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Volume 8
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10.3390/healthcare8040453
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Article

Prediction and Potential Spatially Explicit Spread of COVID-19 in Mexico’s Megacity North Periphery

by
Maria de la Luz Hernández-Flores
1,*,
Jair Escobar-Sánchez
1,
Jesús Eduardo Paredes-Zarco
2,
Giorgio Alberto Franyuti Kelly
3 and
Lamán Carranza-Ramírez
1
1
Consejo Ejecutivo del Complejo Científico y Tecnológico Sincrotrón, Boulevard Ciudad del Conocimiento y la Cultura, Manzana 10 Lote 1, Col. Santa Catarina, San Miguel Tornacuxtla, San Agustín Tlaxiaca 42163, Mexico
2
INABISA, Investigación Aplicada para el Bienestar Social y Ambiental, Rio Papagayo #10, Ampliación el Palmar, Pachuca 42088, Mexico
3
Medical IMPACT, Dept. of Infectious Diseases, Gutemberg 51, Verónica Anzures, Miguel Hidalgo Ciudad de Mexico 54050, Mexico
*
Author to whom correspondence should be addressed.
Healthcare 2020, 8(4), 453; https://doi.org/10.3390/healthcare8040453
Submission received: 3 September 2020 / Revised: 12 October 2020 / Accepted: 16 October 2020 / Published: 2 November 2020
(This article belongs to the Special Issue COVID-19 Pandemic: Challenges Facing the Health System)
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Abstract

The novel COVID-19, detected in Wuhan, China, has reached almost every city across the globe, and researchers from many countries have used several epidemiologic models to describe the epidemic trends. In this context, it is also important to know the geographic extent of the infected population. Following this approach, a Gumpertz model was adapted with official data from the state of Hidalgo, Mexico, in order to estimate the people infected during this COVID-19 pandemic. We found, based on the adjusted data, the highest value in infected people according to official and theoretical data. Furthermore, using a geographical analysis based on geostatistical measures related to density of demographic and economic data, traffic level and geolocation, raster files were generated to estimate probability of coronavirus cases occurrence using the areas where the contagion may occur. We also distributed the maximum contagion obtained by the epidemic model, using these raster files, and a regression model to weight factors according their importance. Based on this estimated distribution, we found that most of the infected people were located in the southern border, a trend related to the economic strip in the southern part of Hidalgo State, associated with its vicinity to the Megacity of Mexico.
Keywords: COVID-19; spatial analysis; density metrics; epidemic; modeling COVID-19; spatial analysis; density metrics; epidemic; modeling

Share and Cite

MDPI and ACS Style

Hernández-Flores, M.d.l.L.; Escobar-Sánchez, J.; Paredes-Zarco, J.E.; Franyuti Kelly, G.A.; Carranza-Ramírez, L. Prediction and Potential Spatially Explicit Spread of COVID-19 in Mexico’s Megacity North Periphery. Healthcare 2020, 8, 453. https://doi.org/10.3390/healthcare8040453

AMA Style

Hernández-Flores MdlL, Escobar-Sánchez J, Paredes-Zarco JE, Franyuti Kelly GA, Carranza-Ramírez L. Prediction and Potential Spatially Explicit Spread of COVID-19 in Mexico’s Megacity North Periphery. Healthcare. 2020; 8(4):453. https://doi.org/10.3390/healthcare8040453

Chicago/Turabian Style

Hernández-Flores, Maria de la Luz, Jair Escobar-Sánchez, Jesús Eduardo Paredes-Zarco, Giorgio Alberto Franyuti Kelly, and Lamán Carranza-Ramírez. 2020. "Prediction and Potential Spatially Explicit Spread of COVID-19 in Mexico’s Megacity North Periphery" Healthcare 8, no. 4: 453. https://doi.org/10.3390/healthcare8040453

APA Style

Hernández-Flores, M. d. l. L., Escobar-Sánchez, J., Paredes-Zarco, J. E., Franyuti Kelly, G. A., & Carranza-Ramírez, L. (2020). Prediction and Potential Spatially Explicit Spread of COVID-19 in Mexico’s Megacity North Periphery. Healthcare, 8(4), 453. https://doi.org/10.3390/healthcare8040453

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