Characteristics and Factors Associated with SARS-CoV-2 Infections in Individuals That Attended Referral Hospitals from Southern Region of Bahia State, Brazil: A Surveillance Network Retrospective Study

Abstract

In December 2019, a novel coronavirus was detected in Wuhan, China, and rapidly spread worldwide. In Brazil, to date, there have been more than 20,000,000 confirmed cases of COVID-19 and more than 550,000 deaths. The purpose of the current study was to determine the clinical and epidemiological profile of the population affected by COVID-19 that have attended referral hospitals in Southern region of Bahia State, to better understand the disease and its risk factors in order to enable more appropriate conduct for patients. An observational, descriptive, cross-sectional, exploratory study was conducted using secondary data collected from the Laboratório de Farmacogenômica e Epidemiologia Molecular, Universidade Estadual de Santa Cruz (LAFEM/UESC). Chi-squared and Fisher’s exact tests were applied to determine the association between clinical symptoms and laboratory results, and to identify risk factors associated with SARS-CoV-2 infection. A total of 3135 individuals with suspected severe respiratory illness were analyzed and 41.4% of them tested positive for SARS-CoV-2 infection. Male individuals and having comorbidities were risk factors significantly associated with SARS-CoV-2 infection (OR = 1.17 and OR = 1.37, respectively). Interestingly, being a healthcare professional was a significantly protective factor (OR = 0.81, p < 0.001). Our findings highlight the importance of routinely testing the population for early identification of infected individuals, and also provide important information to health authorities and police makers to improve control measures, management, and screening protocols.

Comorbidities and Mortality Risk in COVID-19 Infected Patients: A Cross-Sectional Study in North-Eastern Iran

“…Similar to our findings, most studies have shown a male predominance among COVID-19 patients. 10,11,15,16 However, there are some reports of female predominance. 14,17,18 The median of hospitalization of our patients was 3 (IQR 1-7) days and 43.6% of our subjects, had at least one coexisting underlying medical condition.…”

“…The most common comorbidities were hypertension (19.7%), diabetes (15.1%), and CVD (13.3%), which are in line with previous studies. 10,11,16 A meta-analysis of 12,149 COVID-19 patients reported 31% patients to have comorbidities. Similar to our results, hypertension was the most common (20.93%), followed by heart failure (10.5%), diabetes mellitus (10.4%), and coronary heart disease (8.5%).…”

“…Previous studies have also found respiratory distress, fever, and cough to be among the most commonly reported symptoms. 10,11,16,19 A meta-analysis of 281,461 COVID-19 patients showed the most common symptom to be fever (78.8%), followed by cough (53.9%) and malaise 37.9%. 20 In our study anosmia and ageusia were much less prevalent than previous reports, which reported anosmia and ageusia to be between 5-48%, and 5-24% respectively.…”

“…8,9 At-risk individuals for critical outcomes include the elderly, male gender, and individuals with underlying conditions, such as diabetes mellitus, hypertension, obesity, cancer, and chronic cardiovascular and respiratory diseases. [10][11][12] However, severe outcomes can also occur in individuals from all age groups and with no underlying conditions. 11,13 Identifying the epidemiological features and clinical characteristics, and mortality risk factors of COVID-19 can improve our current understanding of the disease and can contribute to the early diagnosis of COVID-19 cases and identification of the at-risk patients.…”

“…[10][11][12] However, severe outcomes can also occur in individuals from all age groups and with no underlying conditions. 11,13 Identifying the epidemiological features and clinical characteristics, and mortality risk factors of COVID-19 can improve our current understanding of the disease and can contribute to the early diagnosis of COVID-19 cases and identification of the at-risk patients. In addition, comparing the epidemiologic and clinical features between the 3 outbreaks of COVID-19 in this region can be helpful in the decision-making of the health policies for the control and prevention of future epidemics.…”