Statistics and Analysis of Covid-19 in Ecuador Using Microsoft Power BI

Main Article Content

Atal Kumar Vivas Paspuel
David Alfredo Vivas Paspuel

Abstract

Given the emergency that Ecuador and the world are going through due to Covid-19, the rapid description and effective analysis of the different variables that explain the evolution of a contagious disease becomes essential. The purpose of this work is to show the versatility that Microsoft Power BI as a business intelligence tool has to describe and analyze the information issued by official health entities that allow generating rapid knowledge and analysis of the data so that it can be taken correct decisions regarding pandemic control. For this, the official information provided by the Ministry of Public Health of Ecuador (MSP) and other news portals was collected. This information was processed and analyzed using the Power BI platform and R software. Analysis of recent data on Covid-19 shows that the disease is still spreading in some localities of the country. The proposal would be to give more and better access to open data and innovate by adding business intelligence to control this pandemic.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

Article Details

How to Cite
Vivas Paspuel, A. K., & Vivas Paspuel, D. A. . (2021). Statistics and Analysis of Covid-19 in Ecuador Using Microsoft Power BI. INGENIO, 4(1), 27–39. https://doi.org/10.29166/ingenio.v4i1.3068
Section
Artículos
Author Biographies

Atal Kumar Vivas Paspuel, Universidad de las Fuerzas Armadas ESPE

Departamento de Ciencias Exactas

David Alfredo Vivas Paspuel, Universidad San Francisco de Quito

Facultad de Ingeniería

References

MSP, “Ministerio de Salud Pública,” Actualización de casos de coronavirus, 2020. https://www.salud.gob.ec/actualizacion-de-casos-de-coronavirus-en-ecuador/ (accessed Aug. 06, 2020).

G. Quiroz, “La letalidad por el covid-19 de Ecuador es la más alta de Sudamérica | El Comercio,” 2020. https://www.elcomercio.com/actualidad/peru-chile-brasil-covid-19.html (accessed Nov. 26, 2020).

M. Benítez, C. Velasco, A. Sequeira, J. Henríquez, F. Menezes, and F. Paolucci, “Responses to COVID-19 in five Latin American countries,” Heal. Policy Technol., vol. 9, no. January, pp. 525–559, 2020, [Online]. Available: https://doi.org/10.1016/j.hlpt.2020.08.014.

G. M. Sechi et al., “Business intelligence applied to emergency medical services in the lombardy region during sars-COV-2 epidemic,” Acta Biomed., vol. 91, no. 2, pp. 39–44, 2020, doi: 10.23750/abm.v91i2.9557.

L. Loewen and A. Roudsari, “Evidence for Busines Intelligence in Health Care: A Literature Review,” Stud. Health Technol. Inform., vol. 235, no. January, pp. 579–583, 2017, doi: 10.3233/978-1-61499-753-5-579.

Primicias, “Primicias. El periodismo comprometido. Noticias, política, economía, sociedad,” 2020. https://www.primicias.ec/ (accessed Jun. 23, 2020).

B. Powell, Creating Business Intelligence Solutions of Analytical Models, Reports and Dashboards. Birmingham: Packt Publishing Ltd., 2017.

N. Pearce, J. Vandenbroucke, T. VandenWeele, and S. Greenland, “Accurate Statistics on COVID-19 Are Essential for Policy Guidance and Decisions,” Am. J. Public Health, vol. 110, no. 7, pp. 964–966, 2020, doi: 10.2105/AJPH.2020.305708.

C. Webb, Power Query for Power BI and Excel. New York: Apress, 2014.

Microsoft, “Data Visualization | Microsoft Power BI,” 2020. https://powerbi.microsoft.com/en-us/ (accessed Nov. 27, 2020).

A. Ferrari and M. Russo, Analyzing Data with Power BI and Power Pivot for Excel, 1st ed. USA: Microsoft Press, 2017.

F. Brauer, C. Castillo-Chavez, and Z. Feng, Mathematical Models in Epidemiology. 2019.

J. Mazurek, Z. Neničková, J. Mazurek, and Z. Nenickova, “Predicting the number of total COVID-19 cases and deaths in the USA by the Gompertz curve.” Accessed: Jun. 23, 2020. [Online]. Available: https://www.researchgate.net/publication/340809381.

J. Stewart, Single Variable Calculus, 8th ed. Boston , 2012.

N. R. Draper and H. Smith, Applied Regression Analysis, vol. 87, no. 10. Wiley, 1998.

E. Arnhold, “easynls: Easy Nonlinear Model,” R Packag. version 5.0, pp. 1–9, 2017. Available: https://cran.r-project.org/package=easynls.

R. Villaseñor, J. Jurado, and D. Salas, “Solución de la ecuación diferencial de crecimiento en peso, de Von Bertalanffy (1938), por dos métodos distintos,” An. DEL Inst. CIENCIAS DEL MAR Y Limnol., vol. 19, 1993, Accessed: Mar. 14, 2021.

Reuters, “Más de 289.000 personas han perdido sus empleos durante pandemia,” 2020. https://www.primicias.ec/noticias/economia/despidos-registro-pandemia-empleo-ecuador/ (accessed Nov. 27, 2020).

E. Farach and A. Romero, “Escenarios estadísticos del COVID-19 en Honduras: análisis desde la inteligencia de negocios y la transparencia de datos,” Innovare Rev. Cienc. y Tecnol., vol. 9, no. 2, pp. 89–96, 2020, doi: 10.5377/innovare.v9i2.10193.

Johns Hopkins, “COVID-19 Map - Johns Hopkins Coronavirus Resource Center,” 2020. https://coronavirus.jhu.edu/map.html (accessed Nov. 27, 2020).

P. Sánchez-Villegas and A. Daponte Codina, “Predictive models of the COVID-19 epidemic in Spain with Gompertz curves,” Gac. Sanit., May 2020, doi: 10.1016/j.gaceta.2020.05.005.

V. Arias and M. Alberto, “Estimación de población contagiada por Covid-19 usando regresión Logística generalizada y heurísticas de optimización,” Apr. 2020. Accessed: Jun. 23, 2020. [Online]. Available: http://www.kerwa.ucr.ac.cr/handle/10669/80859.