ArticleMicroorganisms2020
Forecasting the Spreading of COVID-19 across Nine Countries from Europe, Asia, and the American Continents Using the ARIMA Models.
Article in Microorganisms, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Respiratory viral infections: when and where? A scoping review of spatiotemporal methods.Journal of global health · 2025Article
- Economic burden of breast cancer in India, 2000-2021 and forecast to 2030.Scientific reports · 2025Article
- Impact of the COVID-19 pandemic on number of deaths in Ghana: an application of ARIMA with intervention analysis.Frontiers in public health · 2025Article
- Application of an ARFIMA Model to Estimate Hepatitis C Epidemics in Henan, China.The American journal of tropical medicine and hygiene · 2024Article
- Climate and COVID-19 transmission: a cross-sectional study in Africa.Scientific reports · 2023Article
- Real-time forecasting of COVID-19 spread according to protective behavior and vaccination: autoregressive integrated moving average models.BMC public health · 2023Article
- Special Issue "SARS-CoV-2: Epidemiology and Pathogenesis": Editorial.Microorganisms · 2023Article
- Forecasting emergency medicine reserve demand with a novel decomposition-ensemble methodology.Complex & intelligent systems · 2023Article
- Machine-learning method for analyzing and predicting the number of hospitalizations of children during the fourth wave of the COVID-19 pandemic in the Lviv region.Journal of reliable intelligent environments · 2023Article
- Comparison of ARIMA, ETS, NNAR, TBATS and hybrid models to forecast the second wave of COVID-19 hospitalizations in Italy.The European journal of health economics : HEPAC : health economics in prevention and care · 2022Article
- Mathematical Modeling to Predict COVID-19 Infection and Vaccination Trends.Journal of clinical medicine · 2022Article
- Forecasting COVID-19 Pandemic Using Prophet, ARIMA, and Hybrid Stacked LSTM-GRU Models in India.Computational and mathematical methods in medicine · 2022Article
- Forecasting the Severity of COVID-19 Pandemic Amidst the Emerging SARS-CoV-2 Variants: Adoption of ARIMA Model.Computational and mathematical methods in medicine · 2022Article
- VSHR: A Mathematical Model for the Prediction of Second-Wave COVID-19 Epidemics in Malaysia.Computational and mathematical methods in medicine · 2022Article
- Forecasting fully vaccinated people against COVID-19 and examining future vaccination rate for herd immunity in the US, Asia, Europe, Africa, South America, and the World.Applied soft computing · 2021Article
- Forecasting COVID-19 Confirmed Cases Using Empirical Data Analysis in Korea.Healthcare (Basel, Switzerland) · 2021Article
- COVID-19 epidemic outside China: 34 founders and exponential growth.Journal of investigative medicine : the official publication of the American Federation for Clinical Research · 2021Article
- Predicting Diabetes and Estimating Its Economic Burden in China Using Autoregressive Integrated Moving Average Model.International journal of public health · 2021Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Since mid-November 2019, when the first SARS-CoV-2-infected patient was officially reported, the new coronavirus has affected over 10 million people from which half a million died during this short period. There is an urgent need to monitor, predict, and restrict COVID-19 in a more efficient manner. This is why Auto-Regressive Integrated Moving Average (ARIMA) models have been developed and used to predict the epidemiological trend of COVID-19 in Ukraine, Romania, the Republic of Moldova, Serbia, Bulgaria, Hungary, USA, Brazil, and India, these last three countries being otherwise the most affected presently. To increase accuracy, the daily prevalence data of COVID-19 from 10 March 2020 to 10 July 2020 were collected from the official website of the Romanian Government GOV.RO, World Health Organization (WHO), and European Centre for Disease Prevention and Control (ECDC) websites. Several ARIMA models were formulated with different ARIMA parameters. ARIMA (1, 1, 0), ARIMA (3, 2, 2), ARIMA (3, 2, 2), ARIMA (3, 1, 1), ARIMA (1, 0, 3), ARIMA (1, 2, 0), ARIMA (1, 1, 0), ARIMA (0, 2, 1), and ARIMA (0, 2, 0) models were chosen as the best models, depending on their lowest Mean Absolute Percentage Error (MAPE) values for Ukraine, Romania, the Republic of Moldova, Serbia, Bulgaria, Hungary, USA, Brazil, and India (4.70244, 1.40016, 2.76751, 2.16733, 2.98154, 2.11239, 3.21569, 4.10596, 2.78051). This study demonstrates that ARIMA models are suitable for making predictions during the current crisis and offers an idea of the epidemiological stage of these regions.
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