Forecasting COVID19 parameters using time-series: KSA, USA, Spain, and Brazil comparative case study

Using weather factors and google data to predict COVID-19 transmission in Melbourne, Australia: A time-series predictive model

“…Throughout the pandemic, there has been a large volume of research on developing time-series predictive models to forecast COVID-19 transmission globally, for informing public health policy [ 51 ], ranging from epidemiological methods to machine learning. There are many advanced predictive models available as discussed in many recent studies, with varying strengths and limitations [ 18 , [52] , [53] , [54] , [55] , [56] ]. Some of the time-series models commonly used included susceptible exposed infected recovered (SEIR/SIR) [ 57 ], Kucharski et al described early dynamics of transmission using R eff in Wuhan, China using SEIR in early 2020 [ 58 ], while Campillo-Funollet et al used SEIR to predict healthcare demand and capacity based on local transmission in England from March to June 2020 [ 59 ].…”

A multistate model and its standalone tool to predict hospital and ICU occupancy by patients with COVID-19

“…The COVID-19 pandemic has subjected health systems around the world to unprecedented stress, requiring resources that have even exceeded their planned emergency capacity [ 2 ]. As a matter of fact, versatile models able to accurately predict the evolution of the pandemic at different scales (country, region or organization) are of great interest [ 3 ].…”

Optimizing Electric Vehicle Charging Station Location on Highways: A Decision Model for Meeting Intercity Travel Demand

“…An ARIMA model was compared with LSTM for predicting average stock prices using NASDAQ data and was found to perform better than LSTM except for daily price predictions [25]. Exponential smoothing (ETS) was utilized for forecasting COVID-19 parameters across various countries and outperformed other methods such as LSTM when assessed using RMSE, MAE, and MSE metrics [26]. Several studies were conducted by using the generalized linear model (GLM) and its extensions.…”