In Search of an Integrated Corona Knowledge Ecosystem for Actionable Health Policy--A Mind Mapping Voyage and an Exploratory Decomposition in Spatial Pandemetrics.
Scope and aim
The global rapid rise of COVID-19 has been one of the most serious concerns in public policy over the past years (Barrett and Poot, 2023). Fortunately, after more than three years of corona virus infections, the contagion trajectory of COVID-19 seems to be nowadays on a final downturn in most countries, with small uprises here and there of new, but less harmful corona variants. Medical science has clearly been rather successful in coping effectively with this contagious disease, which has caused the loss of so many people, ranging from 20.000-25.000 people in a country like the Netherlands to millions worldwide. Notwithstanding the great achievement of medical-pharmaceutical science to develop effective vaccines, several serious scientific and policy questions remain, in particular:
--medical/pharmaceutical questions such as: the initial source(s) of the corona virus, its differential spread pattern (space and time), the vulnerability of specific population groups, the development of (herd) immunity against the corona virus, the impact and use of different types of vaccines (and their booster complements) in different countries, as well as the effectiveness of various pharmaceutical and non-pharmaceutical policy intervention measures.
--socio-economic and spatial impact questions such as: the impact of socio-economic status and education on corona infections, the implications of social and interactive behavior of people (e.g., handshaking, social distancing), the effect of online working and shopping modes (including lockdowns), the degree of physical intensity of social interaction among various people, the preventive or protective effect of active micro-mobility (e.g., walking, bicycling), or the rising enjoyment of green or blue natural environments.
In addition to these causal infectious disease questions (which need thorough empirical data and evidence-based research, on both medical and socio-economic/ cultural-geographical dimensions), there is now also a rising interest in important long-run and strategic questions, such as:
--medical-pharmaceutical: stimulus-response questions on the time pattern of the spread of COVID-19 (i.e., space-time medical geography), the underlying causes of the origin and contagion spread of the corona virus with different waves, the long-run causes, and implications of long COVID, etc.
--socio-economic and spatial: impacts of mobility patterns (commuting, shopping, education, family visits etc.) on the spread of COVID-19, the economic consequences of COVID-19 for mobility-rich economic sectors (e.g., tourism), the distinct effectiveness of different corona measures and policies in different countries, the identification of vulnerable groups (e.g., cultural, low-income, low-education), or the impacts of high densities, climatological conditions or unhealthy environments in big cities on the occurrence probability of COVID-19.
The COVID-19 pandemic has thus prompted a range of research challenges in different fields, not only in the medical-pharmaceutical field, but also in the social science field, e.g., geography, economics, psychology, sociology, administrative sciences, law, and data science (e.g., Farca and Dragos, 2020). From both a retrospective learning point of view and a prospective predictability point of view, there is a clear need for an evidence-based knowledge exploration of causes and impacts as well as of space-time patterns of the COVID-19 pandemic. This quantitative analysis of pandemic phenomena in a space-time context may be called coronametrics or--in a more general sense--pandemetrics, which is a cross-disciplinary quantitative (data-based, statistical and econometric) approach to the investigation of pandemic phenomena ranging from local to global levels. In so doing, we need extensive and reliable databases on all aspects of the corona phenomenon.
We also note that the corona crisis has brought to light a major weakness in public health policy, regarding the presence of heterogeneous or sometimes contradictory information and communication, which has led to an erosion of trust in governments. The pandemic has created a great deal of uncertainty among the broader public, due to incomplete and sometimes less transparent or less reliable information on the many aspects related to the sources, transmission, geographical spread, risks, preventive actions and medical consequences of COVID-19. Since the outbreak in 2019 much new information on the complex force field of this pandemic has come to the fore, but a clear comprehensive picture of its multi-faceted mechanism over time and space is still largely missing. The present paper seeks to lay the foundation for an evidence-based mind map based on multi-layer decomposition that depicts the various forces at work. This comprehensive image of the COVID-19 arena is not only useful as a testable communication tool for citizens' engagement and stakeholder confidence in policy measures regarding the control of the corona virus, but is also an empirical tool for understanding and managing the spread of the corona virus (or other pandemics) and for building an effective defense wall against an unlimited dispersion of the virus.
The corona mind map is in this study thus not only an information tool, but serves also as an interactive communication tool with both citizens and medical health authorities. A core element of the corona mind map is formed by a combined scorecard and dashboard on corona cases (including hospital admissions and death tolls), not only at national level but also at regional and local level. The study aims to present a quantitative open-access corona information-communication system, in which in addition to external and personal vulnerability conditions, also the evolution of vaccination rates, immunity rates, government (pharmaceutical and non-pharmaceutical) intervention measures, and human response mechanisms (e.g., social distancing, mobility and physical interactions) are taken into consideration. It seeks to trace the knowledge needed for a systematic understanding of the corona contagion.
The empirical data used in our study comprise inter alia public health data, vaccination data, policy stringency data, Google mobility data, and local COVID-19 data. The database is based on open-access and public space-time information since the beginning of the pandemic, and covers not only macro data, but also whenever possible detailed relevant space-time local data. The mechanism of this interactive corona communication instrument--including policy and behavioral response mechanisms--is illustrated for the space-time trajectory of COVID-19 in the Netherlands by means of open-access decentralized corona scoreboards and dashboards, which contribute to a focused research framing.
There is indeed a wide-ranging research agenda which calls for evidence-based exploratory and causality research that maps out the complex corona force field. The present study will present a multi-layer (cascadic) corona mind map that seeks to offer a simplified but structured image of the 'corona arena'; it is built up in a stepwise way (decomposition), where each of the building blocks represents an important knowledge domain to be covered for a full understanding of the corona phenomenon. Thus our aim is to explore and map out critical knowledge questions by employing a stepwise mind map for scientific and policy answers, at the level of both an integral corona perspective and a decomposed perspective for each of the building blocks of the overall mind map.
This paper has the following structure. After the above-described introduction to the challenge of studying the geography of the corona virus, we will offer in Section 2 a concise review of challenges in spatial corona research, with a particular view to the relevance of coronametric (or pandemetric) research in the post-corona time, while we will also provide a concise and selective overview of some relevant coronametric studies. The complexity of the corona field leads us to the design of a simple but organized corona mind map in Section 3, which will be further specified in an operational corona arena image, which forms the foundation for our knowledge framing exercise. This corona arena image is in Section 4 decomposed into six corona knowledge domains which act as a framework for distilling and specifying quantitative research questions in a geographical or spatial context. The information from the previous sections will be empirically illustrated by means of a large database from the Netherlands in Section 5, which highlights the need for a corona science agenda to be used for policy and scientific purposes. Finally, Section 6 offers concluding remarks.
Understanding the corona spectrum
COVID-19 has shown a world-wide coverage since its first appearance in the end of 2019 in Wuhan (China). Its spatial dispersion pattern follows a typical epidemiological space-time curve all over the world. However, it is characterized by a high degree of heterogeneity with a clear geographical disparity in various parts of the world. The spatial disparity in COVID-19 cases does not only manifest itself at a cross-country level (for instance, New Zealand vs. Italy), but also at regional or urban level (for instance, densely populated city centers vs. green suburbs). Furthermore, the time pattern of COVID-19 also displays clear features of differential dynamics, with different waves of intensity and amplitude in different parts of the world. Consequently, a range of important spatial knowledge questions on corona has arisen (see e.g., Couclelis, 2020; Sassen and Kourtit, 2022; Bouzouina, Kourtit and Nijkamp, 2023; Celbis, Kourtit and Nijkamp, 2023), which altogether comprise of a multi-faceted spectrum of facts, ideas and assertions on COVID-19.
In simple terms, one might describe the corona spectrum as a chain from genesis through intermediate...
To continue readingRequest your trial
COPYRIGHT GALE, Cengage Learning. All rights reserved.