scholarly journals Improving prediction of COVID-19 evolution by fusing epidemiological and mobility data

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Santi García-Cremades ◽  
Juan Morales-García ◽  
Rocío Hernández-Sanjaime ◽  
Raquel Martínez-España ◽  
Andrés Bueno-Crespo ◽  
...  
Keyword(s):  
Health System ◽  
Herd Immunity ◽  
Multivariate Model ◽  
Main Criterion ◽  
Economic Activities ◽  
Medium Term ◽  
Policy Makers ◽  
Mobility Data ◽  
The Impact

AbstractWe are witnessing the dramatic consequences of the COVID-19 pandemic which, unfortunately, go beyond the impact on the health system. Until herd immunity is achieved with vaccines, the only available mechanisms for controlling the pandemic are quarantines, perimeter closures and social distancing with the aim of reducing mobility. Governments only apply these measures for a reduced period, since they involve the closure of economic activities such as tourism, cultural activities, or nightlife. The main criterion for establishing these measures and planning socioeconomic subsidies is the evolution of infections. However, the collapse of the health system and the unpredictability of human behavior, among others, make it difficult to predict this evolution in the short to medium term. This article evaluates different models for the early prediction of the evolution of the COVID-19 pandemic to create a decision support system for policy-makers. We consider a wide branch of models including artificial neural networks such as LSTM and GRU and statistically based models such as autoregressive (AR) or ARIMA. Moreover, several consensus strategies to ensemble all models into one system are proposed to obtain better results in this uncertain environment. Finally, a multivariate model that includes mobility data provided by Google is proposed to better forecast trend changes in the 14-day CI. A real case study in Spain is evaluated, providing very accurate results for the prediction of 14-day CI in scenarios with and without trend changes, reaching 0.93 $$R^2$$ R 2 , 4.16 RMSE and 1.08 MAE.

scholarly journals Enhancing the prediction of COVID-19 evolution by combining models and data sources

2021 ◽  
Author(s):  
Santi García-Cremades ◽  
Juan Morales-García ◽  
Rocío Hernández-Sanjaime ◽  
Raquel Martínez-España ◽  
Andrés Bueno-Crespo ◽  
...  
Keyword(s):  
Health System ◽  
Herd Immunity ◽  
Early Warning Systems ◽  
Warning Systems ◽  
Main Criterion ◽  
Economic Activities ◽  
Medium Term ◽  
Policy Makers ◽  
Mobility Data ◽  
The Impact

Abstract We are witnessing the dramatic consequences of the COVID-19 pandemic which, unfortunately, go beyond the impact on the health system. Until herd immunity is achieved with vaccines, the only available mechanisms for controlling the pandemic are quarantines, perimeter closures and social distancing with the aim of reducing mobility. Governments only apply these measures for a reduced period of time, since they involve the closure of economic activities such as tourism, cultural activities or nightlife. The main criterion for establishing these measures and planning socioeconomic subsidies is the evolution of infections. Early warning systems in all countries monitor the COVID-19 pandemic evolution. However, the collapse of the health system and the unpredictability of human behaviour, among others, make it difficult to predict this evolution in the short to medium term. This article evaluates different models for the early prediction of the evolution of the COVID-19 pandemic to create a decision support system for policy-makers. We consider a wide branch of models including artificial neural networks such as LSTM and GRU and statistically-based models such as autoregressive (AR) or ARIMA. Moreover, several consensus strategies to ensemble all models into one system are proposed to obtain better results in this uncertain environment. Our results reveal that the ensemble of different models improves the overall accuracy of the prediction, reaching up to 0.93 $R^2$, 4.16 RMSE and 3.55 MAE when there are not trend changes in the time-series. Mobility data provided by Google mobility data is also considered as exogenous information for our ensemble model to forecast trend changes, providing a good framework for a complete inference.

Empowering Women Entrepreneurs Through Microfinance - A Case of Rural Bangladesh

2017 ◽  
Vol 3 (2) ◽  
pp. 7
Author(s):  
Saida Parvin
Keyword(s):  
Women's Empowerment ◽  
Assessment Tools ◽  
Women’S Empowerment ◽  
Case Study Method ◽  
Policy Makers ◽  
Theoretical Contribution ◽  
Donor Agencies ◽  
Definition Of ◽  
The Impact

Women’s empowerment has been at the centre of research focus for many decades. Extant literature examined the process, outcome and various challenges. Some claimed substantial success, while others contradicted with evidence of failure. But the success remains a matter of debate due to lack of empirical evidence of actual empowerment of women around the world. The current study aimed to address this gap by taking a case study method. The study critically evaluates 20 cases carefully sampled to include representatives from the entire country of Bangladesh. The study demonstrates popular beliefs about microfinance often misguide even the borrowers and they start living in a fabricated feeling of empowerment, facing real challenges to achieve true empowerment in their lives. The impact of this finding is twofold; firstly there is a theoretical contribution, where the definition of women’s empowerment is proposed to be revisited considering findings from these cases. And lastly, the policy makers at governmental and non-governmental organisations, and multinational donor agencies need to revise their assessment tools for funding.

An Analytical Approach to Cruise Tourism As an Option For Development: a Case Study of the Sultanate of Oman

2020 ◽  
Vol 15 (2) ◽  
pp. 95-109
Author(s):  
Heba Aziz ◽  
Osman El-Said ◽  
Marike Bontenbal
Keyword(s):  
Capital City ◽  
Sultanate Of Oman ◽  
Policy Makers ◽  
Cruise Tourism ◽  
The Impact ◽  
The Relationship ◽  
Average Expenditure ◽  
Return Intention

The objective of this study was to measure the level of cruise tourists' satisfaction as well as the relationship between satisfaction, recommendation, return intention, and expenditure. Also, the impact of factors such as nationality, length of the visit, and age on the level of expenditure was measured. An empirical approach for data collection was followed and a total of 152 questionnaires were collected from cruise tourists visiting the capital city of Oman, Muscat, as cruise liners anchor at Sultan Qaboos Port. Results of the regression analysis supported the existence of a causal relationship between satisfaction with destination attributes, overall satisfaction, recommendation, return intention, and expenditure. It was found that the average expenditure varies according to age and length of the visit. Recommendations for policy makers were suggested on how to increase the role of cruise tourism in strengthening the economy.

scholarly journals Observing the silent world under COVID-19 with a comprehensive impact analysis based on human mobility

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shaobin Wang ◽  
Yun Tong ◽  
Yupeng Fan ◽  
Haimeng Liu ◽  
Jun Wu ◽  
...  
Keyword(s):  
Impact Analysis ◽  
Human Mobility ◽  
Economic Activities ◽  
Underdeveloped Countries ◽  
Mobility Data ◽  
Long Run ◽  
Level Of Economic Development ◽  
Human World ◽  
Dynamic Relationships ◽  
The Impact

AbstractSince spring 2020, the human world seems to be exceptionally silent due to mobility reduction caused by the COVID-19 pandemic. To better measure the real-time decline of human mobility and changes in socio-economic activities in a timely manner, we constructed a silent index (SI) based on Google’s mobility data. We systematically investigated the relations between SI, new COVID-19 cases, government policy, and the level of economic development. Results showed a drastic impact of the COVID-19 pandemic on increasing SI. The impact of COVID-19 on human mobility varied significantly by country and place. Bi-directional dynamic relationships between SI and the new COVID-19 cases were detected, with a lagging period of one to two weeks. The travel restriction and social policies could immediately affect SI in one week; however, could not effectively sustain in the long run. SI may reflect the disturbing impact of disasters or catastrophic events on the activities related to the global or national economy. Underdeveloped countries are more affected by the COVID-19 pandemic.

scholarly journals Benefits and Challenges of Policy Options in Rationing the Hospital Radiology Services: A Case Study

2020 ◽  
Author(s):  
Hasan Jafari ◽  
Mohammad Ranjbar ◽  
Hamideh Mahjoub ◽  
Hamed Ghoshoni ◽  
Mohammad Baghi ◽  
...  
Keyword(s):  
Health System ◽  
Supply And Demand ◽  
Knowledge Network ◽  
System Level ◽  
Radiology Department ◽  
Policy Options ◽  
Policy Makers ◽  
Rationing Policy ◽  
Care Costs

Objective: In many countries, limiting the financial and budgetary resources is a challenge in the health system. One of the most costly parts of the health system is undoubtedly the radiology department of hospitals. Therefore, this study aimed to determine the benefits and challenges of the policies proposed for rationing hospital radiology services. Information sources and selected methods for study: In this narrative or literature review study, Persian (SID, Magiran, Barkat Knowledge network system, Irandoc), and Latin (Google Scholar, PubMed, Scopus, ISI web of sciences) databases were searched. The applied keywords were radiology, rationing, distribution, priority setting, resource allocation, and policy brief. In the initial search, 145 articles were studied. Subsequently, after reviewing the titles and abstracts, 65 studies were selected and investigated. Finally, 44 related studies were thoroughly investigated. The inclusion criteria covered the studies in Persian or English. The exclusion criteria included the studies that did not have full texts. Our search included the studies conducted from 1/1/2000 to 1/1/ 2017. Results: The present study examined the benefits and challenges of radiology services rationing. Policy options were presented at 3 levels of provider, organizational, and system. The provider level consisted of training clinical and non-clinical personnel to use and maintain the medical equipment and requiring the physicians to use clinical guidelines. The organization level included reviewing imaging tariffs, entering insurance in controlling supply and demand for radiology services, and assessing equipment by the Institute for Health Technology Assessment. The system level contained assignment of radiological services to the private sector. Conclusion: As health care costs are rising and resources are increasingly constrained by ever-increasing demands, policy makers and officials can use the proposed solutions with regard to contextual conditions to design a rationing model. Services at the macro level of the health system and operationalization of the rationing process reduce the gap between supply and demand of the health services.  

scholarly journals Comparison of two individual-based model simulators for HIV epidemiology in a population with HSV-2 using as case study Yaoundé-Cameroon, 1980-2005

2019 ◽  
Author(s):  
Diana M Hendrickx ◽  
João Dinis Sousa ◽  
Pieter J.K. Libin ◽  
Wim Delva ◽  
Jori Liesenborgs ◽  
...  
Keyword(s):  
Model Complexity ◽  
Individual Based Model ◽  
Policy Makers ◽  
Basic Model ◽  
Hiv Epidemiology ◽  
Hiv Epidemic ◽  
Simplex Virus ◽  
Evidence For Policy ◽  
The Impact

ABSTRACTModel comparisons have been widely used to guide intervention strategies to control infectious diseases. Agreement between different models is crucial for providing robust evidence for policy-makers because differences in model properties can influence their predictions. In this study, we compared models implemented by two individual-based model simulators for HIV epidemiology in a population with Herpes simplex virus type 2 (HSV-2). For each model simulator, we constructed four models, starting from a simplified basic model and stepwise including more model complexity. For the resulting eight models, the predictions of the impact of behavioural interventions on the HIV epidemic in Yaoundé (Cameroon) were compared. The results show that differences in model assumptions and model complexity can influence the size of the predicted impact of the intervention, as well as the predicted qualitative behaviour of the HIV epidemic after the intervention. Moreover, two models that agree in their predictions of the HIV epidemic in the absence of intervention can have different outputs when predicting the impact of interventions. Without additional data, it is impossible to determine which of these two models is the most reliable. These findings highlight the importance of making more data available for the calibration and validation of epidemiological models.

scholarly journals Analysis of Emergency Evacuation Modal Choice Behavior with Spatial Indicators: Case Study in Xi’an, China

2019 ◽  
Vol 11 (24) ◽  
pp. 7023
Author(s):  
Zhihao Duan ◽  
Jinliang Xu ◽  
Han Ru ◽  
Yaping Dong ◽  
Xingliang Liu
Keyword(s):  
Choice Behavior ◽  
Multinomial Logit Model ◽  
Emergency Evacuation ◽  
Policy Makers ◽  
Effective Measure ◽  
Modal Choice ◽  
Emergency Events ◽  
Spatial Indicators ◽  
The Impact

To reduce the impact of a natural or man-made disaster, an evacuation is often implemented to transfer the population in the potentially impacted area to a safe zone. Evacuation is an effective measure for dealing with emergency events. This paper presents a multinomial logit model for modal choice behavior in a short-notice emergency evacuation, which incorporates spatial indicators into the utility function. The study examined the determinants of evacuees’ modal choice for three evacuation distances and analyzed determinants impacting the mechanism of the modal choice decision process. The data collected in Xi’an was used to provide empirical evidence for the relationship between spatial indicators and modal choice behavior. The findings of this study will help emergency planners and policy-makers develop strategies for evacuation planning and will enable a better understanding of emergency modal choice behaviors.

scholarly journals Smart mobility, age and data justice

2020 ◽  
pp. 146144482090268 ◽  
Author(s):  
Maria Sourbati ◽  
Frauke Behrendt
Keyword(s):  
Public Service ◽  
Social Inclusion ◽  
Data Gathering ◽  
Data Driven ◽  
Policy Makers ◽  
Mobility Data ◽  
Strategic Approach ◽  
Data Gaps ◽  
Smart Mobility

This article examines converging trends in ageing, digitalisation and datafication in the context of mobility and transport. While mobility data are increasingly captured by (public) transport and mobility as a service (MaaS) providers, Internet of Things (IoT) vehicles, apps and so on, the increasing entanglement of mobility and datafication happens unevenly, for example, in relation to age. This is particularly significant in the light of the rise of data-driven policy-making, and its potential impacts on mobility provision for older people. The article highlights new questions for public policy around data gaps and social inclusion and examines them through a UK case study. The results show that old age and mobility is an area with significant gaps in the data available to policy makers. A key recommendation is for commissioning bodies to develop a strategic approach to structured data gathering and analysis that addresses issues of exclusion from smart public service infrastructure.

Promoting entrepreneurial intention through a higher education program integrated in an entrepreneurship ecosystem

2018 ◽  
Vol 10 (1) ◽  
pp. 6-21 ◽  
Author(s):  
Julia Ferrandiz ◽  
Pilar Fidel ◽  
Andrea Conchado
Keyword(s):  
Higher Education ◽  
Group Dynamics ◽  
Education Program ◽  
Current Knowledge ◽  
Practical Experience ◽  
Entrepreneurial Intention ◽  
Medium Term ◽  
Content Type ◽  
The Impact

Purpose The purpose of this paper is to improve the current knowledge of the effects of a higher education program for entrepreneurs, integrated in an entrepreneurial ecosystem, in the entrepreneurial intention of the students. Design/methodology/approach For this, group dynamics have been carried out with the students to know the process of entrepreneurial learning, the acquisition of competences, the mentoring received and the influence of the program in its entrepreneurial intention in the short and medium term. Findings The results suggest that the program positively influences students’ entrepreneurial intention, especially in the medium term. In particular, they point out that working personal skills in the program contribute to the development of their entrepreneurial project. On the other hand, mentoring requires a more methodical accompaniment and a greater degree of specialization of the mentors. Research limitations/implications This research represents an excellent first step toward a better understanding of the factors that influence entrepreneurial intention. In addition, they lead to improve existing knowledge about the impact of entrepreneurial higher education. The only limitation of the paper is given by its nature as a case study. Practical implications The case study aims to provide the results of the practical experience of a higher education program in entrepreneurship and serve as a basis for future lines of research that address the research gap based on the need of identification of best practices in entrepreneurship education and entrepreneurial behavior. Social implications This work brings practical experience that inspires diverse social actors as managers of higher education programs, managers of ecosystems entrepreneurs and public institutions. Originality/value Our findings respond to previous concerns on the results of programs aimed at training future entrepreneurs. Besides, this work describes an interesting case study based on a postgraduate program, while most of the previous studies have been limited to undergraduate programs.

scholarly journals An engineering model of the COVID-19 trajectory to predict the success of isolation initiatives

2021 ◽  
Vol 2 ◽  
Author(s):  
Steven King ◽  
Alberto Striolo
Keyword(s):  
Social Studies ◽  
Age Groups ◽  
Optimal Solution ◽  
Epidemiological Models ◽  
Engineering Model ◽  
Medium Term ◽  
Policy Makers ◽  
Successful Isolation ◽  
The Uk ◽  
The Impact

Much media and societal attention is today focused on how to best control the spread of coronavirus (COVID-19). Every day brings us new data, and policy makers are implementing different strategies in different countries to manage the impact of COVID-19. To respond to the first ‘wave’ of infection, several countries, including the UK, opted for isolation/lockdown initiatives, with different degrees of rigour. Data showed that these initiatives have yielded the expected results in terms of containing the rapid trajectory of the virus. When this article was first prepared (April 2020), the affected societies were wondering when the isolation/lockdown initiatives should be lifted. While detailed epidemiological, economic as well as social studies would be required to answer this question completely, here we employ a simple engineering model. Albeit simple, the model is capable of reproducing the main features of the data reported in the literature concerning the COVID-19 trajectory in different countries, including the increase in cases in countries following the initially successful isolation/lockdown initiatives. Keeping in mind the simplicity of the model, we attempt to draw some conclusions, which seem to suggest that a decrease in the number of infected individuals after the initiation of isolation/lockdown initiatives does not necessarily guarantee that the virus trajectory is under control. Within the limit of this model, it would seem that rigid isolation/lockdown initiatives for the medium term would lead to achieving the desired control over the spread of the virus. This observation seems consistent with the 2020 summer months, during which the COVID-19 trajectory seemed to be almost under control across most European countries. Consistent with the results from our simple model, winter 2020 data show that the virus trajectory was again on the rise. Because the optimal solution will achieve control over the spread of the virus while minimising negative societal impacts due to isolation/lockdown, which include but are not limited to economic and mental health aspects, the engineering model presented here is not sufficient to provide the desired answer. However, the model seems to suggest that to keep the COVID-19 trajectory under control, a series of short-to-medium term isolation measures should be put in place until one or more of the following scenarios is achieved: a cure has been developed and has become accessible to the population at large; a vaccine has been developed, tested and distributed to large portions of the population; a sufficiently large portion of the population has developed resistance to the COVID-19 virus; or the virus itself has become less aggressive. It is somewhat remarkable that an engineering model, despite all its approximations, provides suggestions consistent with advanced epidemiological models developed by several experts in the field. The model proposed here is however not expected to be able to capture the emergence of variants of the virus, which seem to be responsible for significant outbreaks, notably in India, in the spring of 2021, it cannot describe the effectiveness of vaccine strategies, as it does not differentiate among different age groups within the population, nor does it allow us to consider the duration of the immunity achieved after infection or vaccination.

Sign in / Sign up

Export Citation Format

Share Document