Mental health of frontline healthcare workers exposed to COVID-19 in Egypt: A call for action

Abstract

Background:

World Health Organization (WHO) declared Coronavirus disease 2019 (COVID-19) as a pandemic in March 2020. Such widespread outbreaks are associated with adverse mental health consequences.

Aims:

To evaluate mental health outcomes among Egyptian healthcare workers (HCW) treating patients with confirmed or suspected Coronavirus Disease 2019 (COVID-19) to direct the promotion of mental wellbeing, by screening for symptoms of anxiety, insomnia, depression and stress, and analyzing potential risk factors.

Methods:

This cross-sectional, hospital-based survey study collected demographic data and mental health measurements from 502 HCW dealing with COVID-19. HCW were surveyed in 20 hospitals (Fever, Chest, and Quarantine hospitals) in different parts of Egypt, in April and May 2020.

Results:

Among the 502 HCW surveyed; 60.0% were physicians, 16.1% were specialized nurses, and 23.9% were non-specialized nurses. About 35.3% worked in chest hospitals, 17.5% in fever hospitals, and 47.2% in quarantine hospitals. A considerable proportion of HCW had symptoms of anxiety, insomnia, depression, and stress. Females were at higher risk of experiencing symptoms of severe anxiety (odds ratio [OR], 1.85; 95% CI, 1.12–3.05; p = .016), severe depression (OR, 2.013; 95% CI, 1.17–3.4; p = .011), and severe stress (OR, 2.68; 95% CI, 1.5–4.6; p < .001). Fever hospital workers were at higher risk of severe depression (OR, 1.52; 95% CI, 1.11–2.09; p < .01), compared to Quarantine hospital workers.

Conclusion:

Ensuring proper mental health support for HCW is an important component of public health measures for addressing the COVID-19 epidemic and safeguarding the continuity of appropriate medical service.

Keywords

COVID-19 mental health depression anxiety insomnia healthcare workers

Introduction

The World Health Organization (WHO) declared Corona-virus disease 2019 as (COVID-19) pandemic in March 2020, pointing to over 110 countries and territories around the world where coronavirus disease was present. Infectious disease outbreaks such as COVID-19, as well as other public health events, can cause emotional distress and anxiety. These feelings of distress and anxiety can occur even in people that are not at high risk of getting sick (Montemurro, 2020; Rajkumar, 2020; Rcpsych.ac.uk, 2020; WHO, 2020a).

As COVID-19 is rapidly spreading worldwide, on May 30, 2020, there have been 5,819,962 confirmed cases worldwide, with 362,786 deaths. Egypt reported 22,082 confirmed cases and 879 deaths have been reported in EGYPT on 30th of May 2020 (WHO, 2020b).

Besides the direct impact of the pandemic, previous studies reported how much medical staffs suffer from vicarious traumatization. In South and Southeast Asia countries, also in Italy, there were psychological problems in medical staff due to high workload and intermittent lack of protective devices (Kang et al., 2020; Montemurro, 2020).

The modern history of infectious diseases has witnessed emergence of serious ones. Outbreaks of new influenza strains such as H1N1 (swine flu) that appeared in North America in 2009, while a novel virus of avian origin (H7N9) emerged four years later in China. Another example is the largest outbreak of Ebola virus disease that was in West Africa from 2013 to 2016, but the virus was first discovered in 1976 after an outbreak in Central Africa. Each of these past outbreaks raised similar problems for health services and staff in terms of the psychological impact of increased workload, the need for personal protection, and fears of possible infection of themselves and their families (Kisely et al., 2020).

Hence, facing the critical situation of this growing pandemic, healthcare workers on the frontline who are directly involved in the diagnosis, treatment, and care of patients with COVID-19 are at risk of developing psychological distress and other mental health symptoms. The ever-increasing number of confirmed and suspected cases, overwhelming workload, depletion of personal protection equipment, widespread media coverage, lack of specific drugs or proper treatment, and feelings of being inadequately supported may all contribute to the mental burden of these healthcare workers (Lai et al., 2020).

On the other hand, most health professionals working in quarantine units and hospitals very often do not receive any training for providing mental healthcare (Lima et al., 2020). Barbisch et al. (2015) described how the confinement ‘caused a sense of collective hysteria, leading the staff to desperate measures’. Suicidal cases were reported in India (Goyal et al., 2020) but also in other countries, Italy included, where two infected Italian nurses committed suicide in a period of a few days probably due to fear of spreading COVID-19 to patients (Montemurro, 2020 ). The situation in Egypt is becoming more critical with the increasing number of cases and mortality with the possibility of higher actual numbers than the reported (Hassany et al., 2020; Tuite et al., 2020). Moreover the governmental health expenditure in Egypt is only 5.3% of gross domestic product (GDP), such limited resources combined with the ever increasing number of cases place a huge burden on healthcare workers (The world bank, 2020). The Egyptian Ministry of Health announced on March 31 that two hotlines are allocated at the General Secretariat for Mental Health in order to provide psychological support to citizens (including healthcare providers) during the COVID-19 pandemic (Ahramonline, 2020).

The aim of current study is to evaluate mental health outcomes among Egyptian healthcare workers treating patients with confirmed or suspected COVID-19 to serve as important evidence to direct the promotion of mental wellbeing among healthcare workers, by screening for symptoms of depression, anxiety, insomnia, and stress and by analyzing potential risk factors associated with these symptoms.

Methods

Study design

This study was registered at the Faculty of Medicine Ain Shams Research Institute (MASRI) and approved by the Research Ethics Committee of the Faculty of Medicine, Ain Shams University (FMASU REC). Informed consent was included in the survey explaining in details the study design and aim prior to respondents’ enrollment. Participants could terminate the survey at any time they desired. The survey was anonymous, and confidentiality of information was assured.

The study was a cross-sectional, hospital-based survey, conducted in April and May 2020. At the time of the study, the total confirmed cases of COVID-19 in Egypt exceeded 7,000 (WHO, 2020c).

Healthcare workers in 20 hospitals involved in direct care of COVID-19 patients and suspected individuals in either fever hospitals, chest hospitals and quarantine hospitals were approached in this study.

Participants

Healthcare workers involved in direct care of COVID-19 patients and suspected individuals which included doctors, nurses, and non-specialized nurses. ‘Nurses’ refer to those who hold a bachelor’s degree (i.e. university graduates) while ‘non-specialized nurses’ refer to those who are graduated from technical nursing schools. Healthcare workers with history of any psychiatric disorder were excluded. The sample consisted of 30 to 50 healthcare workers from each hospital. The target sample size of participants was calculated using PASS program version 15, setting the type-1 error (α) at 0.05 and margin of error 5%. Result from previous study⁶ showed that 50.4% of healthcare workers dealing with COVID-19 cases had psychological co- morbidities (depression). Calculation according to these values produced a sample size of 500 cases, taking in account 20% dropout rate, and using the formula; N = Zα2P (1 − P)/d2, in which α = 0.05 and Zα = 1.96, and d = 5%.

Sampling method

A multistage probability sample of clusters of hospitals in geographically defined areas was prepared. In the first stage, Egypt was divided geographically into four regions: Delta region, Upper Egypt, Suez Canal region, and Greater Cairo. In the second stage of the sampling plan, one or two hospitals (clusters) were randomly selected from each selected governorate and all healthcare workers in each hospital were invited to participate in the study.

Study tools

Sociodemographic data of the participants including age, sex, educational level (doctorate degree, master’s degree, bachelor’s degree or technical school degree), marital status, and place of work were collected.

We focused on symptoms of depression, anxiety, insomnia, and distress for all participants, using the following tools:

– Patient Health Questionnaire (PHQ) (Spitzer et al., 1999), Arabic version was used after permission of the author (Sawaya et al., 2016). Scores of 0 to 4 are considered normal, 5 to 9 indicate mild depression, scores of 10 to 14 indicates moderate depression, and scores of 15 to 21 indicates severe depression.

– The 7-item Generalized Anxiety Disorder (GAD-7) (Spitzer et al., 2006), Arabic version was used (with authors’ permission) to identify patients with probable GAD (Sawaya et al., 2016). The scale scores range from 0 to 21; with scores of 0 to 4 considered normal, scores of 5 to 9 indicate mild anxiety, scores of 10 to 14 indicates moderate anxiety, and scores of 15 to 21 indicate severe anxiety.

– The 7-item Insomnia Severity Index (ISI) (Morin, 1993), Arabic version was used after permission of the author (Suleiman & Yates, 2011). Scale scores ranges from 0 to 28; with scores of 0 to 7 considered normal, scores of 8 to 14 indicate subthreshold insomnia, scores of 15 to 21 indicate moderate insomnia while scores of 22 to 28 indicate severe insomnia.

– The Perceived Stress Scale (PSS) (Cohen et al., 1983) is one of the most popular tools for measuring psychological stress and evaluating the degree to which individuals believe their life has been unpredictable, uncontrollable, and overloaded during the previous month. In our study we have used the Arabic version after permission of the author (Chaaya et al., 2010). The scale scores of 0 to 8 were considered normal, scores of 9 to 25 indicate mild distress, scores of 26 to 43 indicate moderate distress while scores of 44 to 88 indicate severe distress.

Data management and analysis

Data were revised, coded, entered on a computer and analyzed using SPSS package version number 22. Quantitative data were tested for normality with Shapiro-Wilk test and described as mean, standard deviation (SD) or median/interquartile range according to data distribution. Mann-Whitney U test and Kruskal-Wallis test were used to compare the severity of each symptom between two or more groups. Qualitative data were expressed as frequencies (n) and percentage (%). Chi-square test was used to test the association between qualitative variables. Multivariate logistic regression analysis was performed for detecting risk factors for symptoms of Anxiety, insomnia, depression, and stress in participants, after adjustment for confounders, including age, sex, marital status, job, educational level, type, and site of hospital. p-value ⩽.05 was considered significant.

Results

Descriptive data

Socio-demographic characteristics

In the study, 502 healthcare workers were included; 301 (60.0%) were physicians, 81 (16.1%) were specialized nurses, 120 (23.9%) were non-specialized nurses. One hundred seventy-seven (35.3%) worked in chest hospitals, 88 (17.5%) worked in fever hospital, and 237 (47.2%) worked quarantine hospitals. Male to female ratio was 1:1. Sixty-nine participant (13.7%) aged from 18 to 25, 163 (32.5%) from 26 to 30 years, 223 (44.4%) from 31 to 40 years, and 47 (9.45%) were above 40 years old. As regards marital status; 184 (36.7%) were single, 301 (60%) were married, and 17 (3.4%) were divorced/widowed. Among physicians, 126 (41.9%) were working as chest specialists, 38 (12.6%) were ICU specialists, 87 (28.9%) were internal medicine/pediatric specialists, 40 (13.3%) were laboratory/radiology specialists and 10 (3.3%) were surgery specialists. According to the educational level, 163 (32.5%) had a bachelor’s degree, 198 (39.4%) had master’s degree, 21 (4.2%) had doctorate degree, and 120 (23.9%) had technical institute degree. A 145 participants (28.9%) were distributed in Greater Cairo hospitals, 230 (45.8%) in Delta areas, 94 (18.7%) in Upper Egypt, and 33 (6.6%) in Suez Canal. All the 502 participants were frontline healthcare workers directly engaged in diagnosing, treating, or caring for patients with or suspected to have COVID-19.

The clinical characteristics of the study sample

The total number of participants was 502, however for each of the tools the number of whom completed the tools differed; GAD-7 questionnaire was answered by 484 participants, ISI questionnaire by 473 participants, PHQ by 457, and PSS by 444 participants.

A considerable proportion of healthcare workers had symptoms of anxiety as 370 of the participants (76.4%) were showing abnormal scores on the GAD-7 scale; 175 (36.2%) were mild, 118 (24.4%) were moderate, and 77 (15.9%) were severe. According to the insomnia severity scale 320 (67.7%) showed positive results; 195 (41.2%) were sub-threshold, 101 (21.4%) were moderate and 24 (5.1%) were severe while, 353 (77.2%) had depressive symptoms; 160 (35.0%) were mild, were 109 (23.9%) moderate, and 84 (18.4%) were severe. As regard the perceived stress scale; 359 (80.9%) showed abnormal results, 284 (64.0%) were showing moderate stress levels, and 75 (16.9%) were with high results.

Severity of measurements and associated factors

Through the study non statistical significance was found on comparing the site of the hospital, marital status, educational degree, specialty of the physicians, and the job category of the study participants with the four questionnaires.

On the other hand, when comparing HCW according to age groups as regard the four studied measurement; no statistically significance difference was found regarding GAD 7 and ISI. However, a highly significant difference was found as regard PHQ and PSS, as 41.3% of workers in the youngest age group (18–25) had no depression compared to only 17%, 20%, and 27% of workers in 26 to 30, 31 to 40, and >40 years groups, respectively. Nevertheless, only 11.7% of workers in the youngest age group (18–25) had low grade stress compared to 18.3%, 17.7%, and 39.5% of workers in 26 to 30, 31 to 40, and >40 years groups, respectively (Table 1).

Table 1.

Description and comparison of severity categories of depression, anxiety, insomnia, and stress measurements according to age groups.

		Age group								p *	Sig
		18–25		26–30		31–40		>40
		N	%	N	%	N	%	N	%
GAD-7	Normal	17	25.8	38	24.1	45	21.1	14	29.8	.739	NS
	Mild	27	40.9	55	34.8	79	37.1	14	29.8
	Moderate	15	22.7	43	27.2	49	23.0	11	23.4
	Severe	7	10.6	22	13.9	40	18.8	8	17.0
ISI	None	22	33.8	44	28.9	70	33.2	17	37.8	.508	NS
	Subthreshold	27	41.5	67	44.1	79	37.4	22	48.9
	Moderate	11	16.9	33	21.7	52	24.6	5	11.1
	Severe	5	7.7	8	5.3	10	4.7	1	2.2
PHQ	No	26	41.3	25	17.2	41	20.0	12	27.3	.007	HS
	Mild	16	25.4	48	33.1	76	37.1	20	45.5
	Moderate	14	22.2	42	29.0	47	22.9	6	13.6
	Severe	7	11.1	30	20.7	41	20.0	6	13.6
PSS	Low	7	11.5	26	18.3	35	17.7	17	39.5	.003	HS
	Moderate	47	77.0	84	59.2	131	66.2	22	51.2
	High	7	11.5	32	22.5	32	16.2	4	9.3

Note. NS = non-significant; HS = highly significant; p = p-value; Sig = significance; GAD- 7 = 7-item generalized anxiety disorder; ISI = insomnia severity index; PHQ = patient health questionnaire; PSS = perceived stress scale.

Chi-square tests.

Moreover, on comparing sex groups regarding GAD7, ISI, PHQ, and PSS; statistical significance difference was found between males and females as regard GAD7, PHQ, and PSS with higher proportions of females expressing severe forms of anxiety, depression, and stress compared to males (20% vs 11.9%, 25.1% vs 11.7%, and 22.8% vs 11.1%, respectively).

On comparing between HCW according to type of hospital regarding our study measurements, no significant difference was found regarding ISI and PSS, while a statistical significant difference was found between HCW in different types of hospital as regard GAD7 and PHQ, as 29.7% of quarantine hospitals HCW were normal in GAD7 compared to 19.7% and 14.6% of chest and fever hospital workers respectively. Similarly, 28.2% of quarantine hospitals HCW had no depression using PHQ scale compared to 19.0% and 15.4% of chest and fever hospital workers, respectively (Table 2).

Table 2.

Description and comparison of severity categories of depression, anxiety, insomnia, and stress measurements according to type of hospital of study participants.

		Place of work						p *	Sig
		Chest		Fever		Quarantine
		N	%	N	%	N	%
GAD7	Normal	34	19.7	12	14.6	68	29.7	.032	S
	Mild	62	35.8	29	35.4	84	36.7
	Moderate	44	25.4	24	29.3	50	21.8
	Severe	33	19.1	17	20.7	27	11.8
Insomnia severity index	None	55	32.7	23	28.0	75	33.6	.62	NS
	Subthreshold	69	41.1	41	50.0	85	38.1
	Moderate	36	21.4	13	15.9	52	23.3
	Severe	8	4.8	5	6.1	11	4.9
PHQ	No	31	19.0	12	15.4	61	28.2	.002	HS
	Mild	58	35.6	28	35.9	74	34.3
	Moderate	37	22.7	15	19.2	57	26.4
	Severe	37	22.7	23	29.5	24	11.1
Perceived stress scale	Low	24	15.1	13	16.9	48	23.1	.08	NS
	Moderate	100	62.9	50	64.9	134	64.4
	High	35	22.0	14	18.2	26	12.5

Note. N = number; NS = non-significant; HS = highly significant; p = p-value; Sig = significance. GAD- 7 = 7-item generalized anxiety disorder; PHQ = patient health questionnaire.

Chi-square tests.

Associated Factors to different symptomatology

Participants in the age group of 26-30 years had significantly higher scores in PHQ and PSS. Female participants showed significantly higher scores in all 4 scales compared with males. Fever hospital workers had significantly higher scores in GAD, PHQ and PSS compared to other hospitals workers. As regard occupation; physicians had significantly higher scores in PHQ scale compared to nurses (specialized and non-specialized) while no differences were detected in other tools. Among physicians, Intensive care units (ICU) doctors had significantly higher scores in GAD, PHQ and PSS. Also, participants with bachelor’s degree had significantly higher score in PHQ scale. (Table 3)

Table 3.

Description and comparison of scores of depression, anxiety, insomnia, and stress measurements among participants’ subgroups.

		GAD total			p	ISI total			p	PHQ total			P	PSS total			p
		Med	IQR		p	Med	IQR		p	Med	IQR		P	Med	IQR		p
Age group	18–25	7	4	11	.515*	10	6	14	.131*	6	3	12	.004*	19	16	23	.026*
	26–30	8	5	12		12	7	15		9	6	13		20	16	26
	31–40	8	5	13		10	6	15		9	6	13		19	15	25
	>40	8	4	12		9	5	12		7	4	11		17	11	22
Sex	Male	7	4	11	<.001**	9	5	14	.03**	7	4	11	<.001**	18	13	23	<.001**
Sex	Female	9	7	14	<.001**	11	7	15	.03**	10	6	15	<.001**	21	17	26	<.001**
Marital status	Unmarried	7	4	12	.15**	10	6	14	.68**	8	5	13	.84**	19.5	16	24	.30**
Marital status	Married	8	5	13	.15**	10	6	15	.68**	8	5	13	.84**	19	15	24	.30**
Place of work	Chest	8	6	13	.001*	10	6	15	.91*	9	6	14	.001*	20	16	25	.015*
	Fever	10	6	14		10	7	14		9	7	15		21	17	25
	Quarantine	7	4	11		10	6	15		8	4	11.5		19	14	23
Site of hospital	Greater Cairo Greater Cairo	8	5	13	.051*	10	6	14	.219*	8	5	12	.201*	19	15	24	.65*
	Delta Delta	9	6	13		11	6	15		9	6	14		20	16	25
	Upper Egypt Upper Egypt	7	3	12		9	5	14		8	3	13		19	14	24
	Suez Canal Suez Canal	7	5	9		9	7	15		8	5	10		19	16	21
Job	Physician	8	5	13	.37*	11	6	15	.56*	9	6	13	.014*	20	15	25	.40*
	Sp. Nurse	8	4	12		9	6	15		8	5	13		19	15	22
	Non-sp. Nurse	7	5	12		10	6	14		7	4	11		19	16	23
Degree	Institute	7	5	12	.63*	10	6	14	.77*	7	3	12	.02*	19	15	23	.81*
	Bachelor	8	5	12		11	7	15		9	6	13		19	16	23.5
	MSc	8	5	13		10	6	14		8	6	13		20	15	25
	MD	9	4	12		9	6	14		8	5	11		19	14	22
Specialty	Chest	9	6	14	.016*	11	6	15	.33*	9	7	14	.04*	20	15	25	.017*
	ICU	10	6	14		13	9	17		10	7	15		23	19	27
	Int med/ped	8	4	12		11	6	15		8	5	12		19	14	24
	Lab/radio	8	5	12		9	6	14		9	5	15		18	13	25
	Surgery	4	2	6		8	4	17		5	3	7		14	8	18

Note. p = p-value; Med = median; IQR = interquartile range; GAD-7 = 7-item generalized anxiety disorder; ISI: insomnia severity index; PHQ = patient health questionnaire; PSS = perceived stress scale; Sp.Nurse = specialized nurse; Non-sp. Nurse = non- specialized nurse; MSc = master degree; MD = medical doctor degree; ICU = intensive care unit; Int med = internal medicine; ped = pediatrics; Lab = laboratory; radio: radiology.

Kruskal-Wallis test.

Mann Whitney test.

Risk factors of mental health outcomes

After adjustment of confounders using multivariable logistic regression, it was shown that females were at higher risk of experiencing symptoms of severe anxiety (odds ratio [OR], 1.85; 95% CI, 1.12–3.05; p = .016), severe depression (OR, 2.013; 95% CI, 1.17–3.4; p = .011), and severe stress (OR, 2.68; 95% CI, 1.5–4.6; p < .001) compared to males. Participants with age group (31–40) were at higher risk of severe insomnia compared to those with >40 years old participants (OR, 2.79; 95% CI, 1.02–7.66; p = .01), Participants with age group (26–30) were at higher risk of severe stress compared to those with >40 years old (OR, 3.19; 95% CI, 1.05–9.7; p = .01). Fever hospital workers were at higher risk of severe depression (OR, 1.52; 95% CI, 1.11–2.09; p < .01), compared to Quarantine hospital workers (Table 4).

Table 4.

Multivariable logistic regression analysis of risk factors for mental health outcomes among studied participants.

	No. of severe cases/no. of total cases (%)	Adjusted OR (95% CI)*	p-value**
	No. of severe cases/no. of total cases (%)	Adjusted OR (95% CI)*	Category	Overall
GAD 7, severe anxiety
Sex
Male	29/244 (11.9%)	1 [Reference]	NA	.016
Female	48/240 (20%)	1.85 (1.12–3.05)	.016	.016
Severe insomnia
Age group
>40	5/45 (11.1%)	1 [Reference]	NA	.019
18–25	7/56 (10.8%)	0.73 (0.2–2.63)	.635
26–30	29/152 (19.1%)	1.69 (0.59–4.8)	.323
31–40	49/211 (23.2%)	2.79 (1.02–7.66)	.045
Severe depression
Sex
Male	27/230 (11.7%)	1 [Reference]	NA	.011
Female	57/227 (25.1%)	2.013 (1.17–3.4)	.011	.011
Type of hospital
Quarantine	24/216 (11.1%)	1 [Reference]	NA	.011
Chest	37/163 (22.7%)	1.78 (0.97–3.2)	.059
Fever	23/78 (29.5%)	2.7 (1.4–5.3)	.003
High stress
Age group
>40	4/43 (9.3%)	1 [Reference]	NA	.032
18–25	7/61 (11.6%)	1.164 (0.3–4.3)	.820
26–30	32/142 (22.5%)	3.19 (1.05–9.7)	.042
31–40	32/198 (16.2%)	1.74 (0.57–5.2)	.326
Sex
Male	25/225 (11.1%)	1 [Reference]	NA	.0001
Female	50/219 (22.8%)	2.68 (1.5–4.6)	0.001	.0001

Note. No = number; OR = odds ratio; CI = confidence interval; GAD 7 = 7-item generalized anxiety disorder; NA = not applicable.

Adjusted for Age, sex, marital status, job, educational level, type and site of hospital.

Category refers to the p value for each category vs the reference, while overall refers to the results of the logistic regression.

Discussion

To our knowledge this is one of the earliest studies to address the issue of mental health of frontline healthcare workers during COVID-19 in the middle east and Africa, which may add value to the preexisting literature which mostly was done in Asian countries (Lai et al., 2020; Zhang et al., 2020a, 2020b).

The psychological response of healthcare workers to an epidemic of infectious diseases is complex and might be related to different factors. Sources of distress among healthcare workers may include feelings of vulnerability or loss of control and concerns about one’s health and possibility being, infection of colleagues, spread of virus to others, health of family, and others especially children and old aged group. Other work related factors to consider are employment uncertainty, financial worries, lack of getting rest, exposure to critical life events such as death, and being isolated for long periods. Moreover, Predictable shortages of supplies and an increasing influx of suspected and actual cases of COVID-19 contribute to the pressures and concerns of healthcare workers (SINAnews, 2020; WHO, 2020d).

Furthermore, showing a high rate of transmission and uncertainties about mode of transmission of COVID-19 adds to the worries of this group. It is commonly recognized that droplet transmission is the main route. However, COVID-19 was also found on the surfaces like doors, toilets, personal items as cell phones, and etc. Thereby, healthcare workers are extra vigilant about their behavior and staying safe (e.g. not to touch their faces after contacting with cases or their belongings) which also heightens their anxiety levels (Han et al., 2020).

As there is also no available treatment, nor a definite protective vaccine, it is expected that frontline workers feel worried all the time. There is not even enough evidence that those who survived the infection have developed immunity against the virus (WHO, 2020e). Moreover, there is no consensus on the best management of infected individuals and limited numbers of Intensive Care beds, which healthcare workers are aware of and understand the grievousness of the situation.

Unfortunately, the media impact has not been very helpful, especially social media. Spreading of faulty information and sharing unconfirmed data about the numbers of cases played a role in increasing the mass concerns, even among professionals. Sometimes, governments’ messages were so clear and intimidating to urge people to follow the guidance, which also triggered panic among different categories including healthcare workers. Important aspect needed to be highlighted is the role of social media and technology in such issue, WHO has identified that the ‘COVID-19 outbreak and response have been accompanied by a massive “infodemic” – an over-abundance of information – some accurate and some not – that makes it hard for people to find trustworthy sources and reliable guidance’ (WHO, 2020f), studies indicated social media exposure during pandemics may be associated with higher risk of mental health issues. A recent Chinese study showed that a higher prevalence of mental health problems mainly anxiety and depression was positively associated with frequently social media exposure during the COVID-19 outbreak.(Gao et al., 2020), which was also reported previously in a study which showed that social media exposure may positively related to forming risk perceptions during the Middle East respiratory syndrome (MERS) outbreak in South Korea (Choi et al., 2017). Moreover, many healthcare workers used social media to share their own experiences, complaints about lack of protective equipment and obituaries of their lost colleagues and families (Glenza, 2020).

This cross-sectional survey enrolled 502 participants and revealed a high prevalence of mental health symptoms among healthcare workers treating patients with COVID-19 in Egypt. Overall, 77.3%, 69.5%, 79.3%, and 83.1% of all participants reported symptoms of, anxiety, Insomnia, depression, and stress, respectively. These results are higher than ones reported in different studies by Lai et al.s’ (2020) study, Zhang et al. (2020a), and Zhang et al. (2020b), which may reflect the difficult situation facing Egyptian frontline healthcare workers. It could be related to limited number of Egyptian physicians and nurses as reported by the world bank to be 0.5 per 1,000 person for doctors and 1.9 per 1,000 for nurses, which is lower than most of European and Asian countries including china. Adding to that the presence of low number of hospital beds available (1.6 per 1,000 people) (The world bank, 2020). Placing a huge responsibility on physicians to choose the appropriate cases who which will be most benefited from admission.

This study also supports the existing literature that has examined mental health of healthcare workers during previous outbreaks such as H1N1 influenza and Severe Acute Respiratory Syndrome (SARS) (Lee et al., 2018). For example, during the SARS outbreak in 2003, 18% to 57% of health professionals experienced serious emotional problems and psychiatric symptoms during and after the event in one study conducted by Lee et al. (2018). Another study conducted by Chua et al. (2004) showed that 89% of healthcare workers who were in high-risk situations reported psychological symptoms during the acute SARS outbreak.

On the other hand, females was associated with higher risk of experiencing severe depression, anxiety, insomnia and stress which may be due to the already reported gender difference for anxious and depressive symptoms (Albert, 2015). This finding is consistent with previous studies as Lai et al.s’ (2020) study and Zhang et al. (2020a, 2020b).

On contrary to Lai et al.s’ (2020) study in which nurses reported more severe symptoms on all measurements, this study found that physicians and higher rates educational levels were more prone to depression, this could be related to the higher number of nurses participation when compared with physicians in their study and being females as well.

Ages from 26 to 30 were at higher rates of experiencing insomnia and severe depression. A possible explanation is those age groups usually occupy the junior to intermediate level jobs which require longer working hours and more duties. Our findings are consistent with Lai et al.s’ (2020) study which shows that junior positions are associated with greater risk of psychological problems.

Turning to the ICU workers, they showed higher scores on GAD-7, PHQ, and PSS which could be related to their close, frequent contact with patients. This is consistent with Embriaco et al. (2012) findings that showed that one of every four French ICU workers had symptoms of depression.

A comparison between three different types of hospitals which form the main bulk of hospitals involved in diagnosis and management of COVID-19 patients was done. Fever and Chest hospitals are responsible for diagnosis while Quarantine hospitals responsible for treatment of confirmed cases. This study reported that working in Fever hospitals was associated with higher rates of severe depression than Quarantine hospitals. This may be due to the stress of the triaging and facing higher numbers of patients in emergency rooms than in Quarantine hospitals. Also, the uncertainty surrounding the diagnosis of each examined patient compared to Quarantine hospitals which receive referrals for isolation of confirmed cases without direct contact with suspected cases from general population may also play a role.

Limitations

The cross-sectional nature for this study does not allow follow up of either progression of the symptomatology or improvement of healthcare providers. Also, it might be expected that the pandemic situation may have long term outcome that will only appear in later stages which this study design cannot detect. The lack of baseline statistics of the abovementioned symptomatology prior to the pandemic situation may raise the debate of how to assess the exact impact of the situation. Moreover, the survey nature of the study allows for respondents’ bias.

Strengths

One of the few studies providing a missing aspect, a new approach to support healthcare workers in Egypt and form future plans for the health care sector.

Conclusion

Physicians, female gender and working in Fever hospitals dealing with suspected patients with COVID-19, were associated with high rates of symptoms of depression, anxiety, insomnia, and distress. Protecting healthcare workers is an important component of public health measures for addressing the COVID-19 epidemic. Special interventions need to be immediately implemented, to promote mental well-being in healthcare workers exposed to COVID-19 and to mitigate the effects of the pandemic on their current mental health.

This may include enhancing awareness to the early symptoms of depression, anxiety, and stress. Individual coping strategies, such as acceptance, behavioral activation, and mindfulness, are effective during crises; fostering resilience and recovery by increasing tolerance to distress, enhancing feelings of connectedness and encouraging actions that are goal-directed and value-driven. Adding on to peer-support programs that could help the HCW in changing their psychological reactions toward the stressful situations that they are facing (Polizzi et al., 2020).

Footnotes

Acknowledgements

The authors would like to thank all healthcare workers that took time to fill in the survey and helped.

Author contributions

H.E.: conceptualized the study, drafted the first version, revised it critically for important intellectual content, and approved the version to be published. F.T.: conceptualized the study, drafted the first version, revised it critically for important intellectual content, and approved the version to be published. I.I.: conceptualized the study, collected the data, drafted the first version, revised it critically for important intellectual content, and approved the version to be published. W.S. E.: conceptualized the study, analyzed the data, drafted the first version, revised it critically for important intellectual content, and approved the version to be published. M.S.: collected the data, revised it critically for important intellectual content, and approved the version to be published. S.M.: collected the data, revised it critically for important intellectual content, and approved the version to be published. M.H.: collected the data, revised it critically for important intellectual content, and approved the version to be published. M.A.: collected the data, revised it critically for important intellectual content, and approved the version to be published. A.Z.F.: collected the data, revised it critically for important intellectual content, and approved the version to be published. R.A.: collected the data, revised it critically for important intellectual content, and approved the version to be published. M.S.: conceptualized the study, Methodology, Supervision, Writing – Review & Editing, revised it critically for important intellectual content, and approved the version to be published. A.N.O.: conceptualized the study, Methodology, Supervision, Writing – Review & Editing, revised it critically for important intellectual content and approved the version to be published. All authors reviewed, provided critical feedback, helped in shaping the research, and approved the final version.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Fairouz Tawfik

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