Lockdown Strategies, Mobility Patterns and Covid-19

Askitas, Nikos; Tatsiramos, Konstantinos; Verheyden, Bertrand

doi:10.2139/ssrn.3614241

Cited by 58 publications

(42 citation statements)

References 1 publication

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“…Askitas et al proposed a multi-event model to study the effects of different overlapping and non-overlapping intervention measures varying in timing, duration, and intensity on the overall incidence of COVID-19 and the resultant mobility patterns [75]. Pestieau studied how the lockdown strategies, namely uniform lockdowns and age-differentiated lockdowns, align with social welfare criterion, balancing the trade-off between economy and lives lost [76].…”

Section: Dynamic Lockdown Strategiesmentioning

confidence: 99%

Towards a Unified Pandemic Management Architecture: Survey, Challenges and Future Directions

Roy¹,

Ghosh²,

Uplavikar³

et al. 2022

Preprint

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The pandemic caused by SARS-CoV-2 has left an unprecedented impact on health, economy and society worldwide. Emerging strains are making pandemic management increasingly challenging. There is an urge to collect epidemiological, clinical, and physiological data to make an informed decision on mitigation measures. Advances in the Internet of Things (IoT) and edge computing provide solutions for pandemic management through data collection and intelligent computation. While existing data-driven architectures attempt to automate decision-making, they do not capture the multifaceted interaction among computational models, communication infrastructure, and the generated data. In this paper, we perform a survey of the existing approaches for pandemic management, including online data repositories and contact-tracing applications. We then envision a unified pandemic management architecture that leverages the IoT and edge computing to automate recommendations on vaccine distribution, dynamic lockdown, mobility scheduling and pandemic prediction. We elucidate the flow of data among the layers of the architecture, namely, cloud, edge and end device layers. Moreover, we address the privacy implications, threats, regulations, and existing solutions that may be adapted to optimize the utility of health data with security guarantees. The paper ends with a lowdown on the limitations of the architecture and research directions to enhance its practicality.

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Section: Dynamic Lockdown Strategiesmentioning

confidence: 99%

Towards a Unified Pandemic Management Architecture: Survey, Challenges and Future Directions

Roy¹,

Ghosh²,

Uplavikar³

et al. 2022

Preprint

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show abstract

“…The SEIR epidemiological model, and several variations of it, have been extensively studied both for the purpose of understanding dynamics [10,11,12,8,13,14,15] as well as optimal policy making [16,17,18,19,20]. For a comprehensive review see [21,22].…”

Section: A Seir Model With Mobilitymentioning

confidence: 99%

On the interplay between mobility and hospitalization capacity during the COVID-19 pandemic: The SEIRHUD model

Veloz¹,

Maldonado²,

Ropert³

et al. 2020

Preprint

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Measures to reduce the impact of the COVID-19 pandemic require a mix of logistic, political and social capacity. Depending on the country, different approaches to increase hospitalization capacity or to properly apply lock-downs are observed. In order to better understand the impact of these measures we have developed a compartmental model which, on the one hand allows to calibrate the reduction of movement of people within and among different areas, and on the other hand it incorporates a hospitalization dynamics that differentiates the available kinds of treatment that infected people can receive. By bounding the hospitalization capacity, we are able to study in detail the interplay between mobility and hospitalization capacity.

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“…These measures concerned the reduction in mobility and person-to-person contact. However, it needs to be clarified that measures varied from country to country (mobility was affected differently) [13,14]. Road transport and other transport modes were gradually restricted.…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

The Effect of the COVID-19 Pandemic on Traffic Flow Characteristics, Emissions Production and Fuel Consumption at a Selected Intersection in Slovakia

et al. 2022

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The surveyof traffic intensity is used to obtain information on the number of vehicles on roads during the day. Subsequently, it is possible to derive from this the daily, weekly, and other road traffic intensity information. This survey represents the basis for the calculation of the annual average daily traffic volume and the basic characteristics of traffic flow. The COVID-19 pandemic has caused extensive economic and social damage around the world. These damages have also affected traffic. Changes in traffic behavior have mainly affected the reduction in traffic intensity on road networks. Thanks to the reduction in the demand for transport, there has also been a significant reduction in traffic delays, fuel consumption and emissions. An examination of changes in traffic intensity took place at a selected intersection in 2019, 2020 and 2021. This paper describes the effects of reducing the traffic intensity, fuel consumption and emissions obtained by microsimulation. The results obtained confirmed the reduction in traffic, which also contributed to a significant reduction in vehicle delays.

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Lockdown Strategies, Mobility Patterns and Covid-19

Cited by 58 publications

References 1 publication

Towards a Unified Pandemic Management Architecture: Survey, Challenges and Future Directions

Towards a Unified Pandemic Management Architecture: Survey, Challenges and Future Directions

On the interplay between mobility and hospitalization capacity during the COVID-19 pandemic: The SEIRHUD model

The Effect of the COVID-19 Pandemic on Traffic Flow Characteristics, Emissions Production and Fuel Consumption at a Selected Intersection in Slovakia

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