Jung, Sung-MokSung-MokJungEndo, AkiraAkiraEndoAndrey AkhmetzhanovNishiura, HiroshiHiroshiNishiura2022-01-052022-01-052021-121201-9712https://scholars.lib.ntu.edu.tw/handle/123456789/590989The effective reproduction number (Rt) has been critical for assessing the effectiveness of countermeasures during the coronavirus disease 2019 (COVID-19) pandemic. Conventional methods using reported incidences are unable to provide timely Rt data due to the delay from infection to reporting. Our study aimed to develop a framework for predicting Rt in real time, using timely accessible data - i.e. human mobility, temperature, and risk awareness.enCOVID-19; Japan; effective reproduction number; mobility; regression model; temperature[SDGs]SDG3Article; body temperature; coronavirus disease 2019; cross validation; effective reproduction number; epidemiological data; explanatory variable; human; incidence; linear regression analysis; normal distribution; public health; risk assessment; superspreading event; task performance; uncertainty; basic reproduction number; pandemic; temperature; Basic Reproduction Number; COVID-19; Humans; Pandemics; SARS-CoV-2; Temperaturejournal article10.1016/j.ijid.2021.10.007346280202-s2.0-85118178329WOS:000718302600005https://scholars.lib.ntu.edu.tw/handle/123456789/587499