Medical supply, Coronavirus, Twitter, Big data, Ecuador
Abstract
Historically, the management of medical supplies in Ecuador has represented an obstacle in the timely treatment of diseases due to the insufficiency of these [1]–[4]. This situation worsened in early 2020 due to the coronavirus pandemic. Consequently, people chose to use social networks, such as Twitter, to obtain medicines and medical equipment. For this reason, the present study aims to evaluate the management of medical supplies in Ecuador by citizens, through the social network Twitter using text mining techniques applied to big data, to determine their degree of effectiveness during the pandemic. of the Covid-19 from March 2020 to March 2021. To achieve this, interviews were conducted with doctors to find out the most demanded supplies. From this, web scraping was applied on Twitter to extract publications on the management of inputs. Subsequently, text mining techniques were applied to identify emotions, classify needs and validate the information. Finally, effectiveness indicators were established. The results revealed that March and July 2020 and January 2021 were critical times, especially in provinces such as Guayas, Azuay, Imbabura and Santa Elena being consistent with the information reported by the Emergency Operations Committee (COE) of Ecuador. It is concluded that this study provides information of interest for the formulation of public policies related to the supply of inputs and medical care.
