Cross-sectional study of COVID-19 knowledge, beliefs and prevention behaviours among adults in Senegal

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Abstract

Objectives

The aim of the study was to explore COVID-19 beliefs and prevention behaviours in a francophone West African nation, Senegal.

Design

This was a cross-sectional analysis of survey data collected via a multimodal observational study.

Participants

Senegalese adults aged 18 years or older (n=1452).

Primary and secondary outcome measures

Primary outcome measures were COVID-19 prevention behaviours. Secondary outcome measures included COVID-19 knowledge and beliefs. Univariate, bivariate and multivariate statistics were generated to describe the sample and explore potential correlations.

Setting

Participants from Senegal were recruited online and telephonically between June and August 2020.

Results

Mask wearing, hand washing and use of hand sanitiser were most frequently reported. Social distancing and staying at home were also reported although to a lower degree. Knowledge and perceived risk of COVID-19 were very high in general, but risk was a stronger and more influential predictor of COVID-19 prevention behaviours. Men, compared with women, had lower odds (adjusted OR (aOR)=0.59, 95% CI 0.46 to 0.75, p<0.001) of reporting prevention behaviours. Rural residents (vs urban; aOR=1.49, 95% CI 1.12 to 1.98, p=0.001) and participants with at least a high school education (vs less than high school education; aOR=1.33, 95% CI 1.01 to 1.76, p=0.006) were more likely to report COVID-19 prevention behaviours.

Conclusions

In Senegal, we observed high compliance with recommended COVID-19 prevention behaviours among our sample of respondents, in particular for masking and personal hygiene practice. We also identified a range of psychosocial and demographic predictors for COVID-19 prevention behaviours such as knowledge and perceived risk. Stakeholders and decision makers in Senegal and across Africa can use place-based evidence like ours to address COVID-19 risk factors and intervene effectively with policies and programming. Use of both phone and online surveys enhances representation and study generalisability and should be considered in future research with hard-to-reach populations.

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Most cited references 46

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An interactive web-based dashboard to track COVID-19 in real time

Ensheng Dong, Hongru Du, Lauren Gardner (2020)

In December, 2019, a local outbreak of pneumonia of initially unknown cause was detected in Wuhan (Hubei, China), and was quickly determined to be caused by a novel coronavirus, 1 namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The outbreak has since spread to every province of mainland China as well as 27 other countries and regions, with more than 70 000 confirmed cases as of Feb 17, 2020. 2 In response to this ongoing public health emergency, we developed an online interactive dashboard, hosted by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, Baltimore, MD, USA, to visualise and track reported cases of coronavirus disease 2019 (COVID-19) in real time. The dashboard, first shared publicly on Jan 22, illustrates the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries. It was developed to provide researchers, public health authorities, and the general public with a user-friendly tool to track the outbreak as it unfolds. All data collected and displayed are made freely available, initially through Google Sheets and now through a GitHub repository, along with the feature layers of the dashboard, which are now included in the Esri Living Atlas. The dashboard reports cases at the province level in China; at the city level in the USA, Australia, and Canada; and at the country level otherwise. During Jan 22–31, all data collection and processing were done manually, and updates were typically done twice a day, morning and night (US Eastern Time). As the outbreak evolved, the manual reporting process became unsustainable; therefore, on Feb 1, we adopted a semi-automated living data stream strategy. Our primary data source is DXY, an online platform run by members of the Chinese medical community, which aggregates local media and government reports to provide cumulative totals of COVID-19 cases in near real time at the province level in China and at the country level otherwise. Every 15 min, the cumulative case counts are updated from DXY for all provinces in China and for other affected countries and regions. For countries and regions outside mainland China (including Hong Kong, Macau, and Taiwan), we found DXY cumulative case counts to frequently lag behind other sources; we therefore manually update these case numbers throughout the day when new cases are identified. To identify new cases, we monitor various Twitter feeds, online news services, and direct communication sent through the dashboard. Before manually updating the dashboard, we confirm the case numbers with regional and local health departments, including the respective centres for disease control and prevention (CDC) of China, Taiwan, and Europe, the Hong Kong Department of Health, the Macau Government, and WHO, as well as city-level and state-level health authorities. For city-level case reports in the USA, Australia, and Canada, which we began reporting on Feb 1, we rely on the US CDC, the government of Canada, the Australian Government Department of Health, and various state or territory health authorities. All manual updates (for countries and regions outside mainland China) are coordinated by a team at Johns Hopkins University. The case data reported on the dashboard aligns with the daily Chinese CDC 3 and WHO situation reports 2 for within and outside of mainland China, respectively (figure ). Furthermore, the dashboard is particularly effective at capturing the timing of the first reported case of COVID-19 in new countries or regions (appendix). With the exception of Australia, Hong Kong, and Italy, the CSSE at Johns Hopkins University has reported newly infected countries ahead of WHO, with Hong Kong and Italy reported within hours of the corresponding WHO situation report. Figure Comparison of COVID-19 case reporting from different sources Daily cumulative case numbers (starting Jan 22, 2020) reported by the Johns Hopkins University Center for Systems Science and Engineering (CSSE), WHO situation reports, and the Chinese Center for Disease Control and Prevention (Chinese CDC) for within (A) and outside (B) mainland China. Given the popularity and impact of the dashboard to date, we plan to continue hosting and managing the tool throughout the entirety of the COVID-19 outbreak and to build out its capabilities to establish a standing tool to monitor and report on future outbreaks. We believe our efforts are crucial to help inform modelling efforts and control measures during the earliest stages of the outbreak.

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Using social and behavioural science to support COVID-19 pandemic response

Jay Bavel, Katherine Baicker, Paulo S Boggio … (2020)

The COVID-19 pandemic represents a massive global health crisis. Because the crisis requires large-scale behaviour change and places significant psychological burdens on individuals, insights from the social and behavioural sciences can be used to help align human behaviour with the recommendations of epidemiologists and public health experts. Here we discuss evidence from a selection of research topics relevant to pandemics, including work on navigating threats, social and cultural influences on behaviour, science communication, moral decision-making, leadership, and stress and coping. In each section, we note the nature and quality of prior research, including uncertainty and unsettled issues. We identify several insights for effective response to the COVID-19 pandemic and highlight important gaps researchers should move quickly to fill in the coming weeks and months.

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Knowledge, attitudes, and practices towards COVID-19 among Chinese residents during the rapid rise period of the COVID-19 outbreak: a quick online cross-sectional survey

Bao-Liang Zhong, Wei Luo, Hai-Mei Li … (2020)

Unprecedented measures have been adopted to control the rapid spread of the ongoing COVID-19 epidemic in China. People's adherence to control measures is affected by their knowledge, attitudes, and practices (KAP) towards COVID-19. In this study, we investigated Chinese residents' KAP towards COVID-19 during the rapid rise period of the outbreak. An online sample of Chinese residents was successfully recruited via the authors' networks with residents and popular media in Hubei, China. A self-developed online KAP questionnaire was completed by the participants. The knowledge questionnaire consisted of 12 questions regarding the clinical characteristics and prevention of COVID-19. Assessments on residents' attitudes and practices towards COVID-19 included questions on confidence in winning the battle against COVID-19 and wearing masks when going out in recent days. Among the survey completers (n=6910), 65.7% were women, 63.5% held a bachelor degree or above, and 56.2% engaged in mental labor. The overall correct rate of the knowledge questionnaire was 90%. The majority of the respondents (97.1%) had confidence that China can win the battle against COVID-19. Nearly all of the participants (98.0%) wore masks when going out in recent days. In multiple logistic regression analyses, the COVID-19 knowledge score (OR: 0.75-0.90, P<0.001) was significantly associated with a lower likelihood of negative attitudes and preventive practices towards COVID-2019. Most Chinese residents of a relatively high socioeconomic status, in particular women, are knowledgeable about COVID-19, hold optimistic attitudes, and have appropriate practices towards COVID-19. Health education programs aimed at improving COVID-19 knowledge are helpful for Chinese residents to hold optimistic attitudes and maintain appropriate practices. Due to the limited sample representativeness, we must be cautious when generalizing these findings to populations of a low socioeconomic status.

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Author and article information

Journal

Journal ID (nlm-ta): BMJ Open

Journal ID (iso-abbrev): BMJ Open

Journal ID (hwp): bmjopen

Journal ID (publisher-id): bmjopen

Title: BMJ Open

Publisher: BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )

ISSN (Electronic): 2044-6055

Publication date Collection: 2022

Publication date (Electronic): 26 May 2022

Publication date PMC-release: 26 May 2022

Volume: 12

Issue: 5

Electronic Location Identifier: e057914

Affiliations

[1 ]departmentDepartment Family Medicine and Community Health , University of Pennsylvania Perelman School of Medicine , Philadelphia, Pennsylvania, USA

[2 ]departmentDepartment of Epidemiology , Ohio State University College of Public Health , Columbus, Ohio, USA

[3 ]The African Health and Education Network (NGO RAES) , Dakar, Senegal

[4 ]departmentDepartment of Epidemiology , UCLA Fielding School of Public Health , Los Angeles, California, USA

[5 ]departmentDepartment of Community Health Sciences , UCLA Fielding School of Public Health , Los Angeles, California, USA

[6 ]departmentDepartment of Health, Human Performance and Recreation , University of Arkansas College of Education and Health Professions , Fayetteville, Arkansas, USA

Author notes

[Correspondence to ] Dr Matthew Kearney; kearnm@ 123456pennmedicine.upenn.edu

Author information

Matthew Kearney http://orcid.org/0000-0003-2898-573X

Marta Bornstein http://orcid.org/0000-0002-5200-8181

Roch Nianogo http://orcid.org/0000-0001-5932-6169

Deborah Glik http://orcid.org/0000-0002-2532-3661

Philip Massey http://orcid.org/0000-0002-0577-8618

Article

Publisher ID: bmjopen-2021-057914

DOI: 10.1136/bmjopen-2021-057914

PMC ID: 9136694

PubMed ID: 35618332

SO-VID: ee0a51df-b2d0-47d9-a813-249fa3edefb5

License:

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.

History

Date received : 11 October 2021

Date accepted : 27 April 2022

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access-type free

ScienceOpen disciplines: Medicine

Keywords: covid-19,public health

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ScienceOpen disciplines: Medicine

Keywords: covid-19, public health

Cross-sectional study of COVID-19 knowledge, beliefs and prevention behaviours among adults in Senegal

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Abstract

Objectives

Design

Participants

Primary and secondary outcome measures

Setting

Results

Conclusions

Related collections

Novel Coronavirus Disease COVID-19

Most cited references 46

An interactive web-based dashboard to track COVID-19 in real time

Using social and behavioural science to support COVID-19 pandemic response

Knowledge, attitudes, and practices towards COVID-19 among Chinese residents during the rapid rise period of the COVID-19 outbreak: a quick online cross-sectional survey

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