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.