TY - CHAP
T1 - Geospatial analysis of COVID-19 distribution and its relation to public transportation services
AU - Saldana-Perez, Magdalena
AU - Garrido-Gutierrez, Víctor
AU - Yáñez-Márquez, Cornelio
AU - Moreno-Ibarra, Marco
AU - Torres-Ruiz, Miguel
N1 - Publisher Copyright:
© 2022 Elsevier Inc. All rights reserved.
PY - 2022/1/1
Y1 - 2022/1/1
N2 - COVID-19 has changed our lifestyle; nowadays, activities such as studying, working, and meetings, among others, have drastically changed from being face to face to being remote; however, there is still an activity that has not changed as quickly as needed because of its main purpose, i.e., transportation. In this approach, a complete COVID-19 geospatial analysis is conducted correlating official reported cases of COVID-19-infected individuals and those who died with the data of public transportation, focusing on specific areas and the subway service in Mexico City. The geospatial analysis allows identifying the importance of some subway stations and their influence on the rate of infected people and also allows visualizing the distribution of COVID-19 all over the geographic areas near the subway stations and understanding the distribution of COVID-19 in the city. Finally, the approach generates a visualization model of the distribution of COVID-19 and its relation to the subway service using geospatial intelligence.
AB - COVID-19 has changed our lifestyle; nowadays, activities such as studying, working, and meetings, among others, have drastically changed from being face to face to being remote; however, there is still an activity that has not changed as quickly as needed because of its main purpose, i.e., transportation. In this approach, a complete COVID-19 geospatial analysis is conducted correlating official reported cases of COVID-19-infected individuals and those who died with the data of public transportation, focusing on specific areas and the subway service in Mexico City. The geospatial analysis allows identifying the importance of some subway stations and their influence on the rate of infected people and also allows visualizing the distribution of COVID-19 all over the geographic areas near the subway stations and understanding the distribution of COVID-19 in the city. Finally, the approach generates a visualization model of the distribution of COVID-19 and its relation to the subway service using geospatial intelligence.
KW - COVID-19
KW - Geospatial analysis
KW - Geospatial intelligence
KW - Public transportation
KW - Spatial distribution
KW - Subway
UR - http://www.scopus.com/inward/record.url?scp=85137514603&partnerID=8YFLogxK
U2 - 10.1016/B978-0-12-821318-6.00006-2
DO - 10.1016/B978-0-12-821318-6.00006-2
M3 - Capítulo
AN - SCOPUS:85137514603
SN - 9780128232101
SP - 201
EP - 216
BT - Digital Innovation for Healthcare in COVID-19 Pandemic
PB - Elsevier
ER -