Prehospital Particularities of Covid-19 infection and factors associated with its severity during the omicron variant wave (East-center of Tunisia)

Introduction

In December 2019, an outbreak of an unexplained pneumonia was reported in Wuhan, Hubei Provence, China[1]. A new coronavirus, "severe acute respiratory syndrome coronavirus 2" (SARS-CoV-2) was identified, and the World Health Organization (WHO) named this infection coronavirus disease 2019 (COVID-19)[1].

Given the rapid spread of SARS-CoV2 across the world, the WHO declared a Public Health Emergency of International Concern on 30 January 2020, and named the outbreak as a pandemic on 11 March 2020[2].

In these late years, serial mutants of SARS-CoV-2 have triggered several waves of COVID-19 epidemics. To date, the WHO has identified five mutants characterized as specific Variants of Interest (VOIs) and Variants of Concern (VOCs), including alpha, beta, gamma, delta, and omicron [3,4].

In November 2021, South Africa experienced rapid spread of SARS-CoV-2 fueling the fourth wave of COVID-19. The B.1.1.529 variant (Omicron) was first detected in samples collected in Botswana on November 11 and in South Africa on November 14  and it was declared a VOC by the WHO shortly thereafter[5].Since then, Omicron has spread rapidly worldwide and was detected in Tunisia on 3 December 2021. It was brought from Istanbul by a 23 year old Congolese tourist [6].

It was shown that the Omicron has a significantly higher number of mutationscompared toprevious SARS-CoV-2 variants, particularly in its S-gene, the gene encoding the spike protein [7,8]. These changes affected the virus’s propertiesleading him to a higher potential of transmissibility [7].

Although full vaccination leads to a series of antibody productions, a partial immune evasion has been also noticed with Omicron[9]. However, a marked reduction in hospitalization and mortality rates were reported inVarious studies [7,8].

In this context, we conducted our study in the aim of identifying the epidemiological and clinical characteristics of COVID-19 during the Omicron wave in the territory of the emergency medical service of the east-center of Tunisia (EMS 03), and to study the severity of this variant and its associated factors

Methodology

Study design and setting:

A prospective study was conducted in the in the territory of the EMS 03 during the Omicron wave dating from  January1^st,  to  February 28, 2022.

The EMS 03 manages the pre-hospital medical emergencies occurring in its territory which covers 4 governorates: the governorate of Sousse, Kairouan, Monastir and Mahdia.TheEMS includes:- A medical regulation unit that ensures the appropriate medical response to any urgent call for care. During COVID-19, a sub-unit was created to receive calls for Polymerase-Chain Reaction (PCR) testing. PCR tests were carried out the day after to drivers or passengersin the EMS parking lot through the window of their car (Driving test).

- A mobile resuscitation unit controlled by the regulation and located in the governorates it covers.It provides urgent medical interventions.

Study population

All subjects contacting the EMS 03 during the study period were included. Then, patients with a negative PCR and/or chest CT scan were excluded from the study analysis.Study process and data collection:

-In a first step, we collected the files of allpatients who called the EMS 03 during the study period.

-In a second step, we selected patients suspected to be infected by SARS-Cov-2; having contact with an infected subjects or presenting symptoms suggestive of COVID-19 and we excluded non-suspect subjects.

-In a third step, we excluded subjects confirmed not to have COVID-19.

Data were collected via admission records for hospitalized subjects and via phone calls for subjects who did a Driving Test or those left at home after a medical intervention.

- First, we collected the information concerning the patient’s history and the clinical presentation from the intervention sheets and the digital regulation platform (SI-SAMU software).

Then, we followed up the patients and collected information about the evolution.

Measurements

Sociodemographic characteristics, patient’s history and clinical presentation were evaluated using validated questionnaire (Supplementary material).The collected information included age, sex, area of residence, governorate, education level, healthcare profession, smoking, height, weight, comorbidities, vaccination status and symptoms.A clinical examination and chest computed tomography (CT)were carried out to evaluate the degree of severity.

 The COVID-19 was confirmed by a Rapid antigen testing or a PCR test or by a Chest CT.

The COVID-19 severity was classified as mild, moderate, and severe disease according to the WHO disease severity classification[10,11].

Statistical analysis

Data analysis was carried out using the SPSS Statistics software (SPSS) version 21.0. The Kolmogrov-Smirnov (KS) test was used to check the normality of the quantitative variables.Continuousvariables with a normal distribution were expressed as mean and standard deviation (SD). Variables with asymmetric distribution were presented as the median and the interquartile range (IQR). The Categorialvariables were expressedasFrequency rates and percentages. To study the factors associated with the COVID-19 severity we used the chi-square test or Fisher's exact test for qualitative variables and Student’s test or Mann Whitney's U test for quantitative variables.The variables were included at the 20% threshold in the multivariate analysis, in order to identify the determinants of severity.A multivariate analysis using the binary logistic regression models was performed to determine the independent factors related to COVID-19 severity. A p-value less than 0.05 was considered as statistically significant.

Results

A total of 2,948 calls were received during the period from January 1^st, to February 28, 2022, of which 1,448 concerned suspected patients with Covid-19. Only 420 patients were confirmed Covid-19 positive results as shown in figure 1.

. The mean age was 48 ±21.62 years with extremes ranging between 8 and 103 years. More than half (51%) were female. Almost half of the patients had a higher education level (49.6%) as shown in table 1. Only 3.8% were healthcare professionals.

The proportion of patients with comorbidities was 42.1%. Previous SARS-CoV-2 infection history was found in 9.8% of patients.More than two-thirds of patients (69.6%)were vaccinated against COVID-19.

In our study, the vast majority of patients were symptomatic (99.3%). The main reported symptom was cough (67.5%) followed by arthromyalgia (61.2%), fever/chills (57.4%) and fatigue (54%).No patient reported ageusia and only 1.9% presented anosmia as shown in table 2.

The prevalence of severe forms was 19.5%. Among the 420 patients, 28.3% required hospitalization, most of them were admitted to a medical ward. Only 9.3% of patients were admitted to an intensive care unit (ICU).Only 33.1% of the population required oxygen. Intubation was required in only 3.3 % of patients. The mortality rate reached 15.5%.

Associated factors for severity

Sociodemographic factors

There was a significant association between age and severity (p≤10^-3). In fact, participants aged over 60 presented more severe forms than younger subjects.

Males developed more severe forms than females (25.9% vs 13.6%; p=0.002).

Concerning education level, those with a low education level had more severe forms than those with a high education level (p≤10^-3).

We did not find an association between severity and healthcare profession (p=0.297)

Comorbidities

Patients with comorbidities presented more severe forms (44.4% vs 13.6%, p≤10^-3). Patients with diabetes developed more severe forms than those without diabetes (44.4 % vs 13.6%, p≤10^-3).

The severity rate was significantly higher among patients with arterial hypertension (p≤10-3).We also found that coronary artery disease, systemic disease, asthma and neoplasia were associated factors for severity (p≤10-3) (Table 3).

We found a significantassociation between COVID-19 severity and Chronic Obstructive Pulmonary Disease (COPD) or asthma. Indeed, 46.2% of subjects with COPDor asthma developed a severe form against 16.9% with p≤10-3. Also,renal failure was significantly associated with the severity of COVID-19 disease (p≤10-3).

Vaccination

Patients vaccinated against COVID-19 developed less severe disease than unvaccinated ones (14.7% vs 31.9%; (p≤10-3). On the other hand, we did not find an association between the severity and the number of doses (p=0.128), nor with the type of vaccine (p=0.054).Thus, influenza vaccination has no association with the severity disease (p=0.351).

Symptoms

In our study, we found an association between COVID-19 severity and certain symptoms such as cough (p=0.026), dyspnea(p≤10^-3), sore throat(p≤10^-3) and chest pain(p=0.042).Adjusted logistic regression analysis

Regarding the multivariate analysis, the independent risk factors for the COVID-19 severity were  history of coronary artery disease,history of cancer, history of system disease and the presence of cough as an initial symptom.The presence of sore throat and vaccination were associated with a significant decrease in the severe form of the COVID-19 disease as shown in table 5.

Discussion 

In our study, the vast majority of patients were symptomatic (99.3%). This is consistent with results found in a study conducted in Norway reporting a rate of symptomatic subjects of 98.7% (91% having at least 3 symptoms) [12]. In another study conducted in Japan, the rate of symptomatic subjects was 91.1%[13].It was similar in France with a rate of 89% [14]. However, in in Korea, the rate of asymptomatic subjects reached almost half of cases with a rate of 47.5% [15].

Our patients mainly reported respiratory and general symptoms. Cough was the most common symptom (67.5%) followed by arthromyalgia (61.2%), fever (57.4%) and fatigue (54%). These results are consistent with the literature. However, regarding upper respiratory symptoms, 26.7 % of patients had rhinorrhea and 23% had sore throatwhich is not congruent with the literature showing a high prevalence of these symptoms among patients with Omicron

Astudy conducted inUnited States(US) including 43 subjects infected with Omicron showed that cough and fatigue were the most reported signs (89% and 65% respectively). However, fever was present in 14% of cases [16].A Norwegian study found that cough (83%), followed by rhinorrhea or nasal obstruction (78%), fatigue/asthenia (74%), sore throat (72%), headache (68%) and fever (54%) were the most common reported signs by patients with Omicron [12].ACanadian study on 1,063 cases of Omicron found that that rhinorrhea (73%), cough (65%) and headache (54%) were the most common symptoms [17]. A study in Indiaon 1175 cases of Omicron reported that patients complained mostly of fever (43%), followed by soreness (23%), rhinorrhea (22%) and cough (21%) [18].Finally, a study conducted in the United Kingdom (UK), including only vaccinated individuals who were infected with Omicron, found that rhinorrhea (77%), headache (75%), sore throat (71%) and sneezing (63%) were the most common symptoms[19].

Several studies compared the symptoms between Omicron and different variantsand found a significant rise in upper respiratory symptomsespecially sore throats. For instance, one of these studies conducted in the US found a significantly higher rates of sore throats during Omicron wave than during the pre-delta period (29.6%, P < 0.001) and Delta (29.1%, P < 0.001) [20]. This isconsistent withanotherstudyconducted in UK [21]. However, sore throat was also common in symptomatic cases with negative PCR, suggesting that sore throats may not be a specific predictor of Omicron. Besides, symptoms reported during COVID-19 are similar to signs found in any infection by other respiratory viruses such as (influenza A and B, respiratory syncytial virus, adenovirus, parainfluenza, rhinovirus and human metaneumovirus.As we did not perform sequencing to determine the variant, it is not possible for us to conclude that the symptoms reported in our study are caused exclusively by Omicron alone.The non-predominance of upper respiratory signs can be explained by the coexistence of other variants of SARS-CoV-2 such as Delta during the period of our studies. Further studies are therefore needed.

None of our patients reported agueusia and only 1.9% reported anosmia. This is consistent with the literature which indicates a significant decrease in these signs among Omicron patients compared to other SARS-cov-2 variants  [22][23].This finding suggests that the site of the virus tropism may have changed between variants. This is further reinforced by the fact that the number of Omicron pneumonia is reduced compared to other variants [24,25].Further reinforcing of this hypothesis is the fact that the incidence of sore throathas increased with Omicron, and it can be deducted that the viral replication site could be moved to the upper respiratory tract [19].

In our study, the prevalence of severe disease was 19.5%. Only 28.3% of patients required hospitalization. The hospitalization rate in a resuscitation unit was low (9.3%) and the death rate was 15.5%.Many studies found a significant decrease in severity and mortality with the new Omicron variant. Several cohort studies were conducted comparing the severity of Omicron with other variants, especially the delta, and affirmed this finding.In a study in South Africa, analyzing data of 11,000 patients with COVID-19, the authors found that the hospitalization rate of Omicron patients was significantly lower than other variants and the prevalence of severe forms was significantly lower compared toDelta patients (OR 0.3 , 0.2–0.5) [26].A cohort study in Canada 11 622 Omicron cases paired with Delta cases noted that the hospitalization rate among Omicron cases was only 0.51% and the mortality rate was 0.03%, compared to 1.56% and 0.12% respectively for Delta cases. The risk of hospitalization or death among Omicron cases was 65% lower (relative risk, RH = 0.35, 95% CI: 0.26, 0.46) compared to Delta cases. The risk of admission to a ICU or death was 83% lower (RH = 0.17, 95% CI: 0.08, 0.37) [27].Another study in the UK showed that Omicron cases had a 59% lower risk of hospitalization than Delta and a 69% lower risk of death than Delta [28].Another cohort study in Belgium found that the estimated risk of severe forms and admission to ICU was significantly lower in Omicron patient compared to Delta (RR = 0.63; 95% CI (0.30; 0.97) and RR = 0.56; 95% CI (0.14; 0.99), respectively), while no significant difference was found for mortality (RR = 0.78, 95% CI (0.28–1.29)[29].

Some studies tried to find an explanation for this decrease in mortality and severitywith Omicron. They believe that cell-mediated immunity due to a previous natural COVID-19 infection or to vaccination played an important role in the regression of severity observed during Omicron wave.

Studies showed that natural infection induces a diverse polyepitopical cell-mediated immune response that targets the spike protein (nucleocapsid protein and membrane protein) [30]. Therefore, cell-mediated immunity is likely to be more durable than humeral immunity especially in the context of small mutations affecting the spike protein [31], such as those seen in the Omicron variant. In addition, natural infection induces an immune response to memory T cells, including long-lived cytotoxic T cells (CD8+), which have a half-life of 125 to 255 days, ensuring longer-lasting immunity [32].

Although vaccination status appears to be well documented, in many cases it is likely that a previous infection by COVID-19 has not been documented and the rate of re-infection remains underestimated. If reinfections are less severe than primary infections, this fact could, in part, explain the reduced severity of the disease observed in patients infected with Omicron [33].

Although several studies suggest that Omicron is much less virulent than other variants, other studies taking into account the pre-existing immunity to COVID-19 (vaccination status and previous infection) assume a highest virulence of Omicron compared to other variants.Furthermore, Omicron has the ability to infect people with pre-existing immunity[9], thus protecting them from severe forms.

We found two studies comparing the intrinsic virulence of Omicron with the Delta, taking into account the immunizing effect of undocumented prior infections. Although these studies were conducted in regions where the prevalence of infected cases was different, after correction, each study showed that Omicron was approximately 75% as likely as Delta to cause hospitalization in subjects who were not immunized by either vaccination or previous SARS-CoV-2 infection [34,35].This implies that Omicron have similar intrinsic virulence with previous variants.With the available data, it is not possible to discern whether the low rate of severe forms is related to the effect of pre-existing immunity to COVID-19 or the decrease in intrinsic virulence of Omicron.More comparative studies controlling pre-existing immunity, detection bias, care system capacity and other factors are needed to conclude between these different assumptions.

Concerning associated factors for severity of COVID-19 during the Omicron wave, we found in the univariate analysis a significant association between age and severity (p<0.001), however in multivariate analysis this association has disappeared. A study on 25207 Chinese Omicron patients found that older subjects had a higher rate of severe forms than other age groups [[36]. Several other studies confirmed this association[37–40].This can be explained by the immunosenescence (immune aging), which is responsible for developing weak immune responses to COVID-19 and inadequate immune responses to vaccination [41]. There is also a reduction in immunological memory associated with antibody loss, making elders more vulnerable to infection[41]. It is important to give more attention to older subjects with COVID-19 and to treat them earlier to prevent further deterioration.

In our study males had higher prevalence of severe forms. This association was only found in the univariate analysis and did not persist after adjustment by logistic regression.Several studies have shown an association between male sex and severity of infection by different SARS-CoV-2 variants such as Alpha, Gamma and Delta [42–44]. Male patients may have a greater expression of the ACE2 enzyme, which is controlled by androgenic sex hormones, making this group of people more susceptible to infections and severe forms of SARS-CoV-2, knowing that this virus has great affinity to ACE2 receptors[42,45].

In our study, the risk of developing a severe form was associated with having at least one comorbidity, CVD, diabetes, HTN, coronary artery disease, system disease, COPD/asthma, and cancer. All but CVD and cancer were excluded after logistic regression.Our results are congruent with a recent study conducted on subjects with Omicron. In their univariate analysis, comorbidities, HTN, diabetes, and COPD/asthma were associated with severe forms. However, after binary regression, only the existence of co-morbidities was associated with severity [36].It is widely known that patients with chronic disease infected with COVID-19 are at high risk of death and developing severe forms.In the literature, several studies point to diabetes, hypertension, CVD and obesity as being the comorbidities most at risk of severe form and mortality from COVID-19 [44,46,47].Diabetic patients have impaired phagocytic cells, making the treatment of infections ineffective [48]. Obesity, which is also among the risk factors for the severity of influenza A (H1N1) [49], is associated with a decrease in functional capacity, expiratory reserve volume, and respiratory system compliance [50].CVD and endocrine diseases may be responsible for changes in the expression of angiotensin-2 converting enzyme, which is the receptor where the spike protein of SARS-CoV-2 binds. This condition makes these subjects more susceptible to contracting COVID-19 and developing severe forms [45,51,52].

Regarding vaccination, we found in the univariate analysis that severity was significantly lower in vaccinated patients against COVID-19. However, no association was found after binary regression. Many studies have demonstrated the effectiveness of vaccination against COVID-19. In fact, multiple doses provide additional protection against Omicron, inducing more effective immune responses against symptomatic infection and reducing the risk of hospitalization[53,54]. Considering the overall performance of the vaccination, some studies have reported that the efficacy of the vaccine is lower against Omicron compared to the other variants [55,56]. Additionally, Andrews et al. [57]analyzing South African, German and British studies found a reduced neutralizing activity of vaccines against Omicron compared to that against Delta [57].

Strengths and limitations of the study

For logistical reasons, participants did not have had a genotyping test to confirm infection with the Omicron variant. To genetically determine whether all cases were actually infected with B.1.1.529 variant, additional laboratory testing is needed.

Our study only assessed clinical symptoms at the onset of the infection and did not track symptoms. Symptoms may superimpose after the swab test. To gain insight into the clinical presentation of this variant throughout the course of infection, more detailed data regarding clinical symptoms in the initial and later stages of infection are needed.

Conclusions

In 2021, the SARS-CoV-2 Delta variant was replaced by Omicron, which was classified as a VOC by the WHO [4].Omicron appears to be different from previous variants; it is associated with an important ability of transmission, an ability to escape immune response, it has a different clinical presentation and a lesser degree of severity [28].

Recognizing the factors associated with severity helps health actors to adopt strategies to deal with this variant. Staying alert to COVID-19 and continuing vaccination efforts and adherence to prevention measures are needed to reduce the spread and impact of different variants. The public health system, local, regional and national authorities, must maintain the alert to detect, react and adapt rapidly to the emergence of new variants.

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