ABSTRACT
Objectives: This study was aimed at exploring and analyzing the epidemiological profile, surveillance, and response to COVID-19, including transmission dynamics and cluster formation. Methodology: This was a retrospective analysis of surveillance data, including contact tracing, risk factors, and clinical information. Binary logistic regressions were used to assess the likelihood of admission, cluster formation, and of each individual being an index patient. Clusters were demonstrated through geographic data systems, network analysis, and visualization software. Results: A total of 1100 COVID-19 cases were diagnosed from 20 March to 7 June 2020, of which 144 (13.1%) were asymptomatic. The median time from symptom onset to admission was 7 days (IQR, 4.5-10), and the median symptom duration was 5 days (IQR, 3-9). Eighty-nine clusters containing 736 patients were identified. The surveillance and control actions were divided into three phases. Clusters began to form in phase 2 and became more pronounced in phase 3. Patients ≥50 years of age and patients presenting with fever had relatively higher odds of admission: OR = 12.85 (95% CI 5.13-32.19) and 2.53 (95% CI 1.24-5.17), respectively. Cluster formation was observed among females, asymptomatic patients, and people living in Awabi: OR = 2.3 (95% CI 1.7-3.1), 6.39 (95% CI 2.33-17.2), and 3.54 (95% CI 2.06-6.07), respectively. Patients working in the police and defense sectors had higher odds of being an index patient: OR = 7.88 (95% CI 3.35-18.52). Conclusion: Case-based interventions should be supported by population-wide measures, particularly movement restrictions. Establishing prevention teams or district units, or primary care will be crucial for the control of future pandemics. Prevention should always be prioritized for vulnerable populations.
ABSTRACT
Background: The changing epidemiological profile of the COVID-19 pandemic and the uncertain clinical picture of patients characterise this ongoing and most challenging health event. Objectives: To report clinical features, laboratory characteristics, and mortality risk factors among COVID-19 patients admitted to a secondary hospital in Oman. Methods: A retrospective study for the first 455 patients admitted with COVID-19 to Rustaq hospital from 12th April, 2020 to 27th September, 2020. A predesigned questionnaire collected data from the hospital medical electronic system. Results: The mean age was 42.84 (SD = 19.86) years, and the majority of patients were aged 30 to 59 and 60 or above; 207 (45.5%) and 189 (41.5%), respectively. Male patients constituted approximately two-thirds of the subjects. Fever, dyspnea and cough were the most common presenting symptoms (69%, 66%, and 62%, respectively), while comorbidities with diabetes mellitus and hypertension were 47% and 44%, respectively. Bacterial growth was identified at approximately 10%. Bivariate analysis turned out to be significant with a number of factors. However, multivariate analysis showed significance with patients aged over 60 (OR = 7.15, 95% CI 1.99-25.63), dyspnea (OR = 2.83, 95% CI 1.5-5.33), dyslipidemia (OR = 1.93, 95% CI 1.02-3.66) and being bed-ridden (OR = 5.01, 95% CI 1.73-14.44). Durations from onset of symptoms to admission and respiratory distress were lower among patients who died; p = 0.024 and p = 0.001, respectively. Urea, Troponin and LDH may act as potential diagnostic biomarkers for severity or mortality. Conclusions: This study identified groups of patients with a higher risk of mortality, with severe disturbance in the laboratory markers while some could act as potential diagnostic biomarkers.
