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Background: Terengganu state has experienced fifteen COVID-19 communal clusters throughout the year 2020. Knowing the predisposing factors of COVID-19 transmissibility can be helpful in planning the control and preventive measures. This study aimed to describe the socio-demographic and clinical characteristics of COVID-19 patients in Terengganu state, and to determine the predictors for SARS-CoV-2 transmissibility using RT-PCR cycle threshold (Ct) value as surrogate marker.

Materials and Methods: A cross-sectional study was conducted in Terengganu state including all COVID-19 cases from 1st March 2020 until 31st January 2021 based on retrospective record review. The inclusion criteria were individuals with laboratory RT-PCR confirmed positive test for COVID-19. Descriptive statistics, simple and multiple linear regression analyses were employed for statistical analysis.

Result: There were 2,142 COVID-19 cases in Terengganu during the studied period. The mean age of cases was 33 (±17) years. Majority of COVID-19 cases were male (60.6%), adult (70.0%) and from working group (49.2%). 3.9% of cases were healthcare workers. Among the common symptoms were fever (17.2%) and cough (14.0). The mean RT-PCR Ct value was 25.76 (±10.99). Multiple linear regression revealed older age, male gender, having fever and cough as the significant predictors for high SARS-CoV-2 transmissibility with β: -0.06 (95%CI: -0.09,-0.03); p<0.001; β: -3.80 (95%CI: -4.73,-2.86); p<0.001; β: -1.31 (95%CI: -2.54,-0.08); p=0.037; β: -1.86 (95%CI: -3.51,-0.20); p=0.028, respectively.

Conclusion: Early detection and isolation of vulnerable cases based on pinpointed risk factors in centralized quarantine station or hospital is recommended to reduce the risk of transmission and to ensure optimal care is given.

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References

  1. Elengoe A. COVID-19 Outbreak in Malaysia. Osong Public Health Res Perspect. 2020; 11(3): 93.
    DOI  |   Google Scholar
  2. Ministry of Health. Malaysia's COVID-19 Update (January 31, 2021) Putrajaya, Malaysia: Ministry of Health Malaysia. [Internet] 2021 [cited 2021 31 January]. Available from: https://kpkesihatan.com/2021/01/31/kenyataan-akhbar-kpk-31-januari-2021-situasi-semasa-jangkitan-penyakit-coronavirus-2019-covid-19-di-malaysia/
     Google Scholar
  3. Awang H, Hamzah FH, Ahmad MH, Mahmood MF, Wahab A, Embong K, et al. Polymerase chain reaction cycle threshold value as prerequisite for reporting of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection. Infect. Dis. 2021: 1-3.
    DOI  |   Google Scholar
  4. Awang H, Yaacob EL, Syed Aluawi SN, Mahmood MF, Hamzah FH, Wahab A, et al. A case–control study of determinants for COVID-19 infection based on contact tracing in Dungun district, Terengganu state of Malaysia. Infect. Dis. 2021; 53(3): 222-225.
    DOI  |   Google Scholar
  5. Tom MR, Mina MJ. To Interpret the SARS-CoV-2 Test, Consider the Cycle Threshold Value. Clin. Infect. Dis. 2020.
    DOI  |   Google Scholar
  6. Cevik M, Kuppalli K, Kindrachuk J, Peiris M. Virology, transmission, and pathogenesis of SARS-CoV-2. BMJ. 2020; 371.
    DOI  |   Google Scholar
  7. Sarkar B, Sinha RN, Sarkar K. Initial viral load of a COVID-19-infected case indicated by its cycle threshold value of polymerase chain reaction could be used as a predictor of its transmissibility-An experience from Gujarat, India. Indian J Community Med. 2020; 45(3): 278.
    DOI  |   Google Scholar
  8. Ministry of Health. Guidelines for COVID-19 Ministry of Health Malaysia Malaysia: Ministry of Health; [Internet] 2020 [cited 2020 13 November] Available from: http://covid-19.moh.gov.my/garis-panduan/garis-panduan-kkm.
     Google Scholar
  9. Faul F, Erdfelder E, Buchner A, Lang A-G. Statistical power analyses using G* Power 3.1: Tests for correlation and regression analyses. Behav. Res. Methods. 2009; 41(4): 1149-60.
    DOI  |   Google Scholar
  10. Sim BLH, Chidambaram SK, Wong XC, Pathmanathan MD, Peariasamy KM, Hor CP, et al. Clinical characteristics and risk factors for severe COVID-19 infections in Malaysia: a nationwide observational study. The Lancet Regional Health-Western Pacific. 2020; 4: 100055.
    DOI  |   Google Scholar
  11. The Edge Markets. 1,880 healthcare workers infected with Covid-19 — MoH Kuala Lumpur, Malaysia: The Edge Communications Sdn. Bhd.; [Internet] 2020 [cited 2021 20 February]. Available from: https://www.theedgemarkets.com/article/1880-healthcare-workers-infected-covid19-%E2%80%94-moh.
     Google Scholar
  12. Pujadas E, Chaudhry F, McBride R, Richter F, Zhao S, Wajnberg A, et al. SARS-CoV-2 viral load predicts COVID-19 mortality. medRxiv. 2020.
    DOI  |   Google Scholar
  13. Fajnzylber J, Regan J, Coxen K, Corry H, Wong C, Rosenthal A, et al. SARS-CoV-2 viral load is associated with increased disease severity and mortality. Nat. Commun. 2020; 11(1): 1-9.
    DOI  |   Google Scholar
  14. Heneghan C, Brassey J, Jefferson T. SARS-CoV-2 viral load and the severity of COVID-19. [Internet] 2020. [cited 2021 20 February]. Available from: https://www.cebm.net/covid-19/sars-cov-2-viral-load-and-the-severity-of-covid-19/
     Google Scholar
  15. Wang F, Cao J, Yu Y, Ding J, Eshak ES, Liu K, et al. Epidemiological characteristics of patients with severe COVID-19 infection in Wuhan, China: evidence from a retrospective observational study. Int. J. Epidemiol. 2020.
    DOI  |   Google Scholar
  16. Smith R. Immunity, trauma and the elderly. Injury. 2007; 38(12): 1401-4.
    DOI  |   Google Scholar
  17. Klein SL, Dhakal S, Ursin RL, Deshpande S, Sandberg K, Mauvais-Jarvis F. Biological sex impacts COVID-19 outcomes. PLoS Pathog. 2020; 16(6): e1008570.
    DOI  |   Google Scholar
  18. Tian S, Hu N, Lou J, Chen K, Kang X, Xiang Z, et al. Characteristics of COVID-19 infection in Beijing. J. Infect. 2020.
    DOI  |   Google Scholar
  19. Cheng H-Y, Jian S-W, Liu D-P, Ng T-C, Huang W-T, Lin H-H. Contact tracing assessment of COVID-19 transmission dynamics in Taiwan and risk at different exposure periods before and after symptom onset. JAMA Intern. Med. 2020.
    DOI  |   Google Scholar
  20. He X, Lau EH, Wu P, Deng X, Wang J, Hao X, et al. Temporal dynamics in viral shedding and transmissibility of COVID-19. Nat Med. 2020; 26(5): 672-5.
    DOI  |   Google Scholar
  21. Liu S, Luo H, Wang Y, Cuevas LE, Wang D, Ju S, et al. Clinical characteristics and risk factors of patients with severe COVID-19 in Jiangsu province, China: a retrospective multicentre cohort study. BMC Infect Dis. 2020; 20: 584.
    DOI  |   Google Scholar


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