scholarly journals The Economic Impact from the Decreasing Population Mobility of China’s Mainland during the Epidemic

2020 ◽  
Author(s):  
Yi Xiao ◽  
Jian Peng ◽  
Yuan Chen ◽  
Zheming Yuan
Keyword(s):  
Real Time ◽  
Economic Activity ◽  
Decisive Role ◽  
Control Measures ◽  
Economic Recovery ◽  
Health Economy ◽  
Human Society ◽  
Population Mobility ◽  
Official Report ◽  
The Impact

The COVID-19 pandemic caused by SARS-CoV-2 poses a devastating threat to human society in terms of health, economy and lifestyle. Establishing accurate and real-time models to predict and assess the impact of the epidemic on the economy is instructive. We have designed a new model to quantitatively assess the impact of the COVID-19 on the economy of China’s mainland. The nominal GDP in the Q1 of 2020 that we predicted for China’s mainland with the Baidu Mi-gration Data is RMB 20,785.7 billion, which is less by 3.59% than that in 2019. The estimated val-ue is confirmed roughly by the official report released in April 17, 2020 (RMB 20,650 billion, 6.8% year-on-year declined). Strict control measures during the epidemic have greatly reduced Chi-na's economic activity and had a serious impact on the country's economy. Orderly promotion of population mobility plays a decisive role in economic recovery.

scholarly journals COVID-19, Urbanization Pattern and Economic Recovery: An Analysis of Hubei, China

2020 ◽  
Vol 17 (24) ◽  
pp. 9577
Author(s):  
Wenyi Yang ◽  
Xueli Wang ◽  
Keke Zhang ◽  
Zikan Ke
Keyword(s):  
Rapid Development ◽  
Generalized Method Of Moments ◽  
Economic Recovery ◽  
Population Mobility ◽  
Economic Resilience ◽  
Economic Resource ◽  
Large Cities ◽  
Impact Of Urbanization ◽  
The One ◽  
The Impact

In the context of the rapid development of urbanization and increasing population mobility in China, the outbreak of COVID-19 has had a significant impact on China’s economy and society. This article uses China UnionPay transaction data and takes Hubei, the worst-hit region by COVID-19 in China, as an example, to conduct empirical analysis using the generalized method of moments (GMM) of the impact of current urbanization patterns on the spread of the epidemic and economic recovery from the perspectives of time, industry, and regional differences. The study found that during the different stages of COVID-19, including discovery, outbreak, and subsidence, the overall impact of urbanization on the economy in Hubei Province was first positive, then became negative, and finally gradually increased. This process had significant industrial and urban heterogeneity, which was mainly manifested in losses in tourism and catering industries that were significantly greater than those in the audio-visual entertainment and digital office industries. Similarly, the recovery speed of large cities was lower than that of small and medium-sized cities. The main reason for these differences is that the one-sided problem of urbanization is more obvious in areas with higher urbanization rates. COVID-19 has drawn attention to the development of urbanization in the future, that is, the development path of one-sided economic resource agglomeration and scale expansion should be abandoned, with greater attention paid to the improvement of service functions and the development of amenities. This transformation is necessary to enhance urban economic resilience and reduce public health risks.

scholarly journals Macroeconomic assessment of possible Green Recovery scenarios in Visegrad countries

2021 ◽  
Author(s):  
Bence Kiss-Dobronyi ◽  
Dora Fazekas ◽  
Hector Pollitt
Keyword(s):  
Economic Theory ◽  
Economic Activity ◽  
Three Dimensions ◽  
Economic Recovery ◽  
Keynesian Economic ◽  
Post Keynesian Economic ◽  
The Impact ◽  
Environmental Level ◽  
Visegrád Countries

AbstractThe article discusses how and why Green Recovery could be beneficial for the Visegrad countries based on a modelling exercise using the E3ME macroeconometric model. Green Recovery is defined as including policies in recovery plans that not only target economic recovery, but also contribute to environmental targets. The paper proposes that a Green Recovery could be valuable and suitable for the region contributing to both restoring employment and boosting economic activity as well as reaching climate goals. This is tested through a macroeconomic simulation, using the E3ME model. E3ME is built on Post-Keynesian economic theory and on econometric estimations of macroeconomic relationships. The results of the analysis focus on three dimensions: (1) social – employment, (2) environmental – level of CO2 emissions and (3) economic activity – gross domestic product (GDP). Outcomes indicate that a green recovery can shorten the time needed for employment and economic recovery as well as contributes to CO2 emission reductions. In Hungary, Czechia and Poland, the impact persists into the long-term; however, the paper also concludes that countries with high reliance on coal (e.g. Poland) could return to coal in the long term if no further policies are introduced.

Effects of real time control of sewer systems on treatment plant performance and receiving water quality

2002 ◽  
Vol 45 (3) ◽  
pp. 229-237 ◽  
Author(s):  
T. Frehmann ◽  
A. Niemann ◽  
P. Ustohal ◽  
W.F. Geiger
Keyword(s):  
Real Time ◽  
Treatment Plant ◽  
Drainage System ◽  
Control Measures ◽  
Plant Performance ◽  
Integral Model ◽  
Real Time Control ◽  
Time Control ◽  
The Impact ◽  
Receiving Water

Four individual mathematical submodels simulating different subsystems of urban drainage were intercoupled to an integral model. The submodels (for surface runoff, flow in sewer system, wastewater treatment plant and receiving water) were calibrated on the basis of field data measured in an existing urban catchment investigation. Three different strategies for controlling the discharge in the sewer network were defined and implemented in the integral model. The impact of these control measures was quantified by representative immission state-parameters of the receiving water. The results reveal that the effect of a control measure may be ambivalent, depending on the referred component of a complex drainage system. Furthermore, it is demonstrated that the drainage system in the catchment investigation can be considerably optimised towards environmental protection and operation efficiency if an appropriate real time control on the integral scale is applied.

scholarly journals Real-time estimation of the influenza-associated excess mortality in Hong Kong

2019 ◽  
Vol 147 ◽  
Author(s):  
Jessica Y. Wong ◽  
Edward Goldstein ◽  
Vicky J. Fang ◽  
Benjamin J. Cowling ◽  
Peng Wu
Keyword(s):  
Hong Kong ◽  
Real Time ◽  
Excess Mortality ◽  
Time Estimation ◽  
Surveillance Data ◽  
Control Measures ◽  
Influenza Surveillance ◽  
Mortality Data ◽  
Real Time Estimation ◽  
The Impact

Abstract Statistical models are commonly employed in the estimation of influenza-associated excess mortality that, due to various reasons, is often underestimated by laboratory-confirmed influenza deaths reported by healthcare facilities. However, methodology for timely and reliable estimation of that impact remains limited because of the delay in mortality data reporting. We explored real-time estimation of influenza-associated excess mortality by types/subtypes in each year between 2012 and 2018 in Hong Kong using linear regression models fitted to historical mortality and influenza surveillance data. We could predict that during the winter of 2017/2018, there were ~634 (95% confidence interval (CI): (190, 1033)) influenza-associated excess all-cause deaths in Hong Kong in population ⩾18 years, compared to 259 reported laboratory-confirmed deaths. We estimated that influenza was associated with substantial excess deaths in older adults, suggesting the implementation of control measures, such as administration of antivirals and vaccination, in that age group. The approach that we developed appears to provide robust real-time estimates of the impact of influenza circulation and complement surveillance data on laboratory-confirmed deaths. These results improve our understanding of the impact of influenza epidemics and provide a practical approach for a timely estimation of the mortality burden of influenza circulation during an ongoing epidemic.

scholarly journals A Fast Estimation Method for Satellite in Orbit Management

2020 ◽  
Vol 316 ◽  
pp. 04007
Author(s):  
Zhen Cui ◽  
Ye Ji ◽  
Bin Chen ◽  
Yang Yang
Keyword(s):  
Real Time ◽  
Satellite Telemetry ◽  
Estimation Method ◽  
Decisive Role ◽  
Telemetry Data ◽  
The Real ◽  
Fast Estimation ◽  
Fault Handling ◽  
Rapid Processing ◽  
The Impact

The management of satellites in orbit requires accurate and rapid processing to minimize the impact of failures. Especially for fault handling involving energy security, the real-time nature of the process plays a decisive role. This paper proposes a fast estimation method based on satellite telemetry data. Through the analysis of the shape of the telemetry curve, the geometric method, the correlation analysis of the telemetry data on the satellite, or the physical principles, the required parameters are quickly obtained to facilitate rapid emergency processing. This method is applied to satellite in-orbit management, which can greatly improve the real-time performance of fault processing, and has good engineering practical value.

scholarly journals Spatial Network based model forecasting transmission and control of COVID-19

2020 ◽  
Author(s):  
Natasha Sharma ◽  
Atul Kumar Verma ◽  
Arvind Kumar Gupta
Keyword(s):  
Time Delay ◽  
Human Life ◽  
Extended Period ◽  
Control Measures ◽  
Effective Control ◽  
Health Economy ◽  
Spread Dynamics ◽  
Novel Coronavirus ◽  
Delay Differential ◽  
The Impact

The SARS-CoV-2 driven infectious novel coronavirus disease (COVID-19) has been declared a pandemic by virtue of its brutal impact on the world in terms of loss on human life, health, economy, and other crucial resources. With the aim to explore more about its aspects, we adopted the SEIQRD (Susceptible-Exposed-Infected-Quarantine-Recovered-Death) pandemic spread with a time delay on the heterogeneous population and geography in this work. Focusing on the spatial heterogeneity, the entire population of interest in a region is divided into small distinct geographical sub regions, which interact by means of migration networks across boundaries. Utilizing the estimations of the time delay differential equations based model, we analyzed the spread dynamics of disease in a region and its sub regions. The model based numerical outcomes are validated from real time available data for India. We computed the approximate peak infection in forward time and relative timespan when disease outspread halts. To further evaluate the influence of the delay on the long term system dynamics, the sensitivity analysis is performed on time delay. The most crucial parameter, basic reproduction number R0 and its time-dependent generalization, has been estimated at both regional and sub regional levels. The impact of the most significant lockdown measure that has been implemented in India to contain the pandemic spread has been extensively studied by considering no lockdown scenario. A suggestion based on outcomes, for a bit relaxed lockdown, followed by an extended period of strict social distancing as one of the most effective control measures to manage COVID-19 spread is provided for India.

scholarly journals Estimated Dissemination Ratio—A Practical Alternative to the Reproduction Number for Infectious Diseases

2021 ◽  
Vol 9 ◽  
Author(s):  
Francisco J. Pérez-Reche ◽  
Nick Taylor ◽  
Chris McGuigan ◽  
Philip Conaglen ◽  
Ken J. Forbes ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Infectious Diseases ◽  
Real Time ◽  
Early Warning ◽  
Reproduction Number ◽  
Transmission Rate ◽  
Control Measures ◽  
Epidemic Curve ◽  
The Uk ◽  
The Impact

Policymakers require consistent and accessible tools to monitor the progress of an epidemic and the impact of control measures in real time. One such measure is the Estimated Dissemination Ratio (EDR), a straightforward, easily replicable, and robust measure of the trajectory of an outbreak that has been used for many years in the control of infectious disease in livestock. It is simple to calculate and explain. Its calculation and use are discussed below together with examples from the current COVID-19 outbreak in the UK. These applications illustrate that EDR can demonstrate changes in transmission rate before they may be clear from the epidemic curve. Thus, EDR can provide an early warning that an epidemic is resuming growth, allowing earlier intervention. A conceptual comparison between EDR and the commonly used reproduction number is also provided.

scholarly journals Analysis of Changes in Intercity Highway Traffic Travel Patterns under the Impact of COVID-19

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Mingchen Gu ◽  
Shuo Sun ◽  
Feng Jian ◽  
Xiaohan Liu
Keyword(s):  
Cellular Network ◽  
Prevention And Control ◽  
Empirical Studies ◽  
Control Measures ◽  
Human Society ◽  
Travel Patterns ◽  
Highway Traffic ◽  
Passenger Cars ◽  
And Control ◽  
The Impact

The unprecedented COVID-19 pandemic impacts negatively on the security and development of human society. Comparison and analysis of intercity highway travel patterns before and during the COVID-19 pandemic can bring vital insights for the prevention and control of the pandemic. Empirical studies are conducted using cellular network-based datasets associated with two groups of city pairs in China heavily affected by COVID-19. Spatial matching, full-sample extrapolation, and trajectory feature analysis are adopted to attain travel volumes of intercity highways during four different periods. The reliability of origin-destination (OD) matrices calculated based on the cellular network-based dataset is demonstrated by comparing with the fluctuation trend of traffic count data. The empirical studies show that the OD flows associated with passenger cars on intercity highways in China decreased significantly during COVID-19. With the effective implementation of the pandemic prevention control policy and the orderly promotion of the recovery to work and production, the volumes of intercity highway OD flows returned to the pre-pandemic level in mid-April 2020. Besides, the peak of passenger car trips decreases and the time span for truck trips gets longer owing to implemented control measures in dealing with COVID-19. The results can be applied to the calculation of OD flows between most adjacent cities and analyze the intercity highway traffic travel patterns changes, which provide insightful implications for making intercity travel safety prevention and control policies under epidemic conditions.

scholarly journals Predicting the effect of confinement on the COVID-19 spread using machine learning enriched with satellite air pollution observations

2021 ◽  
Vol 118 (33) ◽  
pp. e2109098118
Author(s):  
Xiaofan Xing ◽  
Yuankang Xiong ◽  
Ruipu Yang ◽  
Rong Wang ◽  
Weibing Wang ◽  
...  
Keyword(s):  
Real Time ◽  
Economic Activity ◽  
Human Mobility ◽  
Surrogate Data ◽  
Satellite Observations ◽  
Control Measures ◽  
The Real ◽  
Mobility Data ◽  
Real Distribution ◽  
Containment Measures

The real-time monitoring of reductions of economic activity by containment measures and its effect on the transmission of the coronavirus (COVID-19) is a critical unanswered question. We inferred 5,642 weekly activity anomalies from the meteorology-adjusted differences in spaceborne tropospheric NO2 column concentrations after the 2020 COVID-19 outbreak relative to the baseline from 2016 to 2019. Two satellite observations reveal reincreasing economic activity associated with lifting control measures that comes together with accelerating COVID-19 cases before the winter of 2020/2021. Application of the near-real-time satellite NO2 observations produces a much better prediction of the deceleration of COVID-19 cases than applying the Oxford Government Response Tracker, the Public Health and Social Measures, or human mobility data as alternative predictors. A convergent cross-mapping suggests that economic activity reduction inferred from NO2 is a driver of case deceleration in most of the territories. This effect, however, is not linear, while further activity reductions were associated with weaker deceleration. Over the winter of 2020/2021, nearly 1 million daily COVID-19 cases could have been avoided by optimizing the timing and strength of activity reduction relative to a scenario based on the real distribution. Our study shows how satellite observations can provide surrogate data for activity reduction during the COVID-19 pandemic and monitor the effectiveness of containment to the pandemic before vaccines become widely available.

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