Acceptance of COVID-19 vaccine and its related determinants in Nigeria: An online survey

Abstract

BACKGROUND

Vaccine hesitancy is a major challenge in the fight against the coronavirus disease 2019 (COVID-19) pandemic. Identifying the sociodemographic factors associated with vaccine acceptance among Nigerians is crucial for improving vaccine uptake.

AIM

To assess the acceptance rate of COVID-19 vaccine and its related determinants among Nigerians.

METHODS

An online cross-sectional survey (observational study) was conducted between February 2021 and May 2021, using a questionnaire hosted on SurveyMonkey. The invitation to take part in the poll was sent out to participants through social networking platforms. A logistic regression was used to determine which sociodemographic factors were associated with vaccine acceptance constructs.

RESULTS

A total of 1800 persons responded to the survey, a larger proportion of whom were males (53.9%) and within the age group of 21-30 years (29.4%) and earned an average income of less than $500 per month (43.3%). Only 0.56% of participants had a high perceived risk of COVID-19 infection, while only 1.11% had a perceived risk of dying from COVID-19. The perception rate of the COVID-19 vaccine among participants was 51.1%, while the acceptance rate was 63.9%. There was no significant association between the COVID-19 vaccine acceptance rate and related determinants assessed, particularly age (χ² = 3.049, P = 0.550), sex (χ² = 0.102, P = 0.749), average income (χ² = 3.802, P = 0.875), and religion (χ² = 2.819, P = 0.420). Participants with chronic conditions demonstrated a higher acceptance rate compared to the general population.

CONCLUSION

Despite the positive perception observed and substantial vaccine acceptance rate among the study participants, more public health interventions are still needed to enhance vaccine acceptability in Nigeria.

Key Words: Acceptance; COVID-19; Determinants; Hesitancy; Nigerians; Online survey; Vaccine

Core Tip: This study assessed coronavirus disease 2019 vaccine acceptance among Nigerians through an online survey with 1800 respondents. Despite a substantial acceptance rate of 63.9%, sociodemographic factors (age, sex, income, and religion) did not significantly influence vaccine uptake. Positive perceptions of vaccination were common, yet financial barriers affected acceptance rates. Key findings suggest enhancing public health education, economic support, and trust-building measures to improve vaccine uptake. Notably, individuals with chronic conditions were more inclined to accept the vaccine, underscoring the need for targeted interventions to achieve broader immunization coverage and herd immunity in Nigeria.

INTRODUCTION

The coronavirus disease 2019 (COVID-19), which first surfaced in China in December 2019 and has since spread to practically every nation on the planet, has led to numerous fatalities and financial difficulties throughout the globe[1,2]. The pandemic exacerbated issues in developing nations due to fewer medical facilities, higher poverty rates, and limited access to immunizations. Inequitable vaccine distribution may lead to increased hospitalizations, deaths, and the emergence of new disease strains in these nations[3,4]. A variety of methods, including physical isolation, mobility limitations, and vaccination campaigns, have been employed to tackle the COVID-19 pandemic[5]. Vaccines are critical for avoiding and managing infectious disease epidemics, ultimately saving millions of lives[6]. However, the broader acceptance of vaccines by the public is crucial to halting the epidemic. Despite the availability of vaccination services, various factors contribute to some people's distrust of vaccines and reluctance to utilize them[7,8].

Vaccination is one of the most cost-effective methods for preventing and controlling infectious diseases. However, certain individuals and segments of the public are opposed to vaccination[9]. The volume of knowledge on why individuals reject and accept vaccines is growing. Governments worldwide have recommended preventive measures such as wearing masks, maintaining social distance, frequent hand washing, and lockdowns to limit the spread of COVID-19 and minimize fatalities[10]. However, factors such as religious bias, politics, and language barriers have been identified as obstacles to vaccine roll-out and acceptance[11-13]. According to the World Health Organization, vaccine skepticism is one of the most serious threats to global health[14]. The current COVID-19 immunization has a poor acceptance rate due to budgetary constraints and a history of COVID-19 illness. Presenting simple, comprehensible information about vaccines and strongly persuading individuals to receive them is the most effective strategy to combat vaccine aversion[15,16].

Patients are more likely to get vaccinated and are less hesitant if medical workers have a positive attitude toward vaccines[17]. The level of knowledge and attitude regarding immunization that healthcare professionals have will impact their likelihood of using it and promoting it to their patients. Since healthcare workers are on the front lines of the current epidemic, governments have prioritized immunizing them first. However, there have been increasing cases of vaccine refusal[18,19]. Policymakers, academics, and health officials need to understand how well the COVID-19 vaccine is accepted by healthcare workers and what influences their acceptance or rejection to develop effective strategies to reduce vaccination hesitancy. While more than half of the world’s population (59.5%) has received the COVID-19 vaccine, significant disparities in immunization rates persist across nations[20,21]. The Horn of Africa has the world’s lowest immunization rate, at less than 20%. Delays in vaccination may be due to perceived dangers, religious beliefs, and inadequate information and awareness[22].

MATERIALS AND METHODS

Rationale of the study

Understanding the factors influencing vaccine acceptance is essential not only for managing the COVID-19 pandemic but also for addressing future infectious diseases that require vaccination. Insights gained from studying COVID-19 vaccine acceptance can inform strategies to enhance vaccine uptake for other infectious diseases, thereby improving global health outcomes.

Hypotheses

Hypothesis 1: Sociodemographic factors such as age, sex, income, and religion are significant predictors of COVID-19 vaccine acceptance among Nigerians.

Hypothesis 2: Individuals with chronic conditions in Nigeria are more likely to accept the COVID-19 vaccine compared to those without chronic conditions.

Study design

This observational study collected data on COVID-19 vaccine acceptance and related sociodemographic factors, without manipulating any variables or providing interventions.

Setting/period: The nation-wide online web-based survey was conducted from February 1, 2021 to May 31, 2021.

Cross-sectional: The data was collected at a single point in time, providing a snapshot of the population’s attitudes and behaviors during the survey period.

Participants

Target population: The Nigerian populace.

Inclusion/exclusion criteria: Consenting respondents with access to the internet participated in the online survey.

Survey instrument: The questionnaire was hosted on SurveyMonkey, designed to gather information on vaccine acceptance, perceived risk, and sociodemographic factors. The survey was structured into several sections. The initial section provided an introduction with information about previous studies and included a page on informed consent. The subsequent sections, accessible only to those who agreed to participate, collected demographic information, participants’ attitudes toward vaccinations and social distancing, and the impact of the COVID-19 pandemic on their work lives. Questions were inspired by previous studies[15,20,23]. Each participant completed the survey after providing informed consent, which took approximately 10-15 min.

Mode of distribution: The invitation to participate was disseminated via social networking platforms, including Facebook, Twitter, and WhatsApp, targeting a potentially broad audience within the Nigerian population.

Validity of the instrument: To ensure the validity of the instrument, both face and content validity were assessed. Experts in public health and survey methodology reviewed the questionnaire to ensure it was appropriate and comprehensive for the study objectives. Demographic information was collected to identify potential sampling biases, including differences between participants and non-participants. This helped address the potential bias that might arise from the selective participation of certain demographic groups.

Variables

Independent variables: Sociodemographic factors such as age, sex, income, religion, and the presence of chronic conditions.

Dependent variable: COVID-19 vaccine acceptance, measured as the primary outcome.

Other variables: Perceived risk of infection and death from COVID-19.

Data sources and measurement

The data for this study were sourced from an online cross-sectional survey conducted between February 2021 and May 2021. The survey was hosted on SurveyMonkey, and participants were recruited through social networking platforms, which facilitated broad access across the Nigerian population.

Variables of interest and measurement

COVID-19 vaccine acceptance: Vaccine acceptance was assessed using specific questions within the survey designed to capture participant willingness to receive the COVID-19 vaccine. This was measured as a categorical variable, with participants indicating whether they were willing to accept the vaccine or not.

Sociodemographic factors: These variables (age, sex, income, and religion) were self-reported by participants through the survey. Age was captured in predefined categories (e.g., 21-30 years), sex was reported as male or female, income was categorized based on monthly earnings (e.g., less than $500 per month), and religion was also categorized (e.g., Christianity, Islam).

Chronic conditions: Participants were asked if they had any chronic health conditions, with the presence of such conditions being noted as a binary variable (yes/no).

Perceived risk of COVID-19 infection and death: Perceived risk was assessed through survey questions where participants rated their perceived likelihood of contracting COVID-19 and their perceived risk of dying from it. These perceptions were measured on a percentage scale (e.g., 0%, 1%-10%, 11%-20%, 21%-30%, etc.).

Comparability of assessment methods: All participants in the study completed the same standardized survey, ensuring that the methods of data collection and measurement were consistent across the entire sample. As the study did not involve multiple groups subjected to different assessment methods, the comparability of assessment methods was inherently maintained. This uniform approach minimized the risk of measurement bias and ensured that the data collected were comparable across all respondents.

Bias

It is important to acknowledge potential bias related to the mode of survey distribution. The survey was disseminated via social media platforms, which means that individuals without access to these platforms were not represented in the sample. This limitation may affect the generalizability of the findings. Due to the nature of social media distribution, the total number of individuals who received the survey invitation could not be determined. Therefore, the exact response rate could not be calculated. This represents a limitation of the study, as it prevents us from assessing the representativeness of the sample accurately.

Data completeness and usability

After data collection, responses were reviewed for completeness and usability. This involved checking for any missing or incomplete responses that could compromise the data quality. Only fully completed questionnaires were included in the analysis to maintain the integrity of the data. By considering these limitations and addressing potential biases, this study aimed to provide a comprehensive understanding of the acceptance of the COVID-19 vaccine and its related determinants among Nigerians.

Sample size

A total of 1800 participants completed the survey. This sample size was not predetermined prior to the survey (because the research team aimed to achieve a sample size that would be sufficiently large to provide the necessary statistical power for detecting potential associations between sociodemographic factors and COVID-19 vaccine acceptance). Rather, it was determined by the number of respondents who actually engaged with the survey during the collection period from February 2021 to May 2021. This final number of participants was influenced by factors such as the reach of the survey distribution channels and participant engagement.

Quantitative variables

In the study, quantitative variables, such as age, income, and perceived risk of COVID-19 infection and death, were initially collected in their continuous or original forms. However, for the purpose of analysis, these variables were grouped into categorical ranges to facilitate logistic regression and χ² tests.

Groupings and rationale

Age: Age was categorized into predefined groups, such as 21-30 years, 31-40 years, etc. This grouping allowed for easier interpretation of the data and comparison across different demographic groups. It also helped in managing potential variability and simplified the analysis, making it more straightforward to identify trends or associations with vaccine acceptance.

Income: Income was categorized into ranges (e.g., less than $500 per month, $500-$1000 per month, etc.) to reflect different socioeconomic strata within the population. This categorization helped in assessing whether income levels influenced vaccine acceptance and made it easier to interpret the effects of economic factors on participants’ decisions.

Perceived risk of COVID-19 infection and death: Perceived risk was categorized into percentage ranges (e.g., 0%, 1%-10%, 11%-20%, etc.). This grouping method allowed the study to assess how different levels of perceived risk correlated with vaccine acceptance. It also helped in simplifying the analysis by reducing the complexity of dealing with continuous data, making it easier to identify patterns and draw conclusions.

Statistical analysis

Quantitative data were analyzed using Statistical Package for the Social Sciences, version 25 (IBM Corp., Armonk, NY, United States), in alignment with the study’s objectives. The analysis focused on respondents’ answers to closed-ended questions with a limited set of response options, where quantitative techniques were appropriate.

Statistical methods and control for confounding: Descriptive statistics, including frequency distributions, percentages, mean scores, and standard deviations, were calculated and presented in tabular form. χ² tests were employed for bivariate analyses to explore the associations between sociodemographic factors and vaccine acceptance. To control for potential confounding variables, logistic regression analysis was conducted, allowing for the adjustment of multiple sociodemographic factors simultaneously. The level of statistical significance was set at P = 0.05.

Subgroup and interaction analysis: Subgroup analyses were performed to examine interactions between key sociodemographic variables and vaccine acceptance. For example, separate logistic regression models were run for different age groups, income levels, and participants with chronic conditions to identify whether these subgroups exhibited different patterns of vaccine acceptance. Interaction terms were also tested within the regression models to assess whether the effect of one variable on vaccine acceptance was modified by another variable (e.g., the interaction between age and income).

Handling of missing data: There was no missing data in this study. All respondents completed the survey in full, ensuring a complete dataset for analysis. As a result, no specific methods for handling missing data were required. The integrity of the dataset was maintained throughout the analysis process.

Analytical methods: To ensure that the findings were as representative as possible, the following analytical methods were employed: (1) Descriptive statistics: Frequency distributions, percentages, mean scores, and standard deviations were computed to describe the characteristics of the sample and the distribution of responses; (2) χ² tests: They were used for bivariate analyses to explore the associations between sociodemographic variables (e.g., age, sex, and income) and vaccine acceptance. χ² tests helped identify significant relationships within the sample; (3) Logistic regression analysis: This method was employed to assess the relationship between sociodemographic factors and vaccine acceptance while adjusting for potential confounders. Logistic regression allowed for the evaluation of the influence of multiple variables simultaneously; and (4) Weighting considerations: Although the study used a convenience sampling method, the analysis considered potential biases by comparing the sample demographics with known population characteristics where possible. This comparison helped in interpreting the findings and understanding their generalizability.

Interpretation and limitations

The cross-sectional design of the study provided a snapshot of vaccine acceptance at a single point in time. Due to the non-random sampling method, the results were interpreted with caution regarding their generalizability to the broader Nigerian population. The findings reflected the attitudes and perceptions of the sample group and may not fully capture the diversity of the entire population.

Sensitivity analyses

In this study, sensitivity analyses were conducted to ensure the robustness and reliability of the findings and ensure that the results were not unduly affected by methodological choices or specific assumptions. The following sensitivity analyses were performed.

Alternative cutoff points for vaccine acceptance: To test the stability of the vaccine acceptance measure, different cutoff points for categorizing participants as having poor or good acceptance rate were examined. This analysis aimed to determine whether the conclusions regarding vaccine acceptance remained consistent across different classification schemes. It helped verify that the results were not unduly influenced by the choice of cutoff points.

Subgroup analyses: Additional analyses were performed within specific subgroups, such as different age ranges, income levels, and chronic condition statuses. These subgroup analyses were conducted to check whether the main findings held true within different segments of the population and to identify any potential variations in vaccine acceptance based on these factors.

RESULTS

Participants

A total of 1800 Nigerians participated in the survey.

Reporting numbers at each stage of the study: (1) Potentially eligible participants: The survey was distributed through social networking platforms. The exact number of individuals who received the survey invitation could not be determined, as the survey was disseminated broadly without precise tracking of potential reach; (2) Examined for eligibility: All individuals who clicked on the survey link were considered as having accessed the survey. There was no formal examination of eligibility beyond the initial access, as the survey was open to any respondent who chose to participate; (3) Confirmed eligible: Since the study was a cross-sectional online survey, eligibility criteria were not formally applied beyond the general inclusion of all consenting respondents. The study assumed that those who participated were representative of the target population; and (4) Included in the study: A total of 1800 respondents participated in the survey and provided complete responses. These individuals were included in the analysis. As this was a cross-sectional study, no follow-up was required or conducted. All 1800 respondents who completed the survey were included in the data analysis.

Reasons for non-participation at each stage: The survey did not track individual responses beyond submission. However, potential reasons for non-participation could include: (1) Non-engagement: Individuals may not have engaged with the survey invitation or chosen to participate within the study period; (2) Incomplete responses: Participants who started the survey but did not complete it were excluded from submission; and (3) Technical issues: Some individuals may have experienced technical problems accessing or completing the survey.

The sociodemographic characteristics of the study participants are presented in Table 1. A larger proportion of the respondents were male (53.9%) and within the age group of 21-30 years (29.4%), earned an average income of less than $500 per month (43.3%), and lived in urban areas (90.6%). Table 2 shows the existence of underlying conditions among the study participants. A small percentage reported underlying conditions, including diabetes (8.3%), heart disease (2.2%), pulmonary disease (1.1%), with none indicating hypertension (0%). Table 3 presents the impacts of the COVID-19 pandemic on the work life of the study participants. According to the survey, 48.9% of respondents were employed, with most perceiving the COVID-19 pandemic as having negative effects on their careers. Nearly one-third of the respondents were receiving less pay for their work.

Table 1 Sociodemographic characteristics of the study participants.

Variable	Categories	Frequency
Age group in yr	≤ 20	310 (17.2)
	21-30	530 (29.4)
	31-40	460 (25.6)
	41-50	380 (21.1)
	> 51	120 (6.7)
Sex	Female	830 (46.1)
	Male	970 (53.9)
Location	Rural	170 (9.4)
	Urban	1630 (90.6)
Average income	Less than $500 per month	780 (43.3)
	$1000-$1999 per month	190 (10.6)
	$2000-$2999 per month	240 (13.3)
	$3000-$4999 per month	110 (6.1)
	$5000-$7999 per month	60 (3.3)
	$500-$999 per month	280 (15.6)
	$8000-$9999 per month	40 (2.2)
	$10000-$12999 per month	30 (1.7)
	$13000 or more per month	70 (3.9)
Religion	Catholic	280 (15.6)
	Christian/Protestant/Methodist/Lutheran/Baptist	1130 (62.8)
	Muslim	380 (21.1)
	Other	10 (0.6)

Data are presented as n (%).

Table 2 Existence of underlying conditions among the study participants.

Underlying conditions	Frequency (%)
Have diabetes	150 (8.3)
Have heart disease	40 (2.2)
Have pulmonary disease	20 (1.1)
Have hypertension	0 (0.0)

Data are presented as n (%).

Table 3 Impacts of the coronavirus disease 2019 pandemic on work and study life of the participants.

Variable	Categories	Frequency
Are you currently	Employed for wages	880 (48.9)
	Homemaker	10 (0.6)
	Out of work for 1 year or more	30 (1.7)
	Out of work for less than 1 year	80 (4.4)
	Self-employed	150 (8.3)
	Student	650 (36.1)
How much has your work changed as a result of the COVID-19 pandemic	I was let go from my job	80 (4.4)
	I work fewer hours	340 (18.9)
	I work more hours	250 (13.9)
	No change. I work the same amount	530 (29.4)
	Not applicable (not working)	600 (33.3)
How much has your salary changed as a result of the COVID-19 pandemic	I am getting paid less	660 (36.7)
	I am getting paid more	40 (2.2)
	No change. I am getting paid the same	1100 (61.1)
In the past week, how often have you gone to work or school outside of the home	0 day	260 (14.4)
	1 day	30 (1.7)
	2 days	150 (8.3)
	3 days	160 (8.9)
	4 days	180 (10.0)
	5 days	510 (28.3)
	6 days	180 (10.0)
	7 days	330 (18.3)
Did you wear a mask at work/school	No	20 (1.1)
	Not applicable (not going out a whole week)	150 (8.3)
	Yes, during my whole time at work/school	1020 (56.7)
	Yes, for part of the time at work/school	610 (33.9)
In the past week, how often have you gone to a grocery store or other food vendor	0 day	170 (9.4)
	1 day	510 (28.3)
	2 days	520 (28.9)
	3 days	360 (20.0)
	4 days	40 (2.2)
	5 days	90 (5.0)
	6 days	50 (2.8)
	7 days	60 (3.3)
Did you wear a mask at the grocery store or other food vendor	No	130 (7.2)
	Not applicable (not going out to grocery store or other food vendor whole week)	80 (4.4)
	Yes, during my whole time at the store	1280 (71.1)
	Yes, for part of the time at the store	310 (17.2)

Data are presented as n (%). COVID-19: Coronavirus disease 2019.

The perception of vaccination and social distancing measures among the study participants is presented in Table 4. The majority of respondents had a positive perception of vaccination and social distancing measures. Most participants strongly agreed that vaccines are important for their health (43.9%), being vaccinated is important for the health of others in my community (47.8%), getting vaccines is a good way to protect oneself from disease (41.1%), and social distancing can protect oneself (53.9%), children (57.2%), and parents (53.9%) from COVID-19. A vast majority (over 95%) of participants with underlying conditions strongly agreed on the importance, effectiveness, and trustworthiness of vaccines and the recommendations from healthcare providers. All of them (100%) strongly agreed that vaccination is crucial for community health and that social distancing protects against COVID-19. Social distancing is widely recognized as beneficial for personal and familial protection against COVID-19. However, there is some uncertainty regarding the risks of new vaccines, with mixed responses (Table 5).

Table 4 Perception of vaccination and social distancing measures among the study participants.

Variable	Strongly agree	Agree	Neither agree nor disagree	Disagree	Strongly disagree
Vaccines are important for my health	790 (43.9)	780 (43.3)	170 (9.4)	20 (1.1)	40 (2.2)
Vaccines are effective	650 (36.1)	870 (48.3)	240 (13.3)	10 (0.6)	30 (1.7)
Being vaccinated is important for the health of others in my community	860 (47.8)	740 (41.1)	140 (7.8)	50 (2.8)	10 (0.6)
All routine vaccines recommended by the healthcare workers are beneficial	580 (32.2)	850 (47.2)	300 (16.7)	60 (3.3)	10 (0.6)
New vaccines carry more risks than older vaccines	330 (18.3)	490 (27.2)	670 (37.2)	220 (12.2)	90 (5.0)
The information I receive about vaccines from the government is reliable and trustworthy	130 (7.2)	610 (33.9)	770 (42.8)	220 (12.2)	70 (3.9)
Getting vaccines is a good way to protect me from disease	740 (41.1)	820 (45.6)	150 (8.3)	50 (2.8)	40 (2.2)
Generally, I follow vaccine recommendations from my doctor or health care provider	650 (36.1)	950 (52.8)	140 (7.8)	50 (2.8)	10 (0.6)
Social distancing can protect yourself from COVID-19	970 (53.9)	730 (40.6)	70 (3.9)	20 (1.1)	10 (0.6)
Social distancing can protect your child or children from COVID-19	1030 (57.2)	650 (36.1)	100 (5.7)	20 (1.1)	0 (0.0)
Social distancing can protect your parents from COVID-19	1030 (57.2)	670 (37.2)	80 (4.4)	20 (1.1)	0 (0.0)

Data are presented as n (%). COVID-19: Coronavirus disease 2019.

Table 5 Perception of vaccination and social distancing measures among those with underlying conditions.

Variable	Strongly agree	Agree	Neither agree nor disagree	Disagree	Strongly disagree
Vaccines are important for my health	200 (95.2)	10 (4.76)	0 (0.0)	0 (0.0)	0 (0.0)
Vaccines are effective	200 (95.2)	10 (4.76)	0 (0.0)	0 (0.0)	0 (0.0)
Being vaccinated is important for the health of others in my community	210 (100)	0 (0.0)	0 (0.0)	0 (0.0)	0 (0.0)
All routine vaccines recommended by the healthcare workers are beneficial	200 (95.2)	10 (4.76)	0 (0.0)	0 (0.0)	0 (0.0)
New vaccines carry more risks than older vaccines	0 (0.0)	20 (9.52)	80 (38.1)	100 (47.6)	10 (4.76)
The information I receive about vaccines from the government is reliable and trustworthy	200 (95.2)	10 (4.76)	0 (0.0)	0 (0.0)	0 (0.0)
Getting vaccines is a good way to protect me from disease	200 (95.2)	10 (4.76)	0 (0.0)	0 (0.0)	0 (0.0)
Generally, I follow vaccine recommendations from my doctor or health care provider	200 (95.2)	10 (4.76)	0 (0.0)	0 (0.0)	0 (0.0)
Social distancing can protect yourself from COVID-19	210 (100)	0 (0.0)	0 (0.0)	0 (0.0)	0 (0.0)
Social distancing can protect your child or children from COVID-19	200 (95.2)	5 (2.38)	5 (2.38)	0 (0.0)	0 (0.0)
Social distancing can protect your parents from COVID-19	200 (95.2)	5 (2.38)	5 (2.38)	0 (0.0)	0 (0.0)

Data are presented as n (%). COVID-19: Coronavirus disease 2019.

The association between the sociodemographic characteristics and perception of vaccination as well as social distancing measures among the study participants is presented in Table 6. There was no significant association between the observed COVID-19 vaccine acceptance rate (63.9%) and related determinants including age (χ² = 3.049, P = 0.550), sex (χ² = 0.102, P = 0.749), location (χ² = 0.005, P = 0.941), average income (χ² = 3.802, P = 0.875), and religion (χ² = 2.819, P = 0.420). Nine hundred twenty participants (51.1%) had good perception, while 880 (48.9%) had poor perception of vaccination and social distancing measures (Figure 1).

Figure 1  Perception on vaccination and social distancing measures among the study participants.

Table 6 Association between sociodemographic and perception of vaccination and social distancing measures among the study participants.

Variable	Categories	Poor perception	Good perception	Total	χ²	P value	Odds ratio (95%CI)
Age group (yr)	≤ 20	220 (12.2)	90 (5.0)	310 (17.2)	8.449	0.076
	21-30	260 (14.4)	270 (15.0)	530 (29.4)			1.25 (0.94-1.65)
	31-40	200 (11.1)	260 (14.4)	460 (25.6)
	41-50	160 (8.9)	220 (12.2)	380 (21.1)
	> 51	40 (2.2)	80 (4.4)	120 (6.7)
Sex	Female	450 (25.0)	380 (21.1)	830 (46.1)	1.75	0.186
	Male	430 (23.9)	540 (30.0)	970 (53.9)			0.74 (0.38-1.44)
Location	Rural	110 (6.1)	60 (3.3)	170 (9.4)	1.88	0.17
	Urban	770 (42.8)	860 (47.8)	1630 (90.6)			0.50 (0.16-1.51)
Average income	Less than $500 per month	410 (22.8)	370 (20.6)	780 (43.3)			1.17 (0.14-9.43)
	$500-$999 per month	110 (6.1)	170 (9.4)	280 (15.6)			0.94 (0.17-5.27)
	$1000-$1999 per month	80 (4.4)	110 (6.1)	190 (10.6)	7.15	0.521
	$2000-$2999 per month	110 (6.1)	130 (7.2)	240 (13.3)			0.38 (0.07-2.21)
	$3000-$4999 per month	40 (2.2)	70 (3.9)	110 (6.1)			1.19 (0.46-3.10)
	$5000-$7999 per month	30 (1.7)	30 (1.7)	60 (3.3)			1.33 (0.34-5.13)
	$8000-$9999 per month	20 (1.1)	20 (1.1)	40 (2.2)			1.59 (0.64-3.96)
	$10000-$12999 per month	30 (1.7)	0 (0)	30 (1.7)			1.26 (0.44-3.65)
	$13000 or more per month	50 (2.8)	20 (1.1)	70 (3.9)			0.00 (0.00-0.00)
Religion	Catholic	150 (8.3)	130 (7.2)	280 (15.6)	2.819	0.42
	Christian/Protestant/Methodist/Lutheran/ Baptist	580 (32.2)	550 (30.6)	1130 (62.8)			0.00 (0.00-0.00)
	Muslim	150 (8.3)	230 (12.8)	38 (21.1)			0.00 (0.00-0.00)
	Other	0 (0.0)	10 (0.6)	1 (0.6)			0.00 (0.00-0.00)

Data are presented as n (%). CI: Confidence interval.

The perceived risk of COVID-19 infection among participants was as follows: 0% (600), 1%-10% (450), 11%-20% (180), 21%-30% (140), 31%-40% (110), and higher percentages. Only ten people considered themselves to have 81%-90% risk of getting infected (Figure 2). On the other hand, the perceived risk of dying from COVID-19 if infected was as follows: 0% (740), 1%-10% (470), 11%-20% (160), 21%-30% (120), 31%-40% (30), etc. Twenty people considered themselves to have an 81%-90% risk of dying if infected (Figure 3). The occurrence of COVID-19 and the severity among the study participants is presented in Table 7. Ten of them (5.6%) indicated that they have been diagnosed with COVID-19 by a doctor, of which only 2.2% had very serious cases, while 3.3% of the cases were not very serious.

Figure 2  Perceived risk of getting infected with the coronavirus disease 2019 in the next month.

Figure 3  Perceived risk of dying from the coronavirus disease 2019 if infected.

Table 7 Occurrence of the coronavirus disease 2019 and the severity among the study participants.

Variable	Categories	Frequency
Diagnosed with COVID-19 by a doctor	No	1700 (94.4)
	Yes	100 (5.6)
How serious was the course of illness when you were infected with COVID-19	Not applicable	1700 (94.4)
	Not very serious	60 (3.3)
	Somewhat serious	40 (2.2)
Do you know people in your immediate social environment (close friends or family members) who are or have been infected with COVID-19	Do not know	420 (23.3)
	No	670 (37.2)
	Yes	710 (39.4)
How serious was the course of illness when your friend or family member was infected with the COVID-19? If you know multiple people who have had COVID-19, think about the most recent one	Not applicable	1090 (60.6)
	Not very serious	260 (14.4)
	Somewhat serious	300 (16.7)
	Very serious	150 (8.3)
Have you seen or read about individuals infected with the COVID-19 on social media or TV	No	30 (1.7)
	Yes	1770 (98.3)
How serious was the course of illness for the most recent COVID-19 case you have seen or read about in social media or on the TV	No idea	30 (1.7)
	Not very serious	260 (14.4)
	Somewhat serious	620 (34.4)
	Very serious	890 (49.4)
Have you ever heard that your local health facilities stop the vaccination service for kids due to COVID-19 pandemic	No	1550 (86.1)
	Yes	250 (13.9)

Data are presented as n (%). COVID-19: Coronavirus disease 2019.

Table 8 shows the COVID-19 vaccine acceptance rates among the study participants. A vaccine with 95% efficacy if the government was offering it as a free and optional vaccine would be accepted by 1380 participants (76.7%). Only 70.0% of the study participants indicated that they would buy and get vaccinated if the vaccine was 95% effective, had a 5% chance of a side effect like a fever or local pain, and was sold for US$50, while 1150 (63.9%) said they would buy and get vaccinated if the vaccine cost was US$100 (Figure 4). All the participants with underlying conditions (100%) indicated acceptance of the vaccine when it was 95% effective and offered for free. Acceptance rates remained high (85.7%-95.2%) even with reduced effectiveness and potential higher side effect risks. They showed 100% acceptance for vaccine prices up to US$100. However, acceptance slightly decreased to 95.2% at a price of US$200. The vaccine had full acceptance at lower price points (US$5, US$12.5, US$25, US$50, and US$100). Overall, the study indicated strong willingness to accept the COVID-19 vaccine among participants with underlying conditions, influenced by the effectiveness, side effects, and cost of the vaccine (Table 9).

Figure 4  Overall coronavirus disease 2019 vaccine acceptance rate among the study participants.

Table 8 Coronavirus disease 2019 vaccine acceptance rates among the study participants.

Variable	Categories	Frequency
Imagine that a new COVID-19 vaccine has just been developed. It has received the same testing as the adult influenza vaccine. The government is offering it as a FREE and optional vaccine. Would you accept a COVID-19 vaccine if the vaccine was 95% effective	No	420 (23.3)
	Yes	1380 (76.7)
The vaccine is 50% effective, with a 5% chance of a side effect like a fever (50% effective means that there is a 50% reduction in disease among those vaccinated compared to those unvaccinated)	No	860 (47.8)
	Yes	940 (52.2)
The vaccine is 95% effective, with a 20% chance of a side effect like a fever (95% effective means that there is a 95% reduction in disease among those vaccinated compared to those unvaccinated)	No	550 (30.6)
	Yes	1250 (69.4)
The vaccine is 75% effective, with a 5% chance of a side effect like a fever (75% effective means that there is a 75% reduction in disease among those vaccinated compared to those unvaccinated)	No	400 (22.2)
	Yes	1400 (77.8)
The vaccine is 75% effective, with a 20% chance of a side effect like a fever (75% effective means that there is a 75% reduction in disease among those vaccinated compared to those unvaccinated)	No	990 (55.0)
	Yes	810 (45.0)
For a COVID-19 vaccine that is 95% effective and a 5% chance of a side effect like fever or local pain? If the price was US$50 for complete vaccination. Would you buy the vaccine and get vaccinated	No	540 (30.0)
	Yes	1260 (70.0)
If the COVID-19 vaccine price was US$100. Would you buy the vaccine and get vaccinated	No	650 (36.1)
	Yes	1150 (63.9)
If the COVID-19 vaccine price was US$200. Would you still buy the vaccine and get vaccinated	No	570 (31.7)
	Yes	1230 (68.3)
If the COVID-19 vaccine price is reduced to US$25. Would you buy the vaccine and get vaccinated	No	550 (30.6)
	Yes	1250 (69.4)
If the COVID-19 vaccine price was US$12.5. Would you buy the vaccine and get vaccinated	No	1210 (67.2)
	Yes	590 (32.8)
If the COVID-19 vaccine price was US$5 only. Would you buy the vaccine and get vaccinated	No	630 (35.0)
	Yes	1170 (65.0)

Data are presented as n (%). COVID-19: Coronavirus disease 2019.

Table 9 Coronavirus disease 2019 vaccine acceptance rates among those with underlying conditions.

Variable	Categories	Frequency
Imagine that a new COVID-19 vaccine has just been developed. It has received the same testing as the adult influenza vaccine. The government is offering it as a free and optional vaccine. Would you accept a COVID-19 vaccine if the vaccine was 95% effective?	No	0 (0.0)
	Yes	210 (100.0)
The vaccine was 50% effective, with a 5% chance of a side effect like a fever? (50% effective means that there is a 50% reduction in disease among those vaccinated compared to those unvaccinated)	No	10 (4.8)
	Yes	200 (95.2)
The vaccine was 95% effective, with a 20% chance of a side effect like a fever? (95% effective means that there is a 95% reduction in disease among those vaccinated compared to those unvaccinated)	No	30 (14.3)
	Yes	180 (85.7)
The vaccine was 75% effective, with a 5% chance of a side effect like a fever? (75% effective means that there is a 75% reduction in disease among those vaccinated compared to those unvaccinated)	No	25 (11.9)
	Yes	185 (88.09)
The vaccine was 75% effective, with a 20% chance of a side effect like a fever? (75% effective means that there is a 75% reduction in disease among those vaccinated compared to those unvaccinated)	No	30 (14.3)
	Yes	180 (85.7)
For a COVID-19 vaccine that was 95% effective and a 5% chance of a side effect like a fever or local pain? If the price is US$50 for complete vaccination. Would you buy the vaccine and get vaccinated?	No	0 (0.0)
	Yes	210 (100)
If the COVID-19 vaccine price was US$100. Would you buy the vaccine and get vaccinated?	No	0 (0.0)
	Yes	210 (100.0)
If the COVID-19 vaccine price was US$200. Would you buy the vaccine and get vaccinated?	No	10 (4.8)
	Yes	200 (95.2)
If the COVID-19 vaccine price was reduced to US$25. Would you buy the vaccine and get vaccinated?	No	0 (0.0)
	Yes	210 (100.0)
If the COVID-19 vaccine price was US$12.5. Would you buy the vaccine and get vaccinated?	No	0 (0.0)
	Yes	210 (100.0)
If the COVID-19 vaccine price was US$5 only. Would you buy the vaccine and get vaccinated?	No	0 (0.0)
	Yes	210 (100.0)

Data are presented as n (%). COVID-19: Coronavirus disease 2019.

The association between the sociodemographic characteristics and COVID-19 vaccine acceptance rates among the study participants is presented in Table 10. No significant associations (P > 0.05) were found between sociodemographic characteristics and COVID-19 vaccine acceptance rates. The overall mean score for vaccine acceptance among participants showed significant differences (P < 0.05) between those willing to accept the vaccine (8.44 ± 1.14) and those not willing (4.18 ± 1.66) (Table 11).

Table 10 Association between sociodemographic and the coronavirus disease 2019 vaccine acceptance rates among the study participants.

Variable	Categories	Poor	Good	Total	χ²	P value	Odds ratio (95%CI)
Age group (yr)	≤ 20	70 (3.9)	240 (13.3)	310 (17.2)	3.049	0.55
	21-30	200 (11.1)	330 (18.3)	530 (29.4)			0.76 (0.57-1.02)
	31-40	180 (10.0)	280 (15.6)	460 (25.6)
	41-50	150 (8.3)	230 (12.8)	380 (21.1)
	> 51	50 (2.8)	70 (3.9)	120 (6.7)
Sex	Female	310 (17.2)	520 (28.9)	830 (46.1)	0.102	0.749
	Male	340 (18.9)	630 (35.0)	970 (53.9)			0.83 (0.42-1.62)
Location	Rural	60 (3.3)	110 (6.1)	170 (9.4)	0.005	0.941
	Urban	590 (32.8)	1040 (57.8)	1630 (90.6)			0.90 (0.29-2.78)
Average income	Less than $500 per month	310 (17.2)	470 (26.1)	780 (43.3)			2.74 (0.25-30.32)
	$500-$999 per month	110 (6.1)	170 (9.4)	280 (15.6)			4.14 (0.44-38.90)
	$1000-$1999 per month	40 (2.2)	150 (8.3)	190 (10.6)	3.802	0.875
	$2000-$2999 per month	90 (5.0)	150 (8.3)	240 (13.3)			0.81 (0.16-4.05)
	$3000-$4999 per month	40 (2.2)	70 (3.9)	110 (6.1)			1.25 (0.47-3.29)
	$5000-$7999 per month	10 (0.6)	50 (2.8)	60 (3.3)			1.33 (0.34-5.22)
	$8000-$9999 per month	10 (0.6)	30 (1.7)	40 (2.2)			1.08 (0.43-2.68)
	$10000-$12999 per month	10 (0.6)	20 (1.1)	30 (1.7)			2.76 (0.81-9.42)
	$13000 or more per month	30 (1.7)	40 (2.2)	70 (3.9)			1.14 (0.09-13.78)
Religion	Catholic	100 (5.6)	180 (10.0)	280 (15.6)	1.804	0.614
	Christian/Protestant/Methodist/Lutheran/Baptist	440 (24.4)	690 (38.3)	1130 (62.8)			0.00 (0.00-0.00)
	Muslim	110 (6.1)	270 (15.0)	380 (21.1)			0.00 (0.00-0.00)
	Other	0 (0.0)	10 (0.6)	10 (0.6)			0.00 (0.00-0.00)

Data are presented as n (%). CI: Confidence interval.

Table 11 Overall mean score of the coronavirus disease 2019 vaccine acceptance rates among the study participants.

Variable	Poor	Good	P value
Overall score on perception of vaccination and social distancing measures among the study participants	8.49 ± 2.72	9.04 ± 1.88	0.112
Overall score on the coronavirus disease 2019 vaccine acceptance rates among the study participants.	4.18 ± 1.66	8.44 ± 1.14	0.000

Unadjusted and confounder-adjusted estimates

Unadjusted estimates: The study found no significant associations between sociodemographic characteristics (age, sex, location, average income, and religion) and COVID-19 vaccine acceptance rates. For instance, the χ² test results showed non-significant P values for these variables (age: χ² = 3.049, P = 0.550; sex: χ² = 0.102, P = 0.749; location: χ² = 0.005, P = 0.941; income: χ² = 3.802, P = 0.875; religion: χ² = 2.819, P = 0.420).

Confounder-adjusted estimates: Logistic regression analysis was conducted to assess the association between sociodemographic factors and vaccine acceptance while adjusting for potential confounders. However, as no significant associations were found in the unadjusted analyses, the adjusted estimates were not substantially different.

Category boundaries for continuous variables

Perceived risk of COVID-19 infection: 0% (600 respondents), 1%-10% (450 respondents), 11%-20% (180 respondents), 21%-30% (140 respondents), 31%-40% (110 respondents), and higher percentages, including 81%-90% (10 respondents).

Perceived risk of dying from COVID-19: 0% (740 respondents), 1%-10% (470 respondents), 11%-20% (160 respondents), 21%-30% (120 respondents), 31%-40% (30 respondents), and higher percentages, including 81%-90% (20 respondents).

Translation of relative risk into absolute risk: The study did not specifically translate relative risk into absolute risk. However, the provided percentages of perceived risk can be used to infer the perceived likelihood of infection and death among participants. For instance, if 48.9% perceived their risk of infection to be between 1%-10%, it suggests that nearly half of the participants consider their risk relatively low.

Other analyses performed: (1) Subgroup and interaction analyses: Subgroup analyses were performed to explore variations in vaccine acceptance based on underlying conditions. Participants with underlying conditions showed high acceptance rates, with 100% acceptance for a vaccine with 95% efficacy if offered free. Sensitivity to price and effectiveness was also examined, revealing high acceptance even with variations in vaccine cost and potential side effects; and (2) Sensitivity analyses: Sensitivity analyses involved testing different cutoff points for categorizing vaccine acceptance and examining the effect of various model specifications on the findings. The study tested alternative thresholds for vaccine acceptance and adjusted for different sociodemographic factors in the regression models. Additionally, analyses of subgroups, such as those with underlying conditions, were conducted to assess the stability of the main findings across different groups.

DISCUSSION

The results of the current study, which examined COVID-19 vaccine acceptance and its determinants among 1800 respondents in Nigeria, revealed several key findings and trends that can be compared with previous studies conducted in Nigeria and beyond.

Summary of key results

The study revealed a vaccine acceptance rate of 63.9% among the Nigerian participants. This indicates a majority willingness to receive the COVID-19 vaccine under the conditions described in the survey. A significant portion of respondents demonstrated a positive perception of both the COVID-19 vaccine and social distancing measures. Specifically, 43.9% of participants strongly agreed on the importance of vaccines for personal health, and 47.8% recognized their importance for community health. In addition, 53.9% of participants believed that social distancing could protect oneself and family from COVID-19. Participants with chronic conditions showed even higher vaccine acceptance, with 100% indicating acceptance for a vaccine with 95% efficacy offered free of charge. This highlights an enhanced willingness among those who may perceive a higher personal risk or benefit from vaccination.

No significant association was found between age and vaccine acceptance, with odds ratios (OR) ranging from 0.94 to 1.65 across different age groups. Male participants showed a lower OR of vaccine acceptance (OR = 0.74, 95%CI: 0.38-1.44), though this result was not statistically significant. Urban residents had a lower adjusted OR (OR = 0.50, 95%CI: 0.16-1.51) for vaccine acceptance compared to rural residents, but this result was also not statistically significant. The OR varied across different income brackets, with no consistent trend and confidence intervals suggesting limited precision. No significant differences were found in vaccine acceptance across different religious groups, with OR indicating no significant associations. Participants’ perceived risk of COVID-19 infection and death was low, with a majority estimating their risk in the lower percentage range (0%-10%). This lower perceived risk may impact their motivation for vaccine uptake. High acceptance was noted when the vaccine was offered free with 95% efficacy. Acceptance rates remained high even when the vaccine cost increased, though there was a slight decline as the price rose to US$200.

The study indicated an overall COVID-19 vaccine acceptance rate of 63.9%, which aligns with similar trends observed in related research, though variations exist across different demographic and professional groups.

Sociodemographic characteristics and vaccine acceptance

The relationship between sociodemographic factors and COVID-19 vaccine acceptance in Nigeria has yielded mixed results across studies. The current study found no significant association between factors like age, sex, income, and religion and vaccine acceptance, aligning with findings by Iwuafor et al[24], who also reported no significant predictors of vaccine refusal among healthcare professionals in Cross River State. This suggests that vaccine hesitancy may be more influenced by individual perceptions and external factors such as misinformation than by demographic variables. However, other studies reported significant associations between sociodemographic factors and vaccine acceptance. Olu-Abiodun et al[25] found that vaccine acceptance rates varied widely (20.0%-58.2%) across demographics, with concerns over vaccine safety, conspiracy theories, and adverse effects playing key roles.

Eze et al[26] identified sex, religion, ethnicity, and geographical location as significant predictors, noting that male sex, Christianity, and Northern residence were positively associated with acceptance. Al-Mustapha et al[27] also found age and income to be significant predictors, with older individuals and those with higher incomes more likely to accept the vaccine. Alice et al[28] reported that increasing age, male sex, and trust in government and public health authorities were associated with higher vaccine acceptance. Njoga et al[29] emphasized the role of geopolitical zones, education, and occupation in vaccine hesitancy, particularly among healthcare workers, academics, and students.

While our study focused on age, sex, location, average income, and religion of the study participants, we recognize the importance of education and socioeconomic status as determinants of vaccine acceptance. Previous studies[30-34] have shown that higher education levels and socioeconomic status correlate with greater vaccine acceptance due to better health literacy and perceived risk. These contrasting findings suggest that the influence of sociodemographic factors on vaccine acceptance may vary by context, and targeted interventions considering these variables may be necessary to address vaccine hesitancy effectively in Nigeria.

Perception

Our study revealed that a majority of respondents have a positive perception of vaccination and social distancing measures. Specifically, 43.9% strongly agreed on the importance of vaccines for health, and 47.8% believed vaccination is crucial for community health. These perceptions are comparable to the findings by Tijani et al[35], who reported a significant association between educational level and monthly income with vaccine uptake, highlighting the importance of awareness and financial stability in fostering positive perceptions towards vaccination.

Impact of COVID-19 on work life

The current study indicated that nearly half of the respondents (48.9%) felt that the COVID-19 pandemic negatively impacted their careers, with many reporting reduced pay. This economic impact likely influenced their perceptions and acceptance of vaccination, similar to findings by Zakari et al[36], where economic factors and skepticism about vaccine efficacy were major reasons for hesitancy among university community members.

Acceptance rates and determinants

A notable finding from the current study was the high acceptance rate (76.7%) for a vaccine with 95% efficacy if provided for free, which dropped to 63.9% if the vaccine costs $100. This trend of price sensitivity aligns with Padonou et al[37], who also observed that financial constraints and economic conditions significantly affected vaccine acceptance rates in Benin. In comparison to the findings from Omale et al[38], where health workers’ acceptance was primarily driven by perceptions of vaccine importance and safety, the respondents in the current study similarly indicated good perception (51.1%) vs poor perception (48.9%) of vaccination measures. This further emphasizes that improving perceptions through education and communication is crucial for enhancing vaccine uptake.

More than two-thirds of respondents in this study expressed willingness to be vaccinated for various reasons, while 64% indicated readiness to get vaccinated for a range of reasons. In terms of willingness to be vaccinated, the result of this current study is higher than those from Italy (53.7%), Russia (54.9%), Poland (56.3%), the United States (56.9%), Greece (57.7%), and France (58%)[39-41]. On the other side, countries such as Ecuador (97.0%), Malaysia (94.3%), Indonesia (93.3%), and China (91.3%) had the highest rates of vaccine acceptability, whilst Jordan (28.4%) and Kuwait (23.6%) had the lowest[40]. Since these factors were shown to be connected with the willingness to become vaccinated, the variation in vaccination rates might be attributed to the respondent’s level of education, employment, or social standing.

In addition, it has been reported that non-governmental groups make significant improvements to the vaccination programs in countries that have a low or moderate income. People living in remote areas and communities that are difficult to access now have easier access to vaccinations. It is possible that many people would pick the non-governmental organization sector to supervise vaccine distribution since they do not put much faith in official organizations. This might be the result of factors such as delay caused by government bureaucracy (delays the administration of vaccinations), nepotism (selects vaccine recipients rather than those who are most susceptible), and corruption (influences the cost of vaccines and how widely they are distributed)[38].

The COVID-19 vaccination has been deemed safe and effective by 60% and 60.1% of individuals, as determined by different systematic reviews and meta-analyses[40,41]. According to the findings of an in-depth study as well as a meta-analysis, 81.65% of the general population was eager to be vaccinated against COVID-19. However, this number was far lower than those who actually received the vaccine[42]. This might provide an explanation for how the COVID-19 epidemic is spreading throughout the world and impacting a variety of countries. It is possible that the gap might be explained by the fact that those who participated in the poll came from a wide array of social and cultural backgrounds. It is also conceivable that some of them do not have access to reliable social media channels where people are sharing authentic information regarding the COVID-19 vaccination. There is a possibility that the differences might be due to divergent points of view on the relevance and importance of the vaccine.

Furthermore, our study observed that a higher percentage of male respondents supported vaccination compared to female respondents. This was in line with the results of a prior study that showed males were much more willing to acquire vaccinations. This might be due to the fact that roughly two-thirds of the males who participated in this study were literate. As a result, they were probably aware of the potentially harmful effects of COVID-19, which increased the likelihood that they would acquire the vaccine. When the vaccine became available, most people elected to get it because they were terrified of getting COVID-19. This fear may have prompted them to make this decision. The lack of understanding on the safety of the vaccine and the absence of clinical trials were the two factors that were brought up as the most common vaccination roadblocks or reasons for skepticism. This was in line with the findings of the majority of the studies that were carried out to establish why some individuals did not acquire the COVID 19 vaccination[43].

Perceived risks

The study assessed perceived risks of infection and death from COVID-19, revealing that a significant number of respondents felt they had minimal risk, with 740 participants considering their risk of dying from COVID-19 as 0%. This low perceived risk could be a contributing factor to vaccine hesitancy, as seen in Olawa et al[44], where mistrust in the government and vaccine benefits led to lower acceptance rates.

Perceived sickness risks have been connected to health-related activity[45]. However, the majority of research on risk perceptions focused primarily on the possibility of being ill[46]. The majority of the respondents in this study had a higher perception of not being infected with COVID-19 as most indicated a lower percentage risk level of getting infected with COVID-19 and risk of hospitalization and dying from COVID-19 if infected. Findings, especially in Sub-Saharan nations, have shown that COVID-19 infected people have no or mild symptoms. This implies that the likelihood of infection may not give much insight into how individuals perceive risk and how this influences their health practices, which may be due to herd immunity of the respondents[47].

The degree of association between these risk measures was relatively weak, and they cannot be used as proxies. Although the majority of participants in this study had good knowledge regarding vaccination, some also exhibited comparatively lower percentages of COVID-19 acceptability, and this might be due to low level of exposure and the perceived risk of dying among the respondents. Moreover, respondents in the age group of 51 years and above demonstrated the lowest level of acceptability, which corroborated with the submission of Fojnica et al[48].

If these people had been better informed about the vaccines and the degree to which the government was unprepared for them, it is possible that they would have been more worried about the accessibility and safety of the immunizations. On the contrary, they had a tendency to become worse. On the other hand, herd immunity against the COVID-19 outbreak may be feasible if the government makes measures that are open and transparent and implements a range of credible diplomatic actions in order to secure enough immunizations for widespread inoculation[49,50].

Vaccine hesitancy

Compared to the study by Mustapha et al[51], which found a vaccine acceptance rate of 40.0% among students, the acceptance rate of the current study was higher. However, both studies highlight the need for targeted education and public health campaigns to address misconceptions and improve vaccine uptake. The present study also suggested the necessity of making vaccines more affordable and accessible, which aligns with recommendations from Kolawole et al[52] and Mahmood et al[53], who emphasized the role of public health professionals and trust in vaccines.

History of underlying conditions and openness to receiving the COVID-19 vaccine

Our findings indicate a significant relationship between a history of chronic illness and openness to receiving the COVID-19 vaccine. People who had a previous diagnosis of a chronic illness had a higher likelihood of responding favorably to the COVID-19 vaccination than those who did not have such a diagnosis. Most of the participants with underlying conditions strongly agree on the importance, effectiveness, and protective benefits of vaccines, indicating a high level of acceptance and trust. This trust in vaccines and the reliability of information from healthcare workers and the government is crucial for achieving high vaccination coverage and community immunity. Public health campaigns should leverage this trust to disseminate important messages and encourage compliance with vaccination schedules.

However, some uncertainty remains regarding the risks associated with new vaccines, highlighting the need for clear, evidence-based information to prevent hesitancy. The implications of high COVID-19 vaccine acceptance rates among individuals with underlying conditions are significant for public health, policy, and society. High acceptance, especially for a free vaccine that is 95% effective, underscores the willingness to get vaccinated, which is vital for achieving herd immunity and controlling the spread of COVID-19. Even with some side effects, acceptance remains high, though slightly lower with increased side effect likelihood. This emphasizes the importance of transparent risk-benefit communication. Vaccines with higher efficacy rates are more likely to be accepted, suggesting that public health efforts should focus on distributing and promoting the most effective vaccines.

Affordability is a key factor, with 100% acceptance for vaccines priced up to $100 and a slight decrease at $200. Policymakers should ensure vaccines are affordable or free, especially for vulnerable populations with underlying conditions. Subsidies, insurance coverage, and financial assistance programs can help maintain high vaccination rates. Ensuring equitable access to vaccines is essential for those more susceptible to severe outcomes from COVID-19. This is consistent with previous studies[54-58]. Both an Australian study and a report by the World Health Organization support these findings[59-61]. This research highlights the need to establish a mechanism that would enable recipients of the COVID-19 vaccination who have a history of chronic diseases to acquire the vaccine. This necessity is emphasized by our findings.

Studies on vaccine history, also known as past vaccination behavior, are accurate predictors of future vaccination behavior[62,63]. A previous survey found that between 2010 and 2015, only 3.4% to 44.1% of healthcare workers in the Kingdom of Saudi Arabia received the influenza vaccine[13]. In addition, earlier studies that used a cross-sectional approach indicated that if people in Russia and Indonesia were not given sufficient knowledge regarding the efficacy and safety of vaccines, they would not support them. This was the case in both countries[62]. In addition, there is a major shortage of COVID-19 vaccines in Nigeria since the country does not get them on a consistent basis or in adequate quantities. In addition, the lack of contracts with alternative healthcare providers abroad has made it difficult to provide immunizations at the appropriate period[63-65]. The opinions of the majority of people about vaccinations in general have been significantly changed, due to concerns surrounding the safety of vaccines and doubts regarding vaccine supply.

Limitations of the study

The study on COVID-19 vaccine acceptance among Nigerians, while providing valuable insights, had several limitations that could affect the interpretation of the results.

Sampling bias (non-random sampling): The study used an online survey distributed through social networking platforms. This method of recruitment can introduce selection bias, as it may not be representative of the entire population. Individuals with higher internet access and engagement with social media are more likely to participate, potentially skewing the sample towards a younger, more urban, and more internet-savvy demographic. This sampling bias could lead to an overrepresentation of younger and more educated individuals who might have higher vaccine acceptance compared to those with less internet access or lower education levels. The extent of this bias is unclear, but it could be substantial given that a significant proportion of participants were in the 21-30 age group and lived in urban areas.

Response bias: The study relied on self-reported data, which can introduce response bias. Participants might provide socially desirable answers or overstate their acceptance of the vaccine to align with perceived social norms. This could lead to an overestimation of vaccine acceptance and a more positive perception of vaccination and social distancing measures. The impact of response bias is difficult to quantify but could be considerable, especially in the context of sensitive topics like vaccine acceptance.

Response rate calculation: Due to the nature of social media distribution, it was impossible to determine the total number of individuals who received the survey invitation. Without this data, accurately calculating the response rate is unfeasible, which limits our ability to assess the representativeness and potential response bias of the sample. The inability to calculate the response rate significantly affects the assessment of sample representativeness and potential biases. It poses a high risk of both overestimating and underestimating the true attitudes and acceptance rates within the general population. The bias could lean towards overrepresenting more engaged and possibly more positive respondents, while underrepresenting less engaged groups who might have different views on the vaccine and social distancing measures.

Measurement issues: The study used percentage-based categories for perceived risk rather than more granular or standardized scales. This method may lack precision and could lead to misclassification of participants’ perceptions. This imprecision could obscure the true distribution of perceived risk and affect the accuracy of the associations with vaccine acceptance. The magnitude of this imprecision could vary but may limit the ability to detect more silent differences in perceived risk.

Cross-sectional design: As a cross-sectional study, it captured data at a single point in time, making it challenging to infer causality or changes in vaccine acceptance over time. The snapshot nature of the data may not reflect shifts in attitudes or external factors affecting vaccine acceptance that occurred after the study period. This limitation is inherent to cross-sectional studies and affects all results similarly, though the exact impact on conclusions about causality is significant.

Sample size: While the sample size of 1800 participants is relatively large, it was not calculated based on formal power analysis. This means the study may have limited power to detect smaller associations or differences. Without an adequate power analysis, the study might not detect significant associations that exist, or it might find associations that are not robust. The lack of power analysis could affect the reliability of the study’s conclusions, particularly for subgroup analyses where sample sizes are smaller.

Confounding variables: Despite adjusting for some sociodemographic factors, other potential confounders such as health literacy, exposure to misinformation, and prior experiences with vaccines were not assessed. The study did not consider education and socioeconomic status, which are crucial determinants of vaccine acceptance. Previous research indicated that individuals with higher education levels and better socioeconomic positions were more likely to understand the benefits of vaccination and perceive higher risks of COVID-19, influencing their acceptance rates. Unmeasured confounders could skew the results in either direction, making it challenging to isolate the true determinants of vaccine acceptance. The magnitude of this bias is difficult to estimate, but could be significant, particularly if these unmeasured factors are strongly related to both sociodemographic characteristics and vaccine acceptance.

Overall interpretation: The study provided valuable insights into the level of COVID-19 vaccine acceptance and the general perception of vaccination and social distancing among Nigerians. However, the limitations regarding sampling methods, response bias, and measurement precision necessitate a cautious interpretation of the results. The relatively high acceptance rate and positive perceptions suggest a generally supportive attitude towards COVID-19 vaccination among the surveyed group, particularly among those with underlying health conditions. The non-random sampling method and potential response biases imply that the findings may not fully represent the broader Nigerian population. The results should be interpreted with caution, acknowledging that the actual acceptance rates and perceptions might differ in the general population.

Generalizability: The findings may not be generalizable to all Nigerians or other populations due to the specific nature of the sample (e.g., higher internet usage and urban focus). This limits the ability to apply the findings broadly and could result in different vaccine acceptance patterns in other demographic groups. The extent of this generalizability issue is substantial, given the specific sociodemographic characteristics of the sample.

Recommendations for future studies

Based on the above limitations, we hereby make the following recommendations: (1) Future studies should employ a multimodal distribution strategy, including face-to-face interviews, telephone surveys, and distribution through traditional media channels (e.g., radio, television) to reach a broader and more diverse population, including those without internet access; (2) It is crucial to incorporate education levels and detailed socioeconomic status indicators in future surveys. These factors significantly influence vaccine acceptance and would provide a clearer understanding of the determinants of vaccine uptake; (3) Conduct longitudinal studies to track changes in vaccine acceptance over time. This approach would help identify trends, evaluate the long-term effectiveness of public health interventions, and observe shifts in public perception as the pandemic evolves; (4) To mitigate social desirability bias, consider using anonymous surveys and validated instruments designed to reduce the impact of self-reporting biases. Additionally, incorporating qualitative methods (e.g., focus groups and in-depth interviews) can provide deeper insights into the reasons behind vaccine acceptance or hesitancy; (5) Based on the study findings, public health campaigns should be tailored to address the specific concerns and barriers identified in the survey. These campaigns should emphasize the safety, efficacy, and importance of COVID-19 vaccines, particularly targeting groups with lower acceptance rates; (6) Governments and policymakers should consider providing vaccines for free or at subsidized rates to alleviate financial barriers. Economic support measures, such as compensation for potential side effects or paid time off for vaccination, could also enhance acceptance; (7) Engage community leaders, healthcare providers, and influencers to build trust and disseminate accurate information about COVID-19 vaccines. This grassroots approach can help counteract misinformation and skepticism, particularly in communities with historically low trust in governmental or medical institutions; and (8) Increase the number and accessibility of vaccination centers, especially in rural and underserved areas. Mobile clinics and community-based vaccination drives can help reach populations with limited access to healthcare facilities.

By addressing these limitations and implementing the recommended strategies, future research and public health efforts can more effectively enhance vaccine acceptance and uptake, contributing to better control of the COVID-19 pandemic in Nigeria.

CONCLUSION

The findings of this study provided valuable insights into the determinants of COVID-19 vaccine acceptance in Nigeria, highlighting the significant role of economic factors, perceptions of vaccine efficacy and safety, and the impact of the pandemic on individuals’ lives. Despite the observed positive perception and a substantial acceptance rate of 63.9% among the study participants, the analysis revealed that sociodemographic factors such as age, sex, income, and religion did not significantly influence vaccine uptake. However, individuals with a history of chronic conditions demonstrated a higher likelihood of accepting the vaccine, underscoring the importance of targeted interventions. To enhance vaccine acceptability and achieve herd immunity, it is imperative to implement comprehensive public health strategies. These should include economic support to alleviate financial barriers, extensive educational campaigns to improve understanding of vaccine efficacy and safety, and trust-building measures to counteract misinformation and skepticism towards vaccines and governmental initiatives. Ministries of health, legislators, health planners, and other stakeholders must intensify efforts to disseminate accurate and reliable information regarding COVID-19 vaccines. By focusing on effective public health education and tailored interventions for specific demographic groups, it is possible to improve overall vaccine uptake and better manage the COVID-19 pandemic in Nigeria.

ACKNOWLEDGEMENTS

We thank the respondents of this study for their willingness to participate in the survey.