Work Related Clusters of COVID-19 in Muscat Governorate in Oman: Epidemiology & Future Implications

Autor: Mohammed Amin, Salwa Al Mashari, Haleema Al Ghazaili, Fatma Al Fahdi, Mariam Al Kalbani, Balqees Al Siyabi, Padmamohan J. Kurup, Lamya Al Balushi, Hanan Al Kindi
Rok vydání: 2021
Předmět:
Zdroj: Open Journal of Epidemiology. 11:135-151
ISSN: 2165-7467
2165-7459
DOI: 10.4236/ojepi.2021.112013
Popis: Introduction: The coronavirus disease 2019 epidemic emerged in December 2019 and spread worldwide. Since workplaces are high-risk location for occupational exposure, understanding of the dynamics of COVID-19 clusters in occupational settings helps reduce the transmission of infectious disease in workplaces. This study presents an overview of the epidemiological characteristics of COVID-19 workplace clusters, preventive strategies adopted and outbreak responses undertaken in Muscat governorate. Materials and Methods: This is a descriptive study on the epidemiological characteristics of cases and distribution of workplace-related clusters of COVID-19 in Muscat Governorate in Oman. Results: A total of 36,798 COVID-19 cases were confirmed in Muscat from 24th February to 31st July 2020 in which 40.5% was belonging to clusters. Out of them 61% were Workplace-Dormitory clusters, predominantly expatriates. 78.6% of employees were symptomatic at time of examination. Fever and cough were the two most common symptoms reported in workplace related clusters. The number of affected employees ranged from 2 to 358 per cluster. Construction, retail, food, beverages, services, industrial manufacturing, oil & gas and transportation were identified as most at risk settings. Within the cases in workplace-related clusters, there was significant higher prevalence of diabetes, hypertension and obesity among females compared to males as also Omani nationals compared to expatriates and smoking among expatriate males compared to Omani males. In conclusion, understanding the epidemiological characteristics of the affected cases in organization setting will assist the policymakers to understand patterns of epidemiological spread and plan for robust interventions.
Databáze: OpenAIRE
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