Abstract

BackgroundFrom the beginning of 2020, the world was plunged into a pandemic caused by the novel coronavirus disease-19 (COVID-19). People increasingly searched for information related to COVID-19 on internet websites. The Baidu Index is a data sharing platform. The main data provided is the search index (SI), which represents the frequency that keywords are used in searches.MethodsJanuary 9, 2020 is an important date for the outbreak of COVID-19 in China. We compared the changes of SI before and after for 7 keywords, including “fever”, “cough”, “nausea”, “vomiting”, “abdominal pain”, “diarrhea”, “constipation”. The slope and peak values of SI change curves are compared. Ten provinces in China were selected for a separate analysis, including Beijing, Gansu, Guangdong, Guangxi, Heilongjiang, Hubei, Sichuan, Shanghai, Xinjiang, Tibet. The change of SI was analyzed separately, and the correlation between SI and demographic and economic data was analyzed.ResultsDuring period I, from January 9 to January 25, 2020, the average daily increase (ADI) of the SI for “diarrhea” was lower than that for “cough” (889.47 vs. 1,799.12, F=11.43, P=0.002). In period II, from January 25 to April 8, 2020, the average daily decrease (ADD) of the SI for “diarrhea” was significantly lower than that for “cough”, with statistical significance (cough, 191.40 vs. 441.44, F=68.66, P<0.001). The mean SI after January 9, 2020 (pre-SI) was lower than that before January 9, 2020 (post-SI) (fever, 2,616.41±116.92 vs. 3,724.51±867.81, P<0.001; cough, 3,260.04±308.43 vs. 5,590.66±874.25, P<0.001; diarrhea, 4,128.80±200.82 vs. 4,423.55±1,058.01, P<0.001). The pre-SI mean was correlated with population (P=0.004, R=0.813) and gross domestic product (GDP) (P<0.001, R=0.966). The post-SI peak was correlated with population (P=0.007, R=0.789), GDP (P=0.005, R=0.804), and previously confirmed cases (PCC) (P=0.03, R=0.670). The growth rate of the SI was correlated with the post-SI peak (P=0.04, R=0.649), PCC (P=0.003, R=0.835).ConclusionsDiarrhea was of widespread concern in all provinces before and after the COVID-19 outbreak and may be associated with novel coronavirus infection. Internet big data can reflect the public’s concern about diseases, which is of great significance for the study of the epidemiological characteristics of diseases.

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