-19 preventive measures, and primary information source being social media [11,12].
COVID-19 remains a global health emergency, causing thousands of illnesses and deaths [13]. The current study aims to analyze public knowledge and beliefs about COVID-19 disease, compliance with control measures, and vaccination in Africa. A pilot study was completed in 2021 to validate the questionnaire for collecting data in the final survey conducted in 2023. The study's objective is to analyze the public's knowledge of COVID-19 disease, factors influencing the practice of preventive measures, and vaccine acceptance towards making recommendations for better policies. The study is part of regional efforts to improve public health in the countries where the studies were conducted.
Materials and Methods
Study Design
This is a cross-sectional survey of the general population in the selected African cities of Port Harcourt, Nigeria, and Port Elizabeth, South Africa. It included people from all walks of life, ages, literacy levels, and professions. Participants were selected by convenience sampling. Those who refused to participate were excluded from the study. The South African Eastern Cape Department of Health approved the survey. One thousand participants were recruited via convenience sampling.
Data Collection
The study was conducted from September to December 2023. The study was questionnaire-based. The questionnaire was validated in a pilot study in 2021. Adjustments were made based on the preliminary data to ascertain that the responses reflected the questions asked and that the questions reflected the study’s objectives. The validated questionnaire was administered partly online and partly in person in 2023. Data collectors administered the questionnaire in person to people in public places. The online questionnaire was disseminated via the research collaborators’ social media accounts, including WhatsApp Messenger, Facebook, and LinkedIn.
Questions included sociodemographic data, knowledge of COVID-19 transmission, control, and remedies. Questions were designed in a multiple-choice format where participants were instructed to choose one or more options. For questions with only one answer choice, the correct answer was allotted one point. Each correct answer is given one point for questions with possible multiple correct answers. No point was given for incorrect responses. The total score was 22 points. A score of less than 11 (50%) was graded as poor, and a score greater than 50% was graded as good.
Knowledge about the COVID-19 vaccine was assessed, including vaccine type, preference, vaccination status, safety, efficacy, benefits, adverse effects, and vaccine ingredients. Questions on vaccine safety, effects, ingredients, and adequacy of vaccine testing were formulated in a Yes, No, and Not Sure format, instructing participants to choose only one option. Questions were graded and given 1 point for each correct answer. A total score of < 50% was graded as poor, and a total score of >50% was graded as good.
Data Analysis
Data was analyzed using IBM® SPSS® Statistics 28 (IBM Corp, Armonk, NY) through Student's t-test, analysis of variance, regression analysis, Pearson Chi-square test, and Fisher's exact test. Continuous variables such as age, knowledge score, and attitude score were converted into appropriate categories and analyzed using proper methods. Multivariate analysis was conducted using logistic regression for knowledge about COVID-19 and attitudes toward vaccines to determine predictors. A P-value <0.05 was considered significant. Quantitative and qualitative data are presented in tables, including numbers, categories, and percentages. The data were compared, analyzed, and interpreted appropriately.
Ethical Consideration
The study aims were explained to the participants. No coercion was used in the recruitment process. Participants were informed about the rationale and purpose of the research and signed an informed consent form before participating in the study.
Results
Table 1 provides an overview of the demographics of the study population. The largest age group in the study (68%) was early adult (20-49 years). Females make up the majority of the study population (57%). Most of the study population have completed either secondary education (31%) or a college/university degree (50%). People living with their spouse or small family comprise 47% of the population, while 30% live alone. More than half of the population (52%) are unemployed; the remainder are employed full-time or part-time. Students comprise 31% of the population, and office work is the second most common occupation, constituting 19%.
In Table 2, an overview of the knowledge of the study population regarding COVID-19 is provided. Most of the population (96%) correctly identified that a virus causes it, and 94% recognized cough as the primary transmission mode. Of those who suggested a treatment, 42% mentioned vaccination, while 35% stated no cure. Most people believed COVID-19 could affect any country (86%) and anyone (87%). The most commonly listed preventive measures were facemask use (72%) and practicing good hand hygiene (61%).
Table 3 presents the knowledge of the study population concerning COVID-19 vaccines. According to the data, AstraZeneca is the most recognized vaccine with a recognition rate of 75%, while Pfizer ranks second with a recognition rate of 20%. Approximately 12% of the study population is not aware of any vaccine. Additionally, 21% of respondents have received the first dose of the COVID-19 vaccine, while only 4.4% have received the second dose. According to the study, 45% of people who are aware of the available vaccines prefer AstraZeneca, with 96% citing efficacy as the primary reason. Most of the population (56%) believe the vaccine is safe, while 41% believe it has minor side effects. Additionally, 63% of respondents reported that older adults would benefit from the vaccine, and 59% thought it is suitable for hospital workers.
Table 4 summarizes the association between the level of knowledge about COVID-19 and sociodemographic parameters. The study reveals a significant association between knowledge about COVID-19 and participants' education level, living status, job status, and job type. The majority of participants with secondary and college/university education demonstrated good knowledge, while the majority of participants with vocational/technical education were reported to have poor knowledge. About 63% of individuals living with a spouse or a small family had good knowledge. Full-time employment was associated with a higher level of knowledge about COVID-19. Among the participants, most business owners/executives, essential workers not in healthcare, and labor workers had good knowledge. In contrast, 61% of healthcare workers were found to have poor knowledge about the cause and disease control variables of COVID-19.
Table 5 depicts the logistic regression analysis of factors associated with poor knowledge of COVID-19. Among the list of sociodemographic parameters, vocational/technical education, unemployment, and being a healthcare worker were significantly associated with inadequate knowledge.
Table 6 shows the association between sociodemographic characteristics and attitudes toward the COVID-19 vaccine. The study showed a significant association between attitudes toward the COVID-19 vaccine and participants' age, education level, living situation, and employment status. Gender and job type were not found to have a significant association. At least 90% of participants aged 13-19 years, participants with vocational/technical education, and those who live in a congregation were found to have poor attitudes towards the vaccine.
Table 7 depicts the logistic regression analysis, including factors associated with attitude level. It presents adjusted OR and p-values for each modality of categorical variables. Unemployment since COVID and before COVID is significantly related to poor attitude (OR=2.89 and OR=2.04, respectively); meaning it is a risk factor for poor attitude. Age above 20 years was protective against poor attitude (OR < 1, p < 0.05). Additionally, living alone or in a small family was protective against poor attitude. Modalities without OR and p-values are reference modalities considered in the analysis.
Discussion
Based on our study, many participants showed a good understanding of the COVID-19 disease. A high percentage (96%) correctly identified the causative organism as a virus, and most also recognized physical contact and respiratory droplets as the primary modes of transmission. A significant portion of the population (42%) identified vaccines as the most effective form of management. The well-informed nature of our study population may be attributed to the online data collection which skewed towards individuals with more digital literacy and perhaps more aware of public health issues. The practical information campaigns conducted by the relevant authorities may also be a contributing factor. This finding aligns with studies conducted in other African countries, which also demonstrated a high level of COVID-19 knowledge among respondents [10,12].
Over 60% of the participants mentioned wearing a mask and practicing hand hygiene as preventive measures, while approximately 56% listed maintaining physical distance. Similar studies in other African countries also showed that awareness of preventive measures is high but compliance with these measures remains below optimal levels. Reasons for poor compliance include negative attitudes, lack of personal protective equipment, and limited access to potable water [10,14]. Many respondents expressed that COVID-19 is a significant public health issue in their country and can potentially affect anyone. Approximately 68% of the participants stated that their governments must improve COVID-19 control and management.
The current study revealed a strong link between COVID-19 knowledge and participants' education level, living arrangement, employment status, and job type. Specifically, vocational/technical education, unemployment, and being a healthcare worker were significantly associated with poor knowledge. People with secondary and college education generally displayed good knowledge about COVID-19, while those with vocational and technical education showed poor knowledge. Some studies in Tanzania, Ethiopia, and Uganda also found that higher education is associated with a better understanding of COVID-19 [11,15]. Additionally, a study in Nigeria found tertiary education is associated with a positive attitude [16].
The current study showed that most people living with a spouse or in a small family had good knowledge about COVID-19, a finding also supported by studies in Nigeria and Ethiopia where marital status was linked to good knowledge [16,17]. Our study also revealed that participants' job status and type were associated with their COVID-19 knowledge. Full-time employment was linked to higher levels of expertise, and 70% of business owners or executives exhibited good knowledge. In contrast, most healthcare workers (61%) were found to have poor knowledge. This is a unique and unexpected finding that contradicts studies conducted among healthcare workers in different African countries [11,15]. The discrepancy could be due to the undefined job description and education level of the healthcare workers in the study in contrast to participants in the comparative analyses.
Most of our study participants (88%) know about the COVID-19 vaccine. AstraZeneca is the most recognized and preferred vaccine among the participants. The increased availability of the AstraZeneca vaccine in Africa compared to other brands may be the reason. Most patients with a vaccine preference (96%) cited efficacy as the primary reason for their choice. Most participants believed the vaccine was suitable for older adults and healthcare workers. Approximately 56% of participants thought the vaccine was safe, and 40% felt it was tested well. Despite this finding, only 21% and 4.4% of the participants received the first and second doses of the COVID-19 vaccine, respectively. These findings show a discrepancy between participants’ knowledge about the vaccine and their decision to get vaccinated. This may be due to negative attitudes towards the vaccine or lack of vaccine availability.
Our study also showed that a majority (81.7%) of study participants, regardless of other socioeconomic characteristics, were found to have poor attitudes toward the vaccine. This finding demonstrates that participants' attitudes might significantly influence their decision to take the vaccine. Approximately 26% of participants reported that they believe that vaccines cause death, and 17% believed that vaccines cause COVID-19, which might have contributed to the negative attitude towards vaccines. This finding implies that there are more factors, in addition to concerns about vaccine safety and efficacy, that influenced participants' attitudes about the COVID-19 vaccine, since the majority of the study participants believed it was safe and 99.8% had a vaccine preference, citing efficacy as their reason for choice. This finding contrasts with other studies on vaccine acceptance in different African countries, which showed a lack of information about the vaccine and uncertainty about the efficacy and safety of the vaccine as the main reasons for vaccine hesitancy [17,19].
The current research revealed a strong association between people's attitudes toward the COVID-19 vaccine and their age, level of education, living situation, and employment status. A significant majority (96%) of individuals aged 13-19 years expressed negative attitudes toward the vaccine. Similar negative attitudes were observed among young participants in other studies examining COVID-19 vaccine perspectives and uptake [20,21].
A study conducted in Zambia stated that participants received information about the vaccine from social media [22]. Young participants believed they were not at risk of COVID-19, with misinformation from social media being identified as a possible factor [22]. Another study in Mozambique focusing on vaccine acceptance noted a strong correlation between institutional trust and vaccine acceptance [12]. The negative impact of social media on young people’s attitude towards the vaccine and its adverse effects on recommendations put out by the government might play a significant role in vaccine acceptance among this age group.
The current study showed that people with primary, vocational, or technical education also reported negative attitudes towards the vaccine. This aligns with other studies that showed individuals with secondary education or higher were more likely to accept the COVID-19 vaccine [23]. Furthermore, 96% of participants living in congregational settings demonstrated negative attitudes toward the vaccine. At the same time, at least 85% of individuals working part-time or unemployed were reported to have poor attitudes. Before and after COVID-19, unemployment was significantly associated with increased negative attitudes, as seen in a study on COVID-19 vaccine acceptance among sub-Saharan Africans, which indicated that unemployment was linked to a higher risk of vaccine resistance [24]. This might result from institutional grievances and mistrust affecting participants’ attitudes towards vaccine recommendations put out by their government.
Limitation
This study explored various sociodemographic factors, permitting a detailed analysis of knowledge and attitudes amongst a large and varied sample of ages, educational backgrounds, and occupational statuses. Online and in-person data collection maximized the inclusivity of the sample, enabling the gathering of diverse perspectives within the selected countries. However, convenience sampling may limit the representativeness of the data, with online data collection increasing the possibility of response bias, where individuals with greater digital competence are overrepresented, skewing results towards those who are more informed about public health campaigns.
Conclusions
Most of the population had a good understanding of COVID-19, with education, occupation, and living arrangements greatly influencing knowledge. Despite awareness of preventative measures, compliance was low due to negative attitudes and limited availability of preventative resources such as facemasks. Most of the population deemed the vaccine safe. However, a minority had concerns regarding the vaccine, including misunderstandings that the vaccine could cause COVID-19 itself.
Efforts should be made to correct misconceptions by providing accessible information about vaccine safety, particularly in communities with poor knowledge. The media and health authorities in the respective countries should work to address the institutional mistrust of health care systems which negatively affects peoples’ attitude towards public health measures recommended by the authorities. Another focus should be widening access to preventative resources. Further research should explore behavioral interventions that can increase compliance with these resources and explore other socioeconomic factors, such as job security, to create targeted policies.
Author Contributions
All the authors testify that all persons designated as authors qualify for authorship and have checked the article for plagiarism. If plagiarism is detected, all authors will be held equally responsible and bear the resulting sanctions imposed by the journal afterward. All authors contributed to the conceptualization, methodology, validation, formal analysis, investigation, data curation, writing of original draft preparation, writing of review and editing, and visualization. The corresponding author, provided supervision, project administration, and funding. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
This clinical study was approved by the South African Eastern Cape Department of Health, which confirmed that it is a quality assurance study and does not require a formal review by the research ethics board.
Informed Consent Statement
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement
The dataset presented in the study is available on request from the corresponding author during submission or after publication.
Acknowledgments
None.
Conflicts of Interest
The authors declare no conflicts of interest.
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Table 1.
Characteristics of the study population.
| Variables | Number | % |
|---|---|---|
| Age Group | ||
| 13-19, Youth | 175 | 18 |
| 20-49, Early adult | 678 | 68 |
| 50-64, Middle-aged adult | 110 | 11 |
| 65-99, Older adult | 37 | 3.7 |
| Gender | ||
| Female | 568 | 57 |
| Male | 432 | 43 |
| Education Status | ||
| Primary school | 92 | 9.2 |
| Secondary school | 312 | 31 |
| College/University | 505 | 50 |
| Vocational/Technical | 91 | 9.1 |
| Living Status | ||
| Congregation | 224 | 22 |
| Single/Alone | 304 | 30 |
| Spouse or Small family | 472 | 47 |
| Job Status | ||
| Full-time work | 316 | 32 |
| Part-time work | 168 | 17 |
| Unemployed because or since COVID | 180 | 18 |
| Unemployed before COVID | 336 | 34 |
| Job Type | ||
| Business owner or executive | 106 | 11 |
| Essential worker, not healthcare | 78 | 7.8 |
| Healthcare worker | 116 | 12 |
| Labour worker | 121 | 12 |
| Market or store worker | 83 | 8.3 |
Table 2.
Knowledge of the population about COVID-19 disease transmission and control.
| Characteristics | Number | % |
|---|---|---|
| Cause of COVID-19 | ||
| Bacteria | 39 | 3.9 |
| Virus | 961 | 96 |
| Route of transmission | ||
| Insects | 32 | 3.2 |
| Cough, sneeze | 939 | 94 |
| Household items | 273 | 27 |
| Close physical contact | 499 | 50 |
| Curse, bad luck | 12 | 1.2 |
| Treatment cure | ||
| Herbalist or spiritual cure | 42 | 4.2 |
| Antibiotic | 117 | 12 |
| Vaccine cure | 418 | 42 |
| Home remedy or mixture | 108 | 11 |
| Dexamethasone | 36 | 3.6 |
| No Cure | 352 | 35 |
| COVID is a problem | ||
| Covid is a problem | 811 | 81 |
| Covid is not a problem | 119 | 19 |
| Population affected | ||
| Affect poor people | 98 | 9.8 |
| Affect rich people | 89 | 8.9 |
| Affect rural people | 72 | 7.2 |
| Affect city people | 61 | 6.1 |
| Affect anyone | 869 | 87 |
| Preventive measures | ||
| Facemask | 716 | 72 |
| Hand hygiene | 614 | 61 |
| Physical distance | 565 | 56 |
| Vaccine | 531 | 53 |
| Medicine or Herb | 68 | 6.8 |
| No prevention | 60 | 6.0 |
| Responsibility for control | ||
| Government control | 678 | 68 |
| Private sector | 319 | 32 |
| Religious group | 325 | 32 |
| WHO control | 518 | 52 |
| Other charities or donors | 191 | 19 |
Table 3.
Knowledge of the COVID-19 vaccine types.
| Characteristics | Number | % |
|---|---|---|
| Awareness about the type of vaccines | ||
| AstraZeneca | 748 | 75 |
| Pfizer-Biontech | 200 | 20 |
| Sinovac | 107 | 11 |
| Covishield | 112 | 11 |
| Sputnik-Gamaleya | 143 | 14 |
| Moderna | 90 | 9.0 |
| Sinopharm | 46 | 4.6 |
| Janssen-Johnson | 250 | 25 |
| No vaccine awareness | 124 | 12 |
| Vaccine doses received | ||
| Vaccine 1st dose received | 213 | 21 |
| Vaccine 2nd dose received | 44 | 4.4 |
| Vaccine preferred | ||
| AstraZeneca | 450 | 45 |
| Covishield | 89 | 8.9 |
| Janssen-Johnson | 275 | 28 |
| Moderna | 115 | 12 |
| Pfizer-Biontech | 71 | 7.1 |
| Reasons of preference | ||
| Safety | 404 | 40 |
| Efficacy | 956 | 96 |
| Recommended by doctor | 107 | 11 |
| Readily available | 195 | 19.5 |
| No choice | 226 | 23 |
| Recommend by government or employer | 241 | 24 |
| Characteristics of vaccines | ||
| Vaccine safe | 557 | 56 |
| Vaccine secret ingredient | 148 | 15 |
| Vaccine tested well | 397 | 40 |
| Vaccine cause Covid | 166 | 17 |
| Vaccine minor effect | 408 | 41 |
| Vaccine death | 262 | 26 |
| Vaccines beneficial for the population | ||
| Vaccines good for old people | 631 | 63 |
| Good for young people | 358 | 36 |
| Good for healthcare worker | 592 | 59 |
| Good for chronic disease | 440 | 44 |
| Good for international travelers | 425 | 42 |
| Good for rich | 266 | 27 |
Table 4.
Association between sociodemographic factors and knowledge level COVID-19 disease.
| Characteristics | Poor knowledge | Good knowledge | p-value | ||
|---|---|---|---|---|---|
| Number N = 430 |
% | Number N = 570 |
% | ||
| Age group | 0.3 | ||||
| 13-19, Youth | 78 | 45 | 97 | 55 | |
| 20-49, Early adult | 297 | 44 | 381 | 56 | |
| 50-64, Middle-aged | 38 | 35 | 72 | 65 | |
| 65-99, Older adult | 17 | 46 | 20 | 54 | |
| Gender | 0.7 | ||||
| Female | 247 | 43 | 321 | 57 | |
| Male | 183 | 42 | 249 | 58 | |
| Education Status | 0.001 | ||||
| Primary school | 41 | 45 | 51 | 55 | |
| Secondary school | 126 | 40 | 186 | 60 | |
| College/University | 206 | 41 | 299 | 59 | |
| Vocational/Technical | 57 | 63 | 34 | 37 | |
| Living Status | 0.001 | ||||
| Congregation | 112 | 50 | 112 | 50 | |
| Single/alone | 143 | 47 | 161 | 53 | |
| Spouse/small family | 175 | 37 | 297 | 63 | |
| Job Status | 0.002 | ||||
| Full-time work | 114 | 36 | 202 | 64 | |
| Part-time work | 69 | 41 | 99 | 59 | |
| Unemployed because or since COVID | 76 | 42 | 104 | 58 | |
| Unemployed before COVID | 171 | 51 | 165 | 49 | |
| Job Type | <0.001 | ||||
| Business owner or executive | 32 | 30 | 74 | 70 | |
| Essential worker, not healthcare | 28 | 36 | 50 | 64 | |
| Healthcare worker | 71 | 61 | 45 | 39 | |
| Labour work | 47 | 39 | 74 | 61 | |
| Market or store worker | 35 | 42.2 | 48 | 57.8 | |
| Office worker | 78 | 42 | 108 | 58 | |
| Student | 139 | 45 | 171 | 55 | |
Table 5.
Logistic regression of factors associated with poor knowledge about COVID-19 disease.
| Characteristic | OR1 | 95% CI1 | p-value |
|---|---|---|---|
| Education Status | |||
| Primary | — | — | |
| Secondary | 0.80 | 0.49 - 1.32 | 0.4 |
| College/University | 0.65 | 0.39 - 1.08 | 0.093 |
| Vocational/Technical | 2.20 | 1.16 - 4.23 | 0.017 |
| Living Status | |||
| Congregation | — | — | |
| Single/alone | 1.22 | 0.84 - 1.77 | 0.3 |
| Spouse/small family | 0.83 | 0.58 - 1.18 | 0.3 |
| Job Status | |||
| Full-time work | — | — | |
| Part-time work | 1.57 | 0.99 - 2.49 | 0.057 |
| Unemployed because or since COVID | 2.03 | 1.30 - 3.19 | 0.002 |
| Unemployed before COVID | 3.37 | 2.17 - 5.29 | <0.001 |
| Job Type | |||
| Business owner or Executive | — | — | |
| Essential worker, not healthcare | 1.22 | 0.61 - 2.43 | 0.6 |
| Healthcare worker | 6.08 | 3.20 - 11.8 | <0.001 |
| Labour work | 1.02 | 0.57 - 1.85 | >0.9 |
| Market or store worker | 1.36 | 0.68 - 2.71 | 0.4 |
| Office worker | 1.56 | 0.91 - 2.71 | 0.11 |
| Student | 0.98 | 0.57 - 1.70 | >0.9 |
1 OR = Odds Ratio, CI = Confidence Interval.
Table 6.
Association between sociodemographic factors and attitude toward COVID-19 vaccine.
| Characteristic | Poor Attitude | Good attitude | p-value | ||
|---|---|---|---|---|---|
| N = 817 | % | N = 183 | % | ||
| Age Group | <0.001 | ||||
| 13-19, Youth | 164 | 94 | 11 | 6.3 | |
| 20-49, Early adult | 546 | 81 | 132 | 19 | |
| 50-64, Middle-aged | 82 | 75 | 28 | 25 | |
| 65-99, Older adult | 25 | 68 | 12 | 32 | |
| Gender | 0.3 | ||||
| Female | 471 | 83 | 97 | 17 | |
| Male | 346 | 80 | 86 | 20 | |
| Education Status | <0.001 | ||||
| Primary | 83 | 100 | 9 | 9.9 | |
| Secondary | 259 | 83 | 53 | 17 | |
| College/University | 391 | 77 | 114 | 23 | |
| Vocational/Technical | 84 | 92 | 7 | 7.7 | |
| Living Status | <0.001 | ||||
| Congregation | 214 | 96 | 10 | 4.5 | |
| Single/alone | 253 | 83 | 51 | 17 | |
| Spouse/small family | 350 | 74 | 122 | 26 | |
| Job Status | <0.001 | ||||
| Full-time work | 224 | 71 | 92 | 29 | |
| Part-time work | 143 | 85 | 25 | 15 | |
| Unemployed because or since COVID | 159 | 88 | 21 | 12 | |
| Unemployed before COVID | 291 | 87 | 45 | 13 | |
| Job Type | 0.1 | ||||
| Business owner or executive | 85 | 80 | 21 | 20 | |
| Essential worker, not healthcare | 69 | 88 | 9 | 12 | |
| Healthcare worker | 91 | 78 | 25 | 22 | |
| Labour work | 99 | 82 | 22 | 18 | |
| Market or store worker | 63 | 75.9 | 20 | 24 | |
| Office worker | 142 | 76 | 44 | 24 | |
| Student | 268 | 86 | 42 | 14 | |
Table 7.
Logistic regression of factors associated with poor attitude toward COVID-19 disease.
| Characteristic | OR1 | 95% CI1 | p-value |
|---|---|---|---|
| Age Group | |||
| 13-19, Youth | — | — | |
| 20-49, Early adult | 0.26 | 0.12, 0.56 | <0.001 |
| 50-64, Middle-aged | 0.22 | 0.08, 0.56 | 0.002 |
| 65-99, Older adult | 0.12 | 0.04, 0.37 | <0.001 |
| Education Status | |||
| Primary school | 12,303 | 0.00, NA | >0.9 |
| Secondary school | 0.56 | 0.23, 1.23 | 0.2 |
| College/University | 0.48 | 0.20, 1.06 | 0.083 |
| Vocational/Technical | 1.23 | 0.40, 3.94 | 0.7 |
| Living Status | |||
| Congregation | — | — | |
| Single/alone | 0.36 | 0.17, 0.72 | 0.006 |
| Spouse/small family | 0.17 | 0.08, 0.33 | <0.001 |
| Job Status | |||
| Full-time work | — | — | |
| Part-time work | 1.68 | 0.96, 3.00 | 0.075 |
| Unemployed because or since COVID | 2.89 | 1.61, 5.33 | <0.001 |
| Unemployed before COVID | 2.04 | 1.18, 3.55 | 0.011 |
| Job Type | |||
| Business owner or executive | — | — | |
| Essential worker, not healthcare | 2.02 | 0.81, 5.37 | 0.14 |
| Healthcare worker | 0.92 | 0.41, 2.07 | 0.8 |
| Labour worker | 0.70 | 0.33, 1.48 | 0.4 |
| Market or store worker | 0.56 | 0.24, 1.30 | 0.2 |
| Office worker | 0.68 | 0.35, 1.31 | 0.3 |
| Student | 0.47 | 0.22, 0.99 | 0.049 |
1 OR = Odds Ratio, CI = Confidence Interval.
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