Time based Meticulous analysis of pandemic spreading ratio using Simpy framework
DOI:
https://doi.org/10.12928/commicast.v5i1.10044Keywords:
Pandemic , Infections , Covid-19 , Extraordinary , Plausible , SimpyAbstract
Due to the unavoidable spread of COVID-19 and even taking all substantial measures, the ratio of infected people and death rate seems to be out of control. In this increasingly worsening situation, the aim of this article is that it is important to take extraordinary measures to deal with this exceptional pandemic situation, and this is only possible if the actual ratio of the spread of the pandemic is known. Therefore, ingenious pandemic models are being developed to produce real-time infection statistics on an hourly, weekly, and monthly basis. This clever model leverages well-known data sets and when they will be applied to determine the status of three types of infections: the number of infected people, the time the pandemic started, and the time it ended. The time-based results are generated by conduction simulation in the Simpy Python framework, and the resulting results are characteristic of the real-time infection spread ratio. This shows when extraordinary measures for the infection ratio are necessary and when they become reasonable.
References
Abad, M., Casas-Roma, J., & Prados, F. (2024). Generalizable disease detection using model ensemble on chest X-ray images. Scientific Reports, 14(1). https://doi.org/10.1038/s41598-024-56171-6
Abotsi, K. S. (2011). A software product line-based self-healing strategy for web-based applications. In ACM International Conference Proceeding Series. https://doi.org/10.1145/2019136.2019171
Allahham, M. S., Khattab, T., & Mohamed, A. (2020). Deep Learning for RF-Based Drone Detection and Identification: A Multi-Channel 1-D Convolutional Neural Networks Approach. 2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies, ICIoT 2020, 112–117. https://doi.org/10.1109/ICIoT48696.2020.9089657
Ashraf, S., Ahmad, A., Yahya, A., & Ahmed, T. (2020). Underwater routing protocols: Analysis of link selection challenges. AIMS Electronics and Electrical Engineering, 4(3), 234–248. https://doi.org/10.3934/ElectrEng.2020.3.234
Ashraf, S., & Ahmed, T. (2020). Sagacious Intrusion Detection Strategy in Sensor Network. 2020 International Conference on UK-China Emerging Technologies, UCET 2020. https://doi.org/10.1109/UCET51115.2020.9205412
Ashraf, S., Gao, M., Chen, Z., Ahmed, T., Raza, A., & Naeem, H. (2021). Erratum: USPF: Underwater Shrewd Packet Flooding Mechanism through Surrogate Holding Time (Wireless Communications and Mobile Computing (2020) 2020 (9625974) DOI: 10.1155/2020/9625974). Wireless Communications and Mobile Computing, 2021. https://doi.org/10.1155/2021/9693787
Ashraf, S., Gao, M., Mingchen, Z., Ahmed, T., Raza, A., & Naeem, H. (2020). USPF: Underwater Shrewd Packet Flooding Mechanism through Surrogate Holding Time. Wireless Communications and Mobile Computing, 2020. https://doi.org/10.1155/2020/9625974
Ashraf, S., Raza, A., Aslam, Z., Naeem, H., & Ahmed, T. (2020). Underwater resurrection routing synergy using astucious energy pods. Journal of Robotics and Control (JRC), 1(5), 173–184. https://doi.org/10.18196/jrc.1535
Ashraf, S., Saleem, S., Ahmed, T., & Arfeen, Z. A. (2022). Succulent link selection strategy for underwater sensor network. International Journal of Computing Science and Mathematics, 15(3), 224–242. https://doi.org/10.1504/IJCSM.2022.10049407
Ashraf, S., Saleem, S., Ahmed, T., Aslam, Z., & Shuaeeb, M. (2020). Iris and Foot based Sustainable Biometric Identification Approach. 2020 28th International Conference on Software, Telecommunications and Computer Networks, SoftCOM 2020. https://doi.org/10.23919/SoftCOM50211.2020.9238333
Aslam, N., Rehman, S. U., Khan, I. U., & Khan, M. A. (2020). Exploring the Development and Progression of 5G: A Bibliometric Analysis of Scholarly Production. Library Philosophy and Practice, 2020.
Ballesteros-Aguayo, L., del Olmo, F. J. R., & Gutiérrez-Lozano, J. F. (2022). Journalistic ethics and persuasive communication in the face of post-truth: credibility in the face of the challenges of Social Networks. Observatorio, 16(3). https://doi.org/10.15847/obsOBS16320222159
Ban, T. (2017). Optimization strategies based on algorithm for queue scheduling model and applications of web frontend performance. In Proceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS (Vol. 2017, pp. 328–331). https://doi.org/10.1109/ICSESS.2017.8342925
Berg, J., Tymoczko, J., & Stryer, L. (2002). Biochemistry, 5th edition. In Biochemistry.
Chen, Y.-C., Lu, P.-E., Chang, C.-S., & Liu, T.-H. (2020). A Time-Dependent SIR Model for COVID-19 with Undetectable Infected Persons. IEEE Transactions on Network Science and Engineering, 7(4), 3279–3294. https://doi.org/10.1109/TNSE.2020.3024723
Cornellia, A. H., Putra, H. S. A., Priyambodo, T. K., & Widyaningsih, Y. A. (2017). Social media based proposed model for museum marketing strategy in Yogyakarta. Advanced Science Letters, 23(11). https://doi.org/10.1166/asl.2017.10119
Dash, P. K., Hota, L., Panda, M., Jhanjhi, N. Z., Sahoo, K. S., & Masud, M. (2023). FSE2R: An Improved Collision-Avoidance-based Energy Efficient Route Selection Protocol in USN. Computer Systems Science and Engineering, 44(3), 2225–2242. https://doi.org/10.32604/csse.2023.024836
Fan, Q., Li, Q., Chen, Y., & Tang, J. (2024). Modeling COVID-19 spread using multi-agent simulation with small-world network approach. BMC Public Health, 24(1). https://doi.org/10.1186/s12889-024-18157-x
Formann, S., Hahn, A., Janke, L., Stinner, W., Sträuber, H., Logroño, W., & Nikolausz, M. (2020). Beyond Sugar and Ethanol Production: Value Generation Opportunities Through Sugarcane Residues. Frontiers in Energy Research, 8. https://doi.org/10.3389/fenrg.2020.579577
Gu, Z. (2005). Research on paging strategy of web application. Jisuanji Gongcheng/Computer Engineering, 31(21), 60–62. https://api.elsevier.com/content/abstract/scopus_id/28244432799
Haider, S. A., Ashraf, S., Larik, R. M., Husain, N., Muqeet, H. A., Humayun, U., Yahya, A., Arfeen, Z. A., & Khan, M. F. (2023). An Improved Multimodal Biometric Identification System Employing Score-Level Fuzzification of Finger Texture and Finger Vein Biometrics. Sensors, 23(24). https://doi.org/10.3390/s23249706
Harmon, M. (2022). The Facility Infection Risk EstimatorTM: A web application tool for comparing indoor risk mitigation strategies by estimating airborne transmission risk. Indoor and Built Environment, 31(5), 1339–1362. https://doi.org/10.1177/1420326X211039544
Jiang, H., Gu, Z., Liu, H., Huang, J., Wang, Z., Xiong, Y., Tong, Y., Yin, J., Jiang, F., Chen, Y., Jiang, Q., & Zhou, Y. (2024). Evaluation of phase-adjusted interventions for COVID-19 using an improved SEIR model. Epidemiology and Infection, 152. https://doi.org/10.1017/S0950268823001796
Khan, M. A., Dharejo, F. A., Deeba, F., Ashraf, S., Kim, J., & Kim, H. (2021). Toward developing tangling noise removal and blind inpainting mechanism based on total variation in image processing. Electronics Letters, 57(11), 436–438. https://doi.org/10.1049/ell2.12148
Kong, X., Wang, K., Wang, S., Wang, X., Jiang, X., Guo, Y., Shen, G., Chen, X., & Ni, Q. (2021). Real-Time Mask Identification for COVID-19: An Edge-Computing-Based Deep Learning Framework. IEEE Internet of Things Journal, 8(21), 15929–15938. https://doi.org/10.1109/JIOT.2021.3051844
Lepeley, M. T., Morales, O., Essens, P., Beutell, N. J., & Majluf, N. (2021). Human centered organizational culture: Global dimensions. In Human Centered Organizational Culture: Global Dimensions. https://doi.org/10.4324/9781003092025
Manohara, G., & Kumbinarasaiah, S. (2024). Numerical approximation of fractional SEIR epidemic model of measles and smoking model by using Fibonacci wavelets operational matrix approach. Mathematics and Computers in Simulation, 221, 358–396. https://doi.org/10.1016/j.matcom.2024.02.021
Mello, I. F., Squillante, L., Gomes, G. O., Seridonio, A. C., & de Souza, M. (2021). Epidemics, the Ising-model and percolation theory: A comprehensive review focused on Covid-19. Physica A: Statistical Mechanics and Its Applications, 573, 125963. https://doi.org/10.1016/j.physa.2021.125963
Moudon, A. V. (2013). Characterizing the food environment: Pitfalls and future directions. Public Health Nutrition, 16(7), 1238–1243. https://doi.org/10.1017/S1368980013000773
Obaid, H. M., Ashraf, S., Asgher Nadeem, M., Shahid, H., Akram, A., & Zafrullah, M. (2024). Performance analysis of a hybrid optical amplifier based 480-Gbps DWDM-FSO system under the effect of different atmospheric conditions. Frontiers in Computer Science, 6. https://doi.org/10.3389/fcomp.2024.1348024
Prakash, K., & Sathya, S. (2023). A Deep Learning-based Multi-Path Routing Protocol for Improving Security using Encryption in Underwater Wireless Sensor Networks. 2023 4th International Conference on Electronics and Sustainable Communication Systems, ICESC 2023 - Proceedings, 581–588. https://doi.org/10.1109/ICESC57686.2023.10193733
Rahmatizadeh, S., Valizadeh-Haghi, S., & Dabbagh, A. (2020). The role of artificial intelligence in management of critical COVID-19 patients. Journal of Cellular and Molecular Anesthesia, 5(1), 16–22. https://doi.org/10.22037/jcma.v5i1.29752
Rasheed, Z., Ashraf, S., Ibupoto, N. A., Butt, P. K., & Sadiq, E. H. (2022). SDS: Scrumptious Dataflow Strategy for IoT Devices in Heterogeneous Network Environment. Smart Cities, 5(3), 1115–1128. https://doi.org/10.3390/smartcities5030056
Siddiki, S. Y. A., Uddin, M. N., Mofijur, M., Fattah, I. M. R., Ong, H. C., Lam, S. S., Kumar, P. S., & Ahmed, S. F. (2021). Theoretical calculation of biogas production and greenhouse gas emission reduction potential of livestock, poultry and slaughterhouse waste in Bangladesh. Journal of Environmental Chemical Engineering, 9(3). https://doi.org/10.1016/j.jece.2021.105204
Tenorio, M. (2018). Céos: A collaborative web-based application for improving teaching-learning strategies. In Advances in Intelligent Systems and Computing (Vol. 725, pp. 107–114). https://doi.org/10.1007/978-3-319-75175-7_12
Wang, L., Lin, Z. Q., & Wong, A. (2020). COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images. Scientific Reports, 10(1). https://doi.org/10.1038/s41598-020-76550-z
Wang, T. (2008). The research of interactive new media on the application of product customization web interface design strategy - take der-horng art frame interactive online system for example. In Proceedings of the 2008 International Conference on Advances in Computer Entertainment Technology, ACE 2008 (p. 428). https://doi.org/10.1145/1501750.1501878
Wang, Y., Qing, F., Li, H., & Wang, X. (2024). Timely and effective media coverage’s role in the spread of Corona Virus Disease 2019. Mathematical Methods in the Applied Sciences, 47(5), 3490–3506. https://doi.org/10.1002/mma.8732
Woods, D. W., & Böhme, R. (2022). The commodification of consent. Computers and Security, 115. https://doi.org/10.1016/j.cose.2022.102605
Zuhair, M. Z., Ashraf, S., Iqbal, M., Rizvi, S. Z. R., Khokhar, A., & Nadeem, M. A. N. (2023). Broaching Uncouth Water Level Snag In Underground Agriculture Field Through Wireless Sensors. Suranaree Journal of Science and Technology, 30(4), 010248(1-16). https://doi.org/10.55766/sujst-2023-04-e0855
Zulfa, M. I. (2020). Caching strategy for Web application – a systematic literature review. In International Journal of Web Information Systems (Vol. 16, Issue 5, pp. 545–569). https://doi.org/10.1108/IJWIS-06-2020-0032
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