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Background: Coronavirus disease 2019 (COVID-19) is a highly infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Large-scale vaccination of risk groups and later the general population is the single most effective public health measure for mitigation of the COVID-19 pandemic.

Methods and Materials: This prospective cross sectional study was carried out at Dhaka North City Corporation dedicated COVID-19 hospital, Mohakhali, Dhaka, enrolling 50 (fifty) vaccinated RT-PCR positive COVID-19 patients.

Results: Majority of the patients were >50 years old. Most of the patients had bilateral lung involvement and ground glass was the predominant CT pattern. 20% patients had consolidation in HRCT scan. Most of the patients (46%) had mild disease and only 18% patients had severe disease. Severe cases were more common (77.8%) in older (>50years) patients. 20% of the patients had 50-75% and only 6 % patients had more than 75% of total lung involvement. 52% patients had less than 25% lung involvement. Lung involvement was significantly higher in older patients. Patients had to stay an average of 6.2 days in hospital. Older patients had to stay more days in the hospital than younger patients. 2% (1) of COVID-19 patients died after admitting into our hospital.

Conclusion: Vaccination can effectively reduce mortality and morbidity of COVID-19 patients by reducing the active number of cases as well as severity of the disease.

References

  1. Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, et al. Clinical characteristics of coronavirus disease 2019 in China. New England Journal of Medicine. 2020; 382(18): 1708-1720.
     Google Scholar
  2. World Health Organization. Coronavirus disease 2019 (COVID-19) situation report–39. World Health Organization, Geneva. [Internet] 2020 [cited 2020 Mar 3] Available from: https://www.who.int/docs/default-source/ coronaviruse/situation-reports/20200228-sitrep-39-covid-19.pdf? sfvrsn=5bbf3e7d_2.
     Google Scholar
  3. Dooling K, McClung N, Chamberland M, Marin M, Wallace M, Bell BP, et al. The Advisory Committee on Immunization Practices’ interim recommendation for allocating initial supplies of COVID-19 vaccine—United States, 2020. Morbidity and Mortality Weekly Report. 2020; 69(49): 1857.
     Google Scholar
  4. Madhu P, Santhosh D, Madhala K. Comparison Study of Lung Involvement in Vaccinated and Un Vaccinated Covid Patients. International Journal of Health and Clinical Research. 2021; 4(10): 229-33.
     Google Scholar
  5. Le TT, Andreadakis Z, Kumar A, Román RG, Tollefsen S, Saville M, et al. The COVID-19 vaccine development landscape. Nat Rev Drug Discov. 2020; 19(5): 305-306.
     Google Scholar
  6. World Health Organization. Draft landscape and tracker of COVID-19 candidate vaccines. [Internet] [cited 2021 Feb 17]. Available from: https://www.who.int/publications/m/item/draft-landscape-of-covid19-candidate-vaccines
     Google Scholar
  7. Bangladesh starts COVID vaccination drive use. Al Jazeera. [Internet] 28 January 2021. [cited 2021 April 30].
     Google Scholar
  8. Covid-19: Why the crisis in vaccines? use. Prothom Alo. 29 April 2021. [cited 2021 April 30].
     Google Scholar
  9. Zu ZY, Jiang MD, Xu PP, Chen W, Ni QQ, Lu GM, Zhang LJ. Coronavirus disease 2019 (COVID-19): a perspective from China. Radiology. 2020; 296(2): E15-25.
     Google Scholar
  10. Ming-Yen N, Lee Elaine YP, Jin Y, Fangfang Y, Xia L, Hongxia W, et al. Imaging profile of the COVID-19 infection: radiologic findings and literature review. Radiology: Cardiothoracic Imaging. 2020; 2(1): e200034.
     Google Scholar
  11. Borghesi A, Maroldi R. COVID-19 outbreak in Italy: experimental chest X-ray scoring system for quantifying and monitoring disease progression. La radiologia medica. 2020; 125(5): 509-13.
     Google Scholar
  12. Bernheim A, Mei X, Huang M, Yang Y, Fayad ZA, Zhang N, Diao K, et al. Chest CT findings in coronavirus disease-19 (COVID- 19): relationship to duration of infection. Radiology. 2020: 200463.
     Google Scholar
  13. Pan F, Ye T, Sun P, Gui S, Liang B, Li L, et al. Time course of lung changes on chest CT during recovery from 2019 novel coronavirus (COVID-19) pneumonia. Radiology. 2020
     Google Scholar
  14. Lei J, Li J, Li X, Qi X. CT imaging of the 2019 novel coronavirus (2019-nCoV) pneumonia. Radiology. 2020; 295(1): 18.
     Google Scholar
  15. Cheng Z, Lu Y, Cao Q, Qin L, Pan Z, Yan F, et al. Clinical features and chest CT manifestations of coronavirus disease 2019 (COVID-19) in a single-center study in Shanghai, China. American Journal of Roentgenology. 2020; 215(1): 121-6.
     Google Scholar
  16. Wang H, Wei R, Rao G, Zhu J, Song B. Characteristic CT findings distinguishing 2019 novel coronavirus disease (COVID-19) from influenza pneumonia. European radiology. 2020; 30(9): 4910-7.
     Google Scholar
  17. Ai T, Yang Z, Hou H, Zhan C, Chen C, Lv W, et al. Correlation of chest CT and RT-PCR testing for coronavirus disease 2019 (COVID-19) in China: a report of 1014 cases. Radiology. 2020; 296(2): E32-40.
     Google Scholar
  18. Lu L, Zhong W, Bian Z, Li Z, Zhang K, Liang B, et al. A comparison of mortality-related risk factors of COVID-19, SARS, and MERS: A systematic review and meta-analysis. Journal of Infection. 2020.
     Google Scholar
  19. Noor FM, Islam MM. Prevalence and associated risk factors of mortality among COVID-19 patients: a meta-analysis. Journal of Community Health. 2020; 45(6): 1270-82.
     Google Scholar
  20. Kumar A, Arora A, Sharma P, Anikhindi SA, Bansal N, Singla V, et al. Clinical features of COVID-19 and factors associated with severe clinical course: a systematic review and meta-analysis. Social Science Research Network. 2020.
     Google Scholar
  21. Li K, Wu J, Wu F, Guo D, Chen L, Fang Z, et al. The clinical and chest CT features associated with severe and critical COVID-19 pneumonia. Investigative Radiology. 2020.
     Google Scholar