COVID-19'a Karşı Sosyal Mesafenin Kanıt İncelemesi

Year 2022, Volume: 5 Issue: 3, 76 - 83, 05.09.2022

Zeynep Güngörmüş , Burcu Çakı

https://doi.org/10.53493/avrasyasbd.1090592

Cited By: 1

Abstract

Hayatımızın her alanını etkileyen COVID-19 pandemisinin kontrol altına alınmasında, sosyal mesafe genel olarak vurgulanmaktadır. COVID-19’un iyice yaygınlaştığı bu süreçte özellikle kapalı alanlarda bulaşı engellemek için toplumun sosyal mesafe ile ilgili bilimsel bilgi düzeyinde hızlı bir artış sağlanmaktadır. Bu derlemede, sosyal mesafe uygulaması ile ilgili literatürü sentezleyerek, sosyal mesafenin önemli olduğu birçok alanı bilgilendirmek için analitik bir çerçeve geliştirilmiştir. Bu alanlar: nüfus etkisi, iletim özellikleri, kaynak kontrolü ve KKD (duyarlı kişilerin sosyal mesafe uygulaması)’dir. COVID-19'un birincil bulaşma yolu solunum yolu partikülleridir ve bulaşın presemptomatik, pausisemptomatik ve asemptomatik bireylerden kaynaklandığı bilinmektedir. Etkili iyileştirici ajanların yokluğu ve virüse karşı bağışıklama eksikliği nedeniyle, nüfusun savunmasızlığı artar. Bu durum göz önüne alındığında, mevcut maske kullanımı, hijyen ve temas izleme stratejileri ile bağlantılı olarak, kaynak kontrolünün etkili bir biçimi olarak sosyal mesafe uygulamasının benimsenmesi önerilmektedir. Hastalığın yayılımını azaltmada, “fiziksel mesafe ve diğer önlemler yoluyla enfekte kişilerin temaslarını sınırlamak ve temas başına bulaşma olasılığını azaltmak” olmak üzere iki unsur önem taşımaktadır. Kanıtlar, sosyal mesafenin hem laboratuvar hem de klinik bağlamlarda enfekte solunum partiküllerinin bulaşmasını azaltarak temas başına bulaşabilirliği azalttığını göstermektedir. Bireylerin sosyal mesafeye uyumunun yüksek olması, virüsün yayılımını azaltmada en etkili yoldur. Bu derleme, COVID-19 salgınını azaltmak ve önlemek için gerekli olan bireysel ve kamusal düzenlemelerde sosyal mesafenin potansiyel faydaları ve risklerine yönelik kanıtların bir incelemesidir.

Keywords

Hemşirelik, İzolasyon, Kanıt, SARS-CoV-2, Sosyal

Supporting Institution

Yok

Project Number

Yok

Evidence Exploration of the Social Distancing Against COVID-19

Abstract

Social distancing is generally emphasized in controlling the COVID-19 pandemic, which affects every aspect of our lives. In this process, where COVID-19 has become widespread, a rapid increase in the scientific knowledge level of the society about social distancing is provided in order to prevent transmission, especially in closed areas. In the present review study, an analytical framework has been developed to inform many areas where social distancing is important by synthesizing the literature on social distancing. These areas are population impact, transmission characteristics, source control, and PPE (personal protective equipment). The primary mode of transmission of COVID-19 is respiratory particles, and its transmission is known to originate from presymptomatic, paucisymptomatic, and asymptomatic individuals. Due to the absence of effective curative agents and the lack of immunization against the virus, the vulnerability of the population increases. Considering this situation, it is recommended to adopt social distancing as an effective form of source control, in conjunction with existing mask use, hygiene, and contact tracing strategies. In reducing the spread of the disease, two elements are important, those are “limiting contacts of infected persons through physical distancing and other measures, and reducing the possibility of transmission per contact”. Evidence suggests that social distancing reduces transmission per contact by lowering the transmission of infected respiratory particles in both laboratory and clinical contexts. The high compliance of individuals with social distancing is the most effective way to reduce the spread of the virus. The present study is a review of the Evidence fort he potential benefits and risks of social distancing in the individual and public arrangements needed to mitigate and prevent the COVID-19 pandemic.

Keywords

Evidence, Isolation, Nursing, SARS-CoV-2, Social

Project Number

Yok

References

• Bian, S., Zhou, B., Bello, H., & Lukowicz, P. (2020). A wearable magnetic field based proximity sensing system for monitoring COVID-19 social distancing. In Proceedings of the 2020 International Symposium on Wearable Computers, 22-26. https://doi.org/10.1145/3410531.3414313
• Brunetti, A., Buongiorno, D., Trotta, G. F., & Bevilacqua, V. (2018). Computer vision and deep learning techniques for pedestrian detection and tracking: A survey. Neurocomputing, 300, 17-33. https://doi.org/10.1016/j.neucom.2018.01.092
• Gralton, J., Tovey, E., McLaws, M. L., & Rawlinson, W. D. (2011). The role of particle size in aerosolised pathogen transmission: a review. Journal of Infection, 62(1), 1-13. https://doi.org/10.1016/j.jinf.2010.11.010
• Gupta, S.D., Jain, R. & Bhatnagar, S. (2020). COVID-19 pandemic in Rajasthan: Mathematical modelling and social distancing. Journal of health management, 22(2), 129-137. https://doi.org/10.1177/0972063420935537
• Han, M. S., Seong, M. W., Kim, N., Shin, S., Im Cho, S., Park, H., ... & Choi, E. H. (2020). Viral RNA load in mildly symptomatic and asymptomatic children with COVID-19, Seoul, South Korea. Emerging infectious diseases, 26(10), 2497. https://doi.org/10.3201/eid2610.202449
• He, W., Yi, G. Y., & Zhu, Y. (2020). Estimation of the basic reproduction number, average incubation time, asymptomatic infection rate, and case fatality rate for COVID‐19: Meta‐analysis and sensitivity analysis. Journal of medical virology, 92(11), 2543-2550. https://doi.org/10.1002/jmv.26041
• Howard, J., Huang, A., Li, Z., Tufekci, Z., Zdimal, V., van der Westhuizen, H. M., ... & Rimoin, A. W. (2021). An evidence review of face masks against COVID-19. Proceedings of the National Academy of Sciences, 118(4). https://doi.org/10.1073/pnas.2014564118
• Imperial College COVID-19 Response Team Report 9: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand. 2020. https://www.imperial.ac.uk/media/imperial-college/medicine/sph/ide/gida-fellowships/Imperial-College-COVID19-NPI-modelling-16-03-2020.pdf
• Imperial College COVID-19 Response Team Report 13: Estimating the number of infections and the impact of nonpharmaceutical interventions on COVID-19 in 11 European countries. 2020. https://www.imperial.ac.uk/media/imperial-college/medicine/mrc-gida/2020-03-30-COVID19-Report-13.pdf
• Karaman, O., Alhudhaif, A., & Polat, K. (2021). Development of smart camera systems based on artificial intelligence network for social distance detection to fight against COVID-19. Applied Soft Computing, 110, 107610.
• Khandelwal, P., Khandelwal, A., Agarwal, S., Thomas, D., Xavier, N., & Raghuraman, A. (2020). Using computer vision to enhance safety of workforce in manufacturing in a post covid world. arXiv preprint arXiv:2005.05287. https://doi.org/10.48550/arXiv.2005.05287
• Liu, P., Beeler, P.& Chakrabarty, R.K. (2020). Dynamic ınterplay between social distancing duration and intensity in reducing COVID-19 US hospitalizations: A Law of diminishing returns. Chaos 30, 071102. https://doi.org/10.1063/5.0013871
• Marchiori, M. (2020). COVID-19 and the social distancing paradox: Dangers and solutions. arXiv preprint arXiv:2005.12446. https://doi.org/10.48550/arXiv.2005.12446
• Milton, D. K. (2020). A Rosetta Stone for understanding infectious drops and aerosols. Journal of the Pediatric Infectious Diseases Society, 9(4), 413-415. https://doi.org/10.1093/jpids/piaa079
• Prather, K. A., Wang, C. C., & Schooley, R. T. (2020). Reducing transmission of SARS-CoV-2. Science, 368(6498), 1422-1424. https://doi.org/10.1126/science.abc6197
• Punn, N. S., Sonbhadra, S. K., Agarwal, S., & Rai, G. (2020). Monitoring COVID-19 social distancing with person detection and tracking via fine-tuned YOLO v3 and Deepsort techniques. arXiv preprint arXiv:2005.01385. https://doi.org/10.48550/arXiv.2005.01385
• Ramadass, L., Arunachalam, S., & Sagayasree, Z. (2020). Applying deep learning algorithm to maintain social distance in public place through drone technology. International Journal of Pervasive Computing and Communications, 16(3), 223-226. https://doi.org/0.1108/IJPCC-05-2020-0046
• Sathyamoorthy, A. J., Patel, U., Savle, Y. A., Paul, M., & Manocha, D. (2020). COVID-robot: Monitoring social distancing constraints in crowded scenarios. arXiv preprint arXiv:2008.06585. https://doi.org/10.48550/arXiv.2008.06855
• Seres, G., Balleyer, A. H., Cerutti, N., Danilov, A., Friedrichsen, J., Liu, Y., & Süer, M. (2021a). Face masks increase compliance with physical distancing recommendations during the COVID-19 pandemic. Journal of the Economic Science Association, 7(2), 139-158. https://doi.org/10.1007/s40881-021-00108-6
• Seres, G., Balleyer, A., Cerutti, N., Friedrichsen, J., & Süer, M. (2021b). Face mask use and physical distancing before and after mandatory masking: No evidence on risk compensation in public waiting lines. Journal of Economic Behavior & Organization, 192, 765-781. https://doi.org/10.1016/j.jebo.2021.10.032
• Setti, L., Auid-Orcid, Passarini, F., & Auid-Orcid (2020). Airborne transmission route of COVID-19: Why 2 meters/6 feet of inter-personal distance could not be enough, 17 (8), 2932. https://doi.org/10.3390/ijerph17082932
• Sun, C., & Zhai, Z. (2020). The efficacy of social distance and ventilation effectiveness in preventing COVID-19 transmission. Sustainable cities and society, 62, 102390.
• Thu, T. P. B., Ngoc, P. N. H., & Hai, N. M. (2020). Effect of the social distancing measures on the spread of COVID-19 in 10 highly infected countries. Science of the Total Environment, 742, 140430. https://doi.org/10.1016/j.scitotenv.2020.140430
• Venkatesh, A., & Edirappuli, S. (2020). Social distancing in covid-19: what are the mental health implications?. Bmj, 369. https://doi.org/10.1136/bmj.m1379
• Vokó, Z., Pitter, J.G. (2020). The effect of social distance measures on COVID-19 epidemics in Europe: an interrupted time series analysis. GeroScience 42, 1075–1082. https://doi.org/10.1007/s11357-020-00205-0
• Vuorinen, V., Aarnio, M., Alava, M., Alopaeus, V., Atanasova, N., Auvinen, M., ... & Österberg, M. (2020). Modelling aerosol transport and virus exposure with numerical simulations in relation to SARS-CoV-2 transmission by inhalation indoors. Safety Science, 130, 104866. https://doi.org/10.1016/j.ssci.2020.104866
• World Commission. (2005). Ethics of Scientific Knowledge and Technology, The Precautionary Principle (United Nations Educational, Scientific and Cultural Organization).
• World Health Organization. (2014). Infection prevention and control of epidemic-and pandemic-prone acute respiratory infections in health care.
• Wölfel, R., Corman, V. M., Guggemos, W., Seilmaier, M., Zange, S., Müller, M. A., ... & Wendtner, C. (2020). Virological assessment of hospitalized patients with COVID-2019. Nature, 581(7809), 465-469. https://doi.org/10.1038/s41586-020-2196-x
• Wu, Y., Jing, W., Liu, J., Ma, Q., Yuan, J., Wang, Y., ... & Liu, M. (2020). Effects of temperature and humidity on the daily new cases and new deaths of COVID-19 in 166 countries. Science of the Total Environment, 729, 139051. https://doi.org/10.1016/j.scitotenv.2020.139051
• Xie, X., Li, Y., Chwang, A. T., Ho, P. L., & Seto, W. H. (2007). How far droplets can move in indoor environments--revisiting the Wells evaporation-falling curve. Indoor air, 17(3), 211-225. https://doi.org/10.1111/j.1600-0668.2007.00469.x
• Yan, J., Grantham, M., Pantelic, J., De Mesquita, P. J. B., Albert, B., Liu, F., ... & Emit Consortium. (2018). Infectious virus in exhaled breath of symptomatic seasonal influenza cases from a college community. Proceedings of the National Academy of Sciences, 115(5), 1081-1086. https://doi.org/10.1073/pnas.1716561115