Author: Torres, M. C.; Buhat, C. A. H.; Dela Cruz, B. P. C.; Felix, E. F. O.; Gemida, E. B.; Mamplata, J. B.
Title: Forecasting COVID-19 cases in the Philippines using various mathematical models Cord-id: ujn9f65y Document date: 2020_10_12
ID: ujn9f65y
Snippet: Due to the rapid increase of COVID-19 infection cases in many countries such as the Philippines, many efforts in forecasting the daily infections have been made in order to better manage the pandemic, and respond effectively. In this study, we consider the cumulative COVID-19 infection cases in the Philippines from March 6 to July 31, 2020 and forecast the cases from August 1 - 15, 2020 using various mathematical models - weighted moving average, exponential smoothing, Susceptible-Exposed-Infect
Document: Due to the rapid increase of COVID-19 infection cases in many countries such as the Philippines, many efforts in forecasting the daily infections have been made in order to better manage the pandemic, and respond effectively. In this study, we consider the cumulative COVID-19 infection cases in the Philippines from March 6 to July 31, 2020 and forecast the cases from August 1 - 15, 2020 using various mathematical models - weighted moving average, exponential smoothing, Susceptible-Exposed-Infected-Recovered (SEIR) model, Ornstein-Uhlenbeck process, Autoregressive Integrated Moving Average (ARIMA) model, and random forest. We then compare the results to the actual data using traditional error metrics. Our results show that the ARIMA(1,2,1) model has the closest forecast values to the actual data. Policymakers can use our result in determining which forecast method to use for their community in order to have data-based information for the preparation of their personnel and facilities.
Search related documents:
Co phrase search for related documents- absolute error and local transmission: 1, 2
- absolute error and lockdown restriction: 1
- absolute error and machine learn: 1
- absolute error and machine learning: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58
- absolute error and machine learning method: 1, 2, 3
- absolute error and machine mathematical: 1
- absolute error and mae absolute mean error: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73
- absolute mean error and actual march: 1, 2
- absolute mean error and local transmission: 1, 2
- absolute mean error and lockdown restriction: 1
- absolute mean error and machine learn: 1
- absolute mean error and machine learning: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58
- absolute mean error and machine learning method: 1, 2, 3
- absolute mean error and machine mathematical: 1
- absolute mean error and mae absolute mean error: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73
Co phrase search for related documents, hyperlinks ordered by date