FACTORS ASSOCIATED WITH COVID-19: A COMPARATIVE CASE-CONTROL STUDY IN BENIN Текст научной статьи по специальности «Фундаментальная медицина»

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FACTORS ASSOCIATED WITH COVID-19: A COMPARATIVE CASE-CONTROL STUDY IN BENIN

Nonvignon Marius KÊDOTÉ1.2.3 , Ablo Prudence WACHINOU2.3.4 , Aymeric Joaquin DARBOUX2.3 , Sètondji Géraud Roméo PADONOU2.3 , Pérince Franel Djidjoho FONTON2.3 , Sevidzem Silas LENDZELE3'5 , Fatou Bintou SARR3'6 , Jacques François MAVOUNGOU3.7 iRegional Institute of Public Health Comlan Alfred Quenum, Ouidah, Benin 2University of Abomey-Calavi, Cotonou, Benin

3African and Malagasy Council for Higher Education, Ouagadougou, Burkina Faso 4National University Hospital for Tuberculosis and Pulmonary Diseases, Cotonou, Benin 5Tropical Ecology Research Institute, University of Dschang, Dschang, Cameroon 6Iba Der Thiam University of Thies, Thies, Senegal international University of Libreville, Libreville, Gabon

Corresponding author: Nonvignon Marius KÊDOTÉ, e-mail: [email protected]

DOI: 10.38045/ohrm.2022.4.03

CZU:

616.98:578.834.1(668.2)

Keywords:

Benin, COVID-19, risk factors, case-control.

Cuvinte cheie:

Benin, COVID-19, factori de risc, caz-control.

Introduction. Although there are several previous publications related to risk factors of COVID-19 infection in Benin, there are very few data to explain the outbreak risk factors. Material and methods. This case-control study, conducted from 14 September to 20 October 2020, aimed to identify the risk factors associated with COVID-19 infection in Benin. Questions on knowledge, attitudes, and practices related to COVID-19, sociodemographic characteristics, nutritional factors, medical history, housing and working conditions of respondents were asked through a questionnaire survey. Bivariate and multivariate logistic regression analyses were conducted to identify the factors associated with COVID-19. The statistical significance was set at 5%. Results. In multivariate logistic regression, no handwashing device installed at the home entrance (ORa=1.86; 95% CI [1.07-3.21]) or a device delivering only water (ORa=5.57; 95% CI [1.9815.65]), using permanently air conditioning at workplaces (ORa=5.48; 95% CI [2.40-12.57]), less knowledge of protective measures (ORa=1.41; 95% CI [1.08-1.84]) and no knowledge on the coro-navirus incubation period (ORa=4.19; 95% CI [2.37-7.44]) were identified as risk factors for COVID-19 infection. Conclusions. Based on the findings of this study, a contextual response should prioritize strategies that will raise awareness and population's knowledge of COVID-19 as well as preventive practices.

FACTORI ASOCIATI CU COVID-19: studiu comparativ caz-CONTROL IN BENIN Introducere. Desi exista mai multe publicatii cu referire la factorii de rise ai infectiei COVID-19 in Benin, sunt prezentate insa foarte putine date care sa explice factorii de rise in perioada de epidemie. Material si metode. Acest studiu caz-control, realizat in peri-oada 14 septembrie - 20 octombrie 2020, si-a propus sa identifice factorii de risc asociati cu infectia COVID-19 in Benin. Respondentilor, prin intermediul unui chestionar, le-au fost adresate intrebari privind cunostintele, atitudinile si practicile legate de COVID-19, caracteristicile socio-demografice, factorii nutritionali, istoricul medical, locuinta si con-ditiile de munca. Au fost efectuate analize de regresie logistica bivariata si multivariate, pentru a identifica factorii asociati cu COVID-19. Semnificatia statistica a fost stabilita la 5%. Rezultate. Cu ajutorul regresiei logistice multivariate, au fost identificati drept factori de risc pentru infectia cu COVID-19: lipsa unui dispozitiv de spalat mainile instalat la intrarea in casa (ORa=1,86; 95% CI [1,07-3,21]) sau al unui dispozitiv care furnizeaza apa (ORa=5,57; 95% CI [1,98-15,65]), prezenta aerului conditionat la locurile de munca (ORa=5,48; 95% CI [2,40-12,57]), cunostinte insuficiente despre masurile de protectie (ORa=1,41; 95% CI [1,08-1,84]) si lipsa de cunostinte privind perioada de incubatie a coronavirusului (ORa=4,19; 95% CI [2,37-7,44]). Concluzii. Pe baza constatarilor aces-tui studiu, un raspuns contextual ar trebui sa prioritizeze strategiile care vor creste gra-dul de constientizare si cunoastere de catre populatie despre COVID-19, precum si practi-cile preventive.

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INTRODUCTION

Coronavirus disease 2019 (COVID-19) has spread rapidly worldwide, causing a global public health crisis (1). The World Health Organization (WHO) declared the outbreak a Public Health Emergency of International Concern on 30 January 2020, and a pandemic on 11 March 2020 and since then the number of cases have been increasing everywhere on the globe along with consecutive waves (2). At present, in comparison with the USA and Europe, Africa has a lower number of cases and lower daily increase in infection. However, WHO continues to express concern about the impact COVID-19 may have on Africa. This is because, from the perspective of capacity, African countries are in a parlous situation compared to Europe, North America and some parts of Asia (3).

Given that the pandemic is caused by a novel strain of coronavirus with unknown original host, in the early stage of the outbreak, the factors associated with its transmission routes, severity and fatality risks has remained unclear for long (4). Several studies indicate that the susceptibility to infection, being seriously ill and the risk of death are influenced by individual-level characteristics such as sociodemographic factors, behavioral traits and pre-existing medical conditions (4, 5). Responses to African epidemics have been threatened by insufficient infrastructure and weak healthcare systems, including lack of sufficient monitoring to determine the magnitude of the outbreak and insufficient structures to prevent, diagnose and treat diseases (6, 7). Contrary to other continents, there is a dearth of data on the drivers of the pandemic in Africa. Aim of the study: we conducted a national case-control study to assess the influence of contextual factors (environmental, socio-cultural, demographic, economic and political) on the dynamic of COVID-19 spread in Benin. The current article, based on data from this national survey aimed to identify risk factors associated with COVID-19 infection in Benin.

MATERIAL AND METHODS

This study was conducted in Benin, a country located in West Africa. Benin is bordered to the West by Togo, in the North by Niger and Burkina-Faso and in the East by Nigeria, which was one of the most affected countries in Africa by

COVID-19. As of February 15, 2022, Benin had 163 deaths out of 26,309 confirmed cases of COVID-19 (8). The survey was carried out in selected health facilities accounting for specific sites for COVID-19 screening and treatment.

A case-control study was conducted from 14 September to 20 October 2020. We considered cases as individuals with a positive reverse tran-scription-polymerase chain reaction (RT-PCR) test for SARS-CoV-2 and who were undergoing treatment, while controls were those with a negative result and who had no symptoms of COVID-19 prior to enrolment in the study. Cases enrolled in the study were those who were healthy enough to be interviewed (not hospitalized for serious conditions).

The selection method was non-probabilistic. Cases and controls were selected for convenience in two stages. The first stage consisted of a purposive selection of nine screening and treatment sites. These sites were identified in collaboration with the health authorities in the view to have a broad geographic coverage of the country (north, center and south). COVID-19 management sites with the highest attendance in terms of tests performed and people being treated and followed up were preferred. In Benin, there was a total of 84 screening and treatment sites, with a least one per city, and more sites in distributed at a rate of one per commune (77), with three more in Cotonou. Six sites were selected in the southern part of the country to account the higher population density, two in the north and one in the south. The second stage consisted of convenience recruitment of cases and controls screened at the sites. A total of 312 participants were enrolled (104 cases for 208 controls). For each case, two unmatched controls from the same site were selected.

Data were collected using a structured questionnaire about the potential risk factors for COVID-19. The questionnaire consisted of 4 main parts: (i) sociodemographic characteristics (age, sex, educational status, marital status, monthly income, religion, occupational status); (ii) risk factors related to medical history, housing conditions, working conditions, transportation conditions and nutritional factors; (iii) participants' knowledge (mode of transmission, persons at risk, protectives measures, incubation period

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and existence of asymptomatic people) and adherence to preventive practices (mask wearing, hand washing, objects/surfaces disinfection, social distancing, teleworking and avoiding risk actions like handshake, mask below the chin, touching the face, eyes or the mouth with hands) for COVID-19; (iv) COVID-19 status of respondents (case symptomatic, case asymptomatic or control).

All statistics were performed using IBM SPSS Statistics software version 20.0.0. Descriptive statistics, bivariate logistic regression and multi-variate logistic regression were used to identify the factor associated with COVID-19 among respondents. A significance level of 5% was and used. To build the initial model, only the independent variables whose p-value at the end of the bivariate analysis was less than or equal to 0.10 were introduced. A backward stepwise mul-tivariate logistic regression was done to obtain the final model.

RESULTS

Description of the sample

A total of 312 (50.96% males and 49.04% females) participants were interviewed. The mean age of the participants was 34.03±11.86 years (34.80±11.89 for cases and 33.64±11.85 among controls). The elders were very few (3.85%). The proportion of symptomatic cases was 56.7% and that of asymptomatic cases was 43.3%. About the educational status, 43.59% went to university, 23.72% secondary school and 13.46% only primary school. Most of them are married (62.7%) and Christians (81.29%) in religion. Civil servant (48.08%) and self-employed person (16.99%) were the most preponderant workers. The quarter of them (25.64%) has an income less than the guaranteed interprofessional minimum wage (40.000 FCFA). About their health status, 24.36% suffered from a disease (not COVID-19) the month before the survey, 3.53% were overweight or obese, 1.28% had a high blood pressure, 0.64% had chronic hepatitis and sickle cell disease, 0.32% had a cancer, 5.77% were suffering from respiratory disorders, 1.60% had a chronic kidney disease and 11.76% were pregnant women or have recently delivered. COVID-19 cases were diagnosed in 12.18% of their family and among their colleagues in 14.74%.

Unadjusted analysis

Table 1 (Appendix 1) presents a comparison between cases and controls regarding socio-demographic characteristics and medical history of the participants in the bivariate analysis. Factors associated with COVID-19 infection were educational status [no formal: OR=3.79 (95%CI; 1.22-11.72, p=0.021); marital status [being married: OR=2.26, 95%CI; 1.34-3.81, p=0.002], monthly income [>300000 FCFA: OR=3.43 (95%CI; 1.55-7.60, p=0.002); recent history of pregnancy [OR=5.03 (95%CI; 1.68-14.97, p=0.002]. No associations were found for age (p=0.066), sex (p=0.055), occupational status (p=0.093), recent illness (p=0.458), confirmed cases in family (p=0.056) or among colleagues (p=0.424), overweight or obesity status (p=0.489), sickle cell disease (p=0.626), respiratory disorders (p=0.610) and chronic kidney disease presence (p=0.219).

Table 2 (Appendix 2) shows the comparison between cases and controls concerning their travel and transports habits. Only using motorcycles taxis was associated with COVID-19 infection (OR: 1.67, 95%CI: 1.03-2.72, p=0.037). No associations were found regarding the travel outside Benin in the last month (p=0.847), municipality of residence (p=0.791), municipality visited inside the sanitary seal (p=0.558), use of individual transport (p=0.120) and use of public transport (p=0.590).

Comparison of working conditions are shown in Table 3 (Appendix 3). There were associations between COVID-19 infection and the type of handwashing device at the home entrance [no device: OR: 1.72 (95%CI: 1.03-2.85, p=0.036) or water supply only: OR: 4.62 (95%CI: 1.84-11.61, p=0.001)] and frequency of using air conditioner [always: OR: 3.38 (95%CI: 1.63-6.97, p=0.001). There were no associations found for the type of house (p=0.409), number of people sleeping in the same room (p=0.115), frequency of using a fan at home (p=0.831) or workplace (p=0.118), frequency of using air conditioner at home (p=0.252), drinking water source at home (p=0.122) or workplace (p=0.231), type of work building (p=0.121), number of people working in the same room (p=0.258), distance between coworkers (p=0.412) and type of handwashing device at workplace (p=0.438).

Table 4 (Appendix 4) presents the practices and

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knowledge of participants related to COVID-19. An association with COVID-19 infection was found for the frequency of mask wearing at home [never: 0.44 (95%CI: 0.20-0.98, p=0.044) or in public places [never/rarely: 2.99 (95%CI: 1.16-7.68, p=0.023), knowledge of persons at risk [0R=0.82, (95%CI: 0.69-0.98, p=0.029)], knowledge of the incubation period of the coro-navirus [0R=2.89, (95%CI: 1.77-4.72, p<0.001)] and knowledge of protective measures [OR=0.73, (95%CI: 0.57-0.94, p=0.015)]. There were no associations regarding other practices like going to celebrations or gatherings (p=0.050), lowering the mask below the chin (p=0.562), touching the face, eyes or mouth (p=0.113), greeting with a handshake (p=0.201), the type of mask worn (p=0.517), the frequency of mask wearing in public transport (p=0.273) and at the workplace (p=0.179), the frequency of hand washing when leaving a public place (p=0.320) or returning to the home (p=0.340). There were also no associations with COVID-19 infection for the knowledge

of modes of transmission (p=0.309), of symptoms (p=0.086), of the existence of asymptomatic cases (p=0.826) and of the ability of asymptomatic cases to transmit the virus to others (p=0.138).

Adjusted analysis

After multivariate analyses (tab. 5), factors independently associated with COVID-19 infection were:

- absence of a handwashing device at the entrance of home (ORa=1.86, 95% CI [1.073.21]) or a handwashing device providing only water (ORa=5.57, 95% CI [1.9815.65]);

- permanent use of air conditioning (ORa=5.48, 95% CI [2.40-12.57]);

- less knowledge of protective measures against COVID-19 (ORa=1.41, 95% CI [1.081.84]);

- no knowledge of the coronavirus incubation period (ORa=4.19, (95% CI [2.37-7.44]).

Table 5. Factors associated with COVID-19 (multivariate final model).

Variables

ORa [IC95%]

p-value

Type of hand washing device at home

No device Water supply only

Water supply with soap/ bleach/ hydroalcoholic gel Frequency of air conditioning use at workplace

Never At one time Always NA*

Knowledge of COVID-19 Incubation Period

Yes No

Number of known protective measures against COVID-19

1.86 [1.07-3.21] 0.027

5.57 [1.98-15.65] 0.001 1

1

1.80 [0.79-4.10] 0.164

5.48 [2.40-12.57] <0.001

1.19 [0.61-2.31] 0.602

4.19 [2.37-7.44] <0.001 1

1.41 [1.08-1.84] 0.011

Note: ORa - adjusted Odds Ratio;

*people not working or working in a building where air conditioner couldn't be installed.

DISCUSSIONS

To the best of our knowledge, this is the first study attempting to determine the risk factors driving the COVID-19 infection in Benin. Four main risk factors were identified: absence of handwashing device or handwashing with only water and no soap, permanent use of air conditioning, less knowledge of protective measures and no lack of knowledge on the virus incubation period.

The first risk factor identified is the absence of an adequate handwashing device at the entrance of home. This measure has been recommended by public health authorities across the world to promote handwashing of visitors, at private and public places. It participates for reducing the spread of the coronavirus. In fact, studies have shown that handwashing is associated with a significantly reduced risk of contracting the

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coronavirus and is known to disrupt the transmission of respiratory diseases in general (9, 10). This finding indicates the necessity for the public to pay attention to personal protective at home and raise the need for health authorities to continue raising awareness about this life saving measure (11). Handwashing before, during, and after preparing food; before eating food; before touching the face; before and after caring for someone who is sick; after blowing the nose, coughing, or sneezing; after being in a public place; after changing diapers or cleaning up a child who has used the toilet; after using the toilet or latrine; after touching an animal, animal feed, or animal waste and after touching garbage is necessary to halt the spread of COVID-19, along with other COVID suitable behaviors (12). Handwashing is seen as the cornerstone for COVID-19 Prevention. However, it is important to notice, as shown by our data, that handwash-ing should be performed with soap and not only water and, this needs to be emphasized during campaign of sensitization.

Of note, after successive waves, there is a risk that population become careless about that measure. Therefore, there is a compulsory need that health authorities continue to sensitize populations on the importance of this live saving

CONCLUSIONS

1.

2.

3.

4.

CONFLICT OF INTERESTS

The authors do not declare any conflict of interest.

ACKNOWLEDGMENTS

The authors would like to thank the Ministry of Health in Benin, the health district coordinator

measure.

The second factor identified is the use of air conditioning permanently at the workplace. SRAS-CoV-2 is known to survive longer in low temperature environments (13). Also, the SARS-CoV-2 has a longer persistence on surfaces like stainless steel, plastics, glass and highly porous fabrics that are often present in workplaces like offices (14). The risk to contract COVID-19 is higher in crowded and confined spaces (15). It is therefore important, that rooms are adequately ventilated to reduce individual infection risk (16, 17).

The third and fourth factors identified are the lack of knowledge of the incubation period of the coronavirus and the low knowledge of protective measures against COVID-19. Overall, studies have showed that level of knowledge has a positive impact on the practices towards COVID-19 (18). The lack of knowledge on COVID-19 appears as a risk factor that may indicate limited access to credible and timely information about the virus among cases. But in some studies, it has been observed that despite good knowledge, attitudes were not always positive (19). This therefore requires additional education to convey the importance of adherence to prevention measures to reduce the spread of COVID-19.

involved in the study planning, the staff of screening and treatment sites for their support, and the participants for their great collaboration for the success of this study. We also thank the Macky SALL Research Fund of the African and Malagasy Council for Higher Education: 20202022 for supporting this study.

The COVID-19 pandemic is still affecting people around the world. Because of its dynamic not being the same in all countries or regions, it is important to identify the factors involved in its spread.

In the present study conducted in Benin, factors related to hand hygiene, working conditions and knowledge of the COVID-19 have been highlighted. These findings could help to strengthen response strategies implemented across the country. To do so, population's knowledge on COVID-19 need to be improved and preventive practices promoted through the ways available.

This national case-control study assessed the influence of some contextual factors on the COVID-19 dynamic in Benin.

Further studies need to be conducted to explore a wider range or others contextual factors not taken into account in that study, which could have a positive or negative influence on the COVID-19 spread in Benin.

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ETHICAL APPROVAL

Administrative authorization was obtained from

health authorities as well as ethical approval

from National Ethics Committee for Health Research in Benin (N 086/MS/DRFMT/ CNERS/SA

REFERENCES

1. Al Abri ZGH, Al Zeedi MASA, Al Lawati AA. Risk Factors Associated with COVID-19 Infected Healthcare Workers in Muscat Gover-norate, Oman. J Prim Care Community Health. 2021; 12:2150132721995454. doi:10.1177/ 2150132721995454

2. Xin H, Jiang F, Xue A, Liang J, Zhang J, Yang F, Han Y. Risk factors associated with occurrence of COVID-19 among household persons exposed to patients with confirmed COVID-19 in Qingdao Municipal, China. Transbound Emerg Dis. 2021;68(2):782-8. doi:10.1111/ tbed.13743

3. Okeahalam C, Williams V, Otwombe K. Factors associated with COVID-19 infections and mortality in Africa: a cross-sectional study using publicly available data. BMJ Open. 2020;10(11):e042750. doi:10.1136/bmjopen-2020-042750

4. Gesesew HA, Koye DN, Fetene DM, Wolde-giorgis M, Kinfu Y, Geleto AB, et al. Risk factors for COVID-19 infection, disease severity and related deaths in Africa: a systematic review. BMJ Open. 2021;11(2):e044618. doi: 10.1136/bmjopen-2020-044618

5. Onovo AA, Atobatele A, Kalaiwo A, Obanubi C, James E, Gado P, et al. Using supervised machine learning and empirical Bayesian kriging to reveal correlates and patterns of COVID-19 disease outbreak in sub-Saharan Africa: exploratory data analysis. medRxiv. 2020. 20082057.

6. Rosenthal PJ, Breman JG, Djimde AA, John CC, Kamya MR, Leke RGF, et al. COVID-19: Shining the Light on Africa. Am J Trop Med Hyg. 2020; 102(6):1145-8. doi:10.4269/ajtmh.20-0380

7. Mohammed M, Muhammad S, Mohammed FZ, Mustapha S, Sha'aban A, Sani NY, et al. Risk Factors Associated with Mortality Among Patients with Novel Coronavirus Disease (COVID-19) in Africa. J Racial Ethn Health Disparities. 2021;8(5):1267-72. doi: 10.1007/s40615-020-00888-3

of August 04, 2020). All participants (cases and controls) gave an informed and written consent and the interviews were conducted in strict respect of their privacy and confidentiality.

8. Gouvernement de la République du Bénin Cotonou (BJ): Informations coronavirus (CO-VID-19). Available from: https:// www.gouv.bj/coronavirus/ [cited 2021 August 02].

9. Chen Y, Klein SL, Garibaldi BT, Li H, Wu C, Osevala NM, et al. Aging in COVID-19: Vulnerability, immunity and intervention. Ageing Res Rev. 2021;65:101205.

10. Gao YD, Ding M, Dong X, Zhang JJ, Kursat Azkur A, Azkur D, et al. Risk factors for severe and critically ill COVID-19 patients: A review. Allergy. 2021;76(2):428-55.

11. Liu T, Liang W, Zhong H, He J, Chen Z, He G, et al. Risk factors associated with COVID-19 infection: a retrospective cohort study based on contacts tracing. Emerg Microbes Infect. 2020;9(1):1546-53. doi:10.1080/22221751.2020.1787799

12. CDC. Handwashing and Making a Solution for Handwashing in Global, Low-Resource Settings. Available at: https://www.cdc.gov/co-ronavirus/2019-ncov/global-covid-19/ handwashing.html [cited 2021 August 02].

13. Riddell S, Goldie S, Hill A, Eagles D, Drew TW. The effect of temperature on persistence of SARS-CoV-2 on common surfaces. Virol J. 2020;17(1):145.

14. Azuma K, Yanagi U, Kagi N, Kim H, Ogata M, Hayashi M. Environmental factors involved in SARS-CoV-2 transmission: effect and role of indoor environmental quality in the strategy for COVID-19 infection control. Environ Health Prev Med. 2020;25(1):66. doi:10. 1186/s12199-020-00904-2

15. Aboubakr HA, Sharafeldin TA, Goyal SM. Stability of SARS-CoV-2 and other coronaviruses in the environment and on common touch surfaces and the influence of climatic conditions: A review. Transbound Emerg Dis. 2021;68(2):296-312.

16. Lelieveld J, Helleis F, Borrmann S, Cheng Y, Drewnick F, Haug G, et al. Model Calculations of Aerosol Transmission and Infection Risk of COVID-19 in Indoor Environments. Int J Environ Res Public Health. 2020;17(21):8114.

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17. Spena A, Palombi L, Corcione M, Carestia M, Spena VA. On the Optimal Indoor Air Conditions for SARS-CoV-2 Inactivation. An Enthalpy-Based Approach. Int J Environ Res Public Health. 2020;17(17):6083.

18. Nwagbara UI, Osual EC, Chireshe R, Bolarin-wa OA, Saeed BQ, Khuzwayo N, Hlongwana KW. Knowledge, attitude, perception, and preventative practices towards COVID-19 in

sub-Saharan Africa: A scoping review. PLoS One. 2021;16(4):e0249853. doi:10.1371/ journal.pone.0249853.

19. Siddiquea BN, Shetty A, Bhattacharya O, Af-roz A, Billah B. Global epidemiology of COVID-19 knowledge, attitude and practice: a systematic review and meta-analysis. BMJ Open. 2021;11(9):e051447. doi:10.1136/ bmjopen-2021-051447

Date of receipt of manuscript: 13/04/2022 Date of acceptance for publication: 07/09/2022

Appendix 1: Table 1. Comparison of sociodeniographic characteristics and medical history of cases and controls.

Variables Total N (%) Cases n(%) Controls n(%) OR iic95%i p-value

Sex

Female 153 f49.04) 59 (56.73) 94(45.19) 1.5910.99-2.561 0.055

Male 159(50.96) 45 (43.27) 114(54.81) 1 -

Age (years)

<30 133 (42.63) 39 (37.50) 94 (45.19) 0.58(0.33-1.031 0.066

30-39 87 (27.88) 36 (34.62) 51 (24.52) 1 -

40-49 53 (16.99) 18 (17.31) 35 (16.83) 0.72(0.35-1.481 0.383

50-59 27 (8.65) 6(5.77) 21 (10.10) 0.40(0.15-1.101 0.077

>60 12 (3.85) 5 (4.81) 7(3.37) 1.01(0.30-3.441 0.985

Educational status

No formal education 15 (4.81) 10 (9.62) 5 (2.40) 3.79(1.22-11.721 0.021

Primary 42 (13.46) 13 (12.50) 29 (13.94) 0.85(0.40-1.781 0.666

Secondary 119 (38.14) 34(32.69) 85 (40.87) 0.75(0.44-1.291 0.306

University 136 (43.59) 47 (45.19) 89 (42.79) 1 -

Marital status

Married/ Common-law marriage 195 (62.50) 77 (74.04) 118 (56.73) 2.26(1.34-3.811 0.002

Single/widowed 116 (37.18) 26 (25.00) 90 (43.27) 1 -

No answer 1 (0.32) 1 (0.96) 0 (0.00) - -

Occupational status

Self-employed person 53 (16.99) 12 (11.54) 41 (19.71) 3.71(0.80-17.161 0.093

Civil servant 150 (48.08) 53 (50.96) 97 (46.63) 0.54(0.22-1.361 0.191

Learner 46(14.74) 15 (14.42) 31 (14.90) 1.02(0.49-2.111 0.969

Retired 4(1.28) 1 (0.96) 3 (1.44) 0.90(0.37-2.201 0.815

Job seeker 10 (3.21) 3 (2.88) 7(3.37) 0.62(0.06-6.521 0.690

Housewife 9 (2.88) 6(5.77) 3 (1.44) 1

Retailer 40 (12.82) 14(13.46) 26(12.50) 0.80(0.19-3.571 0.766

Monthly income (FCFA)

40000 -100000 94 (30.13) 24(23.08) 70 (33.65) 1

<40 000 80 (25.64) 28(26.92) 52 (25.00) 1.57(0.82-3.011 0.175

100000 - 300000 72 (23.08) 20 (19.23) 52 (25.00) 1.12(0.56-2.241 0.745

>300000 37 (11.86) 20 (19.23) 17 (8.17) 3.43(1.55-7.601 0.002

No answer 29 (9.29) 12 (11.54) 17 (8.17) 2.06(0.86-4.931 0.105

Variables Total Cases Controls OR p-value

N (%) nf%) nf%) [IC95%1

111 in the last month

Yes 76 (24.36) 28 (26.92) 48 (23.08) 1.22(0.71-2.101 0.458

No 236 (75.64) 76 (73.08) 160 (76.92) 1 -

Confirmed cases in family

Yes 38 (12.18) 18 (17.31) 20 (9.62) 1.96(1.0-3.911 0.056

No 274 (87.82) 86 (82.69) 188 (90.38) 1 -

Confirmed cases among colleagues

Yes 46 (14.74) 13 (12.50) 33 (15.87) 1 -

No 266 (85.26) 91 (87.50) 175 (84.13) 1.32ro.66-2.631 0.424

Overweight or obesity

Yes 11 (3.53) 5 (4.81) 6 (2.88) 1.70T0.50-5.701 0.396

No 301 (96.47) 99 (95.19) 202 (97.12) 1 -

High blood pressure

Yes 4(1.28) 2 (1.92) 2 (0.96) 2.0K0.28-14.541 0.489

No 308 (98.72) 102 (98.08) 206 (99.04) 1 -

Chronic hepatitis

Yes 2 (0.64) 0 (0.00) 2 (0.96) - -

No 310 (99.36) 104(100) 206 (99.04) - -

Sickle cell disease

Yes 2 (0.64) 1 (0.96) 1 (0.48) 2.01(0.12-32.451 0.626

No 310 (99.36) 103 (99.04) 207(99.52) 1 -

Cancer

Yes 1 (0.32) 1 (0.96) 0 (0.00) - -

No 311 (99.68) 103 (99.04) 208 (100) - -

Respiratory disorders

Yes 18 (5.77) 7 (6.73) 11 (5.29) 1.29(0.48-3.431 0.610

No 294 (94.23) 97(93.27) 197(94.71) 1 -

Chronic kidney disease

Yes 5 (1.60) 3 (2.88) 2 (0.96) 3.05(0.50-18.601 0.219

No 307 (98.40) 101 (97.12) 206 (99.04) 1 -

Pregnant women or recently delivered

Yes 18 (11.76) 13 (22.03) 5 (5.32) 5.03(1.68-14.971 0.002

No 135 (88.24) 46 (77.97) 89 (94.68) 1 -

Appendix 2: Table 2. Comparison of travel and means of travel of cases and controls.

Variables Total N (%) Cases n(%) Controls n(%) OR fIC95%l p-value

Travel outside Benin in the last month

Yes 14 (4.49) 5 (4.81) 9 (4.33) 1.12(0.36-3.421 0.847

No 298 (95.51) 99 (95.19) 199 (95.67) 1 -

Municipality of residence

Inside the area of the sanitary seal 222 (71.15) 73 (70.19) 149 (71.63) 1.07(0.63-1.801 0.791

Outside the area of the sanitary seal 90 (28.85) 31 (29.81) 59 (28.37) 1 -

Municipality visited inside the sanitary seal

Yes 202 (64.74) 65 (62.50) 137(65.87) 0.86(0.53-1.401 0.558

No 110 (35.26) 39 (37.50) 71 (34.13) 1 -

Use of individual transport

Yes 190 (60.90) 57 (54.81) 133 (63.94) 0.68(0.42-1.101 0.120

No 122 (39.10) 47 (45.19) 75 (36.06) 1 -

Use of motorcycle taxis

Yes 110 (35.26) 45 (43.27) 65 (31.25) 1.67(1.03-2.721 0.037

No 202 (64.74) 59 (56.73) 143 (68.75) 1 -

Use of public transport

Yes 31 (9.94) 9 (8.65) 186 (89.42) 0.80(0.35-1.801 0.590

No 281 (90.06) 95 (91.35) (10.58) 1 -

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Appendix 3: Table 3. Comparison of housing and working conditions of cases and controls.

Variables Total N (%) Cases n(%) Controls n(%) OR HC95%] p-va lue

Type of house

Single-family house 114 (36.54) 41 (39.42) 73 (35.10) 1 -

Common courtyard house 182 (58.33) 57 (54.81) 125 (60.10) 0.81(0.50-1.331 0.409

Apartment building 15 (4.81) 6(5.77) 9 (4.33) 1.19(0.40-3.571 0.760

Temporary building 1 (0.32) 0 (0.0) 1 (0.48) - -

Number of people sleeping in the same room* 312 - - 1.06 [0.94-1.20] 0.335

Frequency of ventilation of the dwelling

Never 44(14.10) 12 (11.54) 32 (15.38) 1 -

At some time 138 (44.23) 56 (53.85) 82 (39.42) 1.82[0.84-3.83] 0.115

Always 130 (41.67) 36 (34.62) 94 (45.19) 1.02(0.47-2.201 0.957

Frequency of using a fan

Never 162 (51.92) 55 (52.88) 107 (51.44) 1.06(0.62-1.801 0.831

At some time 101 (32.37) 33 (31.73) 68(32.69) 1 -

Always 49(15.71) 16 (15.38) 33 (15.87) 0.99[0.48-2.07| 0.998

Frequency of using air conditioner

Never 284(91.03) 92 (88.46) 192 (92.31) 0.58[2.34-1.461 0.252

At some time 20 (6.41) 9 (8.65) 11 (5.29) 1 -

Always 7(2.24) 2 (1.92) 5 (2.40) 0.49[0.08-3.141 0.451

No answer 1 (0.32) 1 (0.96) 0 (0.0) - -

Drinking water source

National supply 186 (59.62) 63 (60.58) 123 (59.13) 1 -

Domestic well 64(20.51) 15 (14.42) 49 (23.56) 0.60(0.31-1.151 0.122

Swamp 1 (0.32) 1 (0.96) 0 (0.0) - -

Borehole 61 (19.55) 25 (24.04) 36 (17.31) 1.36(0.75-2.461 0.315

Type of handwashing device at the home entrance

No device 150 (48.08) 55 (52.88) 95 (45.67) 1.72(1.03-2.851 0.036

Water supply only 23 (7.37) 14 (13.46) 9 (4.33) 4.62(1.84-11.611 0.001

Water supply with soap/ bleach/ hydroalcoholic gel 139 (44.55) 35 (33.65) 104 (50.00) 1 -

Type of work building

Closed 121 (41.72) 41 (43.62) 80 (40.82) 1.31(0.72-2.381 0.372

Semi-open 89 (30.69) 25 (26.60) 64 (40.82) 1 -

Open 80 (27.59) 28 (29.79) 52 (26.53) 1.38[0.72-2.651 0.334

Variables Total Cases Controls OR p-value

N (%) n(%) n(%) fIC95%l

NA* 22 (7.05) 10 (9.62) 12 (5.77) 2.13(0.82-5.561 0.121

Number of people working in the same room** 245 - - 0.99(0.99-1.01] 0.258

Distance between co-workers (m)***

<1 125 (69.83) 40 (74.07) 85 (68.00) 0.74(0.36-1.521 0.412

>1 54(30.17) 14 (25.93) 40 (32.00) 1

Frequency of using a fan

Never 179 (73.06) 64 (80.00) 115 (69.70) 2.13(0.83-5.511 0.118

At some time 37(15.10) 10 (12.50) 27 (16.36) 1.42(0.45-4.511 0.552

Always 29 (11.84) 06(7.50) 23 (13.94) 1 -

67 (21.47) 24 (23.08) 43 (20.67) 2.14(0.77-5.981 0.147

Frequency of using air conditioner

Never 168 (53.85) 45 (43.27) 123 (59.13) 1 -

At some time 39 (12.50) 14 (13.46) 25 (12.02) 1.53(0.73-3.201 0.258

Always 38 (12.18) 21 (20.19) 17(8.17) 3.38(1.63-6.971 0.001

67 (21.47) 24 (23.08) 43 (20.67) 1.53(0.83-2.791 0.171

Drinking water source

National supply 238 (76.28) 75 (72.12) 163 (78.37) 1 -

Domestic well 15 (4.81) 7 (6.73) 8 (3.85) 1.90(0.67-5.441 0.231

Swamp 1 (0.32) 1 (0.96) 0 (0.0) - -

Borehole 31 (9.94) 9 (8.65) 22 (10.58) 0.89(0.39-2.021 0.779

No water 3 (0.96) 1 (0.96) 2 (0.96) 1.09(0.10-12.171 0.946

23 (7.37) 10 (9.62) 13 (6.25) 1.67(0.70-3.981 0.246

No answer 1 (0.32) 1 (0.96) 0 (0.0) - -

Type of handwashing device

No device 52 (17.93) 19 (20.21) 33 (16.84) 1.28(0.68-2.431 0.438

Water supply only 30 (10.34) 11 (11.70) 19 (9.69) 1.29(0.58-2.881 0.528

Water supply with soap/bleach /hydroalcoholic gel 207 (71.38) 64 (68.09) 143 (72.96) 1 -

No answer 1 (0.34) 0(0.0) 1 (0.51) - -

Note: *people not working; ** quantitative variable; ***for more thanl person in the same room; ****people not working or working in a building where air conditioner couldn't be installed; ***** people not working or itinerant worker.

Appendix 4: Table 4. Comparison of COVID- 19-related practices and knowledge of cases and controls.

Variables Total N (%) Cases nf%) Controls n(%) OR [IC95%] P-value

Participation in ceremonies

No 286 (91.67) 100 (96.15) 186 (89.42) 1 -

Yes 26 (8.33) 4(3.85) 22 (10.58) 0.34(0.11-1.011 0.050

Frequency of participation in a sporting event as a spectator* 312 - - 0.79(0.56-1.12] 0.199

Frequency of participation in a sporting event as a player* 312 - - 0.90 [0.71-1.11] 0.211

Frequency of beach attendance* 312 - - 1.36 [0.93-1.99] 0.094

Frequency of school attendance* 312 - - 0.96 [0.90-1.02] 0.218

Frequency of bank attendance* 312 - - 0.95 [0.84-1.06] 0.336

Frequency of shop attendance* 312 - - 1.00 [0.99-1.01] 0.252

Frequency of hypermarket attendance* 312 - - 1.08 [0.92-1.27] 0.318

Frequency of market attendance* 312 - - 0.96 [0.91-1.01] 0.192

Type of mask

Cloth mask 179 (57.37) 57 (54.81) 122 (58.65) 0.85(0.53-1.371 0.517

Surgical mask/FFP2 133 (42.63) 47 (45.19) 86 (41.35) 1 -

Frequency of mask wearing in the home

Never 206 (66.03) 63 (60.58) 143 (68.75) 0.44(0.20-0.981 0.044

Rarely 41 (13.14) 12 (11.54) 29 (13.94) 0.41 [0.15-1.121 0.084

Often 37 (11.86) 15 (14.42) 22 (10.58) 0.68(0.25-1.831 0.448

Always 28 (8.97) 14(13.46) 14(6.73) 1

Frequency of wearing a mask on the street

Never/Rarely 35 (11.22) 16(15.39) 19 (9.18) 1.80(0.88-3.661 0.106

Often/ Always 276 (88.78) 88 (84.61) 188 (90.82) 1 -

Frequency of mask wearing in individual transport

Rarely 6 (1.92) 5 (4.81) 1 (0.48) 8.00(0,90-70,991 0.062

Often/ Always 104 (33.33) 40 (38.46) 64(30.77) 1 -

NA** 202 (64.74) 59 (56.73) 143 (68.75) 0,66(0,40-1,081 0.102

Frequency of wearing a mask on public transport

Never/Rarely 9(2.90) 3 (2.91) 6 (2.90) 1.19(0.29-4.93] 0.273

Often/Always 179 (57.74) 53 (51.46) 126(60.87) 1

NA** 122 (39.35) 47 (45.63) 75 (36.23) 1.49(0.92-2.421

Frequency of mask use in the workplace 0.272

Variables Total N (%) Cases n(%) Controls nf%) OR [ICgs%] P-value

Never/Rarely 46 f 14.79) 18(17.31) 28 (13.46) 1.41(0.74-2.711 0.299

Often/Always 243 (78.14) 76 (73.08) 167 (80.29) 1 -

22 (7.07) 10 (9.62) 12 (5.77) 1.83(0.76-4.421 0.179

No answer 1 (0.32) 0 (0.00) 1 (0.48) - -

Frequency of mask wearing in public places

Never/Rarely 19 (6.09) 11 (10.68) 8 (3.85) 2.99(1.16-7.681 0.023

Often/Always 292 (93.59) 92 (89.32) 200 (96.15) 1 -

No answer 1 (0.32) 1 (0.96) 0 (0.00) - -

Frequency of mask change

Once or twice a day 233 (74.68) 79 (75.96) 154(74.04) 1 -

Every two days or more 78 (25.00) 25 (24.04) 53 (25.48) 0.92(0.53-1.591 0.764

No answer 1 (0.32) 0 (0.00) 1 (0.48) - -

Lowering of the mask below the chin

Yes 268 (85.90) 91 (87.50) 177 (85.10) 1.22(0.61-2.451 0.562

No 44 (14.10) 13 (12.50) 31 (14.90) 1 -

Frequency of hand washing before entering public places

Never/Rarely 36 (11.54) 12 (11.54) 24(11.54) 1(0.47-2.081 1.000

Often/Always 276 (88.46) 92 (88.46) 184 (88.46) 1 -

Frequency of hand washing when leaving a public place

Never/Rarely 198 (63.46) 62 (59.62) 136 (65.38) 1.27(0.78-2.071 0.320

Often/Always 114 (36.54) 42 (40.38) 72 (34.62) 1 -

Frequency of hand washing upon returning home

Never/Rarely 73 (23.40) 21 (20.19) 52 (25.00) 0.76(0.42-1.341 0.340

Often/Always 239 (76.60) 83 (79.81) 156 (75.00) 1 -

Frequency of disinfection of objects or surfaces at home

Never 139(44.55) 38 (36.54) 101 (48.56) 0.67(0.32-1.421 0.301

Once to six times a week 134(42.95) 52 (50.00) 82 (39.42) 1.13(0.54-2.371 0.742

Every day 39 (12.50) 14(13.46) 25 (12.02) 1 -

Frequency of disinfection of objects or surfaces at the workplace 0.373

Never 115 (39.89) 35 (33.65) 80 (38.46) 0.68(0.38-1.211 0.191

Once to three times a week 82 (28.37) 23 (22.12) 59 (28.37) 0.60(0.32-1.151 0.125

Every day 92 (31.83) 36 (34.62) 56 (26.92) 1

NA*** 22 (7.05) 10 (9.62) 12 (5.77) 1.30(0.51-3.311 0.588

Variables Total Cases Controls OR [IC95%] P-

Nf%) nf%) n(%) value

No answer 1 (0.32) 0 (0.00) 1 (0.48) -

Frequency of touching the face, eyes or mouth

Never 13 (4.17) 2 (1.92) 11 (5.29) 1

Rarely 95 (30.45) 33 (31.73) 62 (29.81) 2.93(0.61-14.001 0.178

Often 113 (36.22) 44(42.31) 69 (33.17) 3.51(0.74-16.581 0.113

Very often 91 (29.17) 25 (24.04) 66 (31.73) 2.08(0.43-10.071 0.361

Frequency of handshake greeting

Never 213 (68.27) 78 (75.00) 135 (64.90) 1 -

Rarely 62 (19.87) 18 (17.31) 44(21.15) 0.70(0.38-1.311 0.271

Often 22 (7.05) 5 (4.81) 17(8.17) 0.51(0.18-1.431 0.201

Always 15 (4.81) 3 (2.88) 12 (5.77) 0.43(0.12-1.581 0.205

Number of known modes of transmission - - - 0.91 [0.76-1.09] 0.309

Number of known symptoms - - - 0.87(0.74-1.02] 0.086

Number of known persons at risk - - - 0.82(0.69-0.98] 0.029

Knowledge of the incubation period of the Coronavirus

No 147 (47.12) 67 (64.42) 80 (38.46) 2.89(1.77-4.721

Yes 165 (52.88) 37(35.38) 128 (61.54) 1 -

Knowledge of the existence of asymptomatic COVID-19 cases

No 50 (16.03) 16(15.38) 34(16.35) 0.93(0.48-1.771 0.826

Yes 262 (83.97) 88 (84.62) 174(83.65) 1 -

Knowledge of the existence of the capacity of asymptomatic COVID-19 cases to transmit the virus

No 52 (16.67) 22 (21.15) 30 (14.42) 1.59(0.87-2.931 0.138

Yes 260 (83.33) 82 (78.85) 178(85.58) 1 -

Number of known protective measures - - - 0.73 [0.57-0.94] 0.015

Alcohol use

Moderate use 227 (88.78) 185 (88.94) 92 (88.46) 1 -

Misuse 33 (10.58) 22 (10.58) 11 (10.58) 1.01(0.47-2.161 0.989

Addiction 2 (0.64) 1 (0.48) 1 (0.96) 2.01(0.12-32.511 0.623

Note: * quantitative variable; **people not using this mode of transport; ***people not working