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Short Communication

Spatiotemporal dynamics of the COVID-19 pandemic in the arctic: early data and emerging trends

ORCID Icon, , , , & ORCID Icon
Article: 1835251 | Received 11 Sep 2020, Accepted 08 Oct 2020, Published online: 19 Oct 2020
 

ABSTRACT

Since February 2020 the COVID-19 pandemic has been unfolding in the Arctic, placing many communities at risk due to remoteness, limited healthcare options, underlying health issues and other compounding factors. Preliminary analysis of available COVID-19 data in the Arctic at the regional (subnational) level suggests that COVID-19 infections and mortality were highly variable, but generally remained below respective national levels. Based on the trends and magnitude of the pandemic through July, we classify Arctic regions into four groups: Iceland, Faroe Islands, Northern Norway, and Northern Finland with elevated early incidence rates, but where strict quarantines and other measures promptly curtailed the pandemic; Northern Sweden and Alaska, where the initial wave of infections persisted amid weak (Sweden) or variable (Alaska) quarantine measures; Northern Russia characterised by the late start and subsequent steep growth of COVID-19 cases and fatalities and multiple outbreaks; and Northern Canada and Greenland with no significant proliferation of the pandemic. Despite limitations in available data, further efforts to track and analyse the pandemic at the pan-Arctic, regional and local scales are crucial. This includes understanding of the COVID-19 patterns, mortality and morbidity, the relationships with public-health conditions, socioeconomic characteristics, policies, and experiences of the Indigenous Peoples.

Data used in this paper are available at https://arctic.uni.edu/arctic-covid-19.

Acknowledgments

The authors are grateful to Jonathan Voss, Petr Grin and Varvara Korkina for their help with this article. The research is supported by NSF PLR # 2034886.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

Additional information

Funding

This work was supported by the National Science Foundation [2034886].