scholarly journals Time-Varying Spatial Memory Model and Its Impact on Virus Spreading

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Mingyue Xu ◽  
Dingding Han ◽  
Kaidi Zhao ◽  
Qingqing Yao
Keyword(s):  
Spatial Memory ◽  
Management Control ◽  
Control Measures ◽  
Floating Population ◽  
Memory Model ◽  
Cumulative Number ◽  
Time Varying ◽  
Epidemic Spreading ◽  
Virus Spreading ◽  
The Impact

The models of time-varying network have a profound impact on the study of virus spreading on the networks. On the basis of an activity-driven memory evolution model, a time-varying spatial memory model (TSM) is proposed. In the TSM model, the cumulative number of connections between nodes is recorded, and the spatiality of nodes is considered at the same time. Therefore, the active nodes tend to connect the nodes with high intimacy and close proximity. Then, the TSM model is applied to epidemic spreading, and the epidemic spreading on different models is compared. To verify the universality of the TSM model, this model is also applied to rumor spreading, and it is proved that it can also play a good inhibiting effect. We find that, in the TSM network, the introduction of spatiality and memory can slow down the propagation speed and narrow the propagation scope of disease or rumor, and memory is more important. We then explore the impact of different prevention and control methods on pandemic spreading to provide reference for COVID-19 management control and find when the activity of node is restricted, the spreading will be controlled. As floating population has been acknowledged as a key parameter that affects the situation of COVID-19 after work resumption, the factor of population mobility is introduced to calculate the interregional population interaction rate, and the time-varying interregional epidemic model is established. Finally, our results of infectious disease parameters based on daily cases are in good agreement with the real data, and the effectiveness of different control measures is evaluated.

scholarly journals The Dynamic Impacts of the COVID-19 Pandemic on Log Prices in China: An Analysis Based on the TVP-VAR Model

Forests ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 449
Author(s):  
Chenlu Tao ◽  
Gang Diao ◽  
Baodong Cheng
Keyword(s):  
Exchange Rate ◽  
Structural Changes ◽  
Raw Materials ◽  
Supply And Demand ◽  
Oil Prices ◽  
Control Measures ◽  
Var Model ◽  
Time Varying ◽  
Wood Industry ◽  
The Impact

China’s wood industry is vulnerable to the COVID-19 pandemic since wood raw materials and sales of products are dependent on the international market. This study seeks to explore the speed of log price recovery under different control measures, and to perhaps find a better way to respond to the pandemic. With the daily data, we utilized the time-varying parameter autoregressive (TVP-VAR) model, which can incorporate structural changes in emergencies into the model through time-varying parameters, to estimate the dynamic impact of the pandemic on log prices at different time points. We found that the impact of the pandemic on oil prices and Renminbi exchange rate is synchronized with the severity of the pandemic, and the ascending in the exchange rate would lead to an increase in log prices, while oil prices would not. Moreover, the impulse response in June converged faster than in February 2020. Thus, partial quarantine is effective. However, the pandemic’s impact on log prices is not consistent with changes of the pandemic. After the pandemic eased in June 2020, the impact of the pandemic on log prices remained increasing. This means that the COVID-19 pandemic has long-term influences on the wood industry, and the work resumption was not smooth, thus the imbalance between supply and demand should be resolved as soon as possible. Therefore, it is necessary to promote the development of the domestic wood market and realize a “dual circulation” strategy as the pandemic becomes a “new normal”.

scholarly journals Comparative Analysis of Early Dynamic Trends in Novel Coronavirus Outbreak: A Modeling Framework

2020 ◽  
Author(s):  
Huazhen Lin ◽  
Wei Liu ◽  
Hong Gao ◽  
Jinyu Nie ◽  
Qiao Fan
Keyword(s):  
Growth Model ◽  
Control Measures ◽  
Peak Time ◽  
Time Varying ◽  
Modeling Framework ◽  
Epidemic Size ◽  
Significant Public Health ◽  
Novel Coronavirus ◽  
The Uk ◽  
The Impact

AbstractBackgroundThe 2019 coronavirus disease (COVID-19) represents a significant public health threat globally. Here we describe efforts to compare epidemic growth, size and peaking time for countries in Asia, Europe, North America, South America and Australia in the early epidemic phase.MethodsUsing the time series of cases reported from January 20, 2020 to February 13, 2020 and transportation data from December 1, 2019 to January 23, 2020 we have built a novel time-varying growth model to predict the epidemic trend in China. We extended our method, using cases reported from January 26, 2020 - or the date of the earliest case reported, to April 9, 2020 to predict future epidemic trend and size in 41 countries. We estimated the impact of control measures on the epidemic trend.ResultsOur time-varying growth model yielded high concordance in the predicted epidemic size and trend with the observed figures in C hina. Among the other 41 countries, the peak time has been observed in 28 countries before or around April 9, 2020; the peak date and epidemic size were highly consistent with our estimates. We predicted the remaining countries would peak in April or May 2020, except India in July and Pakistan in August. The epidemic trajectory would reach the plateau in May or June for the majority of countries in the current wave. Countries that could emerge to be new epidemic centers are India, Pakistan, Brazil, Mexico, and Russia with a prediction of 105 cases for these countries. The effective reproduction number Rt displayed a downward trend with time across countries, revealing the impact of the intervention remeasures i.e. social distancing. Rt remained the highest in the UK (median 2.62) and the US (median 2.19) in the fourth week after the epidemic onset.ConclusionsNew epidemic centers are expected to continue to emerge across the whole world. Greater challenges such as those in the healthcare system would be faced by developing countries in hotspots. A domestic approach to curb the pandemic must align with joint international efforts to effectively control the spread of COVID-19. Our model promotes a reliable transmissibility characterization and epidemic forecasting using the incidence of cases in the early epidemic phase.

scholarly journals Comparing the responses of the UK, Sweden and Denmark to COVID-19 using counterfactual modelling

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Swapnil Mishra ◽  
James A. Scott ◽  
Daniel J. Laydon ◽  
Seth Flaxman ◽  
Axel Gandy ◽  
...  
Keyword(s):  
Reproduction Number ◽  
Mechanistic Model ◽  
Total Mortality ◽  
Control Measures ◽  
Mortality Data ◽  
Time Varying ◽  
Per Capita ◽  
The Uk ◽  
The Impact ◽  
Counterfactual Approach

AbstractThe UK and Sweden have among the worst per-capita COVID-19 mortality in Europe. Sweden stands out for its greater reliance on voluntary, rather than mandatory, control measures. We explore how the timing and effectiveness of control measures in the UK, Sweden and Denmark shaped COVID-19 mortality in each country, using a counterfactual assessment: what would the impact have been, had each country adopted the others’ policies? Using a Bayesian semi-mechanistic model without prior assumptions on the mechanism or effectiveness of interventions, we estimate the time-varying reproduction number for the UK, Sweden and Denmark from daily mortality data. We use two approaches to evaluate counterfactuals which transpose the transmission profile from one country onto another, in each country’s first wave from 13th March (when stringent interventions began) until 1st July 2020. UK mortality would have approximately doubled had Swedish policy been adopted, while Swedish mortality would have more than halved had Sweden adopted UK or Danish strategies. Danish policies were most effective, although differences between the UK and Denmark were significant for one counterfactual approach only. Our analysis shows that small changes in the timing or effectiveness of interventions have disproportionately large effects on total mortality within a rapidly growing epidemic.

scholarly journals Effects of mobility and multi-seeding on the propagation of the COVID-19 in Spain

2020 ◽  
Author(s):  
Mattia Mazzoli ◽  
David Mateo ◽  
Alberto Hernando ◽  
Sandro Meloni ◽  
Jose Javier Ramasco
Keyword(s):  
Early Stage ◽  
High Mobility ◽  
Mobility Control ◽  
Control Measures ◽  
Order Effects ◽  
Crucial Importance ◽  
Epidemic Spreading ◽  
Susceptible Population ◽  
The Impact ◽  
Higher Order Effects

Assessing the impact of mobility on epidemic spreading is of crucial importance for understanding the effect of policies like mass quarantines and selective re-openings. High mobility between areas contribute to the importation of cases, affecting the spread of the disease. While many factors influence local incidence and making it more or less homogeneous with respect to other areas, the importance of multi-seeding has often been overlooked. Multi-seeding occurs when several independent (non-clustered) infected individuals arrive at a susceptible population. This can give rise to autonomous outbreaks that impact separate areas of the contact (social) network. Such mechanism has the potential to boost local incidence and size, making control and tracing measures less effective. In Spain, the high heterogeneity in incidence between similar areas despite the uniform mobility control measures taken suggests that multi-seeding could have played an important role in shaping the spreading of the disease. In this work, we focus on the spreading of SARS-CoV-2 among the $52$ Spanish provinces, showing that local incidence strongly correlates with mobility occurred in the early-stage weeks from and to Madrid, the main mobility hub and where the initial local outbreak unfolded. These results clarify the higher order effects that mobility can have on the evolution of an epidemic and highlight the relevance of its control.

scholarly journals Policy and Law Assessment of COVID-19 Based on Smooth Transition Autoregressive Model

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Jieqi Lei ◽  
Xuyuan Wang ◽  
Yiming Zhang ◽  
Lian Zhu ◽  
Lin Zhang
Keyword(s):  
Prevention And Control ◽  
Control Measures ◽  
Smooth Transition ◽  
Cumulative Number ◽  
Star Model ◽  
The World ◽  
Transition Points ◽  
And Control ◽  
The Impact ◽  
Smooth Transition Autoregressive

As of the end of October 2020, the cumulative number of confirmed cases of COVID-19 has exceeded 45 million and the cumulative number of deaths has exceeded 1.1 million all over the world. Faced with the fatal pandemic, countries around the world have taken various prevention and control measures. One of the important issues in epidemic prevention and control is the assessment of the prevention and control effectiveness. Changes in the time series of daily new confirmed cases can reflect the impact of policies in certain regions. In this paper, a smooth transition autoregressive (STAR) model is applied to investigate the intrinsic changes during the epidemic in certain countries and regions. In order to quantitatively evaluate the influence of the epidemic control measures, the sequence is fitted to the STAR model; then, comparisons between the dates of transition points and those of releasing certain policies are applied. Our model well fits the data. Moreover, the nonlinear smooth function within the STAR model reveals that the implementation of prevention and control policies is effective in some regions with different speeds. However, the ineffectiveness is also revealed and the threat of a second wave had already emerged.

scholarly journals How the Covid-19 Pandemic Influenced the Approach to Risk Management in Cycling Events

2021 ◽  
Vol 14 (7) ◽  
pp. 296
Author(s):  
Filippo Bazzanella ◽  
Nunzio Muratore ◽  
Philipp Alexander Schlemmer ◽  
Elisabeth Happ
Keyword(s):  
Risk Management ◽  
Social Life ◽  
Emergency Situation ◽  
Control Measures ◽  
Structured Interviews ◽  
Organizational Models ◽  
Sports Events ◽  
Crowd Control ◽  
Virus Spreading ◽  
The Impact

The COVID-19 pandemic has taught us to live in social isolation and has brought an important element of social life, the events industry, to a complete standstill. In resurrecting the events industry, the most urgent focus is on managing the risk of any crowd-control measures with a view to reducing to zero the danger of the virus spreading. This research focuses on the main issue of the impact of the coronavirus disease 2019 (COVID-19) on the organization of sports events (SEs), and in particular, cycling competitions. This study, therefore, aims to provide deeper insights into (a) the measures introduced to face the health emergency situation in cycling events, (b) the comparison of these measures with previous experiences in similar SE contexts, and (c) the possible evolution of organizational models for cycling events in the post-pandemic era. Fifteen semi-structured interviews with cycling athletes, managers, and officials constitute the methodological basis for this study. The results show that countermeasures have been taken that are effective in dealing with pandemic characteristics and are likely to be applied in the future, while others will be phased out or used again only when necessary. This study enhances scientific knowledge by analyzing a renewed approach to risk management for SEs, with a specific focus on pandemics and medical risks. Finally, the study shows that cycling events need to adapt the specifics of such a new approach to the standards projected on future scenarios for which the COVID-19 pandemic has paved the way.

scholarly journals Estimating the global reduction in transmission and rise in detection capacity of the novel coronavirus SARS-CoV-2 in early 2020

2020 ◽  
Author(s):  
Antoine Belloir ◽  
Francois Blanquart
Keyword(s):  
Probability Of Detection ◽  
Control Measures ◽  
Transmission Model ◽  
Time Varying ◽  
Strongly Correlated ◽  
The Novel ◽  
Novel Coronavirus ◽  
The Impact ◽  
Death Data ◽  
Global Reduction

To better control the SARS-CoV-2 pandemic, it is essential to quantify the impact of control measures and the fraction of infected individuals that are detected. To this end we developed a deterministic transmission model based on the renewal equation and fitted the model to daily case and death data in the first few months of 2020 in 79 countries and states, representing 4.2 billions individuals. Based on a region-specific infection fatality ratio, we inferred the time-varying probability of case detection and the time-varying decline in transmissiblity. As a validation, the predicted total number of infected was close to that found in serosurveys; more importantly, the inferred probability of detection strongly correlated with the number of daily tests per inhabitant, with 50% detection achieved with 0.003 daily tests per inhabitants. Most of the decline in transmission was explained by the reductions in transmissibility (social distancing), which avoided 10 millions deaths in the regions studied over the first four months of 2020. In contrast, symptom-based testing and isolation of positive cases was not an efficient way to control the spread of the disease, as a large part of transmission happens before symptoms and only a small fraction of infected individuals was typically detected. The latter is explained by the limited number of tests available, and the fact that increasing test capacity increases the probability of detection less than proportionally. Together these results suggest that little control can be achieved by symptom-based testing and isolation alone.

scholarly journals Reductions of Migrant Population Reduces the Number of COVID-19 Epidemic: A Case Study in China

2020 ◽  
Author(s):  
Lizhen Han ◽  
Jinzhu Jia
Keyword(s):  
Population Density ◽  
Generalized Additive Model ◽  
Hot Spot ◽  
Additive Model ◽  
Hubei Province ◽  
Control Measures ◽  
Cumulative Number ◽  
Migrant Population ◽  
High Prevalence ◽  
The Impact

Abstract Background: The novel coronavirus disease (COVID-19) broke out worldwide in 2020. The purpose of this paper was to find out the impact of migrant population on the epidemic, aiming to provide data support and suggestions for control measures in various epidemic areas. Methods: Generalized additive model was utilized to model the relationship between migrant population and the cumulative number of confirmed cases of COVID-19. The difference of spatial distribution was analyzed through spatial autocorrelation and hot spot analysis. Results: Generalized additive model demonstrated that the cumulative number of confirmed cases was positively correlated with migration index and population density. The predictive results showed that if no travel restrictions are imposed on the migrant population as usual, the total cumulative number of confirmed cases of COVID-19 would have reached 27 483 (95% CI: 16 074, 48 097; the actual number was 23 177). The increase in one city (Jian) would be 577.23% (95% CI: 322.73%, 972.73%) compared to the real confirmed cases of COVID-19. The average increase in 73 cities was 85.53% (95% CI: 19.53%, 189.81%). Among the migration destinations, the number of cases in cities of Hubei province, Chongqing and Beijing was relatively high, and there were large-scale high-prevalence clusters in eastern Hubei province. Meanwhile, without restrictions on migration, the high prevalence areas in Hubei province and its surrounding areas will be further expanded. Conclusions: The reduced population mobility and population density can greatly slow down the spread of the epidemic. All epidemic areas should suspend the transportation between cities, comprehensively and strictly control the population travel and decrease the population density, so as to reduce the spread of COVID-19.

scholarly journals Accounting for imported cases in estimating the time-varying reproductive number of COVID-19

2021 ◽  
Author(s):  
Tim K. Tsang ◽  
Peng Wu ◽  
Eric H. Y. Lau ◽  
Benjamin J. Cowling
Keyword(s):  
Public Health ◽  
Control Measures ◽  
Transmission Dynamics ◽  
Reproductive Number ◽  
Considerable Proportion ◽  
Time Varying ◽  
Health Measures ◽  
Imported Cases ◽  
The Impact ◽  
Local Transmission

ABSTRACTBackgroundEstimating the time-varying reproductive number, Rt, is critical for monitoring transmissibility of an emerging infectious disease during outbreaks. When local transmission is effectively suppressed, imported cases could substantially impact transmission dynamics.MethodsWe developed methodology to estimate separately the Rt for local cases and imported cases, since certain public health measures aim only to reduce onwards transmission from imported cases. We applied the framework to data on COVID-19 outbreaks in Hong Kong.ResultsWe estimated that the Rt for local cases decreased from above one in the early phase of outbreak to below one after tightening of public health measures. Assuming the same infectiousness of local and imported cases underestimated Rt for local cases due to control measures targeting travelers.ConclusionsWhen a considerable proportion of all cases are imported, the impact of imported cases in estimating Rt is critical. The methodology described here can allow for differential infectiousness of local imported cases.

Balanced Scorecard in the strategic planning of a construction company

2018 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Roberth Frias ◽  
Maria Medina
Keyword(s):  
Strategic Planning ◽  
Strategic Management ◽  
Balanced Scorecard ◽  
Organization Theory ◽  
Management Control ◽  
Management Tool ◽  
The Balanced Scorecard ◽  
Construction Company ◽  
Construction Companies ◽  
The Impact

This research focused on the strategic management tool Balanced Scorecard and strategic planning, as a guide to guide the management of companies, allowing communication and the functionality of the strategy using KPIs that allow to identify, maintain control and increase efficiency and the achievement of optimal results. For the deductive hypothetical analysis, the specific factors that affect business management performance were grouped into two variables: Balanced Scorecard and Strategic Planning. The objective of the work was to demonstrate the impact of the Balanced Scorecard in the strategic planning of a construction company. In order to support the research, the following theories were approached: the Financial Theory, the Economic Theory of the Company, the Transaction Costs, the Network Theory, the Organization Theory, the Dependence on Resources, the Strategic Management Theory and the Business Diagnosis Theory. The result obtained confirms the hypothesis that there is a significant incidence of the Balanced Scorecard in the strategic planning of construction companies. In conclusion, the construction company has obtained significant improvements in the results in each of the indicators evaluated with the implementation of the Balanced Scorecard, demonstrating improvements in their management results, affirming that there is better performance and management control allowing them to achieve the organizational objectives set.

Sign in / Sign up

Export Citation Format

Share Document