Trend and forecasting of the COVID-19 outbreak in China

Li, Qiang; Feng, Wei; Quan, Yinghui

doi:10.1016/j.jinf.2020.02.014

Cited by 124 publications

(137 citation statements)

References 9 publications

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“…In recent studies different models have been used to predict COVID-19 incidence, prevalence, and mortality rate in China. For example, Li et al (2020) developed a function to predict the ongoing trend with data-driven analysis and estimate the outbreak size of the COVID-19 in China . Roosa et al (2020) used validated phenomenological models during previous outbreaks to create and evaluate short-term forecasts of the cumulative number of confirmed cases in Hubei, China (Roosa et al, 2020).…”

Section: Contents Lists Available At Sciencedirectmentioning

confidence: 99%

Estimation of COVID-19 prevalence in Italy, Spain, and France

Ceylan

2020

Science of The Total Environment

525

453

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Europe has become the epicentre of the virus and hit the continent harder than China.• The apparent mortality rate of COVID-19 is approximately 13% in Italy, 11% in Spain, and 15% in France. • Time series models are significant in predicting the prevalence of the COVID-19 pandemic. • ARIMA (0,2,1), ARIMA (1,2,0), and ARIMA (0,2,1) were chosen as the best models for Italy, Spain, and France, respectively. were collected from the World Health Organization website. Several ARIMA models were formulated with different ARIMA parameters. ARIMA (0,2,1), ARIMA (1,2,0), and ARIMA (0,2,1) models with the lowest MAPE values (4.7520, 5.8486, and 5.6335) were selected as the best models for Italy, Spain, and France, respectively. This study shows that ARIMA models are suitable for predicting the prevalence of COVID-19 in the future. The results of the analysis can shed light on understanding the trends of the outbreak and give an idea of the epidemiological stage of these regions. Besides, the prediction of COVID-19 prevalence trends of Italy, Spain, and France can help take precautions and policy formulation for this epidemic in other countries.

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Section: Contents Lists Available At Sciencedirectmentioning

confidence: 99%

Estimation of COVID-19 prevalence in Italy, Spain, and France

Ceylan

2020

Science of The Total Environment

525

453

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“…In another study, the trend of the COVID-19 outbreak was estimated in China by Li and Feng. Their results show that rapid and dynamic strategies can be useful to diminish and constrain the current crisis [14]. Chinazzi et al evaluated the effect of travel constraints to reduce the COVID-19 outbreak.…”

Section: Introductionmentioning

confidence: 99%

Investigating a Serious Challenge in the Sustainable Development Process: Analysis of Confirmed cases of COVID-19 (New Type of Coronavirus) Through a Binary Classification Using Artificial Intelligence and Regression Analysis

et al. 2020

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Nowadays, sustainable development is considered a key concept and solution in creating a promising and prosperous future for human societies. Nevertheless, there are some predicted and unpredicted problems that epidemic diseases are real and complex problems. Hence, in this research work, a serious challenge in the sustainable development process was investigated using the classification of confirmed cases of COVID-19 (new version of Coronavirus) as one of the epidemic diseases. Hence, binary classification modeling was used by the group method of data handling (GMDH) type of neural network as one of the artificial intelligence methods. For this purpose, the Hubei province in China was selected as a case study to construct the proposed model, and some important factors, namely maximum, minimum, and average daily temperature, the density of a city, relative humidity, and wind speed, were considered as the input dataset, and the number of confirmed cases was selected as the output dataset for 30 days. The proposed binary classification model provides higher performance capacity in predicting the confirmed cases. In addition, regression analysis has been done and the trend of confirmed cases compared with the fluctuations of daily weather parameters (wind, humidity, and average temperature). The results demonstrated that the relative humidity and maximum daily temperature had the highest impact on the confirmed cases. The relative humidity in the main case study, with an average of 77.9%, affected positively, and maximum daily temperature, with an average of 15.4 • C, affected negatively, the confirmed cases.

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“…Li and Feng investigated the trend of the COVID-19 outbreak in China. Their results show that quick and active strategies could be very effective in reducing and control the epidemic of COVID-19 [21]. evaluated the relationship between environmental parameters and confirmed cases of COVID-19, which is a serious challenge in the sustainable development process.…”

Section: Introductionmentioning

confidence: 99%

Development of an Assessment Method for Investigating the Impact of Climate and Urban Parameters in Confirmed Cases of COVID-19: A New Challenge in Sustainable Development

Haghshenas

Pirouz

Haghshenas

et al. 2020

IJERPH

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Sustainable development has been a controversial global topic, and as a complex concept in recent years, it plays a key role in creating a favorable future for societies. Meanwhile, there are several problems in the process of implementing this approach, like epidemic diseases. Hence, in this study, the impact of climate and urban factors on confirmed cases of COVID-19 (a new type of coronavirus) with the trend and multivariate linear regression (MLR) has been investigated to propose a more accurate prediction model. For this propose, some important climate parameters, including daily average temperature, relative humidity, and wind speed, in addition to urban parameters such as population density, were considered, and their impacts on confirmed cases of COVID-19 were analyzed. The analysis was performed for three case studies in Italy, and the application of the proposed method has been investigated. The impacts of parameters have been considered with a delay time from one to nine days to find out the most suitable combination. The result of the analysis demonstrates the effectiveness of the proposed model and the impact of climate parameters on the trend of confirmed cases. The research hypothesis approved by the MLR model and the present assessment method could be applied by considering several variables that exhibit the exact delay of them to new confirmed cases of COVID-19.

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Trend and forecasting of the COVID-19 outbreak in China

Cited by 124 publications

References 9 publications

Estimation of COVID-19 prevalence in Italy, Spain, and France

Estimation of COVID-19 prevalence in Italy, Spain, and France

Investigating a Serious Challenge in the Sustainable Development Process: Analysis of Confirmed cases of COVID-19 (New Type of Coronavirus) Through a Binary Classification Using Artificial Intelligence and Regression Analysis

Development of an Assessment Method for Investigating the Impact of Climate and Urban Parameters in Confirmed Cases of COVID-19: A New Challenge in Sustainable Development

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