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Tiwari S, Petrov AN, Golosov N, Devlin M, Welford M, DeGroote J, Degai T, Ksenofontov S. Regional geographies and public health lessons of the COVID-19 pandemic in the Arctic. Front Public Health 2024; 11:1324105. [PMID: 38259778 PMCID: PMC10801898 DOI: 10.3389/fpubh.2023.1324105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 12/15/2023] [Indexed: 01/24/2024] Open
Abstract
Objectives This study examines the COVID-19 pandemic's spatiotemporal dynamics in 52 sub-regions in eight Arctic states. This study further investigates the potential impact of early vaccination coverage on subsequent COVID-19 outcomes within these regions, potentially revealing public health insights of global significance. Methods We assessed the outcomes of the COVID-19 pandemic in Arctic sub-regions using three key epidemiological variables: confirmed cases, confirmed deaths, and case fatality ratio (CFR), along with vaccination rates to evaluate the effectiveness of the early vaccination campaign on the later dynamics of COVID-19 outcomes in these regions. Results From February 2020 to February 2023, the Arctic experienced five distinct waves of COVID-19 infections and fatalities. However, most Arctic regions consistently maintained Case Fatality Ratios (CFRs) below their respective national levels throughout these waves. Further, the regression analysis indicated that the impact of initial vaccination coverage on subsequent cumulative mortality rates and Case Fatality Ratio (CFR) was inverse and statistically significant. A common trend was the delayed onset of the pandemic in the Arctic due to its remoteness. A few regions, including Greenland, Iceland, the Faroe Islands, Northern Canada, Finland, and Norway, experienced isolated spikes in cases at the beginning of the pandemic with minimal or no fatalities. In contrast, Alaska, Northern Sweden, and Russia had generally high death rates, with surges in cases and fatalities. Conclusion Analyzing COVID-19 data from 52 Arctic subregions shows significant spatial and temporal variations in the pandemic's severity. Greenland, Iceland, the Faroe Islands, Northern Canada, Finland, and Norway exemplify successful pandemic management models characterized by low cases and deaths. These outcomes can be attributed to successful vaccination campaigns, and proactive public health initiatives along the delayed onset of the pandemic, which reduced the impact of COVID-19, given structural and population vulnerabilities. Thus, the Arctic experience of COVID-19 informs preparedness for future pandemic-like public health emergencies in remote regions and marginalized communities worldwide that share similar contexts.
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Affiliation(s)
- Sweta Tiwari
- ARCTICenter, University of Northern Iowa, Cedar Falls, IA, United States
- Department of Geography, University of Northern Iowa, Cedar Falls, IA, United States
| | - Andrey N. Petrov
- ARCTICenter, University of Northern Iowa, Cedar Falls, IA, United States
- Department of Geography, University of Northern Iowa, Cedar Falls, IA, United States
| | - Nikolay Golosov
- Department of Geography, Pennsylvania State University, University Park, PA, United States
| | - Michele Devlin
- United States Army War College, Carlisle, PA, United States
| | - Mark Welford
- Department of Geography, University of Northern Iowa, Cedar Falls, IA, United States
| | - John DeGroote
- Department of Geography, University of Northern Iowa, Cedar Falls, IA, United States
| | - Tatiana Degai
- ARCTICenter, University of Northern Iowa, Cedar Falls, IA, United States
- Department of Anthropology, University of Victoria, Victoria, BC, Canada
| | - Stanislav Ksenofontov
- ARCTICenter, University of Northern Iowa, Cedar Falls, IA, United States
- Department of Geography, University of Northern Iowa, Cedar Falls, IA, United States
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Tiwari S, Petrov A, Mateshvili N, Devlin M, Golosov N, Rozanova-Smith M, Welford M, DeGroote J, Degai T, Ksenofontov S. Incorporating resilience when assessing pandemic risk in the Arctic: a case study of Alaska. BMJ Glob Health 2023; 8:bmjgh-2022-011646. [PMID: 37286235 DOI: 10.1136/bmjgh-2022-011646] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Accepted: 05/14/2023] [Indexed: 06/09/2023] Open
Abstract
The discourse on vulnerability to COVID-19 or any other pandemic is about the susceptibility to the effects of disease outbreaks. Over time, vulnerability has been assessed through various indices calculated using a confluence of societal factors. However, categorising Arctic communities, without considering their socioeconomic, cultural and demographic uniqueness, into the high and low continuum of vulnerability using universal indicators will undoubtedly result in the underestimation of the communities' capacity to withstand and recover from pandemic exposure. By recognising vulnerability and resilience as two separate but interrelated dimensions, this study reviews the Arctic communities' ability to cope with pandemic risks. In particular, we have developed a pandemic vulnerability-resilience framework for Alaska to examine the potential community-level risks of COVID-19 or future pandemics. Based on the combined assessment of the vulnerability and resilience indices, we found that not all highly vulnerable census areas and boroughs had experienced COVID-19 epidemiological outcomes with similar severity. The more resilient a census area or borough is, the lower the cumulative death per 100 000 and case fatality ratio in that area. The insight that pandemic risks are the result of the interaction between vulnerability and resilience could help public officials and concerned parties to accurately identify the populations and communities at most risk or with the greatest need, which, in turn, helps in the efficient allocation of resources and services before, during and after a pandemic. A resilience-vulnerability-focused approach described in this paper can be applied to assess the potential effect of COVID-19 and similar future health crises in remote regions or regions with large Indigenous populations in other parts of the world.
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Affiliation(s)
- Sweta Tiwari
- ARCTICenter, College of Social & Behavioral Sciences, University of Northern Iowa, Cedar Falls, Iowa, USA
| | - Andrey Petrov
- ARCTICenter, University of Northern Iowa, Cedar Falls, Iowa, USA
- Department of Geography, University of Northern Iowa, Cedar Falls, Iowa, USA
| | - Nino Mateshvili
- ARCTICenter, University of Northern Iowa, Cedar Falls, Iowa, USA
| | - Michele Devlin
- Center for Strategic Leadership, United States Army War College, Carlisle, Pennsylvania, USA
| | - Nikolay Golosov
- Department of Geography, Pennsylvania State University, Harrisburg, Pennsylvania, USA
| | - Marya Rozanova-Smith
- Department of Geography, Columbian College of Arts and Sciences, The George Washington University, Washington, District of Columbia, USA
| | - Mark Welford
- Department of Geography, University of Northern Iowa, Cedar Falls, Iowa, USA
| | - John DeGroote
- Department of Geography, University of Northern Iowa, Cedar Falls, Iowa, USA
| | - Tatiana Degai
- Anthropology, University of Victoria, Victoria, British Columbia, Canada
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Petrov AN, Dorough DS, Tiwari S, Welford M, Golosov N, Devlin M, Degai T, Ksenofontov S, DeGroote J. Indigenous health-care sovereignty defines resilience to the COVID-19 pandemic. Lancet 2023; 401:1478-1480. [PMID: 37084754 PMCID: PMC10112862 DOI: 10.1016/s0140-6736(23)00684-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 03/28/2023] [Indexed: 04/23/2023]
Affiliation(s)
- Andrey N Petrov
- ARCTICenter, University of Northern Iowa, Cedar Falls, IA 50614, USA.
| | | | - Sweta Tiwari
- ARCTICenter, University of Northern Iowa, Cedar Falls, IA 50614, USA
| | - Mark Welford
- Department of Geography, University of Northern Iowa, Cedar Falls, IA 50614, USA
| | - Nikolay Golosov
- Department of Geography, Pennsylvania State University, University Park, PA, USA
| | - Michele Devlin
- Center for Strategic Leadership, United States Army War College, Carlisle, PA, USA
| | - Tatiana Degai
- ARCTICenter, University of Northern Iowa, Cedar Falls, IA 50614, USA; Department of Anthropology, University of Victoria, Victoria, BC, Canada
| | | | - John DeGroote
- Department of Geography, University of Northern Iowa, Cedar Falls, IA 50614, USA
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Tiwari S, Petrov AN, Devlin M, Welford M, Golosov N, DeGroote J, Degai T, Ksenofontov S. The second year of pandemic in the Arctic: examining spatiotemporal dynamics of the COVID-19 "Delta wave" in Arctic regions in 2021. Int J Circumpolar Health 2022; 81:2109562. [PMID: 35976076 PMCID: PMC9387323 DOI: 10.1080/22423982.2022.2109562] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
The second year of the COVID-19 pandemic in the Arctic was dominated by the Delta wave that primarily lasted between July and December 2021 with varied epidemiological outcomes. An analysis of the Arctic’s subnational COVID-19 data revealed a massive increase in cases and deaths across all its jurisdictions but at varying time periods. However, the case fatality ratio (CFR) in most Arctic regions did not rise dramatically and was below national levels (except in Northern Russia). Based on the spatiotemporal patterns of the Delta outbreak, we identified four types of pandemic waves across Arctic regions: Tsunami (Greenland, Iceland, Faroe Islands, Northern Norway, Northern Finland, and Northern Canada), Superstorm (Alaska), Tidal wave (Northern Russia), and Protracted Wave (Northern Sweden). These regionally varied COVID-19 epidemiological dynamics are likely attributable to the inconsistency in implementing public health prevention measures, geographical isolation, and varying vaccination rates. A lesson remote and Indigenous communities can learn from the Arctic is that the three-prong (delay-prepare-respond) approach could be a tool in curtailing the impact of COVID-19 or future pandemics. This article is motivated by previous research that examined the first and second waves of the pandemic in the Arctic. Data are available at https://arctic.uni.edu/arctic-covid-19.
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Affiliation(s)
- Sweta Tiwari
- ARCTICenter, University of Northern Iowa, Cedar Falls, Iowa, USA.,Department of Geography, University of Northern Iowa, Cedar Falls, Iowa, USA
| | - Andrey N Petrov
- ARCTICenter, University of Northern Iowa, Cedar Falls, Iowa, USA.,Department of Geography, University of Northern Iowa, Cedar Falls, Iowa, USA
| | - Michele Devlin
- ARCTICenter, University of Northern Iowa, Cedar Falls, Iowa, USA.,Center for Strategic Leadership, USA Army War College, Carlisle, Pennsylvania, USA
| | - Mark Welford
- Department of Geography, University of Northern Iowa, Cedar Falls, Iowa, USA
| | - Nikolay Golosov
- Department of Geography, Pennsylvania State University, Harrisburg, Pennsylvania, USA
| | - John DeGroote
- Department of Geography, University of Northern Iowa, Cedar Falls, Iowa, USA
| | - Tatiana Degai
- ARCTICenter, University of Northern Iowa, Cedar Falls, Iowa, USA.,Department of Anthropology, University of Victoria, Victoria, British Columbia, Canada
| | - Stanislav Ksenofontov
- ARCTICenter, University of Northern Iowa, Cedar Falls, Iowa, USA.,Department of Geography, University of Northern Iowa, Cedar Falls, Iowa, USA
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Petrov AN, Welford M, Golosov N, DeGroote J, Devlin M, Degai T, Savelyev A. The "second wave" of the COVID-19 pandemic in the Arctic: regional and temporal dynamics. Int J Circumpolar Health 2021; 80:1925446. [PMID: 34125008 PMCID: PMC8205071 DOI: 10.1080/22423982.2021.1925446] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 04/29/2021] [Accepted: 04/29/2021] [Indexed: 10/28/2022] Open
Abstract
This article focuses on the "second wave" of the COVID-19 pandemic in the Arctic and examines spatiotemporal patterns between July 2020 and January 2021. We analyse available COVID-19 data at the regional (subnational) level to elucidate patterns and typology of Arctic regions with respect to the COVID-19 pandemic. This article builds upon our previous research that examined the early phase of the COVID-19 pandemic between February and July 2020. The pandemic's "second wave" observed in the Arctic between September 2020 and January 2021 was severe in terms of COVID-19 infections and fatalities, having particularly strong impacts in Alaska, Northern Russia and Northern Sweden. Based on the spatiotemporal patterns of the "second wave" dynamics, we identified 5 types of the pandemic across regions: Shockwaves (Iceland, Faroe Islands, Northern Norway, and Northern Finland), Protracted Waves (Northern Sweden), Tidal Waves (Northern Russia), Tsunami Waves (Alaska), and Isolated Splashes (Northern Canada and Greenland). Although data limitations and gaps persist, monitoring of COVID-19 is critical for developing a proper understanding of the pandemic in order to develop informed and effective responses to the current crisis and possible future pandemics in the Arctic. Data used in this paper are available at https://arctic.uni.edu/arctic-covid-19.
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Affiliation(s)
- Andrey N. Petrov
- ARCTICenter, University of Northern Iowa, Cedar Falls, IA, USA
- Department of Geography, University of Northern Iowa, Cedar Falls, IA, USA
| | - Mark Welford
- Department of Geography, University of Northern Iowa, Cedar Falls, IA, USA
| | - Nikolay Golosov
- ARCTICenter, University of Northern Iowa, Cedar Falls, IA, USA
- Department of Geography, University of Northern Iowa, Cedar Falls, IA, USA
| | - John DeGroote
- Department of Geography, University of Northern Iowa, Cedar Falls, IA, USA
| | - Michele Devlin
- Department of Health, Recreation, and Community Services, University of Northern Iowa, Cedar Falls, IA, USA
| | - Tatiana Degai
- ARCTICenter, University of Northern Iowa, Cedar Falls, IA, USA
- Department of Geography, University of Northern Iowa, Cedar Falls, IA, USA
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Petrov AN, Welford M, Golosov N, DeGroote J, Degai T, Savelyev A. Spatiotemporal dynamics of the COVID-19 pandemic in the arctic: early data and emerging trends. Int J Circumpolar Health 2020; 79:1835251. [PMID: 33074067 PMCID: PMC7595240 DOI: 10.1080/22423982.2020.1835251] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
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.
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Affiliation(s)
- Andrey N Petrov
- ARCTICenter, University of Northern Iowa , Cedar Falls, IA, USA.,Department of Geography, University of Northern Iowa , Cedar Falls, IA, USA
| | - Mark Welford
- Department of Geography, University of Northern Iowa , Cedar Falls, IA, USA
| | - Nikolay Golosov
- ARCTICenter, University of Northern Iowa , Cedar Falls, IA, USA.,Department of Geography, University of Northern Iowa , Cedar Falls, IA, USA
| | - John DeGroote
- Department of Geography, University of Northern Iowa , Cedar Falls, IA, USA
| | - Tatiana Degai
- ARCTICenter, University of Northern Iowa , Cedar Falls, IA, USA.,Department of Geography, University of Northern Iowa , Cedar Falls, IA, USA
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