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- Title
Factors Associated with Asymptomatic COVID-19 Patients in Petaling District, Selangor, Malaysia.
- Authors
Lim Kuang Kuay; Hanafiah, Ainul Nadziha Mohd; Lee Soo Cheng; Chan Ying Ying; Kassim, Mohd Shaiful Azlan; Chong Zhuo Lin; Sapian, Roslinda Abu; Musa, Nurul Syarbani Eliana; Sanaudi, Ridwan; Yusof, Mohamed Paid
- Abstract
Introduction The rapid spread of the Coronavirus disease 2019 (COVID-19) worldwide has led the World Health Organization to declare COVID-19 outbreak as a pandemic on March 11, 2020. As the local studies on factors leading to the absence or presence of clinical illness among the COVID-19 cases are sparse, the study aims to determine the factors associated with asymptomatic COVID-19 patients in Petaling District, Selangor, Malaysia. Methods Data on COVID-19 patients were extracted from the database of confirmed cases in Petaling District Health Office, Selangor, Malaysia from 3rd February 2020 to 30th April 2020. An asymptomatic laboratory-confirmed case is a person infected with COVID-19 who does not develop any symptoms. The study included socio-demographic variables, the detailed information on clinical manifestations and co-morbidity of the patients. Descriptive and multiple logistic regression analyses were conducted to determine the factors associated with asymptomatic patients. Results The overall COVID-19 patients in Petaling District were 434. Approximately 70% (n= 292) of the patients were symptomatic while 32.7% (n= 142) were asymptomatic. Multivple logistic regression analyses revealed that factors significantly associated with asymptomatic patients were age below 40 years old (aOR: 1.79, 95% CI 1.11, 2.86), non-Malaysians (aOR: 3.22, 95% CI 1.44, 7.19) and local cases (aOR: 2.51, 95% CI 1.42, 4.42). Gender, ethnicity, comorbidity and township were not significantly associated with asymptomatic patients. Conclusions Approximately one-third of COVID-19 patients were asymptomatic and the risk factors identified were younger age, non-Malaysians and local cases. Rigorous epidemiological investigation is helpful in identifying COVID-19 cases among these group of people who are asymptomatic.
- Subjects
SELANGOR; MALAYSIA; COVID-19; COVID-19 pandemic; SYMPTOMS; WORLD Health Organization; MULTIPLE regression analysis; LOGISTIC regression analysis; INFECTIOUS disease transmission
- Publication
International Journal of Public Health Research, 2021, Vol 11, Issue 2, p1418
- ISSN
2232-0253
- Publication type
Article
- DOI
10.17576/ijphr.1102.2021.05