Abstract
The significance of the COVID-19 pandemic has resulted in the availability of an unprecedented amount of data having become available unlike in any comparable health emergency before. Global situation updates were made available on a daily basis. This provides the unique opportunity to gain a better understanding of the underlying spatial patterns that developed during the spread of the virus. This contribution makes use of these data and provides a geographical overview of the spread of the COVID-19 pandemic in 2020, the first year of the (known) spread of the virus. A main emphasis is put on the utilisation of innovative data visualisation approaches by deploying cartogram techniques as a method to emphasise the underlying quantities of global cases and deaths. The cartographic analysis is accompanied by a critical reflection on the sometimes problematic nature of the data and the patterns that have emerged from it.
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References
Cheshire, J. (2020). Next slide please: data visualisation expert on what’s wrong with the UK government’s coronavirus charts. https://theconversation.com/next-slide-please-data-visualisation-expert-on-whats-wrong-with-the-uk-governments-coronavirus-charts-149329. Accessed 27 May 2021.
European Centre for Disease Prevention and Control. (2021). Situation updates on COVID-19. https://www.ecdc.europa.eu/en/COVID-19/situation-updates. Accessed 27 May 2021.
Gastner, M. T., & Newman, M. E. J. (2004). Diffusion-based method for producing density equalizing maps. Proceedings of the National Academy of Sciences USA, 101, 7499–7504.
Gastner, M. T., Seguy, V., & More, P. (2018). Fast flow-based algorithm for creating density-equalizing map projections. Proceedings of the National Academy of Sciences USA, 115(10), E2156–E2164.
Guardian. (2021). COVID UK: coronavirus cases, deaths and vaccinations today. https://www.theguardian.com/world/2021/may/28/COVID-uk-coronavirus-cases-deaths-and-vaccinations-today. Accessed 27 May 2021.
Hennig, B. (2013). Rediscovering the world: Map transformations of human and physical space. Springer.
Hennig, B. D. (2018a). Kartogramm zur Reichstagswahl: An early electoral cartogram of Germany. Bulletin of the Society of Cartographers, 52(1 & 2), 15–25.
Hennig, B. D. (2018b). Worldmapper: Rediscovering the world. Teaching Geography, 43(2), 66–68.
Hennig, B. D. (2019). Remapping geography: Using cartograms to change our views of the world. Geography, 104(2), 71–80.
Hennig, B. D. (2020). COVID-19’s spread across the world. Political Insight, 11(2), 20–21.
Johns Hopkins University. (2021). Coronavirus Resource Center. https://coronavirus.jhu.edu. Accessed 27 May 2021.
Lancet. (2020). COVID-19: Fighting panic with information. Lancet, 395(10224), 537.
Naeem, S. B., & Batti, R. (2020). The COVID-19 ‘infodemic’: A new front for information professionals. Health Information & Libraries Journal, 37(3), 233–239.
New York Times. (2021). Coronavirus in the U.S.: Latest map and case count, https://www.nytimes.com/interactive/2021/us/COVID-cases.html. Accessed 27 May 2021.
Sueddeutsche Zeitung. (2021). Alles Wichtige zu COVID-19. https://www.sueddeutsche.de/thema/Coronavirus. Accessed 27 May 2021.
Taubenberger, J. K., & Morens, D. M. (2006). 1918 influenza: The mother of all pandemics. Emerging Infectious Diseases, 12(1), 15–22.
WHO, World Health Organization. (2021a). WHO Coronavirus (COVID-19) Dashboard. https://COVID19.who.int. Accessed 27 May 2021.
WHO, World Health Organization. (2021b). Coronavirus disease (COVID-19) weekly epidemiological update and weekly operational update. https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports. Accessed 27 May 2021.
Wolkewitz, M., & Puljak, L. (2020). Methodological challenges of analysing COVID-19 data during the pandemic. BMC Medical Research Methodology, 20, 81.
Worldmapper. (2021). COVID-19: Chronology of a Pandemic – Part 2, https://worldmapper.org/COVID-19-coronavirus-part2/ Accessed 27 May 2021.
Yang, W., Petkova, E., & Shaman, J. (2014). The 1918 influenza pandemic in New York City: Age-specific timing, mortality, and transmission dynamics. Influenza and Other Respiratory Viruses. National Institutes of Health, 8(2), 177–188.
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Hennig, B.D. (2022). One Year of COVID-19: Mapping the Spread of a Global Pandemic. In: Brunn, S.D., Gilbreath, D. (eds) COVID-19 and a World of Ad Hoc Geographies. Springer, Cham. https://doi.org/10.1007/978-3-030-94350-9_45
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DOI: https://doi.org/10.1007/978-3-030-94350-9_45
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