This paper is in the following e-collection/theme issue:

JMIR Theme Issue: COVID-19 Special Issue (2391) Infectious Diseases (non-STD/STI) (1485) Epidemiology (135) Outbreak and Pandemic Preparedness and Management (1675) Surveillance Systems (428) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1482) Statistical Methods for Surveillance and Population Health (147)

Published on in Vol 23, No 3 (2021): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/24925, first published .
Short-Range Forecasting of COVID-19 During Early Onset at County, Health District, and State Geographic Levels Using Seven Methods: Comparative Forecasting Study

Short-Range Forecasting of COVID-19 During Early Onset at County, Health District, and State Geographic Levels Using Seven Methods: Comparative Forecasting Study

Short-Range Forecasting of COVID-19 During Early Onset at County, Health District, and State Geographic Levels Using Seven Methods: Comparative Forecasting Study

Authors of this article:

Christopher J Lynch1 Author Orcid Image ;   Ross Gore1 Author Orcid Image
Article Authors Cited by (20) Tweetations (11) Metrics

Journals

  1. Lynch C, Gore R. Application of one-, three-, and seven-day forecasts during early onset on the COVID-19 epidemic dataset using moving average, autoregressive, autoregressive moving average, autoregressive integrated moving average, and naïve forecasting methods. Data in Brief 2021;35:106759 View
  2. Zeng C, Zhang J, Li Z, Sun X, Olatosi B, Weissman S, Li X. Spatial-Temporal Relationship Between Population Mobility and COVID-19 Outbreaks in South Carolina: Time Series Forecasting Analysis. Journal of Medical Internet Research 2021;23(4):e27045 View
  3. Margus C, Brown N, Hertelendy A, Safferman M, Hart A, Ciottone G. Emergency Physician Twitter Use in the COVID-19 Pandemic as a Potential Predictor of Impending Surge: Retrospective Observational Study. Journal of Medical Internet Research 2021;23(7):e28615 View
  4. Nguyen H, Turk P, McWilliams A. Forecasting COVID-19 Hospital Census: A Multivariate Time-Series Model Based on Local Infection Incidence. JMIR Public Health and Surveillance 2021;7(8):e28195 View
  5. Canton Enriquez D, Niembro-Ceceña J, Muñoz Mandujano M, Alarcon D, Arcadia Guerrero J, Gonzalez Garcia I, Montes Gutierrez A, Gutierrez-Lopez A. Application of probabilistic models for extreme values to the COVID-2019 epidemic daily dataset. Data in Brief 2022;40:107783 View
  6. Portelli B, Scaboro S, Tonino R, Chersoni E, Santus E, Serra G. Monitoring User Opinions and Side Effects on COVID-19 Vaccines in the Twittersphere: Infodemiology Study of Tweets. Journal of Medical Internet Research 2022;24(5):e35115 View
  7. Tsai K, Chien T, Lin J, Yeh Y, Chou W. Comparison of prediction accuracies between mathematical models to make projections of confirmed cases during the COVID-19 pandamic by country/region. Medicine 2021;100(50):e28134 View
  8. Singini G, Manda S. Inter-Country COVID-19 Contagiousness Variation in Eight African Countries. Frontiers in Public Health 2022;10 View
  9. Wang X, Wu T, Oliveira L, Zhang D. Sheet, Surveillance, Strategy, Salvage and Shield in global biodefense system to protect the public health and tackle the incoming pandemics. Science of The Total Environment 2022;822:153469 View
  10. Gianquintieri L, Brovelli M, Pagliosa A, Dassi G, Brambilla P, Bonora R, Sechi G, Caiani E. Generating High-Granularity COVID-19 Territorial Early Alerts Using Emergency Medical Services and Machine Learning. International Journal of Environmental Research and Public Health 2022;19(15):9012 View
  11. Du H, Dong E, Badr H, Petrone M, Grubaugh N, Gardner L. Incorporating variant frequencies data into short-term forecasting for COVID-19 cases and deaths in the USA: a deep learning approach. eBioMedicine 2023;89:104482 View
  12. Zamri A, Singh S, Ghazali S, Herng L, Dass S, Aris T, Ibrahim H, Gill B. Effectiveness of the movement control measures during the third wave of COVID-19 in Malaysia. Epidemiology and Health 2021;43:e2021073 View
  13. Ringa N, Iyaniwura S, David S, Irvine M, Adu P, Spencer M, Janjua N, Otterstatter M. Social Contacts and Transmission of COVID-19 in British Columbia, Canada. Frontiers in Public Health 2022;10 View
  14. Wei W, Wang G, Tao X, Luo Q, Chen L, Bao X, Liu Y, Jiang J, Liang H, Ye L. Time series prediction for the epidemic trends of monkeypox using the ARIMA, exponential smoothing, GM (1, 1) and LSTM deep learning methods. Journal of General Virology 2023;104(4) View
  15. Bassanello M, Geppini R, Bonsembiante E, Coli U, Farencena A, D’Aquino M, Gambaro A, Buja A, Baldovin T. Risk of SARS-CoV-2 transmission in the close contacts in a small rural area in the Veneto Region (NE-Italy): past evidence for future scenarios. Frontiers in Public Health 2023;11 View
  16. Cañedo M, Lopes T, Rossato L, Nunes I, Faccin I, Salomé T, Simionatto S, Alouffi A. Impact of COVID-19 pandemic in the Brazilian maternal mortality ratio: A comparative analysis of Neural Networks Autoregression, Holt-Winters exponential smoothing, and Autoregressive Integrated Moving Average models. PLOS ONE 2024;19(1):e0296064 View
  17. Lim M, Singh S, Lai C, Gill B, Kamarudin M, Md Zamri A, Tan C, Zulkifli A, Nadzri M, Mohd Ghazali N, Mohd Ghazali S, Md Iderus N, Ahmad N, Suppiah J, Tee K, Aris T, Ahmad L. Forecasting the effects of vaccination on the COVID-19 pandemic in Malaysia using SEIRV compartmental models. Epidemiology and Health 2023;45:e2023093 View
  18. Karasinghe N, Peiris S, Jayathilaka R, Dharmasena T, Abonazel M. Forecasting weekly dengue incidence in Sri Lanka: Modified Autoregressive Integrated Moving Average modeling approach. PLOS ONE 2024;19(3):e0299953 View
  19. Massey A, Boennec C, Restrepo-Ortiz C, Blanchet C, Alizon S, Sofonea M, Pitzer V. Real-time forecasting of COVID-19-related hospital strain in France using a non-Markovian mechanistic model. PLOS Computational Biology 2024;20(5):e1012124 View