Introduction to the Special Issue on Understanding the Spread of COVID-19, Part 1

Infectious diseases are transmitted between human hosts when in close contact over space and time. Recently, an unprecedented amount of spatial and spatiotemporal data have been made available that can be used to improve our understanding of the spread of COVID-19 and other infectious diseases. This understanding will be paramount to prepare for future pandemics through spatial algorithms and systems to collect, capture, curate, and analyze complex, multi-scale human movement data to solve problems such as infectious diseases prediction, contact tracing, and risk assessment. In exploring and deepening the conversation around this topic, the eight articles included in the first volume of this special issue employ diverse theoretical perspectives, methodologies, and frameworks, including but not limited to infectious diseases simulation, risk prediction, response policy design, mobility analysis, and case diagnosis. Rather than focusing on a narrow set of problems, these articles provide a glimpse into the diverse possibilities of leveraging spatial and spatiotemporal data for pandemic preparedness. © 2022 held by the owner/author(s).

Paleofire Data for Public Health Nursing Wildfire Planning: A Planetary Perspective

Public health Is Increasingly threatened by global warming, land use, and changing wildfire patterns that shape vegetation type, structure, and biodiversity and ultimately affect ecosystem services and our society.1 Uncontrolled large wildfires emit greenhouse gases and aerosols that induce direct and indirect climate feedback through radiative forcing in the atmosphere2 and irreversible changes of natural vegetation, thereby further accelerating climate change and associated fire risks.3 Wildfires are also harmful to human health because they create high pollution concentrations of fine particulate matter that are 2.5 micrometers or smaller (PM2.5) and concentrations of coarse particulate matter that are between 2.5 and 10 micrometers in size. When inhaled, particulate matter significantly increases a myriad of health outcomes, including overall mortality, cardiovascular mortality, and emergency department visits for respiratory morbidity, congestive heart failure, chronic obstructive pulmonary disease, and angina.4,5 Between July and October 2020, high PM2.5 concentrations from massive wildfires surrounding a large regional hospital in the western United States were associated with a 6% increase in COVID-19 cases.6 Risks for developing adverse health effects from wildfire smoke are greatest among people who are living with chronic conditions;who are experiencing intergenerational racial, economic, and housing discrimination;and who are facing social inequities from the COVID-19 pandemic.4The unprecedented recent wildfires in the western United States and their ill effects on human health and society, as well as the multiple other threats to people and places brought about by climate change, draw attention to the increasing urgency of developing new public health approaches and long-term adaptation strategies to support future population health. Observational fire data covering the past few decades give valuable information on current wildfire events.1 However, these data hardly capture long-term trends (i.e., centennial to millennial time scales) of wildfires and associated atmospheric emissions that may help to improve future fire models and thereby provide the base to adapt public health systems.3 To understand long-term trends, natural archives preserve fire history on a wide range ofspatial scales in the past beyond the period of observational fire data;examples include polar and highalpine ice cores;lake, peat, and marine sediment cores.3,8,9 Such paleofire records are based on measurements of the gaseous tracers ammonium and nitrate or particulate matter, such as levoglucosan and black carbon, and charcoal that reflect different components of wildfire-induced atmospheric smoke pollution.8,9 These paleofire records have previously identified complex regional interactions of humans, ecosystems, and climate change.3 Submicron-sized (100-500 nm in diameter) black carbon particles from wildfires and fossil fuel during the industrial era (i.e., the past 250 years) measured in ice cores and lake sediments can be used as a direct tracer for the release of harmful PM2.5 to the atmosphere.8,10 Such paleo black carbon records have been established from both polar and high-alpine glaciers on several continents and are recently developed from lake sediments.10 These found significant changes of fire activity in response to climate and human impact and enhanced pollution levels varying both in time and space. With public health nurses being well positioned to understand population health needs, planetary health, and the health consequences of wildfires, public health nurses can improve upon wildfire adaptation planning and essential public health services by understanding historical perspectives from past fires.9,11,13 Paleofire data provide direct estimates of historical atmospheric emissions from past wildfires and associated harmful concentrations of particulate matter over long distances.

Ruling Abstractions and Unruly Spaces

Olga Tokarczuk, The Book of Jacob A character in Olga Tokarczuk's magnificent novel The Book of Jacob refers to the time that is "not yet" historical;a time that is, in some ways, frozen, and as such excluded from the developmentalist and civilizationist historical narratives. Since its inception, the world-systems perspective has been concerned with the problem of historical time. In world-systems analysis, time and space are seen as substantive properties of social relations, and the network of relations that comprises the capitalist world economy produces its own temporal spatial and temporal configurations. [...]Çaǧrı Ídiman in the second part of his essay on Tributary World-Ecologies, brings into sharper historical relief the distinctive element of capitalist worldecology, distinguished from other world-ecologies by simultaneous transformation of productive relation and mode of appropriation of labor and nature.

PhyloView: A System to Visualize the Ecology of Infectious Diseases Using Phylogenetic Data

Since the onset of the COVID-19 pandemic, mil-lions of coronavirus sequences have been rapidly deposited in publicly available repositories. The sequences have been used primarily to monitor the evolution and transmission of the virus. In addition, the data can be combined with spatiotemporal information and mapped over space and time to understand transmission dynamics further. For example, the first COVID-19 cases in Australia were genetically related to the dominant strain in Wuhan, China, and spread via international travel. These data are currently available through the Global Initiative on Sharing Avian Influenza Data (GISAID) yet generally remains an untapped resource for data scientists to analyze such multi-dimensional data. Therefore, in this study, we demonstrate a system named Phyloview, a highly interactive visual environment that can be used to examine the spatiotemporal evolution of COVID-19 (from-to) over time using the case study of Louisiana, USA. PhyloView (powered by ArcGIsInsights) facilitates the visualization and exploration of the different dimensions of the phylogenetic data and can be layered with other types of spatiotemporal data for further investigation. Our system has the potential to be shared as a model to be used by health officials that can access relevant data through GISAID, visualize, and analyze it. Such data is essential for a better understanding, predicting, and responding to infectious diseases. © 2022 IEEE.

Municipal financial vulnerability in pandemic crises: a framework for analysis

Purpose>This paper explores how global pandemic crises affect the financial vulnerability of municipalities.Design/methodology/approach>This paper is developed from the relevant literature an analytical framework to examine municipal financial vulnerability before a global pandemic crisis and in its immediate aftermath by mapping and systematizing its dimensions and sources. To illustrate how it can be used and evaluate its robustness and flexibility, such a tool was applied to Portugal and Italy, two countries that particularly suffered from the Covid-19 crisis.Findings>The application of the analytical framework has shown how financially vulnerable municipalities are to global pandemic crises. Financial vulnerability relates to issues ranging from institutional design to internal financial conditions and the perception of the capacity to cope with a crisis. Results further reveal that vulnerability has an inherent contingent nature in time and space and can lead to paradoxical outcomes.Research limitations/implications>This paper provides a tool that can be useful for both academic and public policy purposes, to further appreciate municipal financial vulnerability, especially during crises.Practical implications>Municipalities can use the framework to better manage their financial vulnerability, strengthening their anticipatory and copying capacities, while oversight authorities can use it to help municipalities become less financially vulnerable or, at least, more aware of their financial vulnerability.Originality/value>Municipal financial vulnerability to global shocks has not been explored extensively. Also, the Covid-19 pandemic is different from previous global crises as it affected society overnight with the implementation of lockdown and social distancing measures.

Family Issues. Difficulties in Migrant Family Life Exacerbated by the Pandemic

Most of the time, when we talk about the family, we think of the indigenous family, but what happens when the focus shifts to foreign families? Furthermore, in a time of pandemic, what repercussions and impacts have there been on foreign families? And have the interventions proposed by the government to deal with COVID-19 and to support families, taken foreign families into account? The issue is quite complex because it has to deal, on the one hand, with definitional problems related to the difficulties in identifying types of foreign families (Ambrosini, 2020b) present in Italy, and, on the other hand, with an analysis of the impact that the virus has had on family structures. Migrant families represent heterogeneous contexts where there is constant, dynamic interaction between structural dimensions, cultural aspects and subjective choices, and during the pandemic, these have become "families in the balance", vulnerable actors, subjected to extreme marginality. There are many issues, such as the home, which, for example, has become a space/place where to spend one's time and experiment with forms of smart working, but many of the homes where migrant families live are not organised to cope with the pandemic and often reflect a pronounced inequality. Moreover, one should remember that, in Italy in 2019, 65.5% (Istat, 2020) of foreigners were employed in the service sector. It is difficult to imagine activities in these sectors being carried out at a distance. This paper, taking its cue from the cognitive questions posed, will propose a reflection on the situation in Sicily with a focus on the city of Palermo.

Propose a New Quality Model for M-Learning Application in Light of COVID-19

The coronavirus disease (COVID-19) prevented millions of students around the world from receiving their lessons, because of the closure of thousands of schools. The new COVID-19 global epidemic invaded the barriers of time and space. Using mobile phones in education is a new form of the distance learning system. M-learning is characterized by many characteristics, the most important of which are providing an interactive educational environment, flexibility in space and time, better adaptation to individual needs, acquisition of knowledge, interactive effectiveness, and developing self-learning skills for students. The main aim of this paper is to suggest a quality model for M-learning applications for children which contains the most common characteristics of M-learning, which must be taken into account when designing M-learning applications. Through previous studies related to the quality model for M-learning applications, we proposed two quality characteristics, technical and pedagogical. We proposed 8 subcharacteristics with their features following the structure of the IOS/IEC 912 and DeLone and McLean IS model to find the effect of technical and pedagogical factors on user satisfaction with M-learning applications for children. Results show that the proposed model can be useful and effective to ensure the development of high-quality M-learning applications. © 2022 Ahmad Althunibat et al.

Agent-based Modeling as a Tool for Predicting the Spatial-temporal Diffusion of the COVID-19 Pandemic

The article presents the original methodology of using agent-based modeling (ABM) for the numerical simulations of the COVID-19 pandemic's development. The proposed solution makes it possible to analyze changes in the number of cases both in space and time. The devised methodology enables considering spatial conditions in terms of population distribution, such as places of work, rest, or residence, and uses multi-agent modeling to consider spatial interactions. Numerical simulations utilize the spatial and demographic data in GIS databases and the GAMA environment that enables the parameterization of the epidemiological model. Testing the developed methodology on a test area also allowed for checking the effects of a potential decrease or increase in social restrictions numerically. The simulations performed show a high correlation between the level of social distancing and the number of COVID-19 cases. © 2021 IEEE.

“Just because people are old, just because they're ill…” dignity matters in district nursing

PurposeThis paper aims to explore the concept and practice, of dignity as understood and experienced by older adults and district nursing staff. The paper adds a new, nuanced, understanding of safeguarding possibilities in the context of district nursing care delivered in the home.Design/methodology/approachThe research used an ethnographic methodology involving observations of care between community district nursing clinicians and patients (n = 62) and semi-structured interviews with nursing staff (n = 11) and older adult recipients of district nursing care (n = 11) in England.FindingsAbuse is less likely to occur when clinicians are maintaining the dignity of their patients. The themes of time and space are used to demonstrate some fundamental ways in which dignity manifests. The absence of dignity offers opportunities for abuse and neglect to thrive;therefore, both time and space are essential safeguarding considerations. Dignity is influenced by time and how it is experienced temporally, but nurses are not allocated time to “do dignity”, an arguably essential component of the caregiving role, yet one that can become marginalised. The home-clinic exists as a clinical space requiring careful management to ensure it is also an environment of dignity that can safeguard older adults.Practical implicationsDistrict nurses have both a proactive and reactive role in ensuring their patients remain safeguarded. By ensuring care is delivered with dignity and taking appropriate action if they suspect abuse or neglect, district nurses can safeguard their patients.Originality/valueThis paper begins to address an omission in existing empirical research regarding the role of district nursing teams in delivering dignified care and how this can safeguard older adults.

Virtual Reality as Learning Media for Lampung Historical Heritage

Lampung Province has a lot of historical heritage which is a world heritage for future human generations. The Lampung Museum, which was founded in 1975, plays a role in ensuring the continuity of history in the people of Lampung. Dissemination of Lampung history can be improved through education 4.0. Virtual Reality is a technology that allows a user to interact with the environment that exists in the virtual world and can provide information. Virtual Reality can help disseminate the history of Lampung with interactive and humanistic interaction models for historical objects that are presented without being bound by space and time. In addition, the ongoing COVID-19 pandemic has had a major impact on the performance of the Lampung museum in disseminating the history of Lampung. The method used to develop Virtual Reality of Lampung Historical Heritage consists of seven stages, namely Problem Formulation, Determination of Motivation, Idea Development, Design, Prototype Making, Testing, Advanced Development, and Implementation/Release. Eight historical objects were modeled and enriched with information regarding their relationship to Lampung history, namely the Lampung Museum, Thay Hin Bio Vihara, Al-Anwar Mosque, Lampung Siger Tower, Krakatau Monument, Kerti Bhuana Temple, Nuwo Sesat Traditional House, and the Japanese Cave. It is hoped that with the availability of Virtual Reality of Lampung Historical Heritage, the dissemination of Lampung history can be carried out more progressively through education 4.0. © 2021 IEEE.

Blended Network Action Learning – A Digital Lean Approach to Solving Complex Organizational Problems Across Space and Time

Network Action Learning has emerged as an innovative development of Action Learning and has been described as a lean approach to collaborative strategic improvement with problem-solving at its core, be it either within- or across organizational boundaries. Virtual Action Learning is also presented as an emergent variety of Action Learning, bringing together geographically dispersed individuals within and across organizations in an online, virtual environment. Given the onset of new, innovative digital technologies – particularly in response of the Covid-19 pandemic – Blended Learning has also emerged as an educational platform that represents some combination of face-to-face and online learning using mobile technologies and cloud-based resources. Though Virtual Action Learning has been discussed as neither better than nor second best to face-to-face Action Learning, in this paper, we suggest that a blended approach may be the most effective method. Thus, the purpose of this paper is to construct a Blended approach to Network Action Learning, where intra- and inter-firm Network Action Learning can take place using a hybrid, physical-virtual approach to promoting collaborative strategic improvement and gemba-based problem-solving. © 2021, IFIP International Federation for Information Processing.