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Forecasting imported COVID-19 cases in South Korea using mobile roaming data
Soo Beom Choi1,2, Insung Ahn1,2
1Department of Data-centric Problem Solving Research, Korea Institute of Science and Technology Information, Daejeon, Republic of Korea.
Plos One
|November 4, 2020
Summary
A new daily risk score, incorporating COVID-19 cases and mobility data, accurately forecasts imported cases in South Korea 12 days in advance. This tool aids public health by identifying high-risk areas and warning travelers.
Area of Science:
- Epidemiology
- Public Health
- Data Science
Background:
- Rising global COVID-19 cases lead to increased imported infections and ongoing domestic outbreaks.
- Accurate risk assessment for imported coronavirus disease (COVID-19) cases is crucial for effective public health interventions in South Korea.
Purpose of the Study:
- To develop and validate a daily risk score for assessing imported COVID-19 cases in South Korea.
- To forecast future imported COVID-19 cases using predictive models incorporating the daily risk score.
Main Methods:
- Calculated a daily risk score using COVID-19 case data (John Hopkins University), roaming data (Korea Telecom), and the Oxford COVID-19 Government Response Tracker.
- Developed prediction models, including simple linear regression and Autoregressive Integrated Moving Average with eXogenous variables (ARIMAX), to forecast imported COVID-19 cases.
Main Results:
- The daily risk score showed a strong correlation with imported COVID-19 cases after a 12-day lag.
- Linear regression using the risk score achieved a lower root mean squared error (6.2) compared to ARIMA (22.3).
- ARIMAX models incorporating the risk score demonstrated a higher correlation coefficient (0.925) than ARIMA models (0.899).
Conclusions:
- The daily risk score effectively predicts imported COVID-19 cases in South Korea with a 12-day lead time.
- The 12-day lag may reflect delays in observing the impact of government policies on case importation.
- This risk assessment tool can inform public health agencies about potential high-risk areas and alert individuals to their COVID-19 risk status.
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