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The establishment of empirical evidence in the Eastern Mediterranean Region necessitates the implementation of wide-scale studies to describe the demographic, clinical features, and severity profile of patients with COVID-19.
This study aims to assess the patterns of COVID-19 severity and mortality in seven countries, and to determine the risk factors of COVID-19 severity and mortality.
This multicountry study was based on a retrospective review of medical records of hospitalized patients confirmed to have COVID-19. This study includes data from Iraq, Pakistan, Sudan, Somalia, Morocco, Egypt, and Yemen. All demographic and clinical data were extracted from hospital records (paper files) by trained data collectors.
A total of 4141 patients were included in this study from seven countries. Comorbidities were reported by nearly half of the patients, with hypertension (n=1021, 24.7%) and diabetes (n=939, 22.7%) being the most common. Older age, diabetes mellitus, hypertension, and heart diseases were significantly associated with COVID-19 severity and mortality. Ever smoking and renal diseases were significantly associated with severity but not mortality, while male gender, respiratory diseases, and malignancy were significantly associated with mortality but not severity.
The study confirms the role of comorbidities and demographic features on the severity and mortality of COVID-19. Understanding the contributing factors ensures attentive care and informs clinical management of patients with poorer prognoses in the early stages of diseases.
On December 31, 2019, cases of pneumonia of unknown etiology were reported from Wuhan City, Hubei Province of China [
As many of the countries in the region are experiencing war and political instability, cases and deaths are underreported because of inadequate testing facilities, weak health system response, and inadequate vital registration and documentation [
A recent report showed that Iran has accumulated the highest number of cumulative deaths (n=85,694, case-fatality rate [CFR] 2.6%), followed by Pakistan (n=22,582, CFR 2.3%) and Iraq (n=17,515, CFR 1.2%) [
Severe cases of COVID-19 are more likely to deteriorate to conditions that necessitate vital and timely care [
Despite the fact that there is limited evidence on the severity of COVID-19 across the EMR, recent studies from Iraq were consistent with global evidence that old age, male gender, and pre-existing comorbidities were associated with increased mortality among hospitalized patients with COVID-19 [
The establishment of empirical evidence in the EMR necessitates the implementation of wide-scale studies to describe the demographics, clinical features, and severity profiles of patients with COVID-19. Assessing the risk factors of the severe form of COVID-19 is essential to develop appropriate risk reduction strategies and to plan resources for health care as the pandemic unfolds. Furthermore, it will inform clinical management by predicting clinical outcomes and prognostic markers to facilitate the development of a care pathway for COVID-19 critical care. Thus, this study aims to assess the patterns of COVID-19 severity and mortality in seven countries, and to determine the risk factors of COVID-19 severity and mortality.
This multicountry study was based on a retrospective review of medical records of hospitalized patients confirmed to have COVID-19. This study included data from Iraq, Pakistan, Sudan, Somalia, Morocco, Egypt, and Yemen. All data were extracted from hospital records (paper files) by trained data collectors who used a standardized Kobo collect form for data entry. In all participating countries, the data collected were for patients admitted to hospitals by October 2020.
In Iraq, data were collected for patients with COVID-19 who were admitted during the period between June 1 and 30, 2020, to any one of the six selected hospitals in Baghdad and one hospital in Babylon. The seven hospitals were selected out of the 10 hospitals that received patients with COVID-19 in Baghdad and Babylon because of the presence of Field Epidemiology Training Program residents who collected the data. In Sudan, the study was limited to Khartoum and Gazira states, as they were the high spots for COVID-19 in the country. The data were collected from the two main secondary isolation centers and two primary isolation centers (all hospital records of patients with a confirmed diagnosis between March 2020 and October 2020 were included). In Morocco, data were collected from the Cheikh Zaid International University Hospital of Rabat City, which was dedicated to the hospitalization of patients with COVID-19. In Egypt, data from El-Agoza Hospital in Giza governorate (a high-risk governorate) were collected between May and June 2020. El-Agoza Hospital was designated for the screening and isolation of patients with COVID-19. In Yemen, data were collected on patients with COVID-19 who were admitted to three main isolation hospitals in Sana’a City. In Pakistan, data were collected from two hospitals in Rawalpindi (Benazir Bhutto Hospital and Holy Family Hospital) and two other hospitals in Islamabad (Pakistan Institute of Medical Sciences and Pakistan Air force Hospital) of cases admitted between February and August. All four hospitals were COVID-19 treatment centers. In Somalia, data of patients admitted between March and August to De-Martino Hospital (the only COVID-19 treatment center in Mogadishu) were collected.
A standardized data collection tool for all countries was developed and converted to the Kobo Toolbox form. The form consisted of four sections. The first section included patients’ baseline and demographic characteristics (age, gender, smoking history, health care worker [HCW] or not, travel history, and history of contact with patients with confirmed COVID-19). The second section included variables related to clinical history and presentation severity, signs and symptoms, and comorbidities. The third section included severity classification. Section four included outcomes (fully recovered, discharged improved, palliative discharge/disable, and death).
WHO guidelines were used to define the history of contact (exposure during the 2 days before and the 14 days after the onset of symptoms) and travel history (history of travel 14 days before symptom onset) [
Ethical approval was obtained from the institutional review boards in selected countries, and hospital permissions were sought to access patients’ records. Data were coded to maintain confidentiality. All data files were encrypted and saved in a secure database with limited access to the study team.
Data were entered and managed using the Kobo Toolbox (a tool developed by the Harvard Humanitarian Initiative to be used for field data collection in challenging environments) and then exported to SPSS version 23 (IBM Corp) for analysis. Data were described using percentages and counts. The differences between percentages were tested using the chi-square test. Two separate multiple logistic regression analyses were conducted to determine factors associated with COVID-19 severity and mortality. The final logistic regression models included significant variables only. A
A total of 4141 patients were included in this study from seven countries, of which Iraq and Pakistan composed almost 60% of the sample followed by Sudan (n=1011, 24.4%). Almost 38% (n=1571) of patients aged 40-59 years, and male patients constituted 63.8% (n=2641) of the sample. About 14.6% of patients were ever smokers. Almost 4% were HCWs. A history of contact with a patient with COVID-19 was indicated by 40.8% (n=1690) of patients.
Demographic and relevant background characteristics of patients with COVID-19 (N=4141).
Variables | Patients, n (%) | |
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Iraq | 1438 (34.7) |
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Pakistan | 1199 (29.0) |
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Sudan | 1011 (24.4) |
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Somalia | 230 (5.6) |
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Morocco | 123 (3.0) |
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Egypt | 71 (1.7) |
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Yemen | 69 (1.7) |
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<40 | 1193 (28.8) |
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40-59 | 1571 (37.9) |
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≥60 | 1377 (33.3) |
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Male | 2641 (63.8) |
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Female | 1500 (36.2) |
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Non–health care workers | 3994 (96.5) |
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Health care workers | 147 (3.5) |
History of contact with patient with COVID-19 (yes) | 1690 (40.8) | |
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Never | 3537 (85.4) |
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Ever | 604 (14.6) |
The most common symptoms on admission were fever (n=3198, 77.2%), followed by cough (n=3009, 72.7%) and shortness of breath (n=2224, 53.7%). Other common clusters encompassing musculoskeletal symptoms (myalgia or arthralgia, or backache or fatigue) were reported by 37.6% (n=1557) of patients. A cluster of enteric symptoms was less common in this study (n=398, 9.6%). Comorbidities were reported by nearly half of patients, with hypertension being the most common comorbidity (n=1021, 24.7%), followed by diabetes (n=939, 22.7%). Multiple comorbidities were also reported in almost half of the patients (n=2153, 52%;
Distribution of study participants by clinical manifestations and comorbidities (N=4141).
Variables | Patients, n (%) | |
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No comorbidity | 2408 (48.2) |
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Hypertension | 1021 (24.7) |
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Diabetes mellitus | 939 (22.7) |
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Heart diseases | 303 (7.3) |
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Renal disease | 140 (3.4) |
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Asthma | 111 (2.7) |
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Respiratory diseases (COPDa and other respiratory diseases) | 61 (1.5) |
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Malignancy | 62 (1.5) |
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Immune compromising conditions | 45 (1.1) |
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Liver disease | 22 (0.5) |
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Asymptomatic | 124 (3.0) |
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Fever | 3198 (77.2) |
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Cough | 3009 (72.7) |
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Shortness of breath | 2224 (53.7) |
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Musculoskeletal manifestations | 1557 (37.6) |
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Sore throat | 683 (16.5) |
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Headache | 664 (16.0) |
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Loss of taste or smell | 474 (11.4) |
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Chest pain | 458 (11.1) |
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Gastrointestinal or gastroenteric symptoms (nausea/vomiting/diarrhea/abdominal pain) | 364 (8.8) |
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Sputum production | 156 (3.8) |
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Nasal congestion | 118 (2.8) |
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Conjunctival congestion | 37 (0.9) |
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Hemoptysis | 36 (0.9) |
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Other symptoms | 134 (3.2) |
aCOPD: chronic obstructive pulmonary disease.
Of all patients, 27.6% (n=1143) had mild disease, 22.7% (n=940) had moderate disease, 28.9% (n=1197) had severe disease, and 20.7% (n=857) had critical disease. The bivariate analysis had shown that increased age, non–health professions, ever smoking, and comorbidity history, particularly hypertension, diabetes mellitus, heart diseases, and respiratory diseases, were significantly associated with severe or critical COVID-19. Whereas mortality was consistently associated with the aforementioned factors in addition to the male sex, cerebrovascular disease, and malignancy (
Bivariate analysis of factors associated with COVID-19 severity and mortality.
Variable | Severity | Mortality | |||||||||
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Mild-moderate, n (%) | Severe-critical, n (%) | Survivors, n (%) | Deaths, n (%) | |||||||
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.45 |
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.005 | |||||||
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Male | 1318 (49.9) | 1323 (50.1) |
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2132 (80.7) | 509 (19.3) |
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Female | 767 (51.1) | 733 (48.9) |
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1263 (84.2) | 237 (15.8) |
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<.001 |
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<.001 | |||||||
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<40 | 849 (71.2) | 344 (28.8) |
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1115 (93.5) | 78 (6.5) |
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40-59 | 779 (49.6) | 792 (50.4) |
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1334 (84.9) | 237 (15.1) |
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≥60 | 457 (33.2) | 920 (66.8) |
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946 (68.7) | 431 (31.3) |
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<.001 |
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<.001 | |||||||
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Non–health care workers | 1965 (49.2) | 2029 (50.8) |
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3254 (81.5) | 740 (18.5) |
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Health care workers | 120 (81.6) | 27 (18.4) |
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141 (95.9) | 6 (4.1) |
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Positive history of contact with patient with COVID-19 | 1116 (66.0) | 574 (34.0) | <.001 | 1456 (86.2) | 234 (13.8) | <.001 | |||||
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<.001 |
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.29 | |||||||
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Ever | 228 (37.7) | 376 (62.3) |
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486 (80.5) | 118 (19.5) |
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Never | 1857 (52.5) | 1680 (47.5) |
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2909 (82.2) | 628 (17.8) |
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592 (34.2) | 1141 (65.8) | <.001 | 1237 (71.4) | 496 (28.6) | <.001 | |||||
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Hypertension | 353 (34.6) | 668 (65.4) | <.001 | 714 (69.9) | 307 (30.1) | <.001 | ||||
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Diabetes mellitus | 319 (34.0) | 620 (66.0) | <.001 | 650 (69.2) | 289 (30.8) | <.001 | ||||
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Heart diseases | 91 (30.0) | 212 (70.0) | <.001 | 190 (62.7) | 113 (37.3) | <.001 | ||||
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Renal disease | 25 (17.9) | 115 (82.1) | <.001 | 108 (77.1) | 32 (22.9) | .13 | ||||
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Asthma | 50 (45.0) | 61 (55.0) | .26 | 91 (82.0) | 20 (18.0) | >.99 | ||||
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Respiratory diseases | 21 (34.4) | 40 (65.6) | .01 | 38 (62.3) | 23 (37.7) | <.001 | ||||
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Malignancy | 21 (33.9) | 41 (66.1) | .009 | 43 (69.4) | 19 (30.6) | .009 | ||||
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Immunocompromising conditions | 12 (26.7) | 33 (73.3) | .001 | 39 (86.7) | 6 (13.3) | .41 | ||||
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Liver disease | 8 (36.4) | 14 (63.6) | .19 | 16 (72.7) | 6 (27.3) | .26 | ||||
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Tuberculosis | 19 (33.9) | 37 (66.1) | .01 | 42 (75.0) | 14 (25.0) | .17 | ||||
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Cerebrovascular disease | 8 (42.1) | 11 (57.9) | .47 | 12 (63.2) | 7 (36.8) | .03 |
The multiple logistic regression indicated that increased age and smoking were significantly associated with severity (
Multiple logistic regression of factors associated with COVID-19 severity and mortality.
Covariates | Factors associated with COVID-19 severity | Factors associated with COVID-19 mortality | ||||
Sex (female vs male) | —b | N/Ac | 0.8 (0.7-1) | .02 | ||
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<40 (reference) | N/A | N/A | N/A | N/A | |
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40-59 | 2 (1.7-2.4) | <.001 | 1.9 (1.5-2.5) | <.001 | |
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≥60 | 3.1 (2.6-3.8) | <.001 | 4 (3.1-5.3) | <.001 | |
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Health care workers (reference) | N/A | N/A | N/A | N/A | |
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Non–health care workers | 2 (1.2-3.1) | .004 | 2.4 (1-5.6) | .04 | |
History of contact with patient with COVID-19 (no vs yes) | 2.8 (2.4-3.2) | <.001 | 1.4 (1.2-1.7) | <.001 | ||
Diabetes mellitus (yes vs no) | 1.4 (1.2-1.7) | <.001 | 1.6 (1.3-1.9) | <.001 | ||
Hypertension (yes vs no) | 1.2 (1-1.5) | .03 | 1.3 (1.1-1.6) | .003 | ||
Heart diseases (yes vs no) | 1.7 (1.3-2.2) | <.001 | 1.8 (1.4-2.3) | <.001 | ||
Renal disease (yes vs no) | 3.3 (2.1-5.2) | <.001 | — | N/A | ||
Respiratory diseases (yes vs no) | — | N/A | 2.1 (1.2-3.7) | .009 | ||
Malignancy (yes vs no) | — | N/A | 1.8 (1-3.3) | .04 | ||
Symptomatic (yes vs no) | — | N/A | 4.5 (1.6-12.6) | .004 | ||
Smoking (ever vs never) | 9.7 (5.1-18.5) | <.001 | — | N/A |
aOR: odds ratio.
bNot entered in the model because the variable was not statistically significant.
cN/A: not applicable.
Increasing age was a strong predictor of mortality in hospitals, as the older age group (>60 years) was associated with an increased odds of death by almost four times compared to the younger age category (OR 4, 95% CI 3.1-5.3;
The data of a cohort of patients with COVID-19 hospitalized in seven different countries were collected and analyzed. The proportion of hospitalized patients with severe or critical illness in this study (49.6%) is remarkably higher than what is being reported from other parts of the world on hospitalized patients with COVID-19 [
We found older age, diabetes mellitus, hypertension, and heart diseases to be associated with both severity and mortality. Furthermore, ever smoking and renal diseases were associated with severity but not mortality, while male gender, respiratory diseases (COPD or other respiratory diseases), and malignancy were associated with mortality but not severity. The latter category is of special importance, given the fact that these patients might die even if they do not experience severe or critical illness. The majority of these findings are consistent with previous studies on COVID-19 severity or mortality [
Unraveling the pathophysiology of COVID-19 is still a work in progress. Nevertheless, the role of angiotensin-converting enzyme 2 (ACE2) receptors is widely recognized as a key player in the disease process. ACE2 is a metallopeptidase that is expressed in various human organs [
Older patients, males, and patients with type 2 diabetes mellitus were frequently found to have severe or fatal COVID-19 in epidemiological studies. Interestingly, they were also found to have lower ACE2 expression, which might help explain why they are disproportionately affected by poor COVID-19 outcomes [
In addition to ACE2 downregulation, other biological and nonbiological factors might help explain some of our findings. For example, differences in the biological and molecular level in older patients (as compared to younger ones) might have their contribution to the disease course [
Diabetes mellitus is another risk factor where the dysregulated immune response is thought to play a role in a patient’s susceptibility to critical COVID-19 outcomes. Similar to aging, patients with diabetes are in a state of low-grade chronic inflammation [
The fact that an overactive RAS is a key aspect of the pathogenesis of CVD (heart diseases and hypertension) [
Similar to CVD, some renal diseases are characterized by an overactive RAS [
The defective local physiological function of the respiratory system in patients with COPD and other respiratory diseases could explain their predisposition to worse COVID-19 outcomes. Conversely, asthma was not associated with COVID-19 severity or mortality. The evidence in the literature on asthma has been inconclusive [
Despite the fact that smoking is probably underestimated in our study due to associated stigma, particularly among women, we were able to find an association with severity. However, this same underestimation might be the reason why, unlike previous reports [
Unexpectedly, we also found not working in a health care setting and not having a history of contact with a known COVID-19 case to be associated with both severity and mortality. These findings should be interpreted with caution though; patients with a known COVID-19 contact history might be better informed and more likely to seek help early and thus less likely to have critical outcomes.
There is also the possibility that the history of contact is underreported mainly for two reasons. First, the stigma around the disease may prevent many people from telling everyone around them; thus, many people may not realize that they had been in contact with a patient with COVID-19.
Second, the societies in the EMR are among the most social in the world and being friendly to strangers is the social norm. In Iraq, for example, religious mass gatherings where strangers often socialize without observing social distancing is a frequent occurrence. There is a decent possibility that some of the patients in this study might, unknowingly, had come in contact with presymptomatic or mild COVID-19 cases during one of these events.
Similar to our study, a meta-analysis by the American Journal of Emergency Medicine [
Almost a year has passed since the COVID-19 pandemic started, and still the best intervention we have to fight it with is nonpharmaceutical measures. There is no definite treatment to date, and although good news on effective vaccines is emerging, it might take a few years until enough of the population has access to a vaccine. That is why, in the hospital setting, it is still imperative to identify which patients are at higher risk of developing severe disease or dying of COVID-19. Although many studies reported on this worldwide, to our best knowledge, this is the first large multicenter study coming out of the EMR.
This study has its limitations. First, the study was conducted in a hospital setting, which limits our ability to generalize our findings to the general population. Second, given that in many hospitals in the selected countries hospital admissions were reserved for the most severe cases, our study might be biased toward more severe outcomes. Finally, some variables might be underreported due to the inability of the HCWs in the overwhelmed facilities to collect all data for all patients.
This study reports on risk factors of COVID-19 severity and mortality in the seven countries. In a hospital setting, health care providers should be more attentive to older patients, men, smokers, and patients with certain comorbidities (diabetes, hypertension, heart diseases, COPD, malignancy, and renal diseases), as they were shown to be more likely to have severe or fatal COVID-19 in our study.
angiotensin-converting enzyme 2
case-fatality rate
chronic obstructive pulmonary disease
cardiovascular disease
Eastern Mediterranean Region
health care worker
odds ratio
polymerase chain reaction
renin-angiotensin system
World Health Organization
The authors would like to thank the Global Health Development|Eastern Mediterranean Public Health Network for their support. The authors would also like to thank Dr Abdelaziz Barkia (Epidemic Diseases Service, Ministry of Health of Morocco); Dr Younes Zaid (associate professor at Mohammed V University in Rabat, Morocco); Mariam Laatifi (PhD student, Mohammed V University in Rabat, Morocco); Hind Ezzine (PhD student, Mohammed V University in Rabat, Morocco); Alaa Eid, MD (Ministry of Health and Population, Cairo, Egypt); Ehab Kamal, MD (Ministry of Health and Population, Cairo, Egypt); Mohamed Hassany, MD (Ministry of Health and Population, Cairo, Egypt); Hanaa Abu El Sood, MPH (Ministry of Health and Population, Cairo, Egypt); and Dr Anwar Ahmed (ER consultant, Ministry of Health, Sudan).
None declared.