Abstract
Objectives
The resurgence in cases and deaths due to COVID-19 in many countries suggests complacency in adhering to COVID-19 preventive guidelines. Vaccination, therefore, remains a key intervention in mitigating the impact of the COVID-19 pandemic. This study investigated the level of adherence to COVID-19 preventive measures and intention to receive the COVID-19 vaccine among Ugandans.
Design, setting and participants
A nationwide cross-sectional survey of 1053 Ugandan adults was conducted in March 2021 using telephone interviews.
Main outcome measures
Participants reported on adherence to COVID-19 preventive measures and intention to be vaccinated with COVID-19 vaccines.
Results
Overall, 10.2% of the respondents adhered to the COVID-19 preventive guidelines and 57.8% stated definite intention to receive a SARS-CoV-2 vaccine. Compared with women, men were less likely to adhere to COVID-19 guidelines (Odds Ratio (OR)=0.64, 95% CI 0.41 to 0.99). Participants from the northern (4.0%, OR=0.28, 95% CI 0.12 to 0.92), western (5.1%, OR=0.30, 95% CI 0.14 to 0.65) and eastern regions (6.5%, OR=0.47, 95% CI 0.24 to 0.92), respectively, had lower odds of adhering to the COVID-19 guidelines than those from the central region (14.7%). A higher monthly income of ≥US$137 (OR=2.31, 95% CI 1.14 to 4.58) and a history of chronic disease (OR=1.81, 95% CI 1.14 to 2.86) were predictors of adherence. Concerns about the chances of getting COVID-19 in the future (Prevalence Ratio (PR)=1.26, 95% CI 1.06 to 1.48) and fear of severe COVID-19 infection (PR=1.20, 95% CI 1.04 to 1.38) were the strongest predictors for a definite intention, while concerns for side effects were negatively associated with vaccination intent (PR=0.75, 95% CI 0.68 to 0.83).
Conclusion
Behaviour change programmes need to be strengthened to promote adherence to COVID-19 preventive guidelines as vaccination is rolled out as another preventive measure. Dissemination of accurate, safe and efficacious information about the vaccines is necessary to enhance vaccine uptake.
Keywords: COVID-19, public health, epidemiology
Strengths and limitations of this study.
The study assessed the level of adherence to COVID-19 guidelines and intention to receive vaccination using a relatively large sample of adult Ugandan population with representation across different ages, genders and locations hence making generalisation possible.
Strict operational definition of adherence to non-phamacuetical measures (NPIs) against COVID-19 where all participants needed to always observe all the specific NPIs to be considered adherent.
There is, however, the limitation of social desirability bias which is more common with telephone interviews than face-to-face interviews, and this may result in overestimation of reported adherence and vaccination intent.
Causal inference between adherence and vaccination intent with other predictors cannot be established because the cross-sectional study design applied in this survey is not optimal for causal inference.
Participation in the study was voluntary and thus self-selection bias is possible and can affect the results.
Introduction
The incidence of SARS-CoV-2 infection has increased dramatically worldwide since December 2019, when the first case was detected among humans in Wuhan, Hubei Province, China.1 As of 6 May 2022, over 513 million people had been infected with SARS-CoV-2 and about 6.2 million people were reported dead. In Africa, over 8.8 million people had been infected and of these, 116 100 had died.2 Uganda confirmed its first COVID-19 case on 21 March 2020. As of 6 May 2022, Uganda had registered 164 118 COVID-19 cases and 3598 deaths (case fatality rate=2.19%). At the start of the pandemic, countries struggled to contain COVID-19 spread and instituted several preventive and control measures including travel restrictions, geographical lockdowns and quarantine, as well as enforcement of public health guidelines such as hand hygiene, use of face masks and social distancing.3 4 These measures were taken to prevent transmission of the virus as well as flatten the curve. The measures helped countries to contain COVID-19 for some time. However, the resurgence in many countries was evidence that adherence to the measures had waned in the population and adherence to COVID-19 public health measures alone could not contain COVID-19 transmission.5
One key strategy to stop the escalation of the COVID-19 pandemic was to develop and administer effective vaccines to the people. Towards the end of 2020, several vaccines against COVID-19 became available for public use including Pfizer/BioNTech, AstraZeneca-SK Bio, Janssen, Sinovac and Moderna which have since been given Emergency Use Listing approval by WHO.6 Currently, vaccination against COVID-19 is ongoing in all high-income countries as well as in most low/middle-income countries (LMICs). In Uganda, as of February 2021, the National Drug Authority approved the AstraZeneca vaccine and the vaccination was launched in March 2021 amidst reports of side effects such as dizziness, headache, weakness, fever, blood clots and even death in several countries.7
Widespread vaccination with high coverage of the eligible population is important in containing the COVID-19 pandemic.8 However, the availability of vaccines does not guarantee uptake as previous studies have highlighted.9–12 Concerns for not intending to take COVID-19 vaccines have been premised around worries about the newness and the speed at which vaccines were developed, safety as well as potential side effects.4 13 Some studies in sub-Saharan Africa (SSA) have shown low levels of vaccine acceptance.14 15 Such low acceptance levels could be attributed to an increasing infodemic of false information and rumours that make it difficult to find credible sources of information. Further, the low incident cases reported prior to the resurgence could lead to a low-risk perception among members of the public, thus contributing to hesitancy to get vaccinated. Given the high level of vaccine hesitancy reported at the global level and emerging concerns within communities in LMICs, assessing vaccine acceptance at the national level is essential.16
Besides vaccines, large-scale implementation of non-pharmaceutical interventions (NPIs) remains critical in COVID-19 prevention. This is especially crucial in the early phases of vaccination rollout before the attainment of herd immunity. It is also very important for vaccinated individuals to maintain adherence to these interventions since the full protective effect of the vaccine for individuals is attained after about 2 weeks of full vaccination17 18 and there is a possibility of breakthrough infections.19 However, evidence from SSA has indicated only moderate adherence to these public health measures. In Uganda, adherence to the COVID-19 measures was initially high20 but the resurgence of infections suggests complacency in adhering to these measures fuelled by the low-risk perception among the population. Regarding vaccination, there are limited data on acceptance and intention to receive the COVID-19 vaccine in Uganda. In this study, we sought to investigate the level of adherence to COVID-19 preventive measures and intention to receive COVID-19 vaccine among Ugandans to inform decisions about the enhancement of both vaccine uptake and other public health measures.
Methods
Study design and population
This study was part of a multicountry knowledge, attitudes and practices survey to understand the drivers of non-adherence towards COVID-19 preventive measures in eastern and southern Africa using computer-assisted telephone interviews. A total of 1053 adults were interviewed from 60 districts distributed in the four regions of Uganda (central, eastern, northern and western) in March 2021. Random selection of participants was done based on quotas set on age, gender and location proportionate to national COVID-19 case distribution statistics at the time of the study. We included adults 18 years and older with access to cell phones and who had been residents in the study district for at least 6 months. Persons who were unable to communicate or declined to participate were excluded from the study.
Sample size and sampling
The sample size of 1070 was determined using the Kish Leslie formula for cross-sectional studies21 with the following assumptions: two-sided Z statistic corresponding to a 95% CI (1.96), adherence level of 50% since no prior studies had measured the adherence to NPIs in the manner we planned to measure. We considered a 5% margin of error and a design effect of 2.5 to cater for the potential clustering of participants by region. We also considered a non-response rate of 10%.
Regarding sampling, quotas were set on age, gender and location (region) proportionate to national COVID-19 case distribution statistics at the time. A recent analysis of the COVID-19 cases had shown the following distributions (proportions) per quota22 as shown in table 1.
Table 1.
Distribution based on age, gender and location
| Regions | Gender | Age distribution | |||
| 18–35 (51%) | 36–55 (37%) | 56–65 (8%) | 65+ (4%) | ||
| Northern (n=162) | Female (n=65) | 33 | 24 | 5 | 3 |
| Male (n=97) | 49 | 36 | 8 | 4 | |
| Eastern (n=162) | Female (n=65) | 33 | 24 | 5 | 3 |
| Male (n=97) | 49 | 36 | 8 | 4 | |
| Central (n=583) | Female (n=233) | 118 | 86 | 19 | 10 |
| Male (350) | 178 | 130 | 28 | 14 | |
| Western (n=162) | Female (n=65) | 33 | 24 | 5 | 3 |
| Male (n=97) | 49 | 36 | 8 | 4 | |
Age distribution as follows: 18–35 (51%), 36–55 (37%), 56–65 (8%), 65+ (4%).
Gender: the data show that men were ~60% and women ~40%.
Location: central, 55%; eastern/western/northern, 15% each.
With these quotas in place, we used an Excel contact database and a computer-assisted program to randomly sample specific participants per each quota. This probability sampling approach allowed for all individuals in the population of interest to have a relatively equal chance of being selected for the survey.
Data collection
Data were collected through telephone interviews using a WHO survey tool for COVID-19,23 and this was pretested before actual data collection to address any ambiguities. The questionnaire captured data on sociodemographic characteristics, knowledge and perceptions of COVID-19 preventive measures, and uptake of COVID-19 preventive measures. In addition, data on perceptions of safety and efficacy of the available COVID-19 vaccines and intention to take the COVID-19 vaccine were collected.
Knowledge of COVID-19 was assessed by dichotomising a knowledge score based on Bloom’s cut-off24 using four questions. Each correct response was given 1 point and the wrong answer was given 0. Providing four correct responses to the four questions meant good knowledge, otherwise it would mean poor knowledge. Perceptions of the relevance of COVID-19 preventive measures were assessed on a Likert scale with four questions. Each of these was dichotomised with strongly agree/agree coded 1 while not sure, disagree or strongly agree coded 0. Responding appropriately to three of the four perception questions was considered satisfactory, otherwise it would be consider unsatisfactory.
Questions on how participants adhered to five COVID-19 guidelines were assessed with options: ‘always’, ‘sometimes’ and ‘never’. The five questions were based on guidelines including mass gathering, physical distancing, mask-wearing, respiratory etiquette and hand hygiene.
Perceptions of the safety and efficacy of COVID-19 vaccines were measured on a Likert scale with the options: ‘strongly agree’, ‘agree’, ‘not sure’, ‘disagree’ or ‘strongly disagree’.
Intention to take the COVID-19 vaccine was measured using a one-item question: ‘If a vaccine against COVID-19 becomes available, would you take it?’ whose response was categorised as ‘definitely yes’, ‘probably yes’, ‘probably no’ and ‘definitely no’. This was later dichotomised to ‘definitely yes’ (coded 1) and otherwise ‘no’ (coded 0). Data were collected on covariates such as participant age, gender, level of education, income and occupation. Perceived risk of COVID-19 as well as perceptions of the safety and efficacy of the COVID-19 vaccine were also obtained.
The questionnaire was translated into eight local languages spoken in Uganda (Luganda, Lusoga, Lunyakitara, Lugbara, Luo, Lugishu, Ateso, Ngakarimojong), and then programmed and uploaded to the Kobo Collect software installed on a tablet computer used for data collection. The full English questionnaire is available as online supplemental file 1.
bmjopen-2021-057322supp001.pdf (142.1KB, pdf)
Statistical analysis
Data were analysed using Stata V.16 (StataCorp, Texas, USA). Categorical data were summarised using frequencies and percentages and continuous data using the median and IQR. Our primary definition for adherence was compliance with all personal public health and social measures for the prevention of COVID-19 as guided by WHO,25 including frequent hand hygiene, physical distancing, respiratory etiquette, proper use of masks and avoidance of mass gatherings. We developed a composite variable for adherence to COVID-19 preventive guidelines consisting of five variables which were coded 0, 1 and 2 to represent no adherence, adhere sometimes and always adhere, respectively. We obtained a total score by adding the responses from the five questions and trichotomised the composite adherence variable, with those with a score of 10/10 considered to have good adherence, 8–9 out of 10 to have fair adherence and those scoring 7 and below as having poor adherence. We dichotomised adherence with code ‘1’ for good adherence (score 10/10) and code ‘0’ for fair/poor adherence (score 0–9) before running regressions.
We conducted a multivariable logistic regression analysis with the dichotomous composite adherence score as the outcome, adjusting for age and gender at a 5% level of significance. We also performed a modified Poisson regression analysis to assess the predictors of definite intention to receive the COVID-19 vaccine. For this analysis, vaccination intention was dichotomised into ‘definitely yes’ and ‘probably yes/probably no/definitely no’.4 A modified Poisson regression was preferred instead of logistic regression to avoid overestimating relative risk since vaccine intention was high (prevalence >10%) and to ensure robust standard errors.26 Before running the multivariable regressions, we separately ran several simple regressions consisting of the outcome (adherence or vaccination intent) and a single predictor at a time (online supplemental file 2). Variables that had p values of ≤0.2 in these simple bivariate models were considered in the final model building. Statistical significance was considered if variables had a p value of ≤0.05.
bmjopen-2021-057322supp002.pdf (142.9KB, pdf)
Patient and public involvement
No patients or members of the public were involved in the study design, setting the research questions, interpretation or writing up of results, or reporting of the research.
Results
Sociodemographic characteristics of participants
Of the 1070 individuals engaged to take part in the study, 1053 (98.4%) agreed to participate in the study and were included in the analysis. The median age of participants (IQR) was 34 years (18–80). Six hundred fifty-one (61.8%) of the respondents were male and half (50.3%) of the participants were aged between 18 and 34 years. Six hundred twenty-nine (59.8%) had attained secondary education as the highest level of education, 368 (35.0%) were self-employed and 235 (22.6%) earned US$13.7 or less per month. Additional descriptive data are provided in table 2.
Table 2.
Sociodemographic characteristics of study participants
| Characteristics | Frequency, n (%) |
| Age (median (IQR)=34 (18–80)) | |
| 18–34 | 530 (50.3) |
| 35–54 | 419 (39.8) |
| 55–64 | 73 (6.9) |
| 65+ | 31 (2.9) |
| Gender | |
| Male | 651 (61.8) |
| Female | 402 (38.2) |
| Residence | |
| Rural | 545 (51.8) |
| Urban | 508 (48.2) |
| Education | |
| No formal education | 79 (7.5) |
| Primary | 345 (32.8) |
| Secondary | 386 (36.7) |
| Tertiary | 243 (23.1) |
| Occupation | |
| Casual labourer | 56 (5.3) |
| Farmer | 260 (24.7) |
| Formally employed | 171 (16.2) |
| Housewife | 59 (5.6) |
| Self-employed | 368 (35.0) |
| Unemployed | 66 (6.3) |
| Student | 46 (4.4) |
| Others | 27 (2.6) |
| Monthly income (US$1=UGX3650) | |
| ≤13.7 | 235 (22.6) |
| 13.7–27.4 | 165 (15.9) |
| 27.4–54.8 | 197 (19.0) |
| 54.8–137.0 | 289 (27.8) |
| 137.0–274.0 | 98 (9.4) |
| ≥274.0 | 54 (5.2) |
| Household size (median (IQR)=5 (1–20)) | |
| <5 | 374 (35.5) |
| 5–10 | 585 (55.6) |
| >10 | 94 (8.9) |
| History of COVID-19 among self or close relatives or friends | |
| No | 794 (75.4) |
| Yes | 259 (24.6) |
| Reported history of chronic disease (cardiovascular disease, diabetes, HIV/AIDS, hypertension, etc) | |
| No | 804 (76.4) |
| Yes | 249 (23.6) |
UGX, Ugandan shilling.
Knowledge about COVID-19 and sources of information
When asked how COVID-19 spreads, most participants stated physical contact with infected persons (74.6%) and inhalation of infected droplets (70.0%). The major symptoms mentioned included: sneezing (78.9%), coughing (77.9%) and fever (71.7%). Nearly all (99.1%) participants knew that COVID-19 could be prevented. When asked about the COVID-19 preventive measures they knew, most mentioned mask-wearing (94.8%) and washing hands with soap and water or using alcohol hand rub or sanitiser (90.3%), while only half (51.6%) mentioned social distancing. The most trusted sources of information were radio (45.3%) and television (28.9%). Overall, 93.5% of the participants were considered to have high knowledge of COVID-19.
COVID-19 risk and severity perception
Participants had a high perception of susceptibility to COVID-19. Majority (80.3%) were worried about getting COVID-19 in the next few months and 685 (74.5%) agreed that the possibility of contracting COVID-19 was high if they did not get vaccinated. Eight hundred participants (76.0%) felt that if they got a COVID-19 infection, it would be severe. Two hundred seventy (25.6%) believed that they would gain lifelong immunity if they suffered from COVID-19 hence find no urgent need to take precautions. About the relevance of each of the COVID-19 preventive measures, 97.2% (1024), 94.9% (999) and 98.2% (1034) agreed that wearing masks, physical distancing and practising hand hygiene, respectively, were critical for preventing COVID-19. Overall, 89.7% had a positive perception of the preventive measures for COVID-19 (table 3).
Table 3.
Participants’ risk and disease severity perception about COVID-19 and its preventive measures
| Attributes | Strongly agree/agree | Strongly disagree/disagree/not sure |
| Risk and disease severity perception | ||
|
846 (80.3) | 207 (19.7) |
|
785 (74.5) | 268 (25.5) |
|
800 (76.0) | 253 (24.0) |
|
270 (25.6) | 783 (74.4) |
| Perception of preventive measures | ||
|
1024 (97.2) | 29 (2.8) |
|
999 (94.9) | 54 (5.1) |
|
1034 (98.2) | 19 (1.8) |
|
996 (94.6) | 57 (5.4) |
Uptake of COVID-19 preventive measures
Sixty-seven per cent of participants had been to a large gathering in the preceding 14 days. Regarding observance of the preventive measures, a physical distancing of at least 2 m was reportedly observed by 88.9% (928): 47.2% all the time and 41.7% sometimes; while wearing masks was observed by 97.3% (831): 69.0% always and 28.3% sometimes. Overall, 10.2% were considered to have good adherence to the COVID-19 prevention guidelines while 89.8% (946) were non-adherent. Participants were asked about the non-conventional approaches that members of their communities used to prevent COVID-19 infection. Four hundred forty-nine (42.6%) reported that their communities were using herbal remedies, 40.0% (421) were eating fruits and vegetables, and 13.8% (145) reported steaming using local herbs (table 4).
Table 4.
Uptake of COVID-19 preventive measures
| COVID-19 preventive measures | Frequency, n (%) |
| Been to a large gathering in the last 14 days* | |
| Yes | 710 (67.4) |
| No | 343 (32.6) |
| Maintain at least a 2-metre distance when interacting with other people* | |
| Yes | 439 (41.7) |
| No | 117 (11.1) |
| Sometimes | 497 (47.2) |
| Wear a mask in public and when coughing and sneezing* | |
| Yes | 727 (69.0) |
| No | 28 (2.7) |
| Sometimes | 298 (28.3) |
| Wash hand with water and soap and sanitise regularly* | |
| Yes | 682 (64.8) |
| No | 21 (2.0) |
| Sometimes | 350 (33.2) |
| Cover mouth and nose with hand, elbow or handkerchief when coughing or sneezing* | |
| Yes always | 693 (65.8) |
| Yes, only when necessary | 335 (31.8) |
| No | 25 (2.4) |
| Adherence levels to COVID-19 preventive measures | |
| Adherence (10/10 practice score) | 107 (10.2) |
| Non-adherence (<10 practice score) | 946 (89.8) |
| Non-conventional community preventive strategies against COVID-19 | |
| Use of herbal remedies like garlic or ginger | 449 (42.6) |
| Eating fruits and vegetables | 421 (40.0) |
| Steaming using local herbs | 145 (13.8) |
| Physical exercise | 82 (7.8) |
| Others include drinking alcohol, sunbathing, not admitting strangers, etc | 208 (19.8) |
| Nothing | 298 (28.3) |
*Used to calculate a composite COVID-19 prevention practice score.
Factors associated with adherence to COVID-19 preventive guidelines
Bivariable analysis found significant associations between adherence with region, chronic disease history and monthly income (online supplemental file 2). Using multivariable regression, we found the odds of adherence to preventive guidelines were lowest for participants in western (adjusted OR (aOR)=0.30, 95% CI 0.14 to 0.65), northern (aOR=0.28, 95% CI 0.12 to 0.92) and eastern regions (aOR=0.47, 95% CI 0.24 to 0.92) compared with the central region. Male respondents had 35% lower odds of adhering to COVID-19 guidelines than their female counterparts (aOR=0.65, 95% CI 0.41 to 0.99). Higher monthly income was associated with higher adherence to COVID-19 preventive guidelines; those who earned ≥US$274 (OR=2.31, 95% CI 1.14 to 4.58) had higher odds of adhering to all COVID-19 guidelines than those who earned ≤US$13.7.
The odds of adherence to guidelines were higher in participants who reported a history of chronic illness compared with those with no reported history of chronic illness (aOR=1.81, 95% CI 1.14 to 2.86) (table 5).
Table 5.
Factors associated with adherence to COVID-19 preventive guidelines
| Characteristic | Adherent (n=107) | Non-adherent (n=946) | Adjusted OR (95% CI) | P value |
| Region | ||||
| Central | 81 (14.7) | 472 (85.4) | 1 | |
| Eastern | 11 (6.5) | 158 (93.5) | 0.47 (0.24 to 0.92) | 0.027 |
| Northern | 7 (4.0) | 167 (96.0) | 0.28 (0.12 to 0.63) | 0.002 |
| Western | 8 (5.1) | 149 (94.9) | 0.30 (0.14 to 0.65) | 0.002 |
| Age | ||||
| 18–34 | 59 (11.1) | 471 (88.9) | 1 | |
| 35–54 | 38 (9.1) | 381 (90.9) | 0.75 (0.47 to 1.21) | 0.235 |
| 55–64 | 8 (11.0) | 65 (89.0) | 0.90 (0.39 to 2.07) | 0.808 |
| 65+ | 2 (6.4) | 29 (93.6) | 0.47 (0.11 to 2.13) | 0.322 |
| Gender | ||||
| Female | 50 (12.4) | 352 (87.6) | 1 | |
| Male | 57 (8.8) | 594 (91.2) | 0.65 (0.42 to 0.99) | 0.047 |
| Household size | ||||
| <5 | 47 (12.6) | 327 (87.4) | 1 | |
| 5–10 | 52 (8.9) | 533 (91.1) | 0.78 (0.50 to 1.23) | 0.296 |
| >10 | 8 (8.5) | 86 (91.5) | 0.96 (0.41 to 2.22) | 0.931 |
| Monthly income (US$) | ||||
| ≤13.7 | 18 (7.7) | 217 (92.3) | 1 | |
| 13.7–27.4 | 13 (7.9) | 152 (92.1) | 0.98 (0.46 to 2.11) | 0.968 |
| 27.4–54.8 | 17 (8.6) | 180 (91.4) | 1.04 (0.51 to 2.13) | 0.911 |
| 54.8–137 | 33 (11.4) | 256 (88.6) | 1.49 (079 to 2.81) | 0.216 |
| ≥137 | 25 (16.4) | 127 (83.6) | 2.31 (1.16 to 4.58) | 0.017 |
| Reported history of chronic disease | ||||
| No | 71 (8.8) | 733 (91.2) | 1 | |
| Yes | 36 (14.5) | 213 (85.5) | 1.81 (1.14 to 2.85) | 0.012 |
| Will be very sick if I get COVID-19 | ||||
| Strongly agree/agree | 77 (9.6) | 723 (90.4) | 1 | |
| Strongly disagree/disagree | 30 (11.9) | 223 (88.1) | 1.21 (0.76 to 1.93) | 0.428 |
| If I suffer from COVID-19, I cannot be infected again and will not need to take preventive precautions | ||||
| Strongly agree/agree | 33 (12.2) | 237 (87.8) | 1 | |
| Strongly disagree/disagree | 74 (9.4) | 709 (90.6) | 0.76 (0.48 to 1.21) | 0.249 |
Perception of efficacy and safety of COVID-19 vaccines
The majority (75.2%) indicated that getting the vaccine would make them feel less worried about contracting COVID-19. About 55.5% (584) were concerned about safety while 62.5% (658) had concerns about the efficacy of the COVID-19 vaccine.
Intention to take COVID-19 vaccine
Overall, 84.0% (887) participants reported that they were likely to get the SARS-CoV-2 vaccine if it became available, while only 16.0% (168) responded no. Specifically, more than half (57.8%; 609) responded ‘definitely yes’, followed by ‘probably yes’ (26.2%; 276). Only 9.3% (98) responded ‘probably no’ and 6.7% (70) ‘definitely no’. Major reasons for responding no to the vaccine included: worry about side effects (45.8%), little information about the vaccine (42.9%), the perception that vaccine was designed to harm them (31.0%) and that vaccine may not be efficacious (30.9%) (table 6).
Table 6.
Reasons for not intending to take the COVID-19 vaccine
| Attributes | Number of participants, n (%) |
| Reasons for not intending to take the COVID-19 vaccine (n=168) | |
| Vaccine not effective | 52 (30.9) |
| COVID-19 does not exist | 16 (9.5) |
| Vaccines designed to harm us | 52 (31.0) |
| Scared of vaccine side effects | 77 (45.8) |
| Body naturally strong to fight the virus | 19 (11.3) |
| Have little information about vaccine | 72 (42.9) |
| Already had COVID-19 so immune | 5 (3.0) |
| COVID-19 pandemic finished in the country | 2 (1.2) |
| Others | 13 (7.7) |
| No reason | 2 (1.2) |
Predictors of a definite intention to take a COVID-19 vaccine
At bivariable analysis, intention to receive vaccination was associated with region, age, fear of COVID-19 infection and severe disease and worries about side effects (online supplemental file 2). After controlling for potential confounders including age, participants from northern (Prevalence Ratio (PR)=1.24, 95% CI 1.09 to 1.41) and western regions (PR=1.36, 95% CI 1.20 to 1.54), respectively, were more likely to have a definite intention to take COVID-19 vaccine compared with those from the central region. Participants aged 55–64 years were more likely to have a definite intention to take the vaccine compared with those aged 18–34 years (PR=1.20, 95% CI 1.01 to 1.43). Concerns about the possibility of being infected with COVID-19 (PR=1.26, 95% CI 1.06 to 1.48) and developing severe disease (PR=1.20, 95% CI 1.04 to 1.38) were predictors of intention to get vaccinated. Those with concerns about the side effects of the vaccine were less likely to have a definite intention for vaccination (PR=0.75, 95% CI 0.68 to 0.83) (table 7).
Table 7.
Factors associated with a definite intention to take a COVID-19 vaccine
| Characteristic | Definitely yes (n=609) | Probably yes/probably no/definitely no (n=444) | Adjusted Prevalence Ratio (PR) (95% CI) |
P value |
| Region | ||||
| Central | 292 (52.8) | 261 (47.2) | 1 | |
| Eastern | 94 (55.6) | 75 (44.4) | 1.05 (0.90 to 1.23) | 0.508 |
| Northern | 114 (65.5) | 60 (34.5) | 1.24 (1.09 to 1.41) | 0.001 |
| Western | 109 (69.4) | 48 (30.6) | 1.36 (1.20 to 1.54) | <0.001 |
| Residence | ||||
| Rural | 322 (59.1) | 223 (40.9) | ||
| Urban | 287 (56.5) | 221 (43.5) | ||
| Age group | ||||
| 18–34 | 284 (53.6) | 246 (46.4) | 1 | |
| 35–54 | 252 (60.1) | 167 (39.9) | 1.09 (0.98 to 1.22) | 0.126 |
| 55–64 | 51 (69.9) | 22 (30.1) | 1.20 (1.01 to 1.43) | 0.047 |
| 65+ | 22 (71.0) | 9 (29.0) | 1.25 (1.00 to 1.57) | 0.058 |
| Occupation | ||||
| Casual labourer | 30 (53.6) | 26 (46.4) | 1 | |
| Farmer | 156 (60.0) | 104 (40.0) | 1.00 (0.77 to 1.31) | 0.993 |
| Formally employed | 109 (63.7) | 62 (36.3) | 1.12 (0.86 to 1.47) | 0.394 |
| Housewife | 27 (45.8) | 32 (54.2) | 0.75 (0.52 to 1.08) | 0.123 |
| Self-employed | 203 (55.2) | 165 (44.8) | 0.98 (0.76 to 1.28) | 0.890 |
| Unemployed | 45 (68.2) | 21 (21.8) | 1.22 (0.90 to 1.64) | 0.200 |
| Student | 22 (47.8) | 24 (52.2) | 0.92 (0.63 to 1.36) | 0.695 |
| Others | 17 (63.0) | 10 (37.0) | 1.02 (0.69 to 1.53) | 0.904 |
| Perception of COVID-19 preventive measure | ||||
| Poor perception | 53 (49.1) | 55 (50.9) | 1 | |
| Good perception | 556 (58.8) | 389 (41.2) | 1.14 (0.94 to 1.37) | 0.191 |
| Ever had experience with COVID-19 | ||||
| No | 450 (56.7) | 344 (43.3) | 1 | |
| Yes | 159 (61.4) | 100 (38.6) | 1.09 (0.97 to 1.22) | 0.136 |
| Reported history of chronic disease | ||||
| No | 453 (56.3) | 351 (43.7) | 1 | |
| Yes | 156 (62.7) | 93 (37.3) | 1.09 (0.98 to 1.22) | 0.124 |
| Concerned about getting infected with COVID-19 in the future | ||||
| Strongly agree/agree | 514 (60.8) | 332 (39.2) | 1.26 (1.06 to 1.48) | 0.007 |
| Strongly disagree/disagree | 95 (45.9) | 112 (54.1) | 1 | |
| Future changes before the vaccine are high | ||||
| Strongly agree/agree | 474 (60.4) | 311 (39.6) | 1.12 (0.98 to 1.29) | 0.097 |
| Strongly disagree/disagree | 135 (50.4) | 133 (49.6) | 1 | |
| Will be very sick if I get COVID-19 | ||||
| Strongly agree/agree | 489 (61.1) | 311 (38.9) | 1.20 (1.04 to 1.38) | 0.011 |
| Strongly disagree/disagree | 120 (47.4) | 133 (52.6) | 1 | |
| Concerned about side effects of the COVID-19 vaccine | ||||
| Strongly disagree/disagree | 310 (66.1) | 159 (33.9) | 1 | |
| Strongly agree/agree | 299 (51.2) | 285 (48.8) | 0.75 (0.68 to 0.83) | <0.001 |
Discussion
This study assessed reported adherence to COVID-19 preventive measures and intention to take the COVID-19 vaccine in a large, national survey in Uganda. We found that adherence to all COVID-19 preventive guidelines was low despite high knowledge levels on COVID-19, and its prevention and high-risk perceptions. Adherence to NPIs was higher among participants with high income and those with a reported history of chronic disease. More than half (57.8%) of the participants had a definite intention to receive the COVID-19 vaccine and the definite intention was influenced by age of participants, region of residence, perceived susceptibility to COVID-19 and concerns about the safety of the vaccine.
In this study, 93.5% of the participants had high knowledge about COVID-19 and its prevention. This finding is not surprising because this study was conducted 1 year after the COVID-19 pandemic was confirmed in Uganda and hence most people had obtained basic information on the disease. The level of knowledge in this study is comparable with what was reported in an earlier study in Uganda,20 and other studies in China27 and Vietnam28 but higher than what was reported in Malaysia,29 Ethiopia,30 South Africa31 and Bangladesh.32 The observed discrepancies in knowledge about COVID-19 might be explained by the differences in the way the knowledge variable was ascertained across studies; the differences in study populations33; timing of the study period34; the level of information exchange; the sample size involved and methods of data collection. For instance, in Ethiopia, the study was conducted among healthcare workers (HCWs) and observance of the preventive guidelines was based on a 3-point Likert scale and good compliance based on whether HCWs scored ≥75% or less.33 Many of the studies which reported low knowledge were conducted in the early phase of the pandemic and knowledge would more likely have increased since then.
Our findings indicate a high level of perceived susceptibility to COVID-19 among participants implying that public enlightenment in terms of not underestimating the possibility of outbreak resurgence may have had an impact and should be continued until the disease is eliminated. High-risk perception plays a crucial role in influencing compliance with the public health and social measures for the prevention of COVID-1935 36 and intention to receive vaccines.37 38 Participants with higher COVID-19 risk perception showed higher intentions to receive the COVID-19 vaccine but few adopted all non-pharmaceutical preventive guidelines. Further studies are needed to understand why high-risk perception did not translate into the adoption of public health guidelines and consistent adherence.
Radio and television were the main and most trusted sources of information on COVID-19 among the population. This could, in part, be attributed to the fact that most information on COVID-19 by the president of Uganda and interactive communications by the Ministry of Health (MOH) and partners was through mainly television and radio across the country hence making them popular. Radio and television ownership has also increased steadily in Uganda and most households have phones with radios which they use to access information on COVID-19. Our findings corroborate a previous Ugandan study among food vendors where radio and television emerged as major sources of information on COVID-1939 but contradict another study that showed that friends and personal experiences were the major sources of information, with social media and radio ranking third among Ugandans in the informal sectors.40 The latter study was however conducted before the COVID-19 pandemic. Given the increased misinformation on COVID-19, accurate information and facts on COVID-19 should be aired more on radio and television since these remain the most common and most trusted sources of COVID-19 information.
In this study, 71.7% of participants indicated the people in the community were using non-conventional approaches to prevent COVID-19. These approaches included using herbal remedies, steaming with local herbs, eating vegetables and fruits, and doing physical exercises. These strategies are not scientifically proven tools to prevent COVID-19 and should be addressed through educational messaging. Similarly, a healthy diet is important for broader health benefits, but there is no evidence that diet alone is protective against COVID-19 infection and this should also be addressed in education messaging.
In this study, only 10.2% of the participants adhered to all COVID-19 preventive guidelines. Adherence to some measures was relatively high; for instance, 69.0% reported wearing face masks always when going out and 64.8% always washed hands with soap, but only 41.7% reported maintaining a social distance of 2 m and 67% had been to a large gathering in the previous 14 days. The adherence level reported in our study is lower than that described in a previous study in Uganda.34 Our findings suggest complacency in complying with MOH preventive measures. At the time of conducting this study, few confirmed cases and deaths of COVID-19 were being reported daily; hence, the public could have relaxed the observance of the measures with the belief that the disease was under control. This highlights the need to strengthen risk communication strategies and pillars responsible for COVID-19 response, to avoid possibility of further resurgence. It is, therefore, important to strengthen enforcement of all COVID-19 preventive measures—physical distancing, hand hygiene and wearing masks—in order to control the pandemic and halt further viral transmission.
We also found that male participants had lower odds of adhering to all the COVID-19 guidelines than female participants. A recent study in the USA indicated that women were more likely than men to follow guidelines outlined by medical experts to prevent the spread of COVID-19.41 It is already known that men tend to have more challenges and less interest in taking up health behaviours.39 Focused strategies should, therefore, be designed to encourage men to adhere to the guidelines. The level of adherence could be related to the occupations, where in many cases more men than women do outdoor jobs and socialise more in groups; hence, observance of the guidelines may be less seriously taken by men. We found that, unlike the central region, participants from northern, eastern and western regions had lower odds of adhering to all the preventive measures. The fact that approximately 55% of the COVID-19 cases at the time were registered in the central region could suggest a high-risk perception among participants in the central compared with other regions. Interventions targeting behaviour change should put special emphasis on these other regions to cover aspects of risk perception.
Having a higher monthly income was related to higher odds of adhering to all the preventive guidelines. High incomes could be linked to higher education attainment which are important determinants of health. People with higher income can afford to procure masks and handwashing facilities and supplies for themselves making it easier to comply with all the preventive guidelines. A recent study on socioeconomic factors associated with self-protecting behaviour during the COVID-19 pandemic indicated that higher income influence the adoption of public health guidelines.42 It was argued that the adoption of the guidelines is a costly prospect, one that is easier for people with more income. People with low income should be prioritised when distributing free masks and hand hygiene supplies. More health education sessions are given to promote adherence to the recommended guidelines.
Further, we found that participants with a reported history of chronic disease were more likely to adhere to all the guidelines. It is not surprising that people with a history of chronic disease have better adherence because evidence indicates that they are at elevated risk of unfavourable outcomes such as severe disease and death.43 44 Campaigns to ensure sustained adherent behaviour among people with chronic illnesses are warranted and campaigns focused on those with no known chronic disease history should be intensified to raise risk perception among this group.
In this study, despite 84.0% expressing the intention to get vaccinated, only 57.8% had a definite intention to get vaccinated against COVID-19. Our findings are comparable with a study in China that found that 83.5% had the intention to get vaccinated against COVID-19, of which 30% had a definite intent,4 but contradicts another study in Malaysia in which intention to get vaccinated against COVID-19 was higher (94.3%), of which 48.2% had a higher definite intention.45 A good comparison of vaccination intention levels between countries may not be ideal due to the limited evidence available as well as differences in access to vaccines in the countries. It has been suggested that for herd immunity to be attained for COVID-19, more than 70% of the population needs to be vaccinated.46 It is therefore important that health education is intensified to increase people’s confidence in the vaccines so that they can get vaccinated as vaccines become available. Reported definite intention to take the vaccine was highest in northern and western regions. Sensitisation to promote COVID-19 vaccine acceptance should be intensified in the eastern and central regions of Uganda.
We found that older people (at least 55 years) were more likely to have a definite intention to take the vaccine compared with young people (18–34 years). This could be related to the knowledge that vaccines could protect old people more since people of advanced age have a higher risk of getting severe COVID-19 and other adverse outcomes than young people.47 Strategies to promote definite intent to take the vaccine should be continued in old people but they should also be intensified in young people who may have a belief that they have a strong immune system to fight off the COVID-19 infection.
Having concerns about the side effects of COVID-19 was associated with a low definite intention to take the vaccine. Our finding is consistent with that found in China in which concerns about side effects affected intention to take the vaccine.4 Worries about the side effects of the vaccine have been reported before whenever a new vaccine has been introduced.48 It should be noted that although COVID-19 vaccination needs to be rolled out countrywide, the fears raised about the vaccine underscore the need to emphasise facts and accurate information to the public about the safety and efficacy of the vaccine to dispel any rumours or misinformation surrounding the COVID-19 vaccines. Addressing these issues will result in increased confidence and reduced hesitancy to take the vaccines.
Participants who had high perceived susceptibility to the disease and those who felt they would get severe disease if they got SARS-CoV-2 infection were significantly more likely to have a definite intention to take the COVID-19 vaccine. One of the key drivers in people’s vaccination decisions is the risk they associate with the disease the vaccine protects against.49 Susceptibility perceptions are seen to be associated with emotional dimensions that often include fear and worry.50 Previous studies have also indicated a predictive effect of perceived risk on vaccination intentions.51 It is therefore important to keep emphasising in health education and sensitisation that COVID-19 is a real, dangerous and deadly disease so that people can take the vaccination seriously in addition to observing all the COVID-19 preventive guidelines.
The strengths of our study include a large, representative sample of the Ugandan population across age, gender and location. Some methodological limitations in this study include social desirability bias which is generally higher with telephone interviews compared with face-to-face interviews.52 Second, since our outcomes are based on self-report of behaviour (adherence and vaccine intention), there is possible social desirability bias, which would make participants potentially over-report socially desirable behaviours and the voluntary nature of the survey allows selection bias to creep in. Third, causal inference cannot be established with cross-sectional study designs. Despite these limitations, the study findings provide valuable information about the levels of adherence to recommended COVID-19 preventive guidelines and intention to take COVID-19 vaccines.
Conclusions
The study findings indicate a low level of adherence to COVID-19 preventive guidelines despite high knowledge about COVID-19. Male participants and those hailing from the east, west and northern regions had comparatively low adherence, while participants with reported chronic disease history and higher income had reported adherence levels to public health and social measures. Our findings suggest that interventions to improve adherence to COVID-19 preventive guidelines should target men, low-income earners, and people living in the northern, eastern and western regions of Uganda more. Over half of the participants intended to receive the vaccine. Higher perceived risk and severity of COVID-19 infection had a strong and positive effect on vaccination intention while concerns about the safety of the vaccine negatively influenced vaccination intention. Efforts should be directed to the promotion of a high definite intention to get vaccinated against COVID-19 by addressing the fears of side effects and doubts about vaccine effectiveness to enhance confidence and increase vaccine uptake among the population.
Supplementary Material
Acknowledgments
We thank the WHO Africa Regional Office, WHO AFRO, for funding this study. We thank Mr Innocent Komakech (WHO Uganda) for his administrative guidance during the design and implementation of the study. We are also indebted to the research assistants who collected good quality data as well as the study participants for sparing time to participate in the study.
Footnotes
Twitter: @SolomonWafula24, @TableyBasajjat1
Contributors: STW, JB-T and RKW conceptualised and designed the study. STW, IBM and JB-T performed data analysis and interpretation, and wrote the first draft of the manuscript. RKW, BS, SO, AC, MN, AT, RK and TB critically reviewed the analysis and the first manuscript draft. JB-T, AT and RKW provided technical and intellectual content review for the manuscript. All authors have read and approved the final version of the manuscript. JB-T was responsible for the overall content and acted as guarantor.
Funding: This work was funded by the WHO Africa Regional Office, WHO AFRO (award number: N/A).
Competing interests: None declared.
Patient and public involvement: Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review: Not commissioned; externally peer reviewed.
Supplemental material: This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.
Data availability statement
Data are available upon reasonable request. The data used for this study should be requested from the WHO Africa Regional Office.
Ethics statements
Patient consent for publication
Not required.
Ethics approval
Ethical approval was obtained from the Makerere University Higher Degrees Research and Ethics Committee (reference number: HDREC 926), and the Uganda National Council of Science and Technology (UNCST) (reference number: SS862ES). We obtained verbal informed consent from participants. Confidentiality was observed throughout the study.
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Associated Data
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Supplementary Materials
bmjopen-2021-057322supp001.pdf (142.1KB, pdf)
bmjopen-2021-057322supp002.pdf (142.9KB, pdf)
Data Availability Statement
Data are available upon reasonable request. The data used for this study should be requested from the WHO Africa Regional Office.