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1.
11th Simulation Workshop, SW 2023 ; : 184-193, 2023.
Article in English | Scopus | ID: covidwho-20241269

ABSTRACT

This paper describes a hybrid (virtual and online) workshop held as part of the EU STAMINA project that aimed to engage project partners to explore ethics and simulation modelling in the context of pandemic preparedness and response. The purpose of the workshop was to consider how the model's design and use in specific pandemic decision-making contexts could have broader implications for issues like transparency, explainability, representativeness, bias, trust, equality, and social injustices. Its outputs will be used as evidence to produce a series of measures that could help mitigate ethical harms and support the greater possible benefit from the use of the models. These include recommendations for policy, data-gathering, training, potential protocols to support end-user engagement, as well as guidelines for designing and using simulation models for pandemic decision-making. This paper presents the methodological approaches taken when designing the workshop, practical concerns raised, initial insights gained, and considers future steps. © SW 2023.All rights reserved

2.
Weather, Climate, and Society ; 15(1):177-193, 2023.
Article in English | Scopus | ID: covidwho-2292622

ABSTRACT

Machine learning was applied to predict evacuation rates for all census tracts affected by Hurricane Laura. The evacuation ground truth was derived from cellular telephone–based mobility data. Twitter data, census data, geographical data, COVID-19 case rates, the social vulnerability index from the Centers for Disease Control and Prevention (CDC)/Agency for Toxic Substances and Disease Registry (ATSDR), and relevant weather and physical data were used to do the prediction. Random forests were found to perform well, with a mean absolute percent error of 4.9% on testing data. Feature importance for prediction was analyzed using Shapley additive explanations and it was found that previous evacuation, rainfall forecasts, COVID-19 case rates, and Twitter data rank highly in terms of importance. Social vulnerability indices were also found to show a very consistent relationship with evacuation rates, such that higher vulnerability consistently implies lower evacuation rates. These findings can help with hurricane evacuation preparedness and planning as well as real-time assessment. © 2023 American Meteorological Society.

3.
3rd IEEE India Council International Subsections Conference, INDISCON 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2052028

ABSTRACT

In this digital era of online processing, most information is accessible electronically and is prone to cyber threats. There is a vast range of cyber threats whose behavior is hard to understand in the early phases. These attacks may have some motivation behind them that have significant societal impacts in the form of economic damage, psychological disturbance, a threat to national security, and so on. With the worldwide spread of COVID-19, India experienced an astonishing 86% rise in cybercrimes. Nowadays, cybercrime has become an attractive strategy for hackers to create chaos and disruption. This paper is based on the quantitative analysis of cybercrime in India and its impacts on society, with preventive measures to handle them. In our study, we found that digital related offenses and online frauds are drastically increasing in India during COVID-19 pandemic. As a result, awareness campaigns and security solutions are needed to prevent or mitigate them. © 2022 IEEE.

4.
21st ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2022 ; : 15-27, 2022.
Article in English | Scopus | ID: covidwho-2018899

ABSTRACT

With the recent societal impact of COVID-19, companies and government agencies alike have turned to thermal camera based skin temperature sensing technology to help screen for fever. However, the cost and deployment restrictions limit the wide use of these thermal sensing technologies. In this work, we present SIFTER, a low-cost system based on a RGB-thermal camera for continuous fever screening of multiple people. This system detects and tracks heads in the RGB and thermal domains and constructs thermal heat map models for each tracked person, and classifies people as having or not having fever. SIFTER can obtain key temperature features of heads in-situ at a distance and produce fever screening predictions in real-time, significantly improving screening through-put while minimizing disruption to normal activities. In our clinic deployment, SIFTER measurement error is within 0.4°F at 2 meters and around 0.6°F at 3.5 meters. In comparison, most infrared thermal scanners on the market costing several thousand dollars have around 1°F measurement error measured within 0.5 meters. SIFTER can achieve 100% true positive rate with 22.5% false positive rate without requiring any human interaction, greatly outperforming our baseline [1], which sees a false positive rate of 78.5%. © 2022 IEEE.

5.
Weather, Climate, and Society ; 13(3):555-570, 2021.
Article in English | ProQuest Central | ID: covidwho-1892033

ABSTRACT

This study determines the conditions and provides a recommendation for fostering cocreation for climate change adaptation and mitigation (CCA&M). In postulating that insufficient cocreation by stakeholders in the quadruple helix model is an important factor contributing to the low effectiveness of climate actions in the regions, we have focused our research on identifying real stakeholder engagement in climate action and identifying the needs, barriers, and drivers for strengthening the cocreation process. We identified the needs for action highlighted by stakeholders as having an impact on reducing barriers and stimulating drivers. We treated the identified needs for action as deep leverage points (intent and design) focused on three realms—knowledge, values, and institutions—in which engagement and cocreation can be strengthened and have the potential to increase the effectiveness of climate action taken by stakeholders within our quadruple helix. We recommend knowledge-based cocreation, which puts the importance of climate action in the value system and leads to paradigm reevaluation. The implementation of the identified needs for action requires the support of institutions, whereby they develop standards of cooperation and mechanisms for their implementation as a sustainable framework for stakeholder cooperation. The research has proved how the quadruple helix operates for climate action in the Poznań Agglomeration. We believe that this case study can be a reference point for regions at a similar level of development, and the methods used and results obtained can be applied in similar real contexts to foster local stakeholders in climate action.

7.
21st European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2021 ; 1525 CCIS:259-266, 2021.
Article in English | Scopus | ID: covidwho-1750520

ABSTRACT

Natural language processing (NLP) plays a significant role in tools for the COVID-19 pandemic response, from detecting misinformation on social media to helping to provide accurate clinical information or summarizing scientific research. However, the approaches developed thus far have not benefited all populations, regions or languages equally. We discuss ways in which current and future NLP approaches can be made more inclusive by covering low-resource languages, including alternative modalities, leveraging out-of-the-box tools and forming meaningful partnerships. We suggest several future directions for researchers interested in maximizing the positive societal impacts of NLP. © 2021, Springer Nature Switzerland AG.

8.
IEEE Access ; 2022.
Article in English | Scopus | ID: covidwho-1730830

ABSTRACT

Nowadays, the Internet of Things (IoT) has an astonishingly societal impact in which healthcare services stand out. Amplified by the COVID-19 pandemic scenario, challenges include the development of authenticatable smart IoT devices with the ability to simultaneously track people and sense in real-time human body temperature aiming to infer a health condition in a contactless and remote way through user-friendly equipment such as a smartphone. Univocal smart labels based on quick response (QR) codes were designed and printed on medical substrates (protective masks and adhesive) using flexible organic-inorganic luminescent inks. Luminescence thermometry and physically unclonable functions (PUFs) are simultaneously combined allowing non-contact temperature detection, identification, and connection with the IoT environment through a smartphone. This is an intriguing example where luminescent inks based on organic-inorganic hybrids modified by lanthanide ions are used to fabricate a smart label that can sense temperature with remarkable figures of merit, including maximum thermal sensitivity of Sr=1.46 %K-1 and temperature uncertainty of dT=0.2 K, and accuracy, precision, and recall of 96.2%, 98.9%, and 85.7%, respectively. The methodology proposed is feasibly applied for the univocal identification and mobile optical temperature monitoring of individuals, allowing the control of the access to restricted areas and the information transfer to medical entities for post medical evaluation towards a new generation of mobile-assisted eHealth (mHealth). Author

9.
Interface Focus ; 12(2), 2022.
Article in English | Scopus | ID: covidwho-1700516

ABSTRACT

The COVID-19 pandemic, caused by the virus SARS-CoV-2, has touched most parts of the world and devastated the lives of many. The high transmissibility coupled with the initial poor outcome for the elderly led to crushingly high fatalities. The scientific response to the pandemic has been formidable, aided by advancements in virology, computing, data analysis, instrumentation, diagnostics, engineering and infection control. This has led to improvements in understanding and has helped to challenge some established orthodoxies. Sufficient time has elapsed since the start of the COVID-19 pandemic that a clearer view has emerged about transmission and infection risks, public health responses and related societal and economic impacts. This timely volume has provided an opportunity for the science community to report on these new developments. © 2022 The Authors.

10.
Weather Climate and Society ; 13(4):963-973, 2021.
Article in English | Web of Science | ID: covidwho-1691176

ABSTRACT

The coronavirus disease 2019 (COVID-19) pandemic resulted in unprecedented challenges that dramatically affected the way of life in the United States and globally in 2020. The pandemic also made the process of protecting individuals from tornadoes more challenging, especially when their personal residence lacks suitable shelter, and particularly for residents of mobile homes. The necessity of having to shelter with other families-either in a public shelter or at another residence-to protect themselves from a tornado threat conflicted with the advice of public health officials who recommended avoiding public places and limiting contact with the public to minimize the spread of COVID-19. There was also a perception that protecting against one threat could amplify the other threat. Asurvey was undertaken with the public to determine the general viewpoint to see if that was indeed the case. The results found that it was possible to attenuate both threats provided that careful planning and actions were undertaken. Understanding how emergency managers should react and plan for such dual threats is important to minimize the spread of COVID-19 while also maintaining the safety of the public. Because there was no precedence for tornado protection scenarios amid a pandemic, both short-term and long-term recommendations were suggested that may also be useful in future pandemic situations.

11.
18th International Conference on Information Systems for Crisis Response and Management, ISCRAM 2021 ; 2021-May:218-227, 2021.
Article in English | Scopus | ID: covidwho-1589570

ABSTRACT

The devastating economic and societal impacts of COVID-19 can be substantially compounded by other secondary events that increase individuals' exposure through mass gatherings such as protests or sheltering due to a natural disaster. Based on the Crichton's Risk Triangle model, this paper proposes a Markov Chain Monte Carlo (MCMC) simulation framework to estimate the impact of mass gatherings on COVID-19 infections by adjusting levels of exposure and vulnerability. To this end, a case study of New York City is considered, at which the impact of mass gathering at public shelters due to a hypothetical hurricane will be studied. The simulation results will be discussed in the context of determining effective policies for reducing the impact of multi-hazard generalizability of our approach to other secondary events that can cause mass gatherings during a pandemic will also be discussed. © 2021 Information Systems for Crisis Response and Management, ISCRAM. All rights reserved.

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