DOI QR코드

DOI QR Code

Using Ant Colony Optimization to Find the Best Precautionary Measures Framework for Controlling COVID-19 Pandemic in Saudi Arabia

  • Alshamrani, Raghad (Umm Al-Qura University, Department of Computer Science) ;
  • Alharbi, Manal H. (Umm Al-Qura University, Department of Computer Science)
  • Received : 2022.10.05
  • Published : 2022.10.30

Abstract

In this paper, we study the relationship between infection rates of covid 19 and the precautionary measures and strict protocols taken by Saudi Arabia to combat the spread of the coronavirus disease and minimize the number of infected people. Based on the infection rates and the timetable of precautionary measures, the best framework of precautionary measures was identified by applying the traveling salesman problem (TSP) that relies on ant colony optimization (ACO) algorithms. The proposed algorithm was applied to daily infected cases data in Saudi Arabia during three periods of precautionary measures: partial curfew, whole curfew, and gatherings penalties. The results showed the partial curfew and the whole curfew for some cities have the minimum total cases over other precautionary measures. The gatherings penalties had no real effect in reducing infected cases as the other two precautionary measures. Therefore, in future similar circumstances, we recommend first applying the partial curfew and the whole curfew for some cities, and not considering the gatherings penalties as an effective precautionary measure. We also recommend re-study the application of the grouping penalty, to identify the reasons behind the lack of its effectiveness in reducing the number of infected cases.

Keywords

References

  1. "Naming the coronavirus disease (COVID-19) and the virus that causes it," Feb. 11, 2020. [Online]. Available: https://www.who.int/emergencies/diseases/novel-coronavirus-2019/technical-guidance/naming-the-coronavirus-disease-(covid-2019)-and-the-virus-that-causes-it
  2. D. Cucinotta, M. Vanelli. WHO Declares COVID-19 a Pandemic. Acta Bio Med [Internet]. 2020Mar.19 [cited 2020Aug.28];91(1):157-60. Available from: https://www.mattioli1885journals.com/index.php/actabiomedica/article/view/9397
  3. World Health Organization, 2020, https://covid19.who.int/
  4. CGC, 2020. www.cgc.gov.sa/ Saudi Arabia's ruthless fight against coronavirus.
  5. M. Dorigo, Optimization, Learning and Natural Algorithms, PhD thesis, Politecnico di Milano, Italy, 1992.
  6. Zlochin, Mark; Birattari, Mauro; Meuleau, Nicolas; Dorigo, Marco (1 October 2004). "Model-Based Search for Combinatorial Optimization: A Critical Survey". Annals of Operations Research. 131 (1-4): 373-395. CiteSeerX 10.1.1.3.427. doi:10.1023/B:ANOR.0000039526.52305.af. ISSN 0254-5330. S2CID 63137
  7. Hingrajiya KH, Gupta RK, Chandel GS (2012) An Ant Colony Optimization Algorithm for Solving Traveling Salesman Problem. International Journal of Scientific and Research Publications 2: 1-6.
  8. Dorigo M, Gambardella LM (1997) Ant colonies for the traveling salesman problem. Bio Systems. pp: 73-81.
  9. Dorigo M, Gambardella LM (1997) Ant Colony system - A cooperative learning approach to the Traveling salesman problem. IEEE Transactions on Evolutionary Computation.
  10. G. Alkhaldi, GS. Aljuraiban, S. Alhurishi, R. De Souza, K. Lamahewa, R. Lau, F. Alshaikh. Perceptions towards COVID-19 and adoption of preventive measures among the public in Saudi Arabia: a cross sectional study. BMC Public Health. 2021 Jun 29;21(1):1251. doi: 10.1186/s12889-021-11223-8. PMID: 34187425; PMCID: PMC8240080.
  11. Al-Hanawi MK, Angawi K, Alshareef N, Qattan AMN, Helmy HZ, Abudawood Y, Alqurashi M, Kattan WM, Kadasah NA, Chirwa GC, Alsharqi O. Knowledge, Attitude and Practice Toward COVID-19 Among the Public in the Kingdom of Saudi Arabia: A Cross-Sectional Study. Front Public Health. 2020 May 27;8:217. doi: 10.3389/fpubh.2020.00217. PMID: 32574300; PMCID: PMC7266869
  12. N. Sundaram, C. Bonell, S. Ladhani, SM. Langan, F. Baawuah, I. Okike, S. Ahmad, J. Beckmann, J. Garstang, BE. Brent, AJ. Brent, Z. Amin-Chowdhury, F. Aiano, J. Hargreaves. Implementation of preventive measures to prevent COVID-19: a national study of English primary schools in summer 2020. Health Educ Res. 2021 Jul 12;36(3):272-285. doi: 10.1093/her/cyab016. PMID: 33860299; PMCID: PMC8083280.
  13. R. Ali, A. Ghaleb, S. bokresha. (2021). COVID-19 related knowledge and practice and barriers that hinder adherence to preventive measures among the Egyptian community. An epidemiological study in Upper Egypt. Journal of Public Health Research, 10(1). https://doi.org/10.4081/jphr.2021.1943
  14. L. Liu, D. Zhao, F. Yu, A.A. Heidari, C. Li, J. Ouyang, J. Pan, Ant colony optimization with Cauchy and greedy Levy mutations for multilevel COVID 19 X-ray image segmentation, Comput. Biol. Med. (2021), https://doi.org/10.1016/j. compbiomed.2021.104609, 104609
  15. Z. Liu, Z. Li, W. Chen, Y. Zhao, H. Yue, Z. Wu. Path optimization of medical waste transport routes in the emergent public health event of Covid-19: a hybrid optimization algorithm based on the immune-ant colony algorithm. Int J Environ Res Pub Health. 2020;17(16):5831 https://doi.org/10.3390/ijerph17165831
  16. COVID 19 Dashboard: Saudi Arabia.," July. 31, 2020. [Online Available: [https://covid19.moh.gov.sa/].
  17. Saudi Arabia's Experience in Health Preparedness and Response to COVID-19 Pandemic.," October. 27, 2020. [Online Available: [COVID-19-NATIONAL.pdf (moh.gov.sa)].