Pandemic Reemergence and Four Waves of Excess Mortality Coinciding With the 1918 Influenza Pandemic in Michigan: Insights for COVID-19

Retrospective modelling of the disease and mortality burden of the 1918-1920 influenza pandemic in Zurich, Switzerland

BACKGROUND

Our study aims to enhance future pandemic preparedness by integrating lessons from historical pandemics, focusing on the multidimensional analysis of past outbreaks. It addresses the gap in existing modelling studies by combining various pandemic parameters in a comprehensive setting. Using Zurich as a case study, we seek a deeper understanding of pandemic dynamics to inform future scenarios.

DATA AND METHODS

We use newly digitized weekly aggregated epidemic/pandemic time series (incidence, hospitalisations, mortality and sickness absences from work) to retrospectively model the 1918-1920 pandemic in Zurich and investigate how different parameters correspond, how transmissibility changed during the different waves, and how public health interventions were associated with changes in these pandemic parameters.

RESULTS

In general, the various time series show a good temporal correspondence, but differences in their expression can also be observed. The first wave in the summer of 1918 did lead to illness, absence from work and hospitalisations, but to a lesser extent to increased mortality. In contrast, the second, longest and strongest wave in the autumn/winter of 1918 also led to greatly increased (excess) mortality in addition to the burden of illness. The later wave in the first months of 1920 was again associated with an increase in all pandemic parameters. Furthermore, we can see that public health measures such as bans on gatherings and school closures were associated with a decrease in the course of the pandemic, while the lifting or non-compliance with these measures was associated with an increase of reported cases.

DISCUSSION

Our study emphasizes the need to analyse a pandemic's disease burden comprehensively, beyond mortality. It highlights the importance of considering incidence, hospitalizations, and work absences as distinct but related aspects of disease impact. This approach reveals the nuanced dynamics of a pandemic, especially crucial during multi-wave outbreaks.

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 Graves Cannot Be Dug Fast Enough": Excess Deaths Among US Amish and Mennonites During the 1918 Flu Pandemic

Estimating the lethal impact of a pandemic on a religious community with significant barriers to outsiders can be exceedingly difficult. Nevertheless, Stein and colleagues (2021) developed an innovative means of arriving at such an estimate for the lethal impact of COVID-19 on the Amish community in 2020 by counting user-generated death reports in the widely circulated Amish periodical The Budget. By comparing monthly averages of reported deaths before and during the COVID-19 pandemic, Stein and colleagues were able to arrive at a rough estimate of "excess deaths" during the first year of the pandemic. Our research extends the same research method, applying it to the years during and immediately preceding the global influenza pandemic of 1918. Results show similarly robust findings, including three notable "waves" of excess deaths among Amish and conservative Mennonites in the USA in 1918, 1919, and 1920. Such results point to the promise of utilizing religious periodicals like The Budget as a relatively untapped trove of user-generated data on public health outcomes among religious minorities more than a century in the past.

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

The 1918-20 pandemic influenza killed 50-100 million people worldwide, but mortality varied by ethnicity and geography. In Norway, areas dominated by Sámi experienced 3-5 times higher mortality than the country's average. We here use data from burial registers and censuses to calculate all-cause excess mortality by age and wave in two remote Sámi areas of Norway 1918-20. We hypothesise that geographic isolation, less prior exposure to seasonal influenza, and thus less immunity led to higher Indigenous mortality and a different age distribution of mortality (higher mortality for all) than was typical for this pandemic in non-isolated majority populations (higher young adult mortality & sparing of the elderly). Our results show that in the fall of 1918 (Karasjok), winter of 1919 (Kautokeino), and winter of 1920 (Karasjok), young adults had the highest excess mortality, followed by also high excess mortality among the elderly and children. Children did not exhibit excess mortality in the second wave in Karasjok in 1920. It was not the young adults alone who produced the excess mortality in Kautokeino and Karasjok. We conclude that geographic isolation caused higher mortality among the elderly in the first and second waves, and among children in the first wave.

Associations between rurality and regional differences in sociodemographic factors and the 1918-20 influenza and 2020-21 COVID-19 pandemics in Missouri counties: An ecological study

This study compares pandemic experiences of Missouri's 115 counties based on rurality and sociodemographic characteristics during the 1918-20 influenza and 2020-21 COVID-19 pandemics. The state's counties and overall population distribution have remained relatively stable over the last century, which enables identification of long-lasting pandemic attributes. Sociodemographic data available at the county level for both time periods were taken from U.S. census data and used to create clusters of similar counties. Counties were also grouped by rural status (RSU), including fully (100%) rural, semirural (1-49% living in urban areas), and urban (>50% of the population living in urban areas). Deaths from 1918 through 1920 were collated from the Missouri Digital Heritage database and COVID-19 cases and deaths were downloaded from the Missouri COVID-19 dashboard. Results from sociodemographic analyses indicate that, during both time periods, average farm value, proportion White, and literacy were the most important determinants of sociodemographic clusters. Furthermore, the Urban/Central and Southeastern regions experienced higher mortality during both pandemics than did the North and South. Analyses comparing county groups by rurality indicated that throughout the 1918-20 influenza pandemic, urban counties had the highest and rural had the lowest mortality rates. Early in the 2020-21 COVID-19 pandemic, urban counties saw the most extensive epidemic spread and highest mortality, but as the epidemic progressed, cumulative mortality became highest in semirural counties. Additional results highlight the greater effects both pandemics had on county groups with lower rates of education and a lower proportion of Whites in the population. This was especially true for the far southeastern counties of Missouri ("the Bootheel") during the COVID-19 pandemic. These results indicate that rural-urban and socioeconomic differences in health outcomes are long-standing problems that continue to be of significant importance, even though the overall quality of health care is substantially better in the 21st century.

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.

Lost Lessons of the 1918 Influenza: The 1920s Working Hypothesis, the Public Health Paradigm, and the Prevention of Deadly Pandemics

In standard historical accounts, the hyperlethal 1918 flu pandemic was inevitable once a novel influenza virus appeared. However, in the years following the pandemic, it was obvious to distinguished flu experts from around the world that social and environmental conditions interacted with infectious agents and could enhance the virulence of flu germs. On the basis of the timing and geographic pattern of the pandemic, they hypothesized that an "essential cause" of the pandemic's extraordinary lethality was the extreme, prolonged, and industrial-scale overcrowding of US soldiers in World War I, particularly on troopships. This literature synthesis considers research from history, public health, military medicine, veterinary science, molecular genetics, virology, immunology, and epidemiology. Arguments against the hypothesis do not provide disconfirming evidence. Overall, the findings are consistent with an immunologically similar virus varying in virulence in response to war-related conditions. The enhancement-of-virulence hypothesis deserves to be included in the history of the pandemic and the war. These lost lessons of 1918 point to possibilities for blocking the transformation of innocuous infections into deadly disasters and are relevant beyond influenza for diseases like COVID-19. (Am J Public Health. 2022;112(10):1454-1464. https://doi.org/10.2105/AJPH.2022.306976).

Historically High Excess Mortality During the COVID-19 Pandemic in Switzerland, Sweden, and Spain

BACKGROUND

Excess mortality quantifies the overall mortality impact of a pandemic. Mortality data have been accessible for many countries in recent decades, but few continuous data have been available for longer periods.

OBJECTIVE

To assess the historical dimension of the COVID-19 pandemic in 2020 for 3 countries with reliable death count data over an uninterrupted span of more than 100 years.

DESIGN

Observational study.

SETTING

Switzerland, Sweden, and Spain, which were militarily neutral and not involved in combat during either world war and have not been affected by significant changes in their territory since the end of the 19th century.

PARTICIPANTS

Complete populations of these 3 countries.

MEASUREMENTS

Continuous series of recorded deaths (from all causes) by month from the earliest available year (1877 for Switzerland, 1851 for Sweden, and 1908 for Spain) were jointly modeled with annual age group-specific death and total population counts using negative binomial and multinomial models, which accounted for temporal trends and seasonal variability of prepandemic years. The aim was to estimate the expected number of deaths in a pandemic year for a nonpandemic scenario and the difference in observed and expected deaths aggregated over the year.

RESULTS

In 2020, the number of excess deaths recorded per 100 000 persons was 100 (95% credible interval [CrI], 60 to 135) for Switzerland, 75 (CrI, 40 to 105) for Sweden, and 155 (CrI, 110 to 195) for Spain. In 1918, excess mortality was 6 to 7 times higher. In all 3 countries, the peaks of monthly excess mortality in 2020 were greater than most monthly excess mortality since 1918, including many peaks due to seasonal influenza and heat waves during that period.

LIMITATION

Historical vital statistics might be affected by minor completeness issues before the beginning of the 20th century.

CONCLUSION

In 2020, the COVID-19 pandemic led to the second-largest infection-related mortality disaster in Switzerland, Sweden, and Spain since the beginning of the 20th century.

PRIMARY FUNDING SOURCE

Foundation for Research in Science and the Humanities at the University of Zurich, Swiss National Science Foundation, and National Institute of Allergy and Infectious Diseases.

Analysing the trends in breast surgery practice during COVID-19 pandemic: A comparative study with the Pre-COVID era

Background

The emergence of coronavirus disease 2019 (COVID-19) pandemic has crippled the healthcare systems all over the world. Cancer treatment is indispensable and disruption in its provision can lead to unanticipated consequences. No local data exists that has quantified the impact of COVID-19 pandemic on breast cancer surgery in a lower middle-income country (LMIC), therefore, the present retrospective comparative cohort study is directed to determine the trends in breast surgery operative volumes and its outcomes at our institution in Pakistan.

Materials and methods

Data was collected retrospectively from Pre-COVID-19 and COVID-19 era to determine impact of the current pandemic on breast cancer management practices and outcomes.

Results

Cohort results showed a decline in the number of surgeries during COVID-19 era. A total 149 cases were operated during study period vs. 231 during same Pre-COVID-19 i.e. a 35.5% drop in cancer surgeries. In early COVID-19 time frame, only 4 patients had breast reconstruction, 12 out of 149 (8.05%) surgical candidates were identified having positive COVID-19 status preoperatively and one ASA class 3 patient caught COVID-19 post-surgery and succumbed to virus.

Conclusion

Pandemic has a negative effect on cancer management in a LMIC with compromised access and care of cancer patients.

•

Number of breast cancer surgeries declined during COVID-19 era.

•

Breast reconstructions were not offered in early 3 months of COVID-19.

•

High infectivity rate was observed among cancer patients with no major morbidity.

COVID-19 challenges: From SARS-CoV-2 infection to effective point-of-care diagnosis by electrochemical biosensing platforms

In January 2020, the World Health Organization (WHO) identified a new zoonotic virus, SARS-CoV-2, responsible for causing the COVID-19 (coronavirus disease 2019). Since then, there has been a collaborative trend between the scientific community and industry. Multidisciplinary research networks try to understand the whole SARS-CoV-2 pathophysiology and its relationship with the different grades of severity presented by COVID-19. The scientific community has gathered all the data in the quickly developed vaccines that offer a protective effect for all variants of the virus and promote new diagnostic alternatives able to have a high standard of efficiency, added to shorter response analysis time and portability. The industry enters in the context of accelerating the path taken by science until obtaining the final product. In this review, we show the principal diagnostic methods developed during the COVID-19 pandemic. However, when we observe the diagnostic tools section of an efficient infection outbreak containment report and the features required for such tools, we could observe a highlight of electrochemical biosensing platforms. Such devices present a high standard of analytical performance, are low-cost tools, easy to handle and interpret, and can be used in the most remote and low-resource regions. Therefore, probably, they are the ideal point-of-care diagnostic tools for pandemic scenarios.

Tracking Pandemic Severity Using Data on the Age Structure of Mortality: Lessons From the 1918 Influenza Pandemic in Michigan

Objectives. To test whether distortions in the age structure of mortality during the 1918 influenza pandemic in Michigan tracked the severity of the pandemic. Methods. We calculated monthly excess deaths during the period of 1918 to 1920 by using monthly data on all-cause deaths for the period of 1912 to 1920 in Michigan. Next, we measured distortions in the age distribution of deaths by using the Kuiper goodness-of-fit test statistic comparing the monthly distribution of deaths by age in 1918 to 1920 with the baseline distribution for the corresponding month for 1912 to 1917. Results. Monthly distortions in the age distribution of deaths were correlated with excess deaths for the period of 1918 to 1920 in Michigan (r = 0.83; P < .001). Conclusions. Distortions in the age distribution of deaths tracked variations in the severity of the 1918 influenza pandemic. Public Health Implications. It may be possible to track the severity of pandemic activity with age-at-death data by identifying distortions in the age distribution of deaths. Public health authorities should explore the application of this approach to tracking the COVID-19 pandemic in the absence of complete data coverage or accurate cause-of-death data.

Feasibility and utility of facemask sampling in the detection of SARS-CoV-2 during an ongoing pandemic

Easy access to screening for timely identification and isolation of infectious COVID-19 patients remains crucial in sustaining the international efforts to control COVID-19 spread. A major barrier limiting broad-based screening is the lack of a simple, rapid, and cost-effective COVID-19 testing method. We evaluated the feasibility and utility of facemask sampling in a cohort of 42 COVID-19-positive and 36 COVID-19-negative patients. We used a prototype of Steri-Strips™ (3 M) applied to the inner surface of looped surgical facemasks (Assure), which was worn by patients for a minimum wear time of 3 h, then removed and sent for SARS-CoV-2 PCR testing. Baseline demographics and symptomatology were also collected. Facemask sampling positivity was highest within the first 5 days of symptomatic presentation. Patients with nasopharyngeal and/or oropharyngeal swab SARS-CoV-2 PCR Ct values < 25.09 had SARS-CoV-2 detected on facemask sampling, while patients with Ct values ≥ 25.2 had no SARS-CoV-2 detected on facemask sampling. Facemask sampling can identify patients with COVID-19 during the early symptomatic phase or those with high viral loads, hence allowing timely identification and isolation of those with the highest transmission risk. Given the widespread use of facemasks, this method can potentially be easily applied to achieve broad-based, or even continuous, population screening.