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.

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

The global influenza pandemic that emerged in 1918 has become the event of reference for a broad spectrum of policymakers seeking to learn from the past. This article sheds light on multiple waves of excess mortality that occurred in the US state of Michigan at the time with insights into how epidemics might evolve and propagate across space and time. We analyzed original monthly data on all-cause deaths by county for the 83 counties of Michigan and interpreted the results in the context of what is known about the pandemic. Counties in Michigan experienced up to four waves of excess mortality over a span of two years, including a severe one in early 1920. Some counties experienced two waves in late 1918 while others had only one. The 1920 wave propagated across the state in a different manner than the fall and winter 1918 waves. The twin waves in late 1918 were likely related to the timing of the statewide imposition of a three-week social distancing order. Michigan's experience holds sobering lessons for those who wish to understand how immunologically naïve populations encounter novel viral pathogens.

The US Public Health Service House-to-House Canvass Survey of the Morbidity and Mortality of the 1918 Influenza Pandemic.

Between November 20, 1918, and March 12, 1919, the US Public Health Service carried out a vast population-based survey to assess the incidence rate and mortality of the influenza pandemic among 146 203 persons in 18 localities across the United States. The survey attempted to retrospectively assess all self-reported or diagnosed cases of influenza since August 1, 1918. It indicated that the cumulative incidence of symptomatic influenza over 6 months had been 29.4% (range = 15% in Louisville, KY, to 53.3% in San Antonio, TX). The overall case fatality rate (CFR) was 1.70%, and it ranged from 0.78% in San Antonio to 3.14% in New London, Connecticut. Localities with high cumulative incidence were not necessarily those with high CFR. Overall, assuming the survey missed asymptomatic cases, between August 1, 1918, and February 21, 1919, maybe more than 50% of the population was infected, and about 1% of the infected died. Eight months into the COVID-19 pandemic, the United States has not yet launched a survey that would provide population-based estimates of incidence and CFRs analogous to those generated by the 1918 US Public Health Service house-to-house canvass survey of influenza.

Long-lasting effects of pandemics: The case of the 1918 influenza pandemic in Argentina.

The 2019 novel coronavirus disease pandemic poses a serious threat. While its short-term effects are evident, its long-term consequences are a matter of analysis. In this work, the existence of long-lasting negative effects derived from exposure in utero to a great pandemic -1918 influenza pandemic- is analysed for the Argentine case. Outcomes of interest include educational achievement and unemployment status in adulthood -50 years after the pandemic. Based on a regression analysis, temporal differences in the spread of the pandemic and between close birth cohorts are exploited. The results indicate a significant reduction in educational achievement for people exposed in utero to the pandemic. In the region with the highest incidence of cases (Noroeste), this reduction is 0.5 years of education. There are no significant changes in the chances of being unemployed. In the context of climate change, these results constitute a call of attention for the implementation of child protection policies from gestation.

Death, demography and the denominator: Age-adjusted Influenza-18 mortality in Ireland.

Using the Irish experience of the 1918-1919 Spanish flu pandemic ("Influenza-18"), we demonstrate how pandemic mortality statistics can be sensitive to the demographic composition of a country. We build a new spatially disaggregated population database for Ireland's 32 counties for 1911-1920 with vital statistics on births, ageing, migration and deaths. Our principal contribution is to show why, and how, age-at-death data should be used to construct the age-standardised statistics necessary to make meaningful comparisons of mortality rates across time and space. We conclude that studies of the economic consequences of pandemics must better control for demographic factors if they are to yield useful policy-relevant insights. For example, while Northern Ireland had a higher crude death rate during the first wave of the Covid-19 pandemic, it also has an older population; age-adjusted mortality paints a very different picture.

What Can We Learn about Aging and COVID-19 by Studying Mortality?

Promising ideas and directions for further research into biology of aging are discussed using analysis of the age-related kinetics of organisms' mortality. It is shown that the traditional evolutionary theory explaining aging by decreasing force of natural selection with age is not consistent with the data on age-related mortality kinetics. The hypothesis of multistage destruction of organisms with age, including the rate-limiting stage of transition to a state of non-specific vulnerability ("non-survivor"), is discussed. It is found that the effect of the COVID-19 coronavirus infection on mortality is not additive (as it was the case with the Spanish flu epidemic in 1918), but multiplicative (proportional) for ages over 65 years.

The COVID-19 pandemic: the public health reality.

The coronavirus disease (COVID-19), while mild in most cases, has nevertheless caused significant mortality. The measures adopted in most countries to contain it have led to colossal social and economic disruptions, which will impact the medium- and long-term health outcomes for many communities. In this paper, we deliberate on the reality and facts surrounding the disease. For comparison, we present data from past pandemics, some of which claimed more lives than COVID-19. Mortality data on road traffic crashes and other non-communicable diseases, which cause more deaths each year than COVID-19 has so far, is also provided. The indirect, serious health and social effects are briefly discussed. We also deliberate on how misinformation, confusion stemming from contrasting expert statements, and lack of international coordination may have influenced the public perception of the illness and increased fear and uncertainty. With pandemics and similar problems likely to re-occur, we call for evidence-based decisions, the restoration of responsible journalism and communication built on a solid scientific foundation.