Age-specific mortality and the role of living remotely: The 1918-20 influenza pandemic in Kautokeino and Karasjok, Norway

Death on the permafrost: revisiting the 1918-1920 influenza pandemic in Alaska using death certificates

The 1918-1920 influenza pandemic devastated Alaska's Indigenous populations. We report on quantitative analyses of pandemic deaths due to pneumonia and influenza (P&I) using information from Alaska death certificates dating between 1915 and 1921 (n = 7147). Goals include a reassessment of pandemic death numbers, analysis of P&I deaths beyond 1919, estimates of excess mortality patterns overall and by age using intercensal population estimates based on Alaska's demographic history, and comparisons between Alaska Native (AN) and non-AN residents. Results indicate that ANs experienced 83% of all P&I deaths and 87% of all-cause excess deaths during the pandemic. Alaska Native mortality was 8.1 times higher than non-AN mortality. Analyses also uncovered previously unknown mortality peaks in 1920. Both subpopulations showed characteristically high mortality of young adults, possibly due to imprinting with the 1889-1890 pandemic virus, but their age-specific mortality patterns were different: non-AN mortality declined after age 25-29 and stayed relatively low for the elderly, while AN mortality increased after age 25-29, peaked at age 40-44, and remained high up to age 64. This suggests a relative lack of exposure to H1-type viruses pre-1889 among AN persons. In contrast, non-AN persons, often temporary residents, may have gained immunity before moving to Alaska.

The 1919-21 influenza pandemic in Greenland

In Alaska, the 1918-20 influenza pandemic was devastating, with mortality rates up to 90% of the population, while in other arctic regions in northern Sweden and Norway mortality was considerably lower. We investigated the timing and age-patterns in excess mortality in Greenland during the period 1918-21 and compare these to other epidemics and the 1889-92 pandemic. We accessed the Greenlandic National Archives and transcribed all deaths from 1880 to 1921 by age, geography, and cause of death. We estimated monthly excess mortality and studied the spatial-temporal patterns of the pandemics and compared them to other mortality crises in the 40-year period. The 1918-21 influenza pandemic arrived in Greenland in the summer of 1919, one year delayed due to ship traffic interruptions during the winter months. We found that 5.2% of the Greenland population died of the pandemic with substantial variability between counties (range, 0.1% to 11%). We did not see the typical pandemic age-pattern of high young-adult mortality, possibly due to high baseline mortality in this age-group or remoteness. However, despite substantial mortality, the mortality impact was not standing out relative to other mortality crises, or of similar devastation reported in Alaskan populations.

Beyond COVID: towards a transdisciplinary synthesis for understanding responses and developing pandemic preparedness in Alaska

Pandemics are regularly occurring events, and there are foundational principles of pandemic preparation upon which communities, regions, states, and nations may draw upon for elevated preparedness against an inevitable future infectious disease threat. Many disciplines within the social sciences can provide crucial insight and transdisciplinary thinking for the development of preparedness measures. In 2023, the National Science Foundation funded a conference of circumpolar researchers and Indigenous partners to reflect on COVID-19-related research. In this article, we synthesise our diverse social science perspectives to: (1) identify potential areas of future pandemic-related research in Alaska, and (2) pose new research questions that elevate the needs of Alaska and its people, pursuant of a specific body of pandemic knowledge that takes into account the ecological and sociocultural contexts of the region. In doing so, we highlight important domains of research in the social sciences from transdisciplinary perspectives, including the centering of Indigenous knowledges and needs, the contexts of risk perception and resilience, food and housing security, and more. We highlight the contributions of social sciences to pandemic knowledge and provide a foundation for future pandemic-related research in Alaska.

Metaviromic reveals the dynamics and diversity of the virosphere in wastewater samples from Natal, Brazil

The COVID-19 pandemic underscored the significance of omics technology and Wastewater-Based Epidemiology for epidemic preparedness. This study investigates the virosphere in wastewater samples from Natal (Brazil), aiming to understand its structure, relationships, and potential. Metaviromic analysis was used on DNA and RNA from weekly samples collected over a year (June/2021 to May/2022) from three wastewater treatment plants. The virosphere showed stability, particularly in viruses infecting microorganisms and plants. However, an alternation of representatives of viruses that infect animals has been observed. Among the most abundant viruses infecting microorganisms are genera associated with the bacterial genera Escherichia, Pseudomonas, and Caulobacte. Regarding the viruses infecting plants, Sobemovirus and Tobamovirus are the most abundant genera. Odontoglossum ringspot virus was identified as a possible RNA virus biomarker. Among DNA viruses infecting animals, genera Bocaparvovirus and Mastadenovirus are the most prevalent. Intriguingly, some Poxviridae family members were observed in the samples. Co-occurrence network analysis identified potential biomarkers like Volepox virus, Anatid herpesvirus 1, and Caviid herpesvirus 2. Among RNA viruses affecting animals, Mamastrovirus, Rotavirus, and Norovirus genera were the most abundant pathogens. Furthermore, members of the Coronaviridae family exhibited a high degree of centrality values in the co-occurrence network, even connecting with unclassified viruses. The study emphasizes the importance of research in understanding the roles of unclassified viruses. In addition, we observed an association between Coronaviridae reads, rainfall, and the number of reported COVID-19 cases. Our study highlights the diversity and complexity of the viral community in wastewater and the need for research to understand better the ecological roles unclassified viruses play. Such advances will significantly contribute to our preparedness and response to future viral threats. Furthermore, our study contributes to knowledge of virosphere dynamics, offering insights that can contribute to the direction of future public health policies and interventions.

Comparative analysis of COVID-19 diagnoses and mortality among hospitalized indigenous and non-indigenous populations in Chile: 2020-2021

BACKGROUND

Current literature presents mixed effects of the COVID-19 pandemic on Indigenous communities. We aim to highlight potential disparities and temporal shifts in both the impact of COVID-19 and vaccine uptake among hospitalized Indigenous populations in Chile.

METHODS

We conducted an observational analysis utilizing 1,598,492 hospitalization records from 2020 to 2021 based on publicly accessible hospital discharge data spanning 65 healthcare facilities of medium and high complexity funded through the Diagnosis-Related Groups (DRG) mechanism in Chile, representing roughly 70% of the country's total hospitalizations. This was supplemented with publicly available municipal data on COVID-19 vaccinations and socio-demographic variables. We performed logistic regression analysis at 0.05 level of significance to assess the bivariate and multivariable association of Indigenous status with COVID-19 diagnosis and COVID-19 deaths among hospitalized populations. We also performed univariate and multiple linear regression to assess the association of COVID-19 vaccination rate and Indigenous status at the municipality level. In addition, we report the distribution of top 10 secondary diagnoses among hospitalized COVID-19 cases and deaths separately for Indigenous and non-Indigenous populations.

RESULTS

Indigenous populations displayed lower adjusted odds for both COVID-19 diagnosis (OR: 0.76, 95% CI: 0.74, 0.77) and death (OR: 0.91, 95% CI: 0.85, 0.97) when compared to non-Indigenous groups. Notably, the adjusted odds ratio for COVID-19 diagnosis in Indigenous populations rose from 0.59 (95% CI: 0.57, 0.61) in 2020 to 1.17 (95% CI: 1.13, 1.21) in 2021. Factors such as the significantly higher median age and greater number of comorbidities in the non-Indigenous hospitalized groups could account for their increased odds of COVID-19 diagnosis and mortality. Additionally, our data indicates a significantly negative adjusted association between COVID-19 vaccination rates and the proportion of Indigenous individuals.

CONCLUSION

Although Indigenous populations initially showed lower odds of COVID-19 diagnosis and mortality, a marked rise in diagnosis odds among these groups in 2021 underscores the urgency of targeted interventions. The observed negative association between the proportion of Indigenous populations and vaccination rates further underscores the necessity to tackle vaccine access barriers and work towards equitable distribution.

Risk factors for death associated with severe influenza in children and the impact of the COVID-19 pandemic on clinical characteristics

Background

To summarize the clinical features of severe influenza in children and the high-risk factors for influenza-related deaths and to raise awareness among pediatricians.

Methods

A retrospective study of clinical manifestations, laboratory tests, and diagnosis and treatment of 243 children with severe influenza admitted to Shenzhen Children's Hospital from January 2009 to December 2022 was conducted. Univariate logistic regression analysis and Boruta analysis were also performed to identify potentially critical clinical characteristics associated with death, and clinically significant were used in further multivariate logistic regression analysis. Subject receiver operating characteristic (ROC) curves were applied to assess the efficacy of death-related independent risk factors to predict death from severe influenza.

Results

There were 169 male and 74 female patients with severe influenza, with a median age of 3 years and 2 months and 77.4% of patients under six. There were 46 cases (18.9%) in the death group. The most common pathogen was Influenza A virus (IAV) (81.5%). The most common complication in the death group was influenza-associated acute necrotizing encephalopathy (ANE [52.2%]). Severe influenza in children decreased significantly during the COVID-19 pandemic, with a median age of 5 years, a high predominance of neurological symptoms such as ANE (P = 0.001), and the most common pathogen being H3N2 (P < 0.001). D-dimer, acute respiratory distress syndrome (ARDS), and acute necrotizing encephalopathy (ANE) were significant independent risk factors for severe influenza-associated death. Furthermore, the ROC curves showed that the combined diagnosis of independent risk factors had significant early diagnostic value for severe influenza-related deaths.

Conclusion

Neurological disorders such as ANE are more significant in children with severe influenza after the COVID-19 pandemic. Influenza virus infection can cause serious multisystem complications such as ARDS and ANE, and D-dimer has predictive value for early diagnosis and determination of the prognosis of children with severe influenza.

The emergence of a suburban penalty during the 1918/19 influenza pandemic in Malta: The role of a marketplace, railway, and measles

The Malta 1918/19 influenza experience adds to our understanding of the pandemic by illustrating the importance of suburban populations, their vulnerabilities, and elevated mortality rates. Studies on the socio-geographical variation in the 1918/19 influenza mortality has largely overlooked the suburban experience, and thus the often-hidden heterogeneity of the disease experience is missing. A comparison of mortality rates across the three settlement types (urban, suburban, and rural) for the second wave of the pandemic revealed that there were significant differences across the settlement types (x2 = 22.67, 2df, p <0.0001). There was a statistically significant divide between suburban settlement type versus urban and rural communities. Further, the geographical division of the central suburban region had the highest mortality rate at 4.28 per 1000 living of all suburban regions. A closer examination of the central suburban communities revealed that the town of Birchicara was the driving force behind the elevated influenza mortality, with a rate of 5.28 per 1000 living. The exceedingly high rate of influenza mortality in Birchicara was significantly different from the other suburban communities (Z = 2.915, p = 0.004). Birchicara was notable as both a transmission and burden hotspot for influenza infection because of a unique conflation of factors not observed elsewhere on the island. Foremost, was the pitkali market, which was a produce wholesale distributing centre; second, was the fact that the train station was a central hub especially for Maltese labourers; third, was that the measles epidemic in 1916/17 contributed to elevated childhood influenza deaths because the presence of military personnel and their families. We argue that the interaction of the three factors, and in particular, the measles epidemic with childhood influenza, amounted to a syndemic. Factors associated with urbanization and high rates of infectious diseases, such as overcrowding and infant mortality, did not play a primary role in the syndemic.

From pandemic to endemic: Spatial-temporal patterns of influenza-like illness incidence in a Swiss canton, 1918-1924

In pandemics, past and present, there is no textbook definition of when a pandemic is over, and how and when exactly a respiratory virus transitions from pandemic to endemic spread. In this paper we have compared the 1918/19 influenza pandemic and the subsequent spread of seasonal flu until 1924. We analysed 14,125 reports of newly stated 32,198 influenza-like illnesses from the Swiss canton of Bern. We analysed the temporal and spatial spread at the level of 497 municipalities, 9 regions, and the entire canton. We calculated incidence rates per 1000 inhabitants of newly registered cases per calendar week. Further, we illustrated the incidences of each municipality for each wave (first wave in summer 1918, second wave in fall/winter 1918/19, the strong later wave in early 1920, as well as the two seasonal waves in 1922 and 1924) on a choropleth map. We performed a spatial hotspot analysis to identify spatial clusters in each wave, using the Gi* statistic. Furthermore, we applied a robust negative binomial regression to estimate the association between selected explanatory variables and incidence on the ecological level. We show that the pandemic transitioned to endemic spread in several waves (including another strong wave in February 1920) with lower incidence and rather local spread until 1924 at least. At the municipality and regional levels, there were different patterns of spread both between pandemic and seasonal waves. In the first pandemic wave in summer 1918 the probability of higher incidence was increased in municipalities with a higher proportion of factories (OR 2.60, 95%CI 1.42-4.96), as well as in municipalities that had access to a railway station (OR 1.50, 95%CI 1.16-1.96). In contrast, the strong fall/winter wave 1918 was very widespread throughout the canton. In general, municipalities at higher altitude showed lower incidence. Our study adds to the sparse literature on incidence in the 1918/19 pandemic and subsequent years. Before Covid-19, the last pandemic that occurred in several waves and then became endemic was the 1918-19 pandemic. Such scenarios from the past can inform pandemic planning and preparedness in future outbreaks.