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

Journals

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  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
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  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
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  20. Kasasbeh A, Issa E, Khan N, Yildirim M, Booth A, Sayama H, Li D. Web‐Based Healthcare Delivery Integrated System to Forecast COVID‐19 Hospitalizations in a Marginalized Patient Population: A Case Study in Broome County, New York. Advances in Public Health 2024;2024(1) View
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