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Observational Study
. 2020 Aug 5;30(8):362-370.
doi: 10.2188/jea.JE20200150. Epub 2020 May 30.

Early SNS-Based Monitoring System for the COVID-19 Outbreak in Japan: A Population-Level Observational Study

Affiliations
Observational Study

Early SNS-Based Monitoring System for the COVID-19 Outbreak in Japan: A Population-Level Observational Study

Daisuke Yoneoka et al. J Epidemiol. .

Abstract

Background: The World Health Organization declared the novel coronavirus outbreak (COVID-19) to be a pandemic on March 11, 2020. Large-scale monitoring for capturing the current epidemiological situation of COVID-19 in Japan would improve preparation for and prevention of a massive outbreak.

Methods: A chatbot-based healthcare system named COOPERA (COvid-19: Operation for Personalized Empowerment to Render smart prevention And care seeking) was developed using the LINE app to evaluate the current Japanese epidemiological situation. LINE users could participate in the system either though a QR code page in the prefectures' websites or a banner at the top of the LINE app screen. COOPERA asked participants questions regarding personal information, preventive actions, and non-specific symptoms related to COVID-19 and their duration. We calculated daily cross correlation functions between the reported number of infected cases confirmed using polymerase chain reaction and the symptom-positive group captured by COOPERA.

Results: We analyzed 206,218 participants from three prefectures reported between March 5 and 30, 2020. The mean age of participants was 44.2 (standard deviation, 13.2) years. No symptoms were reported by 96.93% of participants, but there was a significantly positive correlation between the reported number of COVID-19 cases and self-reported fevers, suggesting that massive monitoring of fever might help to estimate the scale of the COVID-19 epidemic in real time.

Conclusions: COOPERA is the first real-time system being used to monitor trends in COVID-19 in Japan and provides useful insights to assist political decisions to tackle the epidemic.

Keywords: COVID-19; Japan; large-scale monitoring system.

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Figures

Figure 1.
Figure 1.. Trend in the proportion of non-specific symptoms in three prefectures. Red line, green line, blue line, and purple line indicate the proportion of participants who have a fever (a), a strong feeling of weariness or shortness of breath (b), both (a) and (b), and either (a) or (b), respectively. Gray bars indicate the reported number of COVID-19-positive cases in three prefectures.
Figure 2.
Figure 2.. Monthly trend in each prefecture (left: Kanagawa, middle: Aichi, right: Shiga). Red line, green line, blue line, and purple line indicate the proportion of participants who have a fever (a), a strong feeling of weariness or shortness of breath (b), both (a) and (b), and either (a) or (b), respectively. Gray bar indicates the reported number of COVID-19-positive cases in each prefecture. Pink bands are the banner periods.
Figure 3.
Figure 3.. The proportion of participants with each non-specific symptom among participants with comorbidities and pregnant. 1. Malignant tumor with anticancer drugs, 2. Malignant tumor without anticancer drugs, 3. Cardiovascular diseases, 4. Kidney diseases, 5. Diabetes mellitus, 6. In dialysis treatment, 7. Chronic obstructive pulmonary disease, 8. Treatment with immunosuppressant, 9. Pregnant.
Figure 4.
Figure 4.. Cross correlation function between the time series of reported number of COVID-19 cases and the shifted time series of the proportion of non-specific symptoms (shifted days between −10 to 10). **P < 0.01, *P < 0.05

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