Apr 8, 2020 · We argue that Google Search and Twitter data should complement official numbers. They predict even better than the original values from Johns ...
Apr 5, 2020 · Through Google Trends (2020), we obtain publicly available daily search volume time series data for the term “corona”.
Our approach to forecasting future COVID-19 cases involves 1) modeling the observed incidence cases using a Poisson distribution for the daily incidence number, ...
2) Using a simple regression to adjust the prediction from Johns Hopkins University (JHU) reduces the prediction error to 35%. 3) Google search and Twitter data ...
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It is argued that Google Search and Twitter data should complement official numbers and predict even better than the original values from Johns Hopkins ...
May 25, 2022 · The study proposed the ARIMA, SARIMA and Prophet models to predict daily new cases and cumulative confirmed cases in the USA, Brazil and India over the next 30 ...
While curve-fitting is useful in predicting how many new infections are likely in the near future, a structural model, on the other hand, may be able to predict ...
Dec 15, 2023 · We present a deep learning-based approach to predict the number of daily COVID-19 cases in 30 countries, considering the non-pharmaceutical interventions (NPIs ...
We argue that Google Search and Twitter data should complement official numbers. They predict even better than the original values from Johns Hopkins University ...
The K-Means-LSTM strategy does not predict the infection's pandemic and spread. Instead, it predicts the infected cases time series. The K-Means-LSTM is used ...