Early Outbreak Detection for Proactive Crisis Management Using Twitter Data: COVID-19 a Case Study in the US

• URL: http://arxiv.org/abs/2005.00475v1
• Date: Fri, 1 May 2020 16:27:50 GMT
• Title: Early Outbreak Detection for Proactive Crisis Management Using Twitter Data: COVID-19 a Case Study in the US
• Authors: Erfaneh Gharavi, Neda Nazemi, Faraz Dadgostari
• Abstract summary: During a disease outbreak, timely non-medical interventions are critical in preventing the disease from growing into an epidemic and ultimately a pandemic. This work collects Twitter posts surrounding the 2020 COVID-19 pandemic expressing the most common symptoms of COVID-19 including cough and fever, geolocated to the United States.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: During a disease outbreak, timely non-medical interventions are critical in preventing the disease from growing into an epidemic and ultimately a pandemic. However, taking quick measures requires the capability to detect the early warning signs of the outbreak. This work collects Twitter posts surrounding the 2020 COVID-19 pandemic expressing the most common symptoms of COVID-19 including cough and fever, geolocated to the United States. Through examining the variation in Twitter activities at the state level, we observed a temporal lag between the rises in the number of symptom reporting tweets and officially reported positive cases which varies between 5 to 19 days.

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