Gender and COVID-19 Vaccine Disparities in Cameroon

Abstract

Six months following the national launch of COVID-19 vaccinations in Cameroon, only 1.1% of the target population was fully vaccinated, with women representing less than one-third of the vaccinated population regardless of age, profession, or comorbidities. Hence, the aim of this study was to understand the low COVID-19 vaccination rate of women in order to enhance vaccine uptake. A cross-sectional study was conducted between July and October 2021 through an online survey. Additionally, a retrospective analysis of the Cameroon Ministry of Public Health (MINSANTE) database of the pandemic (COVID-19) for the period of March 2020 to October 2021 was simultaneously carried out. Our sample consisted of 249 responders aged between 18 and 50 years enrolled in the 10 regions of Cameroon, with 142 (57%) who were female. We assessed factors related to having been vaccinated against COVID-19 and predictors of COVID-19 vaccination among non-vaccinated people. Concerning COVID-19 vaccination, 39.2% were not vaccinated. Non-vaccination was statistically associated with being female, being a healthcare worker, fear of adverse effects, and not believing in the vaccine. In the qualitative analysis, women identified themselves as being anti-COVID-19-vaccine for several reasons, including doubts about the quality or safety of the vaccine; the perception that COVID-19 vaccines are presented as being an obligation; and regarding the multitude of vaccines on the market, the belief that there are “more local” effective alternatives to the vaccine. The implementation of the gender approach to COVID-19 vaccination is one factor influencing its effectiveness and sustainability.

1. Introduction

COVID-19 is an emerging respiratory disease caused by the highly contagious novel coronavirus (SARS-CoV-2) and was first detected in December 2019 in Wuhan, China [1,2]. This new virus has quickly spread globally, afflicting 215 countries. As of 13 June 2020, over 7.8 million cases and 430,000 deaths have been reported globally [3].

In Africa, the response has been challenged by fragile healthcare systems in limited infrastructure and resource contexts. This includes the lack of adequate surveillance to assess the scope of the outbreak and inadequate systems for the prevention, diagnosis, and management of a disease. Cases of COVID-19, as with other diseases, are broadly classified as suspected, probable, and confirmed [4].

In Cameroon, the first case confirmed on the 6 March 2020 was in a French national who arrived in Yaoundé. Since then, several preventive measures have been enacted and implemented in the country. These measures include the limitation of the number of passengers on public transportation; quarantine and care for infected people or suspected cases; prohibition of gatherings of more than 50 people; establishment of consumer flow regulations in markets and supermarkets; implementation of virtual meetings; avoiding close contact such as shaking hands or hugging; and covering the mouth when sneezing [5].

At the end of the year 2020, some vaccines against the disease were made available and approved for mass vaccination of populations. Since then, health authorities have initiated vaccination in their countries even though many have still lagged behind.

Cameroon’s national vaccination campaign was launched on 12 April 2021 with two types of vaccines: Sinopharm and AstraZeneca [6], with an aim to vaccinate at least 15 million people. Thirty days after the campaign was launched in Cameroon, it was unfortunate to notice that women constituted only one-third of the vaccinated population regardless of age, health conditions, and type of vaccine. Cameroon’s demographics of 2020 [7] showed, as in many countries in the world, that females were more represented than males in the non-vaccinated population, with a sex ratio of 100.06/100, which might jeopardize the COVID-19 vaccination rates in Cameroon. We carried out this study, the main objectives of which were to determine factors associated with the low vaccination rate in women compared to men and describe the COVID-19 epidemiological context in Cameroon. To achieve these objectives, we carried out a cross-sectional and analytical study in a Cameroonian population.

2. Methodology

2.1. Study Design, Period, and Setting

For the web survey, a cross-sectional observational study was conducted. It was conducted in Cameroon between July and October 2021. Cameroon is a country in Central Africa with an estimated population in 2020 of 26,545,864, among which 13,268,789 are women [7,8,9]. According to the WHO, there are nearly 1.1 doctors and 7.8 nurses and midwives per 10,000 inhabitants [10]. The country is divided into ten regions with heterogeneous sociodemographic characteristics.

A retrospective analysis of the Cameroon Ministry of Public Health (MINSANTE) database of the pandemic (COVID-19) for the period of March 2020 to October 2021 was simultaneously carried out to highlight the epidemiological data of the disease since the beginning of the pandemic in the country.

2.2. Study Population

Cameroonian residents who were aged 18 years or over, understood the content of the form, and agreed to participate in the study completed the questionnaire. Additionally, all participants whose data were recorded in the COVID-19 database of MINSANTE were included in this study.

2.3. Data Collection Tools and Procedures

The online survey was anonymous, administered in official languages (French and English), and hosted on Google Forms (Alphabet Inc., Mountain View, CA, USA). Data were collected using a pre-tested questionnaire [11]. This method was chosen because of its logistical advantages and its ease of use, especially in the context of restrictions due to the COVID-19 pandemic. Google Forms is a cloud-based data management tool used to design and develop web questionnaires. Data collection complied with the terms and conditions of Google Forms.

Data on the COVID-19 pandemic in the country were recorded on a daily basis across the national territory from various COVID-19 care centers disseminated throughout the country in a web platform called District Health Information Software (DHIS2 version 2.39) used by the Cameroon MINSANTE for national data collection of all programs and easily made available for extraction and analysis at all levels of the health pyramid.

2.4. Measures

The form of the web survey consisted of four sections: a briefing note with informed consent, sociodemographic characteristics, determinants, and suggestions. The briefing note included a brief introduction on the background, purpose, and voluntary nature of participation and anonymity and confidentiality statements. The 27 questions of the form were divided into three sections, namely 10 elements on sociodemographic characteristics, 14 on the determinants of vaccination against COVID-19, and 3 suggestions to increase vaccination coverage.

In the database of the Cameroon MINSANTE, sociodemographic, clinical, paraclinical, and prognostic data of COVID-19 patients were recorded in the DHIS2.

2.5. Data Processing and Analysis

Once the web questionnaire was completed online, the data were saved to a Google spreadsheet in an analyzable format [12]. However, the data were extracted into an Excel 2010 (Microsoft Corp., Redmond, WA, USA) sheet, where data curation and coding were carried out, and then imported into Statistical Package for Social Science (SPSS) version 26 (IBM, New York, NY, USA) to analyze and design different cross tables. The statistical difference between values of cells was assessed using a bilateral test of Fisher’s exact test. Only statistically significant variables (p-value 0.05) in the univariate logistic regression were included in the multivariate logistic regression to establish the strength of an association and control for possible confounding. Depending on whether a variable was in univariate or multivariate analysis, crude or adjusted odds ratios were presented, respectively, using the Wald test.

Data from the database were extracted from DHIS2 to an Excel 2010 form and then exported to SPSS Version 26 for further processing and analysis. The threshold of significance was set at 0.05, with confidence intervals (CI) at 95%. A qualitative analysis was conducted to assess the socio-anthropologic roots of vaccinal hesitancy among participants.

Ethical Considerations

The Ethical Review Board of the Faculty of Medicine and Biomedical Sciences of the University of Yaoundé approved the study under the ethical clearance N° 0129/UY1. In addition, we received administrative authorization from the Ministry of Public Health of Cameroon. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional review board of the committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent was obtained from all individual participants included in the study. The survey started with a consent statement, and participants who gave consent to willingly participate in the survey clicked the ‘Continue’ button and were directed to complete the self-administered questionnaire. Respondents were free to terminate the survey at any time, and no identifying information was captured.

3. Results

3.1. National Epidemiological Results on COVID-19 Cases and Death

From the start of the epidemic in March 2020 until October 2021, 79,861 confirmed cases of COVID-19 were recorded in the national database. The median age was 35 years, with an interquartile range of 23 to 40 years. They were mostly adults, with the most represented age group of 30 to 49 years comprising 38.3% followed by that of 50 years and over.

In a total of 76,434 confirmed cases in which the sex was known, it appears that the men were more affected than the women, with 54.6 % and 45.4 %, respectively, yielding a sex ratio of 1.2. Among affected women with COVID-19, 0.4% were pregnant.

Out of 50,580 cases whose evolution was recorded, 1232 deaths were reported, with a case fatality rate of 2.4%. The risk of death was slightly higher in women than in men, with an OR of 1.135 (CI: 1.012–1.274). Regarding age, 71.4% of deaths occurred in people aged 50 and over. The probability of death was 4.6 times higher in the elderly, and this difference was statistically significant (p = 0.001). Case confirmation could be made in 482 people who died at the time of notification, accounting for 0.8%.

3.2. COVID-19 Cases and Comorbidities

The elderly had more comorbidities than the young people. The majority of people with comorbidities were aged 50 and over (59.8%), and this difference was statistically significant (p = 0.001).

Out of the 46,587 forms filled out by health personnel, 3461 (7.4%) of them tested positive. Among healthcare workers affected by COVID-19, 25 of them died, with a resulting case fatality rate of 0.7%.

3.3. Web survey Results on COVID-19 Disparities

Demographic Characteristics

In total, 249 out of 583 subjects who were approached completed the online survey, yielding a response rate of 42.71%. Among 249 respondents enrolled from the 10 regions of Cameroon, 142 (57%) were female. They were aged 18 years old and over, with 133 (53.4%) aged between 25 and 34 years old. A majority of respondents were single (45%), followed by married people (41.8%). A total of 130 (52.2%) resided in the Centre Region, and 170 (68.3%) were healthcare workers (HWCs) (

Table 1. Sociodemographic characteristics of participants, n = 249.

Variable	Count (%)
Age
18–24	23 (9.2)
25–34	133 (53.4)
35–44	66 (26.5)
45–49	1 (0.4)
50+	18 (7.2)
Gender
Female	142 (57.0)
Male	105 (42.2)
Prefer not to say	2 (0.8)
Education
Primary	2 (0.8)
Secondary	23 (9.2)
University	224 (90.0)
Employment status
Self-employed	11 (4.4)
Unemployed	17 (6.8)
Students	37 (14.9)
Employed	183 (73.5)
Retired	1 (0.4)
Marital status
Single	112 (45.0)
Cohabitating	23 (9.2)
Divorced	3 (1.2)
Married	104 (41.8)
Prefer not to say	7 (2.8)
Religion
Catholic	115 (46.2)
Muslim	30 (12.0)
Protestant	78 (31.3)
Other	26 (10.4)
Region of residence
Adamawa	11 (4.4)
Centre	130 (52.2)
East	13 (5.2)
Far-North	8 (3.2)
Littoral	26 (10.4)
North-West	3 (1.2)
North	27 (108)
West	12 (4.8)
South-West	10 (4.0)
South	9 (36)
Having children
No	71 (28.5)
Yes	178 (71.5)
Healthcare worker
No	79 (31.7)
Yes	170 (68.3)
No	228 (91.6)
Yes	21 (8.4)

).

3.4. Descriptive Epidemiology

This study revealed that nearly 28.91% of participants had experienced sickness due to the novel coronavirus disease. The age group declared to be most affected by COVID-19 was 25–34 years with 38 (15.3%) cases followed by the age group of 34–39 years, and the difference between these age groups was statistically significant (p = 0.043). Among the 249 respondents, women were more affected than men, with a proportion of 44 (17.7%) cases. Single and married participants had almost the same proportion of cases estimated at 33 (13.3%) and 31 (12.4%), respectively, with no statistical difference (p = 0.87). People living with children reported more cases of COVID-19 (20.9%) than those without children (

Table 2. Epidemiology of COVID-19 among participants, n = 249.

Variables	Past History of Novel Coronavirus Sickness
	Yes	Percentage	No	Percentage	I Don’t Know	Percentage	p-Value *
Age							0.043 **
18–24	8	3.2	13	5.2	2	0.8
25–34	38	15.3	81	32.5	14	5.6
35–44	25	10.0	35	14.1	7	2.8
45–49	0	0	17	6.8	1	0.4
50+	1	0.4	7	2.8	0
Gender							0.42
Female	44	17.7	85	34.1	13	5.2
Male	28	11.2	67	26.9	10	4.1
Prefer not to say	0		1	0.4	1	0.4
Marital status							0.87
Single	33	13.3	65	26.1	14	5.6
Cohabitating	7	2.8	14	5.6	2	0.8
Married	31	12.4	66	26.5	7	2.8
Divorced	0		3	1.2	0
Prefer not to say	1	0.4	5	2.0	1	0.4
Underlying chronic disease							0.36
No	64	25.7	143	57.4	21	8.4
Yes	8	3.2	10	4.1	3	1.2
Having children							0.37
No	20	8.1	44	17.6	7	2.8
Yes	52	20.9	109	43.8	17	6.8

* bilateral p-value of the Fisher exact test. ** p < 0.05.

).

3.5. Vaccination Status

Out of the 249 study participants, 99 (39.8%) declared having received at least one dose of the COVID-19 vaccine. The age group of 25–34 years was the most vaccinated group (18.6%) followed by 35–44 years (14.5%). The association between age group and vaccination status was statistically significant (p = 0.001). A majority of participants were not vaccinated (60.2%), and the same age groups above were the most represented. Females were less vaccinated (41.0%) than males. A proportion of 36.1% of participants were vaccinated healthcare workers, and the association between being an HCW and vaccination status was significant (p < 0.001). There was a significant association between having children and vaccination status in the studied population (p = 0.004). People with children who were not vaccinated were the most represented (39.0%) (

Table 3. Vaccination status among sociodemographic and clinical groups, n = 249.

Variables	COVID-19 Vaccination
	No	Percentage	Yes	Percentage	p-Value *
Age					0.001 ***
18–24	20	8.0	3	1.2
25–34	87	34.9	46	18.6
35–44	31	12.4	36	14.5
45–49	7	2.8	11	4.4
50+	5	2.0	3	1.2
Gender					<0.001 ****
Female	102	41.0	40	16.1
Male	46	18.5	59	23.1
Prefer not to say	2	0.8	0	0
HCW					<0.001 ****
No	70	28.1	9	3.7
Yes	80	32.1	90	36.1
Marital status					0.22
Single	73	29.3	39	15.7
Cohabitating	16	6.4	7	2.8
Married	55	22.1	49	19.7
Divorced	1	0.4	2	0.8
Prefer not to say	5	2.0	2	0.8
Underlying chronic disease					0.64
No	136	54.7	92	36.9
Yes	14	5.6	7	2.8
Having children					0.004 ***
No	53	21.3	18	7.2
Yes	97	39.0	81	32.5
Past history of COVID-19					0.55
No	88	35.3	65	26.1
Yes	46	18.5	26	10.4
Don’t know	16	6.4	8	3.3

* Bilateral p-value of Fisher’s exact test. *** p < 0.01; **** p < 0.001.

).

3.6. Analytic Epidemiology

This study noted various factors associated with non-vaccination in the study population. After binary logistic regression analysis, several factors were identified to be significantly associated with non-vaccination. As risk factors: female gender (COR: 3.1; p < 0.001), age under 35 years (COR: 2.15; p = 0.004), having children (COR 2.64; p = 0.002), fear of adverse events (COR: 7.6; p < 0.001), no belief in the vaccine (COR: 17.04; p < 0.001), and being an HCW. The age between 35–44 years appeared to be protective in univariate analyses probably due to confounders (COR: 0.513; p = 0.019) (

Table 4. Global synthesis of associated risk factors to COVID-19 non-vaccination, n= 249.

Variable	COR	p-Value	AOR	95% CI	p-Value
Female gender	3.10	<0.001 ***	2.45	1.18–5.09	0.016 *
Age 25–34 years	1.41	0.188
Age 35–44 years	0.513	0.019 *	1.64	0.45–5.33	0.485
Age under 35 years	2.15	0.004 **	2.50	0.77–8.14	0.127
Single	1.50	0.124
Having children	2.64	0.002 **	1.60	0.71–3.2	0.260
Past history of COVID-19	1.28	0.368	-	-	-
COVID-19 cases in the immediate surroundings	1.22	0.474	-	-	-
Knowledge on an existing treatment	0.75	0.30	-	-	-
HCW	0.53	0.022 *	0.34	0.16–0.69	0.003 **
Fear of adverse event	7.61	<0.001 ***	7.77	3.00–20.08	<0.001 ***
No belief in the vaccine	17.041	<0.001 ***	13.32	3.56–76.43	0.001 **
Women with some doubts about vaccine content a	8.44	<0.001 ***	1.87	0.73–4.76	0.19
Health personnel with doubt about vaccine content a	9.40	<0.001 ***	3.97	1.29–12.25	0.016 *

Note: COR: Crude Odds Ratio in univariate analysis, AOR: Odds Ratio in multivariate analysis of significant variables in univariate analysis, * Significant at p < 0.05, ** Significant at p < 0.01, *** Significant at p < 0.001, ^a evaluate the existence of interaction between being a woman or healthcare personnel and having more doubts about vaccine contents than the rest of the population.

).

There was a covariation between female gender, being an HCW, and having some doubts about the vaccine content. This covariation was shown in bivariate analysis to be statistically significant for female gender (COR: 8.44; p < 0.001) and for HCWs (COR: 9.40; p = 0.001).

Multinomial logistic regression analysis showed that women were 2.5 (CI: 1.18–5.09) times more at risk of not being vaccinated than men. People experiencing fear of adverse events and with no belief about the vaccine content were 7.7 (CI: 3.00–20.08) and 13.32 (CI: 3.56–76.43) times more at risk of not being vaccinated than others, respectively. HCWs were 2.9 (AOR: 0.53; CI: 0.16–0.69) times less at risk of being unvaccinated. On the other hand, HCWs were significantly more susceptible to having doubts about the vaccine, and those with doubts were 3.91 (CI: 1.29–12.25) times more at risk of not being vaccinated than others (Table 4).

3.7. Female-Gender-Specific Associated Factors

We found that from 142 women enrolled in this study, only 40 (28.2%) were vaccinated against COVID-19. Evaluation of risk factors associated with non-vaccination specifically among women showed the following results. In bivariate logistic regression analysis, women having children (COR: 3.70; p = 0.007), fear of adverse events (COR: 5.41; p = 0.003), and doubts about vaccine content (COR: 14.61; p < 0.001) were significantly less likely to be vaccinated. On the other hand, being an HCW was a favorable factor for vaccine uptake (COR: 0.098; p < 0.001).

Multinomial logistic regression showed that women having some doubts about vaccine content were 5.44 times (CI: 1.42–20.86) more at risk of not being vaccinated than those without doubts. Fear of adverse events was also associated with non-vaccination but not statistically significant. Female healthcare workers were 6.6 times (AOR: 0.15; CI: 0.04–0.56) less at risk of not being vaccinated than non-HCW women (

Table 5. Specific factors associated with non-vaccination among female gender, n= 142.

Variable	COR	p-Value	AOR	95% CI	p-Value
Age 25–34 years	0.80	0.559	-	-	-
Age 35–44 years	0.70	0.424	-	-	-
Age under 35 years	1.39	0.408	-	-	-
Single	2.06	0.056	-	-	-
Having children	3.70	0.007 **	2.13	0.71–6.45	0.18
Past history of COVID-19	1.03	0.931	-	-	-
COVID-19 cases in the immediate surroundings	1,26	0.557	-	-	-
Knowledge on an existing treatment	0.85	0.683	-	-	-
HCW	0.098	<0.001 ***	0.15	0.04–0.56	0.005 **
Fear of adverse event	5.41	0.003 **	2.88	0.82–10.17	0.100
Woman with some doubts about vaccine content	14.61	<0.001 ***	5.44	1.42–20.86	0.014 *

Note: COR: Crude Odds Ratio in univariate analysis, AOR: Odds Ratio in multivariate analysis of significant variables in univariate analysis, * Significant at p < 0.05, ** Significant at p < 0.01, *** Significant at p < 0.001.

).

3.8. Associated Factors of COVID-19 Acceptability

Out of 150 non-vaccinated participants, only 56 (37.33%) had a willingness to receive the vaccine. Binary logistic regression revealed that the female gender had a lower willingness to get the vaccine if they were proposed a COVID-19 vaccine, but this result was not statistically significant (COR: 0.65; p = 0.317). Similar findings that were statistically significant were noted for those who had COVID-19 cases in their immediate surroundings (COR: 0.18; p = 0.007), no belief in the vaccine (COR: 0.080; p = 0.016), and no vaccine preference (COR: 0.14; p < 0.001) and for women having some doubts about vaccine content (COR: 0.13; p = 0.033).

Moreover, the results revealed that health professionals (COR: 3.20; p = 0.014) and people having Sinopharm vaccine preference (COR: 3.42; p = 0.033) had a higher willingness to receive COVID-19 vaccination if they were proposed one (

Table 6. Predictors of acceptability of later COVID-19 vaccine uptake, n= 249.

Variables	COR	p-Value	AOR	95% CI	p-Value
Female gender	0.65	0.317	-	-	-
Age 25–34 years	0.89	0.774	-	-	-
Age 35–44 years	1.48	0.410	-	-	-
Age under 35 years	0.65	0.317	-	-	-
Single	0.867	0.733	-	-	-
Having children	0.84	0.696	-	-	-
Past history of COVID-19	1.16	0.732	-	-	-
COVID-19 cases in the immediate surroundings	0.18	0.007 **	0.15	0.03–0.56	0.007 **
Knowledge on an existing treatment	0.82	0.667	-	-	-
HCW	3.20	0.014 *	1.71	0.55–5.31	0.350
Fear of adverse event	0.41	0.070	-	-	-
No belief in the vaccine	0.082	0.016 *	0.17	0.02–1.52	0.114
Janssen preference	3.35	0.18	1.5	0.31–7.33	0.611
Sinopharm preference	3.42	0.033 *	3.58	0.61–21.12	0.160
No vaccine preference	0.14	<0.001 ***	0.28	0.07–1.12	0.072
Woman with some doubts about vaccine content a	0.13	<0.001 ***	0.11	0.03–0.411	0.001 **
Health personnel with doubt about vaccine content a	0.37	0.061	-	-	-

Note: COR: Crude Odds Ratio in univariate analysis, AOR: Odds Ratio in multivariate analysis of significant variables in univariate analysis, * Significant at p < 0.05, ** Significant at p < 0.01, *** Significant at p < 0.001, ^a evaluate the existence of interaction between being a woman or health personnel and having more doubts about vaccine contents than the rest of the population.

).

Only two negative predictors were statistically significant in multinomial logistic regression analysis. People having had cases of COVID-19 in their immediate surroundings and women with some doubts about vaccine content were 6.6 and 9.1 times less susceptible to vaccination than others, respectively (Table 6).

3.9. Qualitative Analysis Result

Some informants identified themselves as being anti-COVID-19-vaccine and explained several reasons, including doubts about the quality or safety of the vaccines: “You must first know if the content of the vial is really a vaccine against COVID-19”; the fact that COVID-19 remains a disease of the “white”; “That they should not force Africans to get vaccinated when the disease kills white people much more”; and the fact that the vaccine is perceived or presented as being an obligation: “I am against an imposed vaccine”.

Another reason was the fact that there is a multitude of vaccines on the market: “The COVID-19 pandemic is real but the real problem arises with the variety of vaccines”; and “The efficacy difference in percentage of vaccines and different names generally creates doubt in people, especially women”. According to them, women are more insightful than men: “We women have much more wisdom in decision-making. One problem already has several vaccine proposals in such a short time, why? Let the people in charge of those vaccines first agree on one, do some testing and release the results over time, and then we’ll see”. Other informants finally suggested that there are alternatives to the vaccine: “It would be better to use naturopathy, to overcome this pandemic:” “Do not take any vaccine, take Ekouk and Mfol, it is effective”.

A few participants had no suggestions to share, either because they had no idea about it or because they felt it was a personal decision: “I have no advice for them. Everyone is free to engage in it or not”. Others, because they themselves are against the vaccine, stated: “For common vaccines, I can agree. But for COVID-19 I cannot encourage people even less women because, they are responsible for lives and their security”.

The people who were pro-COVID-19-vaccine thought that the vaccination of women should be obvious because: “For me, women are more vulnerable because of their fragility”; “She must protect herself and those around her since women remain at the center of many activities”. One respondent, however, underlined the incongruity of the question because according to him: “There is no difference for me, the same actions must be carried out in both sexes”.

Some respondents have suggested that we could improve the vaccination acceptance and uptake by ensuring their reliability through the implication of African companies in the manufacture of the COVID-19 vaccine, or by manufacturing vaccines for young people and pregnant women. They stated that we could also: “Distribute the same vaccine throughout the country’’ and ‘’ Introduce COVID-19 vaccine as routine vaccine”. This means “We can take advantage of pregnancy to let them be vaccinated”. It must not be forgotten to “Bring the vaccine closer to the population, in other words create more vaccination centers even in the neighborhoods”. Because: “The vaccination team does not cover a tenth of health areas”.

They stated a need to support vaccination; that is, “Provide financial motivation for vaccination. “They also stated a need to think about ways to:” Make compensation commitments in case the side effects exist”.

To improve women’s adherence to COVID-19 vaccination, some informants believed that it was necessary to: “First gain men’s confidence in the admissibility of globally credible and acceptable vaccines”. As an appropriate solution to implement, the majority identified “sensitization.’’ They also identified “Communication”. For upstream solutions, participants stated that: “We must first identify the reasons for their refusal and after that it will be easier to carry out campaigns to raise their awareness”. In order for women to be more receptive, it would be necessary to: “Engage female leaders at all social levels”. Therefore, “We need to develop better communication on COVID-19”. This can be presented in several ways: “Proximity sensitization”; “Targeted sensitization”; “Door to door sensitization”; “Community sensitization”; “Educational meeting”; and “Put the posters everywhere”.

More specifically, it is: “The need to make them understand that the vaccine is for both sexes and has no negative effects on women”; “Famous women who received the vaccine should communicate strongly about it” and “They need role models”; “Make videos with more actresses that show the benefits of the vaccine and develop messages that contradict the fake news about vaccination”; “Raise awareness, testify, remind people of the benefits of vaccination, give the right information on the risks on fertility, procreation, breastfeeding, etc.”; “I have published my photos of the vaccine action in associations and meeting, I do with my neighborhood comrades. I made them aware of vaccination benefits”; “Get closer to women’s associations, community meetings for women, put women at the front of the business”; “Good communication and essential messages with community leaders, religious, influencers and extend to all women layers”; “Focused sensitization and health education. Encouragement and no attempt at all at coercion or obligation. Government has to increase opportunities for sensitization of women and general public. But also, we have to be honest and produce very credible and convincing reports on how we have used COVID-19 funds, because this issue of mismanagement of COVID-19 funds has come to embolden earlier suspicion that there is no COVID-19 and that government is using it to get money from Europe and America and from monetary organizations”; “Raise awareness of the importance of the vaccine and reduce beliefs that the vaccine is harmful or lethal”; “Organize sensitization sessions in health facilities, in places of gathering (places of worship, markets, etc.), explain to men the need to have their girlfriends, wives, sisters, mothers, etc. vaccinated”; “deny fake news from the social media”; and “Strengthen pre and post vaccination counselling”.

“We recognize the good tree by the sweetness of its fruits, if we realize that the vaccine really protects with contamination drop in vaccinated countries like Israel, sensitization will be easy and convincing.” Statistics from good model countries such as Israel might just as well be convincing. However, the most drastic measure is to: “Make vaccination compulsory”.

In response to the second question of how to use social media to improve vaccine confidence and vaccine uptake, a few informants had no knowledge to share. Other respondents shared their doubts about the feasibility of this project: “Very difficult because we find too many rumors in social media”.

Some people thought that social networks are not suitable for impacting the population: “The media and Radio Stations are great sources of manipulation. The population has already understood it, that is why you will always see thousands of likes but few acts. “But according to some people, Social networks should rather help to sensitize people on the respect of barrier measures.” To improve confidence in vaccines and vaccine uptake, it is important that people: “Do not avoid the mistakes of scientists. One dose, two doses, three doses. Vaccinated people who still get contaminated by the disease etc.”.

Social networks are important channels of communication and networking between communities, and to use social networks in improving confidence in vaccines and vaccine uptake, informants stated: “Communicate regularly on: the role of vaccines, the advantages of prevention over treatment, the quality of the vaccine, the possible side effects and their management in Cameroon, indicate the vaccination points, schedules etc.”; “Post the comparative reports of a country affected by COVID-19 before and after taking the vaccine”; “By posting videos of people who have received the vaccines, videos that explain the types of vaccine”; “Aggressively invest social networks with messages, videos and images on the benefits of vaccination”; “Encourage more social groups to create their accounts in social media and let the leaders of such groups share their pics on how they already took the jab”; “Make videos from theatres to illustrate the benefits of COVID-19 vaccination and the harms of not doing so”; “By live sessions during the vaccination sessions in the sites and share them”; “Invite vaccinated and infected people to speak at a round table or a health program”; “By using our status to share positive images”; “Take pictures showing people who get vaccinated and who give good testimonials”; “By sending messages to our contacts informing them about the importance of the vaccine, by advertising through leaflets on the benefits of the vaccine”; and “The government itself should have their own specific social media platform, whose duty will be to scan social media for all the COVID-19 vaccine negative propaganda, and elaborate simple, clear, objective and convincing messages, reports, short videos or audios, brief social media slots to disperse the propaganda. To make info available to everybody. Social media is the most followed media today and we must be serious to get on with it”.

It emerges from the respondents’ answers that all communication through social media should be carried out transparently and by professionals, people who have been vaccinated, opinion leaders, or influencers trained for this purpose.

The respondents wished to point out that while social networks are important for information dissemination, professionals should take a closer look at the information circulating: “A lot of rumors and fake-news are disseminated through social networks”. They offered several solutions to this, including: “Set up at all levels, monitoring/listening committees for social networks”; “Strengthen the information system and rumor management”; “To counter information, that is to say deny what has been said with the help of experts in the field”; “prevent doctors and other health personnel who are against the vaccine to give their opinions on TV channels to discourage others”; “The state needs to control all the sterile information that can create social psychosis, if possible, completely suppress social media”; and “why not even punish those who spread fake news of the vaccines”.

4. Discussion

4.1. Epidemiology of COVID-19

As of October 2021, Cameroon registered 79,861 cases, with women being more represented, which could be explained by the high demand for healthcare among the female gender when they feel ill. In contrast, during the initial outbreak, in an epidemiological study of 425 coronavirus cases in Wuhan, 56% were male, and the median age of infected individuals was 59 years, which is more than the median age of 35 years found in this study [13,14]. The age group of 30–49 years was the most represented among COVID-19 cases. Cameroon being an African country with a young working population could explain the fact that the above age group is the most affected by COVID-19. A study carried out in February 2020 found that the 30–70-year-old age group represented 86.6% of COVID-19 cases in the world [14]. A case fatality rate (CFR) of 2.4% was computed in this study. This result is similar to 2.3% found in a study in February 2020 [14], inferior to the global CFR of 6.7% found in an African review in April 2020 [15]. Moreover, in Africa, countries such as Egypt, Algeria, Burkina Faso, and Morocco had CFRs above 5% [16]. A majority of COVID-19 deaths among cases were in the age group of 50 years and above; this could be explained by the fact that this age group is more susceptible to have underlying comorbidities that are risk factors of death due to COVID-19. In addition, our study found that a majority of COVID-19 patients with comorbidities were people aged 50 years and over. We recorded 0.7% of deaths among healthcare workers, which is close to 0.5% found in a meta-analysis in 2020 [17].

4.2. COVID-19 Vaccination Disparities

Vaccine hesitancy is an old phenomenon that represents a serious threat to global health, as shown by the resurgence of some infectious diseases (e.g., outbreaks of measles and pertussis) [18,19]. The huge leaps in developing efficacious and safe COVID-19 vaccines within a short period were unprecedented [20,21]. Nevertheless, COVID-19 vaccine hesitancy can be a limiting step in the global efforts to control the current pandemic, with negative health and socio-economic effects [22,23].

In this study, the aim was to highlight reasons for vaccination disparity and non-vaccination among Cameroonians and specifically among the female gender. We found that nearly 39.8% of participants had received at least one dose of COVID-19 vaccine, which is much higher than the national coverage estimated to be around 4% [24]. Some sociodemographic factors, such as sex, age, and having children, were associated with vaccine uptake in addition to some psychological factors, especially the perception of adverse events and doubts about the vaccine content of COVID-19 vaccines [25]. Our findings represent one of the first estimates of the uptake and acceptance of COVID-19 vaccines in Cameroon that can be used to plan COVID-19 vaccine uptake among the general public and especially targeting women.

Vaccinations are widely recognized as one of the most effective preventive measures in public health [26]. Vaccine hesitancy varies across time, place, and type of vaccine and is influenced by a variety of factors [27]. Therefore, it is necessary to assess vaccine acceptance of COVID-19 vaccines and the factors that influence it in each region in order to plan educational activities to increase vaccine acceptance. Previous studies conducted outside of Cameroon reported that various factors, such as sociodemographic factors, attitudes and beliefs regarding COVID-19 infection and vaccination, and political views, influence vaccine acceptance [28,29,30,31,32]. Our results showed that the participants aged between 25 to 34 years were the most represented, which could be due to the method of enrolment into the study of using social networks to share the questionnaire, as this age group is particularly connected on this form of communication according to Facebook Data [33].

Vaccine acceptance in Cameroon was lower among several sociodemographic groups, such as the female gender, adults aged 25–34 years, those having had COVID-19 cases in their immediate surroundings, those with no belief in the vaccine, those with no vaccine preference, and women having some doubts about vaccine content, which coincides with many previous studies [25,28,30,31,32,34]. In order to increase COVID-19 vaccine coverage in Cameroon, it may be important to ensure vaccination among these populations with low vaccine acceptance. Therefore, interventions targeted at modifying such health beliefs about COVID-19 may lead to improved vaccination rates.

People having had contact with a COVID-19 case had a lower willingness to receive the vaccine in contrast to the results of a USA study, where this group of individuals had a higher willingness to get the vaccine [35]; this suggests that the perception of this disease by the population may be quite different from one region to another due to sociocultural backgrounds. Moreover, other studies found similar results concerning women who had a lower willingness to get vaccinated [25,35,36]. We found a proportion of 37.73% of participants having a willingness to get vaccinated, which is lower than the findings of studies conducted in Japan [25] and the USA [37]. A global survey of 19 countries showed that 71.5% of the participants responded that they would receive a vaccine if it was proven to be safe and effective [34].

A total of 94 (62.67%) participants had a low level of willingness to protect others by getting themselves vaccinated. This may suggest that a certain number of people want to benefit from the indirect protection provided by the vaccination of other people without getting vaccinated themselves [25]. Therefore, trying to change people’s perceptions of the effectiveness of the COVID-19 vaccine and increasing awareness to willingly protect others by getting oneself vaccinated may be important in promoting vaccine acceptance.

4.3. Psychological Barriers Mentioned in a Global and Non-Specific Way

Vaccination hesitation can be attributed to a set of psychosocial factors observable outside of the religious context and the current state of health of individuals. In this study, we found that 60.2% of people were unvaccinated, and 50.2% were without a vaccination plan.

Lack of information: Not understanding and not knowing what to think about the need to be vaccinated can contribute to vaccination hesitancy. Contradictory opinions and an information deficit can generate some perplexity: why get vaccinated if, in one way or another, you can catch the virus and transmit it? Why vaccinate young people if they are less vulnerable to the virus? Not finding a satisfactory answer to these questions paralyzes thinking and decreases mobilization.

Anxiety and fears related to stings: The apprehension of needles or pain is sometimes so anxiety-provoking that it can lead to avoiding any situation directly or indirectly involving vaccination, sometimes to the point where the mere sight of vaccination pictures can be a source of anxiety. In an anxiety-provoking situation, everyone reacts differently. Some will be in action and find solutions, and others will confide in relatives or be more emotionally overwhelmed. Others will react in denial. Denial is an automatic, unconscious reflex that acts as a band-aid to control anxiety. In the pandemic context, this can be expressed as denial of the severity of the disease, denial of one’s own vulnerability to contract the virus, or even denial of the existence of the virus.

Feeling of rejection and exclusion: As social beings, we are extremely sensitive to rejection. Some individuals have had a life course in which experiences of rejection have been more present and painful than others. They feel more excluded from society and do not recognize themselves in the official discourse and the proposed standards. According to them, the announced health measures are perceived as “controlling”. When, like them, we feel neither represented nor listened to by the authorities and when we are parodied or criticized by other groups in society, we reactivate the wounds of a past already marked by rejection, and we replay them, leading to suffering. These people may also feel more excluded and may be less open to following recommendations. They are also likely to feel better understood by alternative and refractory voices that make them dare to hear that they are finally heard.

Dependence and conflict avoidance: Some people (women) are more dependent on the opinions of those close to them (their spouses). Relationship dynamics may lead a person to doubt themselves and trust the other person to make day-to-day decisions while seeking to minimize conflicts with them. This seems to be the case for women in the African and Cameroonian sociocultural context in particular. In these cases, the position and choice of the person will be influenced by the fact that a peer does not consider vaccination to be important.

Confidence crisis: The aforementioned factors may crystallize into greater mistrust of government sources, health authorities, and the pharmaceutical industry towards a crisis of confidence and mistrust of what is on offer. Conspiracy theories and the rejection of authority come to shape thought and identity. Some will need more explanation, and others will need to be accompanied when receiving the vaccine or have a space to feel listened to and accepted in their sense of irritation. Finally, to avoid feeling “controlled”, people will prefer to follow alternative recommendations, such as having regular screening tests, rather than receiving the vaccine. In order to offer relevant solutions and move forward collectively in this pandemic crisis, let us better understand everyone’s reactions in order to better guide the authorities in the transmission of information, as well as in the choice and presentation of measures. For a measure to be respected, one must know the underlying reasons for its rejection.

5. Limitations

There are some limitations in the present study. Firstly, subjects were recruited and surveyed online instead of in a face-to-face interview, which may lead to a potential risk of selection bias. Hence, people without internet access or who are unwilling to participate in online surveys could not be reached. The sample size of the web survey might have not been sufficient to detect the significance of some variables declared as statistically not significant. Additionally, during survey implementation, the absence of human interaction can encourage hesitation and make it difficult to differentiate junk mail from actual research. Secondly, psychological patterns linked to vaccine hesitancy were general and non-specific, and thus, there is a need for a more specific and in-depth study on the subject.

6. Conclusions

This study offers insights into reasons of women falling behind in the race to vaccinate against COVID-19. Concerns about vaccine safety is a major contributing factor. Vaccine equity and gender have a role to play in national health responses to COVID-19. The implementation of the gender approach to COVID-19 vaccination is one factor influencing its effectiveness and sustainability.