Epidemiology: Open Access
Open Access

The appearance of a new coronavirus disease (COVID-19) was first reported in December 2019 in Wuhan, China [1]. The number of cases has increased exponentially not only in China but in the world. The Moroccan health authorities announced the first confirmed case of Covid-19 on March 2, 2020. COVID-19 was officially declared a pandemic by the world health organization on March 11, 2020 [2]. From December 2019 until the time of writing this article, 11, 4 million cases of COVID-19 have been confirmed worldwide and more than 535 000 people have died [3]. This pandemic has put global public health institutions on alert [4,5,6]. Morocco, like many countries in the world, declared a state of health emergency and quarantine on March 20, 2020.

Admittedly, quarantine and the state of health emergency have a great interest in controlling the spread of the pandemic [7]. However, it is also important to understand the implications of these restrictions on the health and well-being of the community.

We hypothesized that health-related quality of life is more likely to be affected during the COVID-19 pandemic.

Therefore, we aim in this study to provide an analysis of the health and well-being of a sample of the general population during the quarantine period.

Characteristics of the participants

We conducted a descriptive cross-sectional online survey about two months after the declaration of quarantine and the COVID-19 state of emergency in Morocco. All participants were adults over the age of 18, resident in Morocco who were not epidemiologically infected with the virus, but they lived in places affected by COVID-19. To have a representative national sample and cover people in areas of varying severity of COVID-19, we interviewed citizens across the 12 regions of Morocco.

Study procedure

Given the circumstances of the quarantine, the study announcements, containing brief information about the study and a link to a web page, were shared by e-mail (to personal and professional networks), and published on Facebook and other popular social media websites, including Twitter and Instagram. The online survey was administered by Google Forms to ensure wide reach and easy access. Participants were asked to share the survey with their families and acquaintances.

Responses to all elements of the questionnaire were required, and respondents could only submit their responses if all questions were answered. The data reported in this study was collected between May 25 and June 6, 2020.

Participation was voluntary and all participants gave informed consent electronically and without any remuneration for their participation. No identifying information was collected to protect the anonymity of participants.

Variables studied

Participants provided their socio-demographic characteristics, such as gender, age, education and residence (region and city) as well as their knowledge and practices regarding the Covid-19 pandemic. Given that COVID-19 is more dangerous for people with comorbidities [8], so we asked if the participants had a chronic disease.

We assessed individual health using the Short Form-12 (SF12). We used a Moroccan version validated in Arabic and French [9]. SF12 contains 12 elements and 8 dimensions: physical activity (2 elements), limitations due to physical activity (2 elements), physical pain (1 element), perceived general health (1 element), vitality (1 element), social functioning (1 element), limitations due to mental state (2 elements) and mental health (2 elements) [10]. The eight dimensions form two physical and mental subscores (PCS and MCS), with a possible total score ranging from 0 to 100 [11]. A higher SF12 score indicates better health.

Statistical analyzes

We report descriptive statistics of the study variables. The analyzes were performed by IBM SPSS Statistics v 21. We used the t-student test to compare the means of the summary physical and mental scores of the SF-12, after having checked the normality of the distribution of the two scores. The materiality threshold was set at 0.05.

279 participants responded to the survey. Table 1 presents the descriptive characteristics of the participants. The average age was 34.75 years (± 11.8). The majority of participants were men (51.6%), singles (66.3%) and those with a university level (88.9%). All regions were represented. The Marrakech–Safi region was the most represented (25.40%). 13.3% of the participants indicated that they have a family member or know a loved one with a confirmed Covid-19 infection. 10.40% of the participants reported that they suffered from chronic diseases.

Table 1: Description of participants (n=279).

Regarding participants' knowledge of Covid-19 (Table 2): 76.4% think it is a dangerous disease and 30% think it is fatal in 15 to 40% of cases. 90% believe that transmission is through the droplets of an infected person. The most vulnerable group according to participants is the elderly and people with chronic diseases in 87.1% and 91.8% of the responses respectively. The majority of respondents reported fever, cough and difficulty breathing as major symptoms of the disease in 95.7%, 93.2% and 88.5% of the responses. 62.70% of participants believe that there is no specific current treatment for Covid-19 infection. 95.69% of participants believe that wearing a mask is effective in preventing Covid-19 infection.

Table 2: Participants' knowledge of the Covid-19 (n = 279).

Concerning the practices of the population in the face of the Covid-19 pandemic. The majority of participants (96.77%) report that they follow the health recommendations for coronavirus and 75.95% comply with the quarantine recommendations in more than 80% (Figure 1). 90.32% of the respondents report that they always wear the mask when leaving the house. 97.50% of participants wash their hands daily at least with soap and water.

Figure 1: Level of commitment of participants in quarantine.

Participants' fear of catching the coronavirus was assessed using an increasing numerical scale from 1 to 10 (Figure 2). 60.6% of the participants reported a fear less than or equal to 5 degrees.

Figure 2: Level of fear of Covid-19 participants.

Based on the SF12 algorithm [9], all participants obtained a total average score of 70.60 (± 13.1) with a mental health score (MCS) of 34.49 (± 6.44) and a physical health score (PCS) of 36.10 (± 5.82). The physical (PCS) and mental (MCS) scores of participants with chronic diseases were 32.51 (± 7.14) and 29.28 (± 1.23), respectively.

Overall, the participants' PCS and MCS scores suffered from chronic diseases and the elderly participants were lower than those of young participants without comorbidities.

Restrictive measures applied in several countries around the world appear to be effective in containing the spread of COVID-19 [7]. However, these measures have disrupted people's daily employment and daily activities and can therefore have important implications for their health and well-being [12].

As was the case previously with the Middle East respiratory syndrome coronavirus (MERS-CoV) [13,14], the COVID-19 pandemic also causes panic and mental health problems for the general population [15,16.17]. In addition, quarantine could affect the psychological health of the public [18,19]. This can influence the general health and quality of life of people.

People with chronic health conditions are vulnerable populations with a lower quality of life during this Covid-19 crisis [20]. However, health systems have largely neglected this fragile population.

Our results show that the quality of life linked to the general health of people in quarantine is poor and especially if there are chronic health problems, as shown by SF12. Insignificant differences in some dimensions of SF12 (body pain, physical functioning and social functioning) were present, since people who had not been directly affected by the virus would not differ much in these dimensions.

An article published on Lancet pointed out that people in quarantine have reported a high prevalence of symptoms of distress and psychological disorders and some of these symptoms seem to persist long after quarantine.

We may need to pay more attention to those affected and those with co-morbidities, but also physically active people, who may be more frustrated with the quarantine restrictions. Such identification can help health systems prioritize those who may have more impact during this health crisis.

We present this data on general quality of life disruptions to provide evidence on the health of the community during this Covid-19 crisis.

The study has certain limitations. First of all, this study was based on a cross-sectional observation survey. The data do not allow conclusions to be drawn about the nature or the orientation of the associations examined. We also do not know whether this lower quality of life existed before COVID-19.

Likewise, online self-assessment questionnaires may be influenced by the difficulty of completing them. This could affect the validity of the data provided.

Given our recruitment methods and our sample size, the results may not be generalized to the entire population of Morocco and other countries. Nevertheless, the hypotheses reported could be targets for future studies.

The results underscore the importance of social ties to mitigate the negative consequences of the COVID-19 pandemic on mental health and physical well-being. Policymakers managing the COVID-19 pandemic can benefit from understanding these implications for the health and well-being of the population, especially the elderly and those with chronic diseases.

We declare no competing interests.

None

1. O’Loughlin J, Robitaille V, Boivin JF, Suissa S (1993) Incidence of and risk factors for falls and injurious falls among the community-dwelling elderly. Am J Epidemiol 137: 342-354.
2. National Center for Health Statistics (NCHS), National Vital Statistics System. Accessed from Centers for Disease Control and Prevention (CDC).
3. Siracuse JJ, Odell DD, Gondek SP, Odom SR, Kasper EM, et al. (2012) Health care and socioeconomic impact of falls in the elderly. Am J Surg 203: 335-338
4. Afilalo J, Karunananthan S, Eisenberg MJ, Alexander KP, Bergman H (2009) Role of frailty in patients with cardiovascular disease. Am J Cardiol 103: 1616-1621.
5. Yeung SSY, Reijnierse EM, Pham VK, Trappenburg MC, Lim WK, et al. (2019) Sarcopenia and its association with falls and fractures in older adults: A systematic review and meta-analysis. J Cachexia Sarcopenia Muscle 10: 485-500.
6. Fülster S, Tacke M, Sandek A, Ebner N, Tschöpe C, et al. (2013) Muscle wasting in patients with chronic heart failure: Results from the studies investigating co-morbidities aggravating heart failure (SICA-HF). Eur Heart J 34:512-519.
7. Park JK, Deutz NEP, Cruthirds CL, Kirschner SK, Park H, et al. (2020) Risk factors for postural and functional balance impairment in patients with chronic obstructive pulmonary disease. J Clin Med 9: 609.
8. The Centers for Disease Control and Prevention (CDC). STEADI Algorithm for Fall Risk Screening, Assessment, and Intervention.
9. Hamel C, Hekmatjah N, Hakakian B, Banooni M, Lalezari J, et al. 2019. Evidence-Based Community Fall Prevention Programs at Senior Centers Near 10 US Academic Centers. J Am GeriatrSoc 67: 1484-1488.
10. Zijlstra GA, van Haastregt JC, Ambergen T, van Rossum E, van Eijk JT, et al. (2009) Effects of a multicomponent cognitive behavioral group intervention on fear of falling and activity avoidance in community-dwelling older adults: Results of a randomized controlled trial. J Am GeriatrSoc 57: 2020-2028.
11. Clemson L, Cumming RG, Kendig H, Swann M, Heard R, et al. (2004) The effectiveness of a community-based program for reducing the incidence of falls in the elderly: A randomized trial. J Am Geriatr Soc 52: 1487-1494.
12. Li F, Harmer P, Fitzgerald K, Eckstrom E, Akers L, et al. (2018) Effectiveness of a Therapeutic Tai JiQuan Intervention vs. a Multimodal Exercise Intervention to Prevent Falls Among Older Adults at High Risk of Falling A Randomized Clinical Trial. JAMA Intern Med 178: 1301-1310.
13. Smith M, Towne S, Herrera-Venson A, Cameron K, Horel SA, et al. (2018) Delivery of fall prevention interventions for at-risk older adults in rural areas: Findings from a national dissemination. Int J Environ Res Public Health 15: 2798.
14. Campbell AJ, Robertson MC, Gardner MM, Norton RN, Buchner DM (1999) Falls prevention over 2 years: A randomized controlled trial in women 80 years and older. Age Ageing 28: 513-518.
15. Shumway-Cook A, Silver IF, LeMier M, York S, Cummings P, et al. (2007) Effectiveness of a community-based multifactorial intervention on falls and fall risk factors in community-living older adults: A randomized, controlled trial. J Gerontol A BiolSci Med Sci 62: 1420-1427.
16. Callahan LF, Cleveland RJ, Altpeter M, Hackney B (2016) Evaluation of Tai Chi Program Effectiveness for People with Arthritis in the Community: A Randomized Controlled Trial. J Aging Phys Act 24: 101-110.
17. Podsiadlo D, Richardson S (1991) The timed “Up and Go”: A test of basic functional mobility for frail elderly persons. J Am Geriatr Soc 39: 142-148.
18. Pfeiffer E (1975) A short portable mental status questionnaire for the assessment of organic brain deficit in elderly patients. J Am Geriatr Soc 23: 433-441.
19. Wilson LA, Brass W (1973) Brief assessment of the mental state in geriatric domiciliary practice. The usefulness of the mental status questionnaire. Age Ageing 2: 92-101.
20. Folstein MF, Folstein SE, McHugh PR (1975) "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 12: 189-198.