Statistical and mathematical method to monitor COVID-19 status in relation to the peak of the epidemic
Keywords:
data analysis, coronavirus, COVID-19, statistical and numerical data, statistical graphs, mathematics, decision makingAbstract
Introduction: several models have tried to predict and evaluate the current status of the pandemic that the new coronavirus, labeled SARVS-CoV2, has caused. This evaluation would be the basis for decision making. Therefore, the importance of monitoring the COVID-19 status in a selected period of time is very important for the process of information management, which can be done through statistical and mathematical methods in order to make big decisions to control the epidemic.
Objective: to propose a mathematical and statistical method to monitor COVID-19 status in contrast to the peak of the epidemic in a selected period of time.
Method: several theoretical methods were used, specially: analysis, synthesis, abstract; and other purely mathematical methods.
Results: as a result of the practical application of the methods used, valid and reliable information was generated in charts, supporting an effective process of decision making
Conclusions: this proposal shows the robustness of its theoretical aspects and a practical effectiveness that, even if elaborated to submit Cuban-generated national data, it could be used in other countries, and even in a provincial or municipal level.
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2. Camacho A, Kucharski A, Aki-Sawyerr Y, White MA, Flasche S, Baguelin M, Pollington T, Carney JR, Glover R, Smout E, Tiffany A, Edmunds WJ, Funk S. Temporal Changes in Ebola Transmission in Sierra Leone and Implications for Control Requirements: A Real-time Modelling Study. PLoS Curr [en línea]. 2015 Feb. [citado 11 Ago 2020]. Disponible en: http://currents.plos.org/outbreaks/index.html%3Fp=55052.html
3. Jaramillo O. Pertinencia del perfil de los profesionales de la información con las demandas del mercado laboral. Rev Int Bibliotecol [en línea]. 2015 [citado 11 Ago 2020]; 38(2):111-120. Disponible en: http://www.scielo.org.co/pdf/rib/v38n2/v38n2a3.pdf
4. Rivera Z, León M, García T. El mercado laboral para el profesional de la información en Cuba: ¿qué piensan los empleadores al respecto? Alcance: Rev Cubana Inf Comun [en línea]. 2017 [citado 11 Ago 2020]; 7(15):6-27. Disponible en: http://scielo.sld.cu/pdf/ralc/v7n15/ralc02118.pdf
5. Dorta-Contreras AJ. Criticar la ciencia y ciencia de la crítica. Rev Hab Cienc Méd [en línea]. 2007 Nov [citado 11 Ago 2020]; 6(4):[aprox. 5 p.] Disponible en: http://scielo.sld.cu/pdf/rhcm/v6n4/rhcm01407.pdf
6. Holton G. On the Integrity of Science: The Issues Since Bronowski. Leonardo [en línea]. 1985 [citado 11 Ago 2020]; 18(4):229-232. Disponible en: https://www.jstor.org/stable/1578071?seq=1
7. Singhal A, Singh P, Lall B, Joshi SD. Modeling and prediction of COVID-19 pandemic using Gaussian mixture model. Chaos Solitons Fractals [en línea]. 2020 [citado 11 Ago 2020]; 138:110023. DOI: https://doi.org/10.1016/j.chaos.2020.110023
8. Chaolin Huang YW, Xingwang Li, Lili Ren, Jianping Zhao, Yi Hu, Li Zhang, Guohui Fan JX, et al. Clinical features of patients infected with 2019 novel coronavirus in wuhan, china. Lancet [en línea]. 2020 [citado 11 Ago 2020]; 395(10223):497-506. DOI: https://doi.org/10.1016/S0140-6736(20)30183-5
9. Cooper BS, PitmanR, Edmunds WJ, Gay NJ. Delaying the international spread of pandemic influenza. PLoS Med [en línea]. 2006 [citado 11 Ago 2020]; 3(e212). DOI: https://doi.org/10.1371/journal.pmed.0030212
10.Covid19-Dashboard Cuba. Covid19CubaData 2019. [citado 15 Sep 2020]. Disponible en: https://covid19cubadata.github.io/#cuba