Incorporating resilience when assessing pandemic risk in the Arctic: a case study of Alaska.

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.

Regional geographies and public health lessons of the COVID-19 pandemic in the Arctic.

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.

The second year of pandemic in the Arctic: examining spatiotemporal dynamics of the COVID-19 "Delta wave" in Arctic regions in 2021.

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.

The "second wave" of the COVID-19 pandemic in the Arctic: regional and temporal dynamics.

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.

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

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.

Performing collaborative research: a dramaturgical reflection on an institutional knowledge brokering service in the North East of England.

BACKGROUND: To increase the uptake of research evidence in practice, responsive research services have been developed within universities that broker access to academic expertise for practitioners and decision-makers. However, there has been little examination of the process of knowledge brokering within these services. This paper reflects on this process within the AskFuse service, which was launched in June 2013 by Fuse, the Centre for Translational Research in Public Health, in North East England. The paper outlines the challenges and opportunities faced by both academics and health practitioners collaborating through the service. METHODS: The authors reflected on conversations between the AskFuse Research Manager and policy and practice partners accessing the service between June 2013 and March 2017. Summary notes of these conversations, including emails and documents relating to over 240 enquiries, have been analysed using an auto-ethnographic approach. FINDINGS: We identified five challenges to knowledge brokering in an institutional service, namely length of brokerage time required, limits to collaboration, lack of resources, brokering research in a changing system, and multiple types of knowledge. CONCLUSIONS: To understand and overcome some of the identified challenges, we employ Goffman's dramaturgical perspective and argue for making better use of the distinction between front and back stages in the knowledge brokering process. We emphasise the importance of back stages for defusing destructive information that could discredit collaborative performances.

Validation of inverse seasonal peak mortality in medieval plagues, including the Black Death, in comparison to modern Yersinia pestis-variant diseases.

BACKGROUND: Recent studies have noted myriad qualitative and quantitative inconsistencies between the medieval Black Death (and subsequent "plagues") and modern empirical Y. pestis plague data, most of which is derived from the Indian and Chinese plague outbreaks of A.D. 1900+/-15 years. Previous works have noted apparent differences in seasonal mortality peaks during Black Death outbreaks versus peaks of bubonic and pneumonic plagues attributed to Y. pestis infection, but have not provided spatiotemporal statistical support. Our objective here was to validate individual observations of this seasonal discrepancy in peak mortality between historical epidemics and modern empirical data. METHODOLOGY/PRINCIPAL FINDINGS: We compiled and aggregated multiple daily, weekly and monthly datasets of both Y. pestis plague epidemics and suspected Black Death epidemics to compare seasonal differences in mortality peaks at a monthly resolution. Statistical and time series analyses of the epidemic data indicate that a seasonal inversion in peak mortality does exist between known Y. pestis plague and suspected Black Death epidemics. We provide possible explanations for this seasonal inversion. CONCLUSIONS/SIGNIFICANCE: These results add further evidence of inconsistency between historical plagues, including the Black Death, and our current understanding of Y. pestis-variant disease. We expect that the line of inquiry into the disputed cause of the greatest recorded epidemic will continue to intensify. Given the rapid pace of environmental change in the modern world, it is crucial that we understand past lethal outbreaks as fully as possible in order to prepare for future deadly pandemics.

Did medieval trade activity and a viral etiology control the spatial extent and seasonal distribution of Black Death mortality?

Recent research into the world's greatest recorded epidemic, the Medieval Black Death (MBD), has cast doubt on Bubonic Plague as the etiologic agent. Prior research has recently culminated in outstanding advances in our understanding of the spatio-temporal pattern of MBD mortality, and a characterization of the incubation, latent, infectious, and symptomatic periods of the MBD. However, until now, several mysteries remained unexplained, including perhaps the biggest quandary of all: why did the MBD exhibit inverse seasonal peaks in mortality from diseases recorded in modern times, such as seasonal Influenza or the Indian Plague Epidemics of the early 1900 s? Although some have argued that climate changes likely explain the observed differences between modern clinical Bubonic Plague seasonality and MBD mortality accounts, we believe that another factor explains these dissimilarities. Here, we provide a synthetic hypothesis which builds upon previous theories developed in the last ten years or so. Our all-encompassing theory explains the causation, dissemination, and lethality of the MBD. We theorize that the MBD was a human-to-human transmitted virus, originating in East-Central Asia and not Africa (as some recent work has proposed), and that its areal extent during the first great epidemic wave of 1347-1350 was controlled hierarchically by proximity to trade routes. We also propose that the seasonality of medieval trade controlled the warm-weather mortality peaks witnessed during 1347-1350; during the time of greatest market activity, traders, fairgoers, and religious pilgrims served as unintentional vectors of a lethal virus with an incubation period of approximately 32 days, including a largely asymptomatic yet infectious period of roughly three weeks. We include a description of the rigorous research agenda that we have proposed in order to subject our theory to scientific scrutiny and a description of our plans to generate the first publicly available georeferenced GIS dataset pertaining to MBD mortality, as far as we are aware. This proposed theory, if supported by our aggressive and statistically robust proposed research activities, finally contains all of the elements necessary to convincingly reanalyze both the greatest historical epidemic of the last millennium, and the risk to modern populations in light of such findings.