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Determinants of knowledge, attitudes, and practices of front-line health workers during the first wave of COVID-19 in Africa: a multi-center online cross-sectional study

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Abstract

Background: During its first wave of COVID-19 infection in sub-Saharan Africa, there was insufficient understanding of the pandemic among front-line health care professionals that has led to a misidentification, and mistreatment of affected patients, with a potential risk of contracting and spreading the disease. This study was carried out to determine the Knowledge, attitude, and practices (KAP) of front-line health workers (HWs) towards COVID-19 in Africa and their related factors. Methods: This was a multi-centers online cross-sectional study conducted over a 3-months study-period using a google survey link among front lines HWs involved in the COVID-19 response in 26 African countries. Chi-square test & logistic regression were used in the bivariate and multivariate analysis respectively to assess determinants of KAP. Statistical analysis was done using STATA version 16; all tests were two-sided with 95% confidence interval. Results: Five hundred and seventeen (517, 96.3%) consented to participate in this study from 26 African countries; 289 (55.9%) were male and 228 (44.1%) female. Overall, most of HWs, 379 (73.3%) showed poor knowledge about COVID-19 infection and preventive measures. In contrast, majority of them showed good attitude (89%) and practice (90.3%) towards prevention of COVID-19 infections. Knowledge varied among countries; Uganda had the greatest number of HWs with good knowledge. (OR = 28.09, p <0.0001) followed by Ghana (OR=10.92, p=0.001) and DRC (OR: 4.59, p=0.015). The cadre of HWs also influenced knowledge; doctors were the most knowledgeable as compared to other cadres (OR: 3.4, p= 0.005). Additionally, knowledge increased with increasing HWs’ education level (p=0.011). Attitude and practice were both influenced by HWs country of workplace (p=0.05 & p< 0.0001 respectively) and their cadre (p = 0.025 & p < 0.0001 respectively). Conclusions: Majority of the front-line HWs in the African region had an overall good attitude and practice towards COVID-19 infection and practice measures despite relatively poor Knowledge. The KAP is influenced by HWs country of workplace, their cadre and level of education.
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Determinants of knowledge, attitudes, and practices
of front-line health workers during the rst wave of
COVID-19 in Africa: a multi-center online cross-
sectional study
Larrey Kasereka Kamabu ( kamabularry@gmail.com )
1 Faculty of Medicine, Université Catholique du Graben, Butembo
Hervé Monka Lekuya
2 Department of Surgery, School of Medicine, Makerere University
Richard Newton Iranya
2 Department of Surgery, School of Medicine, Makerere University
Bienvenu Muhindo Kasusula
3 Department of Internal Medicine, Matanda Teaching Hospital,
Franck Katembo Sikakulya
4 Department of surgery, Kampala International University, Western campus
Saviour Kicaber
2 Department of Surgery, School of Medicine, Makerere University
Moise Muhindo Valimungighe
1 Faculty of Medicine, Université Catholique du Graben, Butembo
Sifa Katungu Nganza
1 Faculty of Medicine, Université Catholique du Graben, Butembo
Eric Sadiki Butala
6. Department of Obstetrics and Gynecology, Consolata Hospital Mathari,
Zacharie Muhindo Sikiminya
7. Department of ophthalmology, Kinshasa Teaching Hospital, Université de Kinshasa.
Louange Maha Kathaka
1 Faculty of Medicine, Université Catholique du Graben, Butembo
Dalton Kambale Munyambalu
4 Department of surgery, Kampala International University, Western campus
Agnès Kavira Katsioto
1 Faculty of Medicine, Université Catholique du Graben, Butembo
Thérèse Yenyi Ahuka Longombe
9 Department of Anesthesia and Critical Care, School of Medicine, University of Cheikh Anta Diop de
Dakar,
Bienfait Mumbere
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4 Department of surgery, Kampala International University, Western campus
Adelard Kalima Nzanzu
1 Faculty of Medicine, Université Catholique du Graben, Butembo
Frederic Kavughe
11. Department of Education and psychology, Faculty of Education and Psychology, Adventist
University of Lukanga, Lukanga,,
Thaddée Katembo Kambere
12. Department of Public health sciences, Faculty of Medicine, Adventist University of Lukanga,
Lukanga,
Ssebuufu Robinson
4 Department of surgery, Kampala International University, Western campus
Research Article
Keywords: Knowledge, Attitude, Practices, COVID-19, Frontline Health caregivers, Africa, survey
Posted Date: December 14th, 2021
DOI: https://doi.org/10.21203/rs.3.rs-1164116/v1
License: This work is licensed under a Creative Commons Attribution 4.0 International License. 
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Abstract
Background: During its rst wave of COVID-19 infection in sub-Saharan Africa, there was insucient
understanding of the pandemic among front-line health care professionals that has led to a
misidentication, and mistreatment of affected patients, with a potential risk of contracting and
spreading the disease. This study was carried out to determine the Knowledge, attitude, and practices
(KAP) of front-line health workers (HWs) towards COVID-19 in Africa and their related factors.
Methods: This was a multi-centers online cross-sectional study conducted over a 3-months study-period
using a google survey link among front lines HWs involved in the COVID-19 response in 26 African
countries. Chi-square test & logistic regression were used in the bivariate and multivariate analysis
respectively to assess determinants of KAP. Statistical analysis was done using STATA version 16; all
tests were two-sided with 95% condence interval.
Results: Five hundred and seventeen (517, 96.3%) consented to participate in this study from 26 African
countries; 289 (55.9%) were male and 228 (44.1%) female. Overall, most of HWs, 379 (73.3%) showed
poor knowledge about COVID-19 infection and preventive measures. In contrast, majority of them showed
good attitude (89%) and practice (90.3%) towards prevention of COVID-19 infections. Knowledge varied
among countries; Uganda had the greatest number of HWs with good knowledge. (OR = 28.09, p <0.0001)
followed by Ghana (OR=10.92, p=0.001) and DRC (OR: 4.59, p=0.015). The cadre of HWs also inuenced
knowledge; doctors were the most knowledgeable as compared to other cadres (OR: 3.4, p= 0.005).
Additionally, knowledge increased with increasing HWs’ education level (p=0.011).
Attitude and practice were both inuenced by HWs country of workplace (p=0.05 & p< 0.0001
respectively) and their cadre (p = 0.025 & p < 0.0001 respectively).
Conclusions: Majority of the front-line HWs in the African region had an overall good attitude and practice
towards COVID-19 infection and practice measures despite relatively poor Knowledge. The KAP is
inuenced by HWs country of workplace, their cadre and level of education.
Introduction
The emergence of Corona virus disease (COVID-19) in 2019 from Wuhan-China, and its exponential
transmission to all countries in the World, including the fty-two countries of Africa, present a delicate
situation for low-resource countries. This current pandemic has shaken the entire World [1-4, 5, 6].
During its rst wave, while millions of people worldwide stayed at home to minimize the transmission of
the COVID-19, most healthcare workers (HWs) remained at the forefront of the response to this pandemic.
They go to clinics and hospitals, exposing themselves to a high risk of COVID-19 [7]. In addition to
exposure to the pathogen, long hours of work, psychological stress, fatigue, social stigma and physical
abuse were some of the additional burdens faced by the HWs [8]. A recent study by Hakan E. et al., found
that 300,000 HWs from thirty-seven countries had already gotten COVID-19. In addition to the high
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number of infections, over 115,000 of HWs have already lost their lives around the World as of 22th
October 22, 2021. Of the thirty-seven countries surveyed, the United States had the highest coronavirus
infections among HWs with 114,500 infections(9). Mexico followed with a reported 78,200 infections
while France and Italy had 30,000 and 29,000 coronavirus infections, respectively(9). While the United
States had the highest number of infections, the rate of infections adjusted for the population size was
highest in Mexico, Italy, and France [9].
As of 16th October 2021, over242,801,421cases and4,929,826deaths have been reported globally (2.96
%). The USA is the most affected, with over 50% of cases and 60% of deaths reported in this region(10).
The United States of America, with over 45 million cases of COVID-19 and over 733,000 deaths, currently
constitutes the most infected country in the World [10]. Still, an overall decrease in the number of cases
and deaths across the region has been reported by 11% in the last 40 days. Despite the overall decrease
of cases in the region, Uganda reported an intensive community transmission in capital Kampala and an
increase of over 300% of cases; and similarly, an overall increase in the case number has been reported in
Namibia and Nigeria in term of 55% and 19% respectively [11,12]. Despite resource limitations in the
African health care system, COVID-19 seems to be contained and under control. Several hypotheses have
been fronted; one of them is the relatively younger population in the continent (more than 60% of the
population in Africa are below the age of 25). Other factors cited include low travel and outdoor living,
expertise in epidemic control from tackling other outbreaks, and cross-immunity from other coronaviruses
[13].
Despite governmental efforts to mobilize HWs to support the health systems, most of those health
professionals were not suciently educated about preventive measures of this novel disease and were at
a high risk of contracting and subsequently spreading the virus to uninfected patients who
seekassessment [6, 8, 14]. A study among HWs in Henan, China, revealed that over 80% of HWs had
sucient Knowledge of COVID-19 and correct practices regarding COVID-19 [15].  In Uganda, a study
done at Mulago and Kiruddu Hospitals reported 69% of HWs had good Knowledge, 21% had a positive
attitude, and 74% had good practices towards COVID-19 [14, 16]. Several studies reported that age and
education level were signicantly associated with good Practice and Knowledge towards COVID-19 [16-
18]. There is a paucity of evidence of the current KAP towards COVID-19 in sub-Saharan Africa, despite
several WHO materials, up-to-date, and governments' guidelines. Understanding front-line HWs' KAP and
possible risk factors help to improve the safety of both the HWs and the general population. This study
aimed to assess the KAP of the front-line HWs towards COVID- 19 during the rst wave of the pandemic,
and also to identify determinant factors of KAP towards COVID-19 pandemic.
Methods
Study design, setting, and participants: This was a cross-sectional descriptive study using an online
structured questionnaire (French and English versions), sent to the frontline HWs in several African
countries via emails between April 2020 and July 2020. The frontline HWs surveyed included nurses,
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doctors and other cadres (anesthesia and laboratory personnel) in any level of practice experience and
working in any level of African hospital involved in COVID-19 patient care.
Study instrument, variables and data collection:The online Google Form link was sent to frontline health
care givers via emails, or social media platforms (WhatsApp, Twitter, and Facebook) with a help of a
focal lead country person, and reminders were sent 3 times a week for duration of 4
months.Standardized and pre-tested screening tools and adjusted pre-validated questionnaire were used
to obtain information on the study variables. Questions and answers about COVID-19 in the webpage of
WHO and other previous studies [16, 23-26] were adapted to formulate the questionnaire for the interview.
A pilot study was carried out on 11 HWs from Benin, Ghana, Malawi and Niger, and adjustment were
made based on their opinions relating to the feasibility of the questionnaire, and the nal questionnaire
was reviewed by the authors accordingly. The nal questionnaire had four sections. The rst section
comprised of 7 questions on socio-demographic characteristics of the participants. The second section
included 12 questions regarding the Knowledge of HWs on COVID-19 using two points scale. Each
incorrect response weighed 0 point and 1 for correct responses. A HW who got sixty percent or more of
the responses correct was categorized as having a good knowledge while the one who got less than sixty
percent correct responses was categorized as having poor knowledge. The third section had 5 questions
assessing attitude of HWs in a Likert scale of agreement format [16, 25]. A HW who got sixty percent or
more of the responses correct was categorized as having a good attitude while the one who got less the
sixty percent, poor attitude. The fourth section included 5 questions regarding the practices of COVID-19.
The responses were: always, occasional, never, and neutral each weighing 3, 2, and 1 point respectively
for a given practice. Again, a cut of score of sixty percent or more differentiated good from poor
practice.As part of quality assurance, the most active email of each participant was collected to identify
duplicate responses. We used the random sampling to recruit the study participants.
Statistical analysis: Fully completed questionnaires were extracted from Google Forms and exported to a
Microsoft Excel 2016 for cleaning and coding. The cleaned data was exported to STATA version 16 for
analyses [16, 25]. The means and standard deviations were used to describe continuous data, while the
frequencies and proportions described categorical data. Chi-square test of independence was used in the
bivariate analysis to identify potential predictors of KAP. All variables in the bivariate analysis with p-
value < 0.2 were included in the multivariatelogistic regression model to assess determinants of KAP
towards COVID-19 African frontline health workers during the rst wave of COVID-19 pandemic. All
analysis were two-sided with 95 percent condence level. Results reported in crude and adjusted Odds
ratio.
Ethical considerations: The protocol has been cleared by the Integrated Multidisciplinary Research Center
Ethics committee (IMRCEC) of Adventist University of Lukanga (Campus Wallace, Lukanga, D.R. Congo)
(Protocol Number.02/2020), and all participants provided an informed consent, and their anonymity were
guaranteed.
Results
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Socio-demographic characteristic of study participants:A total of ve hundred and thirty-seven (537)
Health workers from 26 African countries responded to the survey. Five hundred and seventeen (517,
96.3%) consented to participate in the study. Majority of the HWs were from the Democratic republic of
Congo; DRC (48%), Uganda (11.6%), Algeria (11.0%), Ghana (7.2%) and 22.24% from the other countries
(See table 1).Table 2 shows the socio-demographic characteristics of the study participants.  Of the 517
health care givers, 289 (55.9%) were males and 228 (44.1%) females.Based on HWs’ cadre, 297 (57.4%)
of the HWs were doctors, 154 (29.8%) nurses and the rest 66 (12.8%) where other cadres (anaesthesia
personnel, laboratory technicians etc.). In terms of education level, 64.4% of the HWs were degree holders,
the least numbers were for certicate holders (2.9%).Overall, most of the HWs showed poor knowledge
about COVID-19 infection and preventive measures (73.3% and 26.7% for poor and good knowledge
respectively). In contrast, majority of them showed good attitude and practice measures towards
prevention of COVID-19 infections. (89% and 90.3% respectively).
Determinants of Knowledge of COVID-19 among healthcare givers:Generally, statistically signicant
determinants of knowledge of COVID-19 infection and prevention measures in the multivariate analysis
were HWs’ country of workplace, their cadre, and education level.
Algeria had the least number of HWs with good knowledge about COVID-19 while Uganda had the
greatest number with good knowledge. (OR = 34.09, p < 0.0001) followed by Ghana (OR=13.22, p <
0.0001). HWs from DRC were also more knowledgeable on COVID-19 than those from Algeria (OR = 4.59,
p=0.015). Compared to other cadres of HWs (Allied HWs), doctors were 3.26 times more knowledgeable
on COVID-19 infection and preventive measures (OR= 3.26, p = 0.005) while nurses were 36% less likely to
have good knowledge of COVID-19 infection and prevention measures compared to the allied health
caregivers although this difference was not statistically signicant (OR=0.64, p=0.383). Except for
certicate holders, knowledge of COVID-19 infection and prevention measures increase with increasing
level of education from diploma to master's level.
Determinants of attitudes towards COVID-19 among HWs:As shown in Table 6, differences in HWs’
attitudes towards COVID-19 infection and prevention measures were statistically signicant among the
various countries. All study participants (HWs) from Ghana showed a good attitude towards COVID-19
infection and preventive measures. Algeria had the least number of HWs with a good attitude compared
to those from Uganda (OR: 4.58, p= 0.046), DRC (OR: 3.95, p=0.013), and others (OR: 2.57, p=0.045).The
cadre of HWs also had a statistically signicant positive inuence on attitude towards COVID-19 infection
and prevention measures. Doctors were 3.6 times more likely to have a positive attitude than allied HWs.
Similarly, nurses were also 3.61 times more likely than allied HWs to have a positive attitude towards
COVID-19 infection and prevention measures (see table 6).Positive differences in attitude were also
noted among HWs of various age categories, sex, but these differences were not statistically signicant.
Determinants of the practice of COVID-19 preventive measures among HWs in Africa:Table 8 shows a
multivariate logistic regression model for determinants of the practice of COVID-19 preventive measures
among HWs in Africa. Overall, statistically signicant differences in terms of the practice of COVID-19
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preventive measures existed among HWs of the various countries. Algeria had the lowest number of HWs
with good practice of COVID-19 infection and prevention measures as compared to Uganda (OR 55.63, p
< 0.0001), DRC (OR: 19.72, p < 0.0001), Ghana (OR: 6.00, p = 0,009) and others (OR= 11.60, p<0.0001).
Statistically signicant differences in the practice of COVID-19 preventive measures also existed among
various cadres of HWs in Africa. Both doctors (OR: 8.60, p < 0.0001) and nurses (OR: 4.25, p < 0.003)
showed good practice of COVID-19 preventive measures compared to Allied (other) cadres of HWs.Good
practice of COVID-19 preventive measures also varied among HWs of different religions, and education
levels but these differences were not statistically signicant.
Relationships between knowledge, attitude, and practice of COVI-19 infection and prevention among HWs
in Africa:Tables 9, 10, and 11 show respectively, the inuence of knowledge on HWs’ attitude, knowledge
on practice, and attitude on HWs practice of COVID-19 infection and prevention measures. Adjustments
were made for confounding socio-demographic characteristics.Good knowledge of COVID-19 infection
and prevention measures had a statistically signicant positive impact on HWs attitude (OR:3.52, p =
0.037). Knowledge also positively impacted HW’s practice of COVID-19 prevention measures, but this
relationship was not statistically signicant (OR: 2.21, p = 0.189).Similarly, a good attitude had a highly
statistically signicant positive relationship with good practice of COVID-19 prevention measures
(OR:4.66, p < 0.0001).
Discussion
This study aimed to describe and establish the determinants of frontline health workers' Knowledge,
attitudes, and practices during the COVID-19rst wave in Africa and their related factors.Five hundred
and thirty-seven (537) Health workers (HWs) from 26 African countries responded to the survey.The
study showed that most HWs had poor Knowledge(73.3%)about COVID-19 infection and preventive
measures. This could be because COVID-19 is a new infectious disease in Africa.This poor knowledge
would cause rapid spread of the disease, nosocomial contamination, and exposing the lives of several
patients [1]. In addition, this misunderstanding would contribute to the spread of the virus to uninfected
patients who seek an assessment [6, 7, 12]. Frontline HWs are directly exposed to SARS-CoV-2 infections.
The risk of acquiring COVID-19 is higher among HWs compared to the general population [27].In
addition, this nding highlights the knowledge gap among African HWs and could explain the major
barriers to infection control in the African region. Therefore, most HWs had not encountered it in their
practice,this agrees with a study done among HWs in Ethiopia on Ebola [27]. However, since Africa has
experienced several deadly infectious diseases in the past, most of the HWs demonstrated a good
attitude(89%)and(90.3%)practicemeasures towards preventing COVID-19infections.This nding
agrees with a study conducted in Pakistan which reported a high positive attitude among HWs about
COVID-19 [27], but higher than ndings reported in Uganda and Ethiopia with 21% and 35% respectively
[16, 28].
Generally, statistically signicant determinants of knowledge of COVID-19 infection and prevention
measures in the multivariate analysis were HWs’ country of work, their cadre, and education level. This
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nding differs from the study by Mulusew Andralem where age less than 34 years, rural residence and
access to infection prevention (IP) training were determinants of knowledge of HW towards COVID-19 in
Ethiopia [29]. This study revealed that Algeria had the least number of HW with good knowledge about
COVID-19 while Uganda had the greatest number of HWs with good knowledge. (OR = 34.09, p < 0.0001)
followed by Ghana (OR=13.22, p < 0.0001). HWs from DRC were also more knowledgeable on COVID-19
than those from Algeria (OR = 4.59, p=0.015).Compared to other cadres of HWs (Allied HWs), doctors
were 3.26 times more knowledgeable on COVID-19 infection and preventive measures (OR= 3.26, p =
0.005) while nurses were 36% less likely to have good knowledge of COVID-19 infection and prevention
measures compared to the allied health caregivers although this difference was not statistically
signicant (OR=0.64, p=0.383).The study also showed that in most countries, doctors were more
knowledgeable on COVID-19 compared to other cadres of HWswhich showed a similar result with the
study by Olum et al [16].This could be because doctors are always the rst to contact patients, which
could have prompted them to read more about the novel COVID-19 to better their Knowledge for
diagnosis and prevention of the disease.This is consistent with other studies whereby clinical HWs were
more knowledgeable on COVID-19 than their non-clinical counterparts[26]. Except for certicate holders,
knowledge of COVID-19 infection and prevention measures increase with increasing level of education.
This nding agrees with the nding of Kassie and colleagues [30].Good knowledge about COVID-19 is
correlated with having a higher educational status because of increased opportunity to access local and
international information, mini-round, seminars, lectures, research, conference, and knowledge. These
results are different from other studies which reported that the majority of frontline HWs use social media
to seek information about COVID-19 [16, 27, 35, 36].This study showed that 89% of participants had a
positive attitude towards COVID-19. This nding agrees with a study conducted in Pakistan which
reported a high positive attitude among HWs about COVID-19 (15). This result is higher than the ndings
reported in Uganda and Ethiopia in term of 21% and 65.7% respectively [8, 14, 25, 29]. This nding could
be explained by the fact that Africa has experienced several deadly infectious diseases in the past, most
of the HWs demonstrated a good attitude (89%) and (90.3%) practice measures towards preventing
COVID-19 infections. This statement is conrmed by a multivariate positive logistic regression found
between attitude and practice in this study. The above nding of positive attitude among African frontline
HWs is corroborated with the ndings of Bhagavathula et al. who revealed that 78% of HWs, had positive
attitude about COVID-19 [26].
Interestingly, the factors positively associated with Attitude of frontline HWs towards COVID-19 in Africa
were countriesof workplaceand cadre of HWs.All study participants from Ghana showed good attitude
towards COVID-19 preventive measures. This nding corroborates with previous studies [32-34]. Algeria
had the least number of HW with good attitude compared to those from Uganda (OR: 4.58, p= 0.046),
DRC (OR: 3.95, p=0.013) and others (OR: 2.57, p=0.045). The cadre of HWs also had a statistically
signicant positive inuence on attitude towards COVID-19 infection and prevention measures. Doctors
were 3.6 times more likely to have a positive attitude than allied HWs. Similarly, nurses were also 3.61
times more likely than allied HWs to have a positive attitude towards COVID-19 infection and prevention
measures (see table 6). Positive differences in attitude were also noted among HWs of various age
Page 9/26
categories, sex, but these differences were not statistically signicant. These results are similar with other
surveys [15, 22]. The cadre of HWs also had a statistically signicant positive inuence on attitude
towards COVID-19 infection and prevention measures. Doctors were 3.6 times more likely to have a
positive attitude than allied HWs. Similarly, nurses were also 3.61 times more likely than allied HWs to
have a positive attitude towards COVID-19 infection and prevention measures (see table 6).Positive
differences in attitude were also noted among HWs of various age categories, sex, but these differences
were not statistically signicant.
In addition, the survey found that 90.3 % of participants had good practices regarding COVID-19. This
nding has revealed a good practice among African HWs. This result corroborates with previous studies
[29]. Overall, statistically signicant differences exist among HWs of the various countries in terms of
practice of COVID-19 preventive measures. Algeria had the lowest number of HWs with good practice of
COVID-19 infection and prevention measures as compared to Uganda (OR 55.63, p < 0.0001), DRC
(OR:19.72, p < 0.0001), Ghana (OR: 6.00, p = 0,009) and others (OR= 11.60, p<0.0001). Statistically
signicant differences in practice of COVID-19 preventive measures also existed among various cadres of
HWs in Africa. Both doctors (OR: 8.60, p < 0.0001) and nurses (OR: 4.25, p < 0.003) showed good practice
of COVID-19 preventive measures compared to Allied cadres of HWs. Good practice of COVID-19
preventive measures also varied among HWs of different religions, and education levels but these
differences were not statistically signicant. The results of this could inform policy makers on the
practice of African frontline HWs towards SARS-CoV-2 infections. The ndings by providing a more
precise assessment of the magnitude of good practice among frontline HWs, offer an additional robust
knowledge in literature. However, the determinants of practice towards COVID-19 identied in this study
differe from those revealed by Mulusew Andualem where rural residence, facility type, access to IP
training, presence of IP guidelines, knowledge about COVID-19, having chronic illnesses, lack of protective
equipment (PPE), and high workload were factors of COVID-19 prevention [29].
Correlations among Knowledge, attitude and practice of COVID-19 infection measures showed that good
Knowledge of COVID-19 infection and prevention measures impacted HWs attitude and practice on
COVID-19 preventive measures. Similar ndings werealsoreported inprevious studies [27, 29, 30]. This
further emphasizes the need to have all HWs handling COVID-19 patients better trained about the disease
for better patient health care outcomesand supplied with all the necessary PPEs toensure that HWs do
not get infected with the virus when handling patients [29, 31].
Limitation of the study: This study collected data from 26 countries in Africa. This means that our study
ndings could be truly representative of the KAP of HWs from across Africa. However, we acknowledge
that some countries' responses were fewer than others, which could have affected the study ndings. As
the area of study was bigger and nancial constraint, we didn’t nd adequate sample size to include in
our study which could help us to assess better knowledge, attitude and practices of African frontline
HWs. Then, the study assessed knowledge and attitude and practice, it may not necessarily reect the
actual attitude, practice and that people comply with. The best way to assess practice could be by daily
Page 10/26
observation of African frontline HWs. Despite these limitations, our ndings provide valuable information
about African frontline HWs’ KAP regarding COVID-19.
Conclusions
Majority of the frontline HW in Africa had an overall good attitude and practice towards the COVID-19
infection and prevention measures despite a comparatively poor knowledge about the disease. A good
knowledge of COVID-19 infection and prevention measures however, positively impacted HWs attitude
and practice on COVID-19 preventive measures. Determinants of knowledge of COVID-19 infection
prevention measures among HWs include, country of workplace, cadre and level of education while
country of workplace and HWs’ cadre were the determinants for both attitude and practice.  Promoting
inter-state bench-marking and experience sharing among African countries in addition to regular refresher
trainings for HWs could help to enhance their KAP towards COVID-19 infection and prevention measures.
List Of Abbreviations
OR: Odds ratio; CI: Condence interval; HW: Health worker; KAP: Knowledge-Attitude-Practice.
Declarations
Ethics approval, consent to participate and for publication: Before collecting data, Ethical approval has
been cleared by the Integrated Multidisciplinary Research Center Ethics committee (IMRCEC) of Adventist
University of Lukanga (Campus Wallace, Lukanga, DRCongo). (Protocol Number.02/2020). The study
was conducted according to the Declaration of Helsinki and all participants signed a written informed
consent. Participants consented for Publication.
Competing interests: Authors declare no competing interests.
Availability of data and materials:The datasets generated during and analyzed during the current study
are not publicly available due tolegal and ethical reasonsbut are available from the corresponding
author on reasonable request.
Funding Statement:No funding is to be disclosed.
Author contributions:LKK conceived and designed the study and wrote the rst draft of the manuscript.
LKK, HML, ESB, ZMS, DKM, BMK, SKN, FKS, MMV, LMK, AKK, YALT, BMV, undertook the data collection
and coordinated of the activities in different countries; LMK and RNI did the statistical analysis. KS, HML
and LKK discussed the ndings. LKK, HML, RNI, BMK, AKN, FK, LMK. ESB, FK, TKK did the manuscript
correction, critical review of the nal manuscript and LKK and SR did the supervision of the work. All
authors contributed in intellectual content and approved of the nal manuscript. All authors have read
and agreed to the nal manuscript.
Page 11/26
Acknowledgments:The authors would like to thank all respondents for their voluntary participation and
cooperation in this study. LK is grateful to the
Uganda government
through the
Excellence scholarship
program under Ministry of Health Sponsorship in the FY 2020/2021
HML and SKN are thankful to the
Else-Kröner-Fresenius-Stiftung
,
Holger-Poehlmann-Stiftung
and the NGO
Förderverein Uni Kinshasa
e.V
.,
f
UNIKIN through the Excellence Scholarship Program ”Bourse d’Excellence Bringmann aux Universités
Congolaises, BEBUC”.
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Tables
Page 15/26
Table 1:Distribution of frontlines COVID-19 HWs by country of workplace.
Country Frequency (n) Percentage (%)
Algeria 57 11.0
Benin 14 2.7
Burkina Faso 2 .4
Burundi 8 1.5
Cameroon 1 0.2
Chad 1 0.2
Congo Brazzaville 3 0.6
DRC 248 48.0
Egypt 9 1.7
Ethiopia 1 0.2
Gabon 1 0.2
Ghana 37 7.2
Guinea 2 0.4
Ivory Coast 3 0.6
Kenya 10 1.9
Libya 4 0.8
Malawi 1 0.2
Mali 1 0.2
Morocco 2 0.4
Niger 3 0.6
Nigeria 3 0.6
Rwanda 5 1.0
Senegal 25 4.8
South Africa 11 2.1
Tanzania 5 1.0
Uganda 60 11.6
Table 2: Socio-demographic characteristics of frontlines COVID-19 HWs
Page 16/26
Socio-demographic characteristic Frequency: n (%)
Age category
< 21 years 16 (3.1)
21-30 years 180 (34.8)
31-40 years 167 (32.3)
41-50 years 93 (18.0)
51-60 years 47 (9.1)
Sex 
Male 289 (55.9)
female 228 (44.1)
Cadre of HWs
Allied HW (others) 66 (12.8)
Nurses 154 (29.8)
Doctors 297 (57.4)
Education level of HWs
Certificate 15 (2.9)
Diploma 54 (10.4)
Degree/Bachelors 333 (64.4)
Masters 81 (15.7)
Others 22 (4.3)
Marital status of HWs
Single 218 (42.2)
Married 299 (57.8)
Religion of HWs
Muslim 82 (15.9)
Christians 396 (76.6)
Jehovah’s witness 16 (3.1)
Others 23 (4.4)

Table 3:Bivariate analysis showing determinants of Knowledge towards COVID-19
infections & prevention.*-
p value from chi-square analysis.
Page 17/26
Knowledge category
Variables Poor: n (%) Good: n (%) p-value*
Country of workplace < 0.0001
 Algeria 53 (93.0) 4 (7.0)
 DRC 192 (77.4) 56 (22.6)
 Uganda 17 (28.3) 46 (71.7)
 Ghana 21 (56.8) 16 (43.2)
 Others 96 (83.5) 19 (16.5)
Age category 0.216
 < 20 years 15 (93.8) 1 (6.2)
 21-30 years 125 (69.4) 55 (30.6)
 31-40 years 120 (71.9) 47 (28.1)
 41-50 years 70 (75.3) 23 (24.7)
 51-60 years 37 (78.7) 10 (21.3)
Sex category 0.170
 Female 205 (70.9) 84 (29.1)
 Male 174 (76.3) 54 (23.7)
Cadre of HW < 0.0001
 Others (Allied HW) 56 (84.8) 10 (15.2)
 Nurses 141 (91.6) 13 (8.4)
 Doctors 182 (61.3) 115 (38.7)
Education level < 0.0001
  Certificate 13 (86.7) 2 (13.3)
 Diploma 49 (90.7) 5 (9.3)
  Degree/Graduate 249 (74.8) 84 (25.2)
 Masters 46 (56.8) 35 (43.2)
 Others 22 (64.7) 12 (35.3)
Marital status 0.811
 Single 161 (73.9) 57 (26.1)
 Married 218 (72.9) 81 (27.1)
Religion of HW 0.195
 Muslim 66 (80.5) 16 (19.5)
 Christian 282 (71.2) 114 (28.8)
 Jehovah’s witness 14 (87.5) 2 (12.5)
 Others 17 (73.9) 6 (26.1)
Table 4:Multivariate analysis showing determinants of Knowledge for COVID-19 infections
& preventions.
b
only variables in the bivariate analysis with p < 0.2 were included.
Page 18/26
Odds for good knowledge
Bivariate Logistic regression Multivariate Logistic regression
Variables
b
Crude OR p-value Adjusted OR p-value
Country < 0.0001
 Algeria Reference - -
 DRC 3.9 (1.3 – 11.1) 0.012 4.59 (1.34 – 15.73) 0.015
 Uganda 33.5 (10.5 – 107.0) < 0.0001 34.09 (9.26 – 125.48) < 0.0001
 Ghana 10.1 (3.0 – 33.7) < 0.0001 13.22 (3.36 – 52.00) < 0.0001
 Others 2.6 (0.8 – 8.1) 0.094 2.09 (0.63 – 6.89) 0.227
Sex   0.331
Female Reference  -
Male 1.3 (0.89 – 1.96) 0.170 0.78 (0.48 – 1.28) 0.331
Cadre of HW < 0.0001
 Others Reference - -
 Nurses 0.5 (0.21 – 1.25) 0.140 0.64 (0.23 – 1.75) 0.383
 Doctors 3.5 (1.74 – 7.21) 0.001 3.26 (1.43 – 7.43) 0.005
Education level 0.011
  Certificate Reference -
 Diploma 0.7 (0.12 – 3.82) 0.046 0.17 (0.02 – 1.33) 0.091
  Degree/Graduate 2.2 (0.48 – 9.92) 0.308 0.50 (0.09 – 3.68) 0.569
 Masters 4.9 (1.05 – 23.35) 0.044 0.99 (0.15 – 6.56) 0.991
 Others 3.5 (0.68 – 18.40) 0.132 1.46 (0.20 – 10.74) 0.712
Religion of HWs 0.885
Muslims Reference - 
Christians 1.7 (0.93 – 3.00) 0.088 0.98 (0.43 – 2.22) 0.955
Jehovah’s Witnesses 0.6 (0.12 – 2.86) 0.512 0.67 (0.122 – 3.85) 0.668
Others 1.5 (0.49 – 4.28) 0.495 1.48 (0.38 – 5.75) 0.574
Table5: Bivariate analysis showing determinants of attitude towards COVID-19 infection
and prevention.
*p-value from chi-square analysis.
Page 19/26
Attitude category
Variables Bad: n (%) Good: n (%) p-value*
Country of workplace < 0.0001
 Algeria 20 (35.1) 37 (64.9)
 DRC 19 (7.7) 229 (92.3)
 Uganda 3 (5.0) 57 (95.0)
 Ghana 0 (0) 37 (100)
 Others 15 (13.0) 100 (87.0)
Age category < 0.0001
 < 20 years 7 (43.8) 9 (56.2)
 21-30 years 14 (7.8) 166 (92.2)
 31-40 years 15 (9.0) 152 (91.0)
 41-50 years 11 (11.8) 82 (88.2)
 51-60 years 7 (14.9) 40 (85.1)
Sex category 0.002
 Female 36 (15.8) 192 (84.2)
 Male 21 (7.3) 268 (92.7)
Cadre of HW 0.004
 Others (Allied HW) 11 (16.7) 55 (83.3)
 Nurses 25 (16.2) 129 (83.8)
 Doctors 21 (7.1) 276 (92.9)
Education level 0.001
  Certificate 6 (40.0) 9 (60.0)
 Diploma 6 (11.1) 48 (88.9)
  Degree/Graduate 40 (12.0) 293 (88.0)
 Masters 4 (4.9) 77 (95.1)
 Others 1 (2.9) 33 997.1)
Marital status 0.784
 Single 25 (11.5) 193 (88.5)
 Married 32 (10.7) 267 (89.3)
Religion of HW < 0.0001
 Muslim 19 (23.2) 63 (76.8)
 Christian 29 (7.3) 367 (92.7)
 Jehovah’s witness 4 (25.0) 12 (75.0)
 Others 5 (21.7) 18 (78.3)
Table 6:Multivariate analysis showing determinants of attitude towards COVID-19
infections & preventions measures.
a
All HWs had good attitude towards COVID-19
infection and prevention measures b . variables in the bivariate analysis with p < 0.2, * p-
value from binary logistic regression,
Page 20/26
Odds for good attitude
Bivariate Logistic regression Multivariate Logistic regression
Variables
a
Crude OR p-value Adjusted OR p-value*
Country   0.052
 Algeria Reference - - -
 DRC 6.52 (3.18 – 13.35) < 0.0001 3.95 (1.33 – 11.69) 0.013
 Uganda 10.27 (2.85 – 37.02) < 0.0001 4.58 (1.03 – 20.45) 0.046
 Ghana
b
- - - -
 Others 3.60 (1.67 – 7.77) 0.001 2.57 (1.02 – 6.47) 0.045
Sex   0.144
Female Reference - - -
Male 2.39 (1.35 – 4.23) 0.003 1.6 90.81 – 3.17) 0.178
Cadre of HW 0.025
 Others Reference -
 Nurses 1.03 (0.48 – 2.24) 0.937 3.61 (1.29 – 10.12) 0.015
 Doctors 2.63 (1.20 – 5.76) 0.016 3.60 (1.36 – 9.53) 0.010
Education level 0.208
 Certificate Reference - -
 Diploma 5.33 (1.40 – 20.31) 0.014 3.08 (0.43 – 22.01) 0.263
 Degree/Graduate 4.88 (1.65- 14.45) 0.004 1.80 (0.32 – 9.97) 0.503
 Masters 12.83 (3.04 – 54.24) 0.001 4.74 (0.65 – 34.60) 0.125
 Others 22.00 (2.34 – 207) 0.007 10.17 (0.71 – 146.09) 0.088
Religion of HWs 0.541
Muslims Reference - -
Christians 3.82 (2.02 – 7.22) <0.0001 1.38 (0.54 – 3.55) 0.504
Jehovah’s Witnesses 0.91 (0.26 – 3.13) 0.875 0.57 (0.14 – 2.31) 0.426
Others 1.09 (0.36 – 3.31) 0.885 0.66 (0.17 – 2.54) 0.544
Age (years) 0.427
<21 Reference  -
21-30 9.22 (3.00 – 28.50) < 0.0001 3.35 (0.86 – 13.02) 0.081
31-40 7.88 (2.57 – 24.18) < 0.0001 2.41 (0.63 – 9.24) 0.200
41-50 5.80 (1.80 – 18.70) 0.003 1.79 (0.46 – 7.04) 0.403
51-60 4.44 (1.24 – 15.87) 0.022 1.84 (0.44 – 7.78) 0.408
Table 7: Bivariate analysis showing determinants of HW’s Practice of COVID-19 infections
measures.*
p values from chi-square analysis.
Page 21/26
Practice category
Variables Bad: frequency (%) Good: frequency (%) p-value*
Country of workplace < 0.0001
 Algeria 20 (35.1) 37 (64.9)
 DRC 15 (6.0) 233 (94.0)
 Uganda 1 (1.7) 59 (98.3)
 Ghana 6 (16.2) 31 (83.8)
 Others 8 (7.0) 107 (93.0)
Age category 0.031
 < 20 years 5 (31.3) 11 (68.7)
 21-30 years 18 (10.0) 162 (90.0)
 31-40 years 11 (6.6) 156 (93.4)
 41-50 years 11 (11.8) 82 (88.2)
 51-60 years 5 (10.6) 42 (89.4)
Sex category 0.075
 Female 28 (12.3) 200 (87.7)
 Male 22 (7.6) 267 (92.4)
Cadre of HW < 0.0001
 Others (Allied HW) 15 (22.7) 51 (77.3)
 Nurses 21 (13.6) 133 (86.4)
 Doctors 14 (4.7) 283 (95.3)
Education level 0.087
  Certificate 3 (20.0) 12 (80.0)
 Diploma 6 (11.1) 48 (88.9)
  Degree/Graduate 37 (11.1) 296 (88.9)
 Masters 2 (2.5) 79 (97.5)
 Others 2 (5.9) 32 (94.1)
Marital status 0.782
 Single 22 (10.1) 196 (89.9)
 Married 28 (9.4) 271 (90.6)
Religion of HW
 Muslim 16 (19.5) 66 (80.5) 0.009
 Christian 30 (7.6) 366 (92.4)
 Jehovah’s witness 1 (6.3) 15 (93.7)
 Others 3 (13.0) 20 87.0)
Table 8: Multivariate analysis showing determinants of practice towards COVID-19
infections & preventions.
a
only variables in the bivariate analysis with p < 0.2 were
included. * p-value from binary logistic regression.
Page 22/26
Odds for good practice
Bivariate Logistic regression Multivariate Logistic regression
Variables
a
Crude OR p-value Adjusted OR p-value*
Country < 0.0001
 Algeria Reference -
 DRC 8.40 (3.95 – 17.85) < 0.0001 19.72 (6.08 – 63.92) < 0.0001
 Uganda 31.90 (4.11 – 247.7) < 0.0001 55.63 (5.90 – 524.6) < 0.0001
 Ghana 2.79 (1.00 – 7.82) 0.001 6.00 (1.57 – 23.02) 0.009
 Others 7.23 (2.94 – 17.80) 0.051 11.60 (3.87 – 34.74) < 0.0001
Sex   0.951
Female Reference  
Male 1.70 (0.94 – 3.06) 0.077 0.98 (0.473 – 2.02) 0.951
Cadre of HW < 0.0001
 Others Reference
 Nurses 1.86 (0.86 – 3.89) 0.098 4.25 (1.65 – 10.93) 0.003
 Doctors 5.95 (2.71 -13.06) < 0.0001 8.60 (3.22 – 23.00) < 0.0001
Education level 0.221
  Certificate Reference -
 Diploma 2.00 (0.44 – 9.18) 0.373 2.60 (0.33 – 20.37) 0.363
  Degree/Graduate 2.00 (0.54 – 7.42) 0.300 1.40 (0.22 – 8.90) 0.724
 Masters 9.88 (1.49 – 65.33) 0.018 6.42 (0.63 – 65.90) 0.118
 Others 4.00 (0.59 – 26.97) 0.154 3.76 (0.30 – 47.04) 0.304
Religion of HWs 0.633
Muslims Reference - 
Christians 2.96 (1.53 – 5.73) 0.001 0.97 (0.36 – 2.64) 0.957
Jehovah’s Witnesses 3.64 (0.45 – 29.60) 0.227 2.84 (0.27- 29.96) 0.386
Others 1.62 (0.43 – 6.12) 0.480 2.25 (0.42 – 12.05) 0.342
Age category (years) 0.742
<21 Reference  
21-30 4.09 (1.28 – 13.10) 0.003 0.50 (0.11 – 2.16) 0.350
31-40 6.45 (1.90 – 21.86) 0.003 0.77 (0.17 – 3.54) 0.737
41-50 3.39 (1.00 – 11.60) 0.052 0.46 (0.10 – 2.16) 0.324
51-60 3.82 (0.94 – 15.58) 0.062 0.66 (0.12 – 3.54) 0.624
Table 9: Multi-variate logistic regression showing the influence of HW’s knowledge on their
attitude towards COVID-19 prevention measures: adjusted for socio-demographic factors.
Page 23/26
Odds for good attitude
Adjusted odds
ratio
95% Confidence interval
(CI)
p-value
Lower limit Upper limit
Knowledge
Category
 
Bad Reference - - -
Good 3.52 1.08 11.45 0.037
Age Category
< 20 years Reference - - -
21-30 years 3.67 0.93 14.42 0.063
31-40 years 2.62 0.68 10.13 0.161
41-50 years 1.92 0.49 7.57 0.353
51-60 years 2.01 0.47 8.51 0.345
Sex category
Female Reference - - -
Male 1.72 0.86 3.44 0.126
HW category
Others Reference - - -
Nurses 3.78 1.34 10.69 0.012
Doctors 3.13 1.17 8.37 0.023
Religion   
Muslims Reference - - -
Christians 1.41 0.55 3.61 0.472
Jehovah’s
Witnesses
0.61 0.15 2.50 0.493
Others 0.66 0.17 2.58 0.548
Country   
Algeria Reference - - -
DRC 3.45 1.16 10.23 0.025
Uganda 2.31 0.48 11.21 0.300
Ghana - - - 1
Others 2.55 1.01 6.44 0.048
Education level
Certificate Reference - - -
Diploma 3.62 0.49 26.58 0.206
Degree/Bachelors 1.84 0.33 10.37 0.492
Masters 4.59 0.61 34.34 0.138
Others 8.96 0.61 131.14 0.109
Table 10: Influence of HW’s knowledge on their practice of COVID-19 infection and
prevention measures (adjusted for confounding socio-demographic factors).*
p-value from
binary logistic regression.
Page 24/26
Odds for good practice
p-value* Adjusted odds ratio 95% Confidence interval (CI)
Knowledge category
0.189 Lower limit Upper limit
Bad Reference 
Good 0.189 2.21 0.68 7.24
Age Category 0.766
< 20 years Reference
21-30 years 0.373 0.51 0.12 2.24
31-40 years 0.761 0.79 0.17 3.63
41-50 years 0.351 0.48 0.10 2.26
51-60 years 0.680 0.70 013 3.80
Sex category 0.993
Female Reference 
Male 0.993 1.00 0.48 2.10
HW category < 0.0001
Others Reference 
Nurses 0.003 4.18 1.62 10.74
Doctors < 0.0001 7.51 2.77 20.40
Religion of respondent 0.597
Muslims Reference 
Christians 0.997 1.00 0.37 2.72
Jehovah’s Witnesses 0.337 3.17 0.30 33.29
Others 0.325 2.32 0.43 12.45
Country < 0.0001
Algeria Reference 
DRC <0.0001 18.12 5.78 59.00
Uganda 0.002 36.16 3.61 362.05
Ghana 0.018 5.24 1.33 21.00
Others < 0.0001 11.57 3.87 34.62
Education level 0.243
Certificate Reference 
Diploma 0.334 2.77 0.35 21.78
Degree/bachelors 0.725 1.40 0.22 8.92
Masters 0.122 6.33 0.61 65.50
Others 0.410 3.00 0.23 37.58
Table 11: Influence of HW’s attitude on their practice of COVID-19 infection prevention
measures; (adjusted for confounding socio-demographic factors).*
p-value from binary
logistic regression.
Page 25/26
Odds for good practice
Adjusted odds
ratio
95% Confidence interval
(CI)
p-value*
Lower limit Upper limit
Attitude category
Bad Reference - - -
Good 4.66 1.98 10.99 < 0.0001
Age Category
< 21 years Reference - - -
21-30 years 0.33 0.07 1.57 0.162
31-40 years 057 0.11 2.84 0.488
41-50 years 0.36 0.07 1.86 0.224
51-60 years 0.61 0.10 3.65 0.586
HCW category
Others Reference - - -
Nurses 3.78 1.36 9.42 0.010
Doctors 7.25 2.65 19.86 < 0.0001
Religion   
Muslims Reference - - -
Christians 0.85 0.30 2.43 0.756
Jehovah’s
Witnesses
2.83 0.28 28.32 0.376
Others 2.91 0.45 18.56 0.26
Country   
Algeria Reference - - -
DRC 18.60 5.10 61.26 < 0.0001
Uganda 44.25 4.57 428.21 0.001
Ghana 3.86 0.96 15.45 0.056
Others 10.47 3.35 32.75 < 0.0001
Sex category
Female Reference - - -
Male 0.90 0.43 19.20 0.792
Education level
Certificate Reference - - -
Diploma 2.02 0.20 20.32 0553
Degree/bachelors 1.09 0.13 9.09 0.939
Masters 4.14 0.32 53.73 0.278
Others 2.45 0.14 42.83 0.74
Figures
Page 26/26
Figure 1
COVID-19 Knowledge, Attitude and Practice distribution among HWs in Africa.
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