Resetting the Initial Conditions for Calculating Epidemic Spread: COVID-19 Outbreak in Italy

Babac, Marina Bagić; Mornar, Vedran

doi:10.1109/access.2020.3015923

Cited by 3 publications

(2 citation statements)

References 42 publications

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“…Since the outbreak of COVID-19, scholars have conducted numerous studies from the perspectives of pathological diagnosis (Xie and Zhu, 2020), drugs and vaccines , transmission relationships (Heidari et al, 2020), spatiotemporal models (Babac and Mornar, 2020), epidemic prediction (Wang et al, 2020a), transmission simulation (Werth et al, 2021), risk assessment (Jia et al, 2020), and epidemic impact (Du et al, 2020), and all of these studies have played a positive role in the prevention and treatment of COVID-19. In terms of epidemic risk assessment, Jia proposed a risk model of population mobility and conducted risk assessment of an epidemic by analyzing population mobility data (Jia et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Risk Assessment and Prediction of COVID-19 Based on Epidemiological Data From Spatiotemporal Geography

Zhou

Wang

et al. 2021

Front. Environ. Sci.

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COVID-19 is a highly infectious disease and public health hazard that has been wreaking havoc around the world; thus, assessing and simulating the risk of the current pandemic is crucial to its management and prevention. The severe situation of COVID-19 around the world cannot be ignored, and there are signs of a second outbreak; therefore, the accurate assessment and prediction of COVID-19 risks, as well as the prevention and control of COVID-19, will remain the top priority of major public health agencies for the foreseeable future. In this study, the risk of the epidemic in Guangzhou was first assessed through logistic regression (LR) on the basis of Tencent-migration data and urban point of interest (POI) data, and then the regional distribution of high- and low-risk epidemic outbreaks in Guangzhou in February 2021 was predicted. The main factors affecting the distribution of the epidemic were also analyzed by using geographical detectors. The results show that the number of cases mainly exhibited a declining and then increasing trend in 2020, and the high-risk areas were concentrated in areas with resident populations and floating populations. In addition, in February 2021, the “Spring Festival travel rush” in China was predicted to be the peak period of population movement. The epidemic risk value was also predicted to reach its highest level at external transportation stations, such as Baiyun Airport and Guangzhou South Railway Station. The accuracy verification showed that the prediction accuracy exceeded 99%. Finally, the interaction between the resident population and floating population could explain the risk of COVID-19 to the highest degree, which indicates that the effective control of population agglomeration and interaction is conducive to the prevention and control of COVID-19. This study identifies and predicts high-risk areas of the epidemic, which has important practical value for urban public health prevention and control and containment of the second outbreak of COVID-19.

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Section: Introductionmentioning

confidence: 99%

Risk Assessment and Prediction of COVID-19 Based on Epidemiological Data From Spatiotemporal Geography

Zhou

Wang

et al. 2021

Front. Environ. Sci.

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“…Many studies about clinical diagnosis [6], transmission relationship [7], drug vaccine [8], spatiotemporal pattern [9], risk assessment [10], and epidemic transmission [11] of COVID-19 have been done by scholars since the breakout of the epidemic, which has made great contributions to the prevention and control of COVID-19. With the arrival of the post-epidemic period, the risk assessment of epidemic has gradually become the focus of attention [12,13].…”

Section: Introductionmentioning

confidence: 99%

COVID-19 Risk Assessment: Contributing to Maintaining Urban Public Health Security and Achieving Sustainable Urban Development

Zhang

Yuan

2021

Sustainability

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As the most infectious disease in 2020, COVID-19 is an enormous shock to urban public health security and to urban sustainable development. Although the epidemic in China has been brought into control at present, the prevention and control of it is still the top priority of maintaining public health security. Therefore, the accurate assessment of epidemic risk is of great importance to the prevention and control even to overcoming of COVID-19. Using the fused data obtained from fusing multi-source big data such as POI (Point of Interest) data and Tencent-Yichuxing data, this study assesses and analyzes the epidemic risk and main factors that affect the distribution of COVID-19 on the basis of combining with logistic regression model and geodetector model. What’s more, the following main conclusions are obtained: the high-risk areas of the epidemic are mainly concentrated in the areas with relatively dense permanent population and floating population, which means that the permanent population and floating population are the main factors affecting the risk level of the epidemic. In other words, the reasonable control of population density is greatly conducive to reducing the risk level of the epidemic. Therefore, the control of regional population density remains the key to epidemic prevention and control, and home isolation is also the best means of prevention and control. The precise assessment and analysis of the epidemic conducts by this study is of great significance to maintain urban public health security and achieve the sustainable urban development.

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Regression analysis of the most frequent medical diagnoses in a Mediterranean country

Bezić,

Bagić Babac

2023

Computational Intelligence for Medical Internet of Things (MIoT) Applications

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Resetting the Initial Conditions for Calculating Epidemic Spread: COVID-19 Outbreak in Italy

Cited by 3 publications

References 42 publications

Risk Assessment and Prediction of COVID-19 Based on Epidemiological Data From Spatiotemporal Geography

Risk Assessment and Prediction of COVID-19 Based on Epidemiological Data From Spatiotemporal Geography

COVID-19 Risk Assessment: Contributing to Maintaining Urban Public Health Security and Achieving Sustainable Urban Development

Regression analysis of the most frequent medical diagnoses in a Mediterranean country

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