Early Detection of COVID-19 Epidemic Using Search Engine Query Data (preprint)

Background: Early warnings of emerging infectious disease are crucial to prevent epidemics. However, in the early stage of the COVID-19 pandemic, traditional infectious disease surveillance failed to deliver a warning alert. The aim of this work is to develop search-engine-based surveillance methods for the early warning and prediction of COVID-19 outbreaks. Methods: By using more than 444 million Baidu search queries from China as training set, we collected 32 keywords from the Baidu Search Index that may related to COVID-19 outbreak from 18 December 2019 to 11 February 2020. The Beijing Xinfadi outbreak from 30 May 2020 to 30 July 2020 was used as independent test set. A multiple linear regression was applied to model the relationship between the daily query frequencies of keywords and the daily new cases. Findings: Our results show that 11 keywords in search queries were highly correlated to the daily numbers of confirmed cases (r =0.96, P <0.01). An abnormal initial peak (1.46 times the normal volume) in queries appeared on 31 December 2019, which could have served as an early warning signal for an outbreak. Of particular concern, on this day, the volume of the query “Wuhan Seafood Market” increased by over 240 times (from 10 to 2410), the volume of the query “Wuhan outbreak” increased by over 622 times (from 7 to 4359), and 17.5% of China’s query volume originated from Hubei Province, 51.15% of which was from Wuhan city. The quantitative model using four keywords (“Epidemic”, “Masks”, “Coronavirus” and “Clustered pneumonia”) successfully predicted the daily numbers of cases for the next two days, and detected an early signal during the Beijing Xinfadi outbreak (R2 =0.80). Interpretation: Our study demonstrates the ability of search engine query data to detect COVID-19 outbreaks, and suggests that abnormalities in query volume can serve as early warning signals.

Transmission Dynamics of Coronavirus Disease 2019 (COVID-19) in the World: The Roles of Intervention and Seasonality (preprint)

The coronavirus disease 2019 (COVID-19) is spreading rapidly all over the world. The transmission dynamics of the COVID-19 pandemic is still unclear, but developing strategies for mitigating the severity of the pandemic is yet a top priority for global public health. In this study, we developed a novel compartmental model, SEIR-CV(susceptible-exposed-infectious-removed with control variables), which not only considers the key characteristics of asymptomatic infection and the effects of seasonal variations, but also incorporates different control measures for multiple transmission routes, so as to accurately predict and effectively control the spread of COVID-19. Based on SEIR-CV, we predicted the COVID-19 epidemic situation in China out of Hubei province and proposed corresponding control strategies. The results showed that the prediction results are highly consistent with the outbreak surveillance data, which proved that the proposed control strategies have achieved sound consequent in the actual epidemic control. Subsequently, we have conducted a rolling prediction for the United States, Brazil, India, five European countries (the United Kingdom, Italy, Spain, Germany, and France), southern hemisphere, northern hemisphere, and the world out of China. The results indicate that control measures and seasonal variations have a great impact on the progress of the COVID-19 pandemic. Our prediction results show that the COVID-19 pandemic is developing more rapidly due to the impact of the cold season in the southern hemisphere countries such as Brazil. While the development of the pandemic should have gradually weakened in the northern hemisphere countries with the arrival of the warm season, instead of still developing rapidly due to the relative loose control measures such as the United States and India. Furthermore, the prediction results illustrate that if keeping the current control measures in the main COVID-19 epidemic countries, the pandemic will not be contained and the situation may eventually turn to group immunization, which would lead to the extremely severe disaster of about 5 billion infections and 300 million deaths globally. However, if China's super stringent control measures were implemented from 15 July, 15 August or 15 September 2020, the total infections would be contained about 15 million, 32 million or 370 million respectively, which indicates that the stringent and timely control measures is critical, and the best window period is before September for eventually overcoming COVID-19.