Padmavathy K M, Rohith Sharan S, Noorzaid M, Rehanna M
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Padmavathy K M1*, Rohith Sharan S2, Noorzaid M1, Rehanna M1
1 Cluster for Integrative Physiology and Molecular Medicine (CIPMM), Faculty of Medicine, Universiti Kuala Lumpur Royal College of Medicine Perak, Jalan Greentown, 30450 Ipoh, Perak, Malaysia.
2Yerevan State Medical University, Armenia.
Volume - 14,
Issue - 9,
Year - 2021
The ongoing COVID-19 pandemic has affected around forty million people worldwide and causing over a million deaths. Since no treatment guideline is considered the most efficient, and with no vaccine approved for prophylaxis, currently the COVID-19 response demands efficient use of available technology and tools in medical field for controlling the disease. The knowledge and experience gained from the epidemics of Severe Acute Respiratory Syndrome (SARS), Middle East Respiratory Syndrome (MERS), Ebola, and Zika virus play a pivotal role in this pandemic response. The required technologies and tools are adapted from the existing technologies and are modified to serve the purpose of COVID-19 response which is applied in the prevention, diagnosis and treatment of Coronavirus infection. The technologies applied at the prevention stage aims at limiting the spread of infection by using personal protective equipment, contact-tracing, and modelling. At the stage of diagnosis, technologies are used efficiently and the correct diagnosis of infected cases is done by molecular, immunological testing and radiological imaging. Artificial-Intelligence is employed in building applications that use the available information and radio-images to aid in differential diagnosis of Coronavirus infection. The treatment in COVID-19 incorporates technology in both in-patient and remote care of the cases. Though the COVID-19 response strategy differs from country to country, it is devised based on the recommendations made by the international health authorities such as the World Health Organization (WHO) and the National Center for Disease Control and Prevention of the United States (NCDCP-US). The controlling of the pandemic depends on the collective effort of all nations which rest on efficient scientific communication and in the advancement of the medical field.
Cite this article:
Padmavathy K M, Rohith Sharan S, Noorzaid M, Rehanna M. Praxis of Technology and Tools in COVID-19 Response. Research Journal of Pharmacy and Technology. 2021; 14(9):4808-4. doi: 10.52711/0974-360X.2021.00836
Padmavathy K M, Rohith Sharan S, Noorzaid M, Rehanna M. Praxis of Technology and Tools in COVID-19 Response. Research Journal of Pharmacy and Technology. 2021; 14(9):4808-4. doi: 10.52711/0974-360X.2021.00836 Available on: https://rjptonline.org/AbstractView.aspx?PID=2021-14-9-50
1. World Health Organization (WHO). Coronavirus disease (COVID-19). https://www.who.int/emergencies/diseases/novel-coronavirus-2019. Accessed October 20, 2020.
2. Mor S, Saini P, Wangnoo SK, Bawa T. Worldwide spread of COVID-19 Pandemic and risk factors among Co-morbid conditions especially Diabetes Mellitus in India. Res J Pharm Technol. 2020; 13(5): 25-30.
3. Ahmad S, Shoaib A, Ali MS, et al. Epidemiology, risk, myths, pharmacotherapeutic management and socioeconomic burden due to novel COVID-19: A recent update. Res J Pharm Technol. 2020; 13(9): 4435-4442.
4. World Health Organization (WHO). WHO Coronavirus Disease (COVID-19) Dashboard | WHO Coronavirus Disease (COVID-19) Dashboard. https://covid19.who.int/. Accessed October 20, 2020.
5. World Health Organization (WHO). Country and Technical Guidance - Coronavirus disease (COVID-19). https://www.who.int/emergencies/diseases/novel-coronavirus-2019/technical-guidance. Accessed October 20, 2020.
6. Aguiar ERGR, Navas J, Pacheco LGC. The COVID-19 Diagnostic Technology Landscape: Efficient Data Sharing Drives Diagnostic Development. Front Public Heal. 2020; 8: 309.
7. Rathore I. Swine Flu (H1N1 Influenza A): A Recent Pandemic and Future Threat. Asian J Nurs Educ Res. 2017; 7(2): 239-242.
8. Deepa R. Education on Prevention of Swine Flu among Early Adults in Sri Ramakrishna Arts and Science College, Coimbatore. Asian J Nur Edu Res. 1(1): 01-02.
9. Pradhan R. Effect of Leaflets on Knowledge Regarding Prevention and Management of Swine Flu among staff nurses working in selected Hospital, Bhubaneswar, Odisha. Asian J Nurs Educ Res. 2017; 7(4): 502-504.
10. Pandurangan H. Middle East Respiratory Syndrome (MERS) a Threat to Asian Countries. Asian J Nurs Educ Res. 2018; 8(3): 375-378.
11. Ross AGP, Crowe SM, Tyndall MW, Petersen E. Planning for the Next Global Pandemic. Int J Infect Dis. 2015; 38: 89-94.
12. Amisha, Malik P, Pathania M, Rathaur V. Overview of artificial intelligence in medicine. J Fam Med Prim Care. 2019; 8(7): 23-28.
13. Malik M, Camm AJ, Huikuri H, et al. Electronic gadgets and their health-related claims. Int J Cardiol. 2018; 258: 163-164.
14. Xu M, Wang D, Wang H, et al. COVID‐19 diagnostic testing: Technology perspective. Clin Transl Med. 2020; 10(4): e158.
15. Amanat F, Stadlbauer D, Strohmeier S, et al. A serological assay to detect SARS-CoV-2 seroconversion in humans. Nat Med. 2020; 26(7): 1033-1036.
16. Kumar A, Gupta PK, Srivastava A. A review of modern technologies for tackling COVID-19 pandemic. Diabetes Metab Syndr Clin Res Rev. 2020; 14(4): 569-573.
17. Carter C, Notter J. COVID-19 disease: a critical care perspective. Clin Integr Care. 2020; 1: 100003.
18. Sorbello M, El-Boghdadly K, Di Giacinto I, et al. The Italian coronavirus disease 2019 outbreak: recommendations from clinical practice. Anaesthesia. 2020; 75(6): 724-732.
19. World Health Organization (WHO). Contact tracing in the context of COVID-19- Interim guide. https://www.who.int/publications/ i/item/contact-tracing-in-the-context-of-covid-19. Published 2020. Accessed October 18, 2020.
20. Aminnejad R, Alikhani R. Physical distancing or social distancing: that is the question. Can J Anesth. 2020; 67(10): 1457-1458.
21. Wei L, Lin J, Duan X, et al. Asymptomatic COVID-19 Patients Can Contaminate Their Surroundings: an Environment Sampling Study. mSphere. 2020; 5(3): e00442-20.
22. NCDCP US. Guidance Documents | CDC. https://www.cdc.gov/coronavirus/2019-ncov/communication/guidance-list.html?Sort=Date%3A%3Adesc. Accessed October 20, 2020.
23. Ting DSW, Carin L, Dzau V, Wong TY. Digital technology and COVID-19. Nat Med. 2020; 26(4): 459-461.
24. Conforti C, Dianzani C, Agozzino M, et al. Cutaneous manifestations in confirmed covid-19 patients: A systematic review. Biology (Basel). 2020; 9(12): 1-28.
25. Ruszkiewicz DM, Sanders D, O’Brien R, et al. Diagnosis of COVID-19 by analysis of breath with gas chromatography-ion mobility spectrometry - a feasibility study. E Clinical Medicine. 2020; 29-30: 100609.
26. Faezipour M, Abuzneid A. Smartphone-based self-testing of COVID-19 using breathing sounds. Telemed e-Health. 2020; 26(10): 1202-1205.
27. Chen L, Liu W, Zhang Q, et al. RNA based mNGS approach identifies a novel human coronavirus from two individual pneumonia cases in 2019 Wuhan outbreak. Emerg Microbes Infect. 2020; 9(1): 313-319.
28. Lan L, Xu D, Ye G, et al. Positive RT-PCR Test Results in Patients Recovered from COVID-19. JAMA - J Am Med Assoc. 2020; 323(15): 1502-1503.
29. Jiang M, Pan W, Arasthfer A, et al. Development and Validation of a Rapid, Single-Step Reverse Transcriptase Loop-Mediated Isothermal Amplification (RT-LAMP) System Potentially to Be Used for Reliable and High-Throughput Screening of COVID-19. Front Cell Infect Microbiol. 2020; 10: article 331.
30. Crook D. Evaluation of antibody testing for SARS-CoV-2 using ELISA and lateral flow immunoassays.
31. Xu X, Jiang X, Ma C, et al. Deep Learning System to Screen Coronavirus Disease 2019 Pneumonia. Appl Intell. 2020; 2019:1-5. http://arxiv.org/abs/2002.09334. Accessed October 18, 2020.
32. Li L, Qin L, Xu Z, et al. Using Artificial Intelligence to Detect COVID-19 and Community-acquired Pneumonia Based on Pulmonary CT: Evaluation of the Diagnostic Accuracy. Radiology. 2020; 296(2): E65-E71.
33. Raiju P, Gireesh GR, Sachina BT et al. Effectiveness of Structured Teaching Programme on Knowledge regarding modes of Mechanical Ventilator among Staff Nurses at a selected Hospital, Bangalore. Asian J Nurs Educ Res. 2015; 5(1): 98-104.
34. Cattel F, Giordano S, Bertiond C, et al. Ozone therapy in COVID-19: A narrative review. Virus Res. 2021; 291: 198-207.
35. Guzik TJ, Mohiddin SA, Dimarco A, et al. COVID-19 and the cardiovascular system: implications for risk assessment, diagnosis, and treatment options. Cardiovasc Res. 2020; 116(10): 1666-1687.
36. Lee Y, Raviglione MC, Flahault A. Use of digital technology to enhance tuberculosis control: Scoping review. J Med Internet Res. 2020; 22(2): e15727.
37. Patidar K. A Study to Assess the Effectiveness of Self Instructional Module on Knowledge Regarding Prevention of Acute Respiratory Tract Infection Among the Mother of Under Five Year Children in Bhandu Village, Mehsana District. Asian J Nurs Educ Res. 2018; 8(1): 5-6.
38. Elavally S, Usha S, Ramya S. Effect of a Dash Board Teaching Programme on Venous Thromboembolism (VTE) Risk Assessment Compliance among Primary Care Nurses in an Urban Tertiary Care Hospital. Asian J Nurs Educ Res. 2015; 5(4): 492-494.
39. Waller R, Hodge S, Holford J, et al. Lifelong education, social inequality and the COVID-19 health pandemic. Int J Lifelong Educ. 2020; 39(3): 243-246.
40. Mirchandani P. Health Care Supply Chains: COVID-19 Challenges and Pressing Actions. Ann Intern Med. 2020; 173(4): 300-301.
41. Ventrella E. Privacy in emergency circumstances: data protection and the COVID-19 pandemic. ERA Forum. September 2020:21: 379–393.
42. Galvão J. COVID-19: the deadly threat of misinformation. Lancet Infect Dis. 2020; S1473-3099(20)30721-0.