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. 2021 Apr;7(4):e06650.
doi: 10.1016/j.heliyon.2021.e06650. Epub 2021 Mar 29.

SARS-CoV-2 molecular identification and clinical data analysis of associated risk factors from a COVID-19 testing laboratory of a coastal region in Bangladesh

Md Roushan Ali  1   2 , Md Rayhan Chowdhury  1 , Md Atik Mas-Ud  1 , Shirmin Islam  1 , Ajmeri Sultana Shimu  1 , Fahmida Begum Mina  1 , Nur E Sharmin  3 , Md Faruk Hasan  1
Affiliations

SARS-CoV-2 molecular identification and clinical data analysis of associated risk factors from a COVID-19 testing laboratory of a coastal region in Bangladesh

Md Roushan Ali et al. Heliyon. 2021 Apr.

Abstract

Background and aim: Outbreak of COVID-19 seems to have exacerbated across the globe, including Bangladesh. Scientific literature on the clinical data record of COVID-19 patients in Bangladesh is inadequate. Our study analyzes the clinical data of COVID-19 positive patients based on molecular identification and risk factor correlated with three variables (age, sex, residence) and COVID-19 prevalence in the four districts of Chattogram Division (Noakhali, Feni, Lakshmipur and Chandpur) with an aim to understand the trajectory of this pandemic in Chattogram, Southern Bangladesh.

Methods: A cross-sectional study is conducted in the context of RT-PCR-based COVID-19 positive 5,589 individuals diagnosed with SARS-CoV-2 infection from the COVID-19 testing laboratory, Abdul Malek Ukil Medical College, Noakhali-3800, Bangladesh. For molecular confirmation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), standard diagnostic protocols through real-time reverse transcriptase-polymerase chain reaction (RT-qPCR) were conducted. Different patient demographics were analyzed using SPSS version 22 for exploring the relationship of three factors - age, sex, and residence with a cumulative number of COVID-19 positive cases and prevalence of COVID-19 in four districts in Chattogram division. The data was recorded between May to July, 2020.

Results: Among the three parameters, the present study revealed that 20-40 cohort had the highest incidence of infection rate (51.80%, n = 2895) among the different age groups. Among the infected individuals, 56.8% (n = 3177) were male and 43.2% (n = 2412) were female, denoting males being the most susceptible to this disease. Urban residents (52.7%, n = 2948) were more vulnerable to SARS-CoV-2 infection than those residing in rural areas (47.3%, n = 2641). The prevalence of COVID-19 positive cases among the four districts was recorded highest in the Noakhali district with 36.8% (n = 2057), followed by the Feni, Lakshmipur and Chandpur districts with 25.9% (n = 1448), 20.8% (n = 1163) and 16.5% (n = 921), respectively.

Conclusions: This study presents a statistical correlation of certain factors linked to Bangladesh with confirmed COVID-19 patients, which will enable health practitioners and policy makers to take proactive steps to control and mitigate disease transmission.

Keywords: Bangladesh; COVID-19; Epidemiology; Prevalence; SARS-CoV-2.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Prevalence of COVID-19 in different age groups.
Figure 2
Figure 2
Prevalence of COVID-19 by sex.
Figure 3
Figure 3
Prevalence of COVID-19 by residence.
Figure 4
Figure 4
Prevalence of COVID-19 among four districts in Chattogram, Bangladesh.
See this image and copyright information in PMC

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