scholarly journals 1363Just a flu? Comparing COVID-19 and influenza mortality

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
David Muscatello ◽  
Peter McIntyre
Keyword(s):  
New York ◽  
Death Rate ◽  
Influenza Season ◽  
Influenza Pandemic ◽  
The United States ◽  
Epidemiological Methods ◽  
Influenza Pandemics ◽  
Specific Mortality ◽  
Standardized Mortality Ratios ◽  
1918 Influenza

Abstract Background Benchmarks are needed for assessing the severity of the COVID-19 pandemic. However, comparisons can be misleading unless marked differences in age-specific mortality and differences in population age structure are considered. Methods Using COVID-19 death rates for New York City as at 2 June 2020, we used indirect age standardization to estimate standardized mortality ratios (SMR) for the first winter waves of the 1918 and 2009 influenza pandemics and the severe 2017-2018 influenza season in the United States (US). Data were obtained from published statistics. Results After adjusting for age, New York City’s death rate during the 1918 winter influenza pandemic wave was 6.7 times higher overall compared with the first wave of COVID-19 in 2020. New York City's first wave COVID-19 death rate was an estimated 59 times higher than that of the 2009 US influenza pandemic, and 14 times higher than that of the severe 2017-2018 influenza season. In < 45 year-olds, the 1918 influenza death rate was 42 times higher than COVID-19 in 2020. In ≥ 65 year-olds, compared with the 2009 pandemic, the COVID-19 death rate was 320 times higher, while in children it was one half. Conclusions The 1918 pandemic was more deadly than COVID-19, which was, in turn, far more deadly than both the 2009 influenza pandemic and severe seasonal influenza. Age-specific mortality differences should be considered in decisions on COVID-19 vaccination strategies. Key messages Fundamental epidemiological methods remain valuable for modern epidemic risk assessment. COVID-19 is not just a ‘flu’.

scholarly journals Did the 1918 influenza cause the twentieth century cardiovascular mortality epidemic in the United States?

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e2531 ◽  
Author(s):  
Steven Tate ◽  
Jamie J. Namkung ◽  
Andrew Noymer
Keyword(s):  
United States ◽  
Twentieth Century ◽  
Cardiovascular Mortality ◽  
Death Rate ◽  
Causes Of Death ◽  
Influenza Pandemic ◽  
The United States ◽  
Point Of View ◽  
1918 Influenza

During most of the twentieth century, cardiovascular mortality increased in the United States while other causes of death declined. By 1958, the age-standardized death rate (ASDR) for cardiovascular causes for females was 1.84 times that for all other causes,combined(and, for males, 1.79×). Although contemporary observers believed that cardiovascular mortality would remain high, the late 1950s and early 1960s turned out to be the peak of a roughly 70-year epidemic. By 1988 for females (1986 for males), a spectacular decline had occurred, wherein the ASDR for cardiovascular causes was less than that for other causes combined. We discuss this phenomenon from a demographic point of view. We also test a hypothesis from the literature, that the 1918 influenza pandemic caused the cardiovascular mortality epidemic; we fail to find support.

scholarly journals Timing of social distancing policies and COVID-19 mortality: county-level evidence from the U.S.

2021 ◽  
Author(s):  
Catalina Amuedo-Dorantes ◽  
Neeraj Kaushal ◽  
Ashley N. Muchow
Keyword(s):  
New York ◽  
Political Ideology ◽  
Death Rate ◽  
The United States ◽  
County Level ◽  
Level Data ◽  
Level Information ◽  
Alternative Measures ◽  
The U.S ◽  
Pharmaceutical Interventions

AbstractUsing county-level data on COVID-19 mortality and infections, along with county-level information on the adoption of non-pharmaceutical interventions (NPIs), we examine how the speed of NPI adoption affected COVID-19 mortality in the United States. Our estimates suggest that adopting safer-at-home orders or non-essential business closures 1 day before infections double can curtail the COVID-19 death rate by 1.9%. This finding proves robust to alternative measures of NPI adoption speed, model specifications that control for testing, other NPIs, and mobility and across various samples (national, the Northeast, excluding New York, and excluding the Northeast). We also find that the adoption speed of NPIs is associated with lower infections and is unrelated to non-COVID deaths, suggesting these measures slowed contagion. Finally, NPI adoption speed appears to have been less effective in Republican counties, suggesting that political ideology might have compromised their efficacy.

scholarly journals Influenza Circulation in United States Army Training Camps Before and During the 1918 Influenza Pandemic: Clues to Early Detection of Pandemic Viral Emergence

2015 ◽  
Vol 2 (2) ◽  
Author(s):  
Daniel S. Chertow ◽  
Rongman Cai ◽  
Junfeng Sun ◽  
John Grantham ◽  
Jeffery K. Taubenberger ◽  
...  
Keyword(s):  
United States ◽  
World War I ◽  
United States Army ◽  
Respiratory Diseases ◽  
National Guard ◽  
Influenza Pandemic ◽  
Case Fatality ◽  
The United States ◽  
Low Incidence ◽  
1918 Influenza

Abstract Background.  Surveillance for respiratory diseases in domestic National Army and National Guard training camps began after the United States’ entry into World War I, 17 months before the “Spanish influenza” pandemic appeared. Methods.  Morbidity, mortality, and case-fatality data from 605 625 admissions and 18 258 deaths recorded for 7 diagnostic categories of respiratory diseases, including influenza and pneumonia, were examined over prepandemic and pandemic periods. Results.  High pandemic influenza mortality was primarily due to increased incidence of, but not increased severity of, secondary bacterial pneumonias. Conclusions.  Two prepandemic incidence peaks of probable influenza, in December 1917–January 1918 and in March–April 1918, differed markedly from the September–October 1918 pandemic onset peak in their clinical-epidemiologic features, and they may have been caused by seasonal or endemic viruses. Nevertheless, rising proportions of very low incidence postinfluenza bronchopneumonia (diagnosed at the time as influenza and bronchopneumonia) in early 1918 could have reflected circulation of the pandemic virus 5 months before it emerged in pandemic form. In this study, we discuss the possibility of detecting pandemic viruses before they emerge, by surveillance of special populations.

Calculating Age-Standardized Death Rates Among People With HIV Comparable Across Jurisdictions and Over Time

2021 ◽  
Vol 111 (1) ◽  
pp. 121-126
Author(s):  
Qiang Xia ◽  
Ying Sun ◽  
Chitra Ramaswamy ◽  
Lucia V. Torian ◽  
Wenhui Li
Keyword(s):  
United States ◽  
New York ◽  
New York City ◽  
York City ◽  
Death Rate ◽  
Age Distribution ◽  
The United States ◽  
Local Health ◽  
Death Rates ◽  
Over Time

The Centers for Disease Control and Prevention (CDC) and local health jurisdictions have been using HIV surveillance data to monitor mortality among people with HIV in the United States with age-standardized death rates, but the principles of age standardization have not been consistently followed, making age standardization lose its purpose—comparison over time, across jurisdictions, or by other characteristics. We review the current practices of age standardization in calculating death rates among people with HIV in the United States, discuss the principles of age standardization including those specific to the HIV population whose age distribution differs markedly from that of the US 2000 standard population, make recommendations, and report age-standardized death rates among people with HIV in New York City. When we restricted the analysis population to adults aged between 18 and 84 years in New York City, the age-standardized death rate among people with HIV decreased from 20.8 per 1000 (95% confidence interval [CI] = 19.2, 22.3) in 2013 to 17.1 per 1000 (95% CI = 15.8, 18.3) in 2017, and the age-standardized death rate among people without HIV decreased from 5.8 per 1000 in 2013 to 5.5 per 1000 in 2017.

scholarly journals COVID-19 in Newborns and Infants—Low Risk of Severe Disease: Silver Lining or Dark Cloud?

2020 ◽  
Vol 37 (08) ◽  
pp. 845-849 ◽  
Author(s):  
Munmun Rawat ◽  
Praveen Chandrasekharan ◽  
Mark D. Hicar ◽  
Satyan Lakshminrusimha
Keyword(s):  
Influenza Pandemic ◽  
Severe Disease ◽  
The United States ◽  
Dark Cloud ◽  
Symptomatic Infection ◽  
Key Points ◽  
High Incidence ◽  
1918 Influenza ◽  
Novel Coronavirus ◽  
Low Prevalence

One hundred years after the 1918 influenza pandemic, we now face another pandemic with the severe acute respiratory syndrome–novel coronavirus-2 (SARS-CoV-2). There is considerable variability in the incidence of infection and severe disease following exposure to SARS-CoV-2. Data from China and the United States suggest a low prevalence of neonates, infants, and children, with those affected not suffering from severe disease. In this article, we speculate different theories why this novel agent is sparing neonates, infants, and young children. The low severity of SARS-CoV-2 infection in this population is associated with a high incidence of asymptomatic or mildly symptomatic infection making them efficient carriers. Key Points

scholarly journals Lessons From Influenza Pandemics of the Last 100 Years

2019 ◽  
Author(s):  
Arnold S Monto ◽  
Keiji Fukuda
Keyword(s):  
Avian Influenza ◽  
Seasonal Influenza ◽  
Influenza Pandemic ◽  
Risk Groups ◽  
Influenza Viruses ◽  
Avian Influenza Viruses ◽  
Influenza Pandemics ◽  
Fundamental Difficulty ◽  
1918 Influenza ◽  
The Impact

Abstract Seasonal influenza is an annual occurrence, but it is the threat of pandemics that produces universal concern. Recurring reports of avian influenza viruses severely affecting humans have served as constant reminders of the potential for another pandemic. Review of features of the 1918 influenza pandemic and subsequent ones helps in identifying areas where attention in planning is critical. Key among such issues are likely risk groups and which interventions to employ. Past pandemics have repeatedly underscored, for example, the vulnerability of groups such as pregnant women and taught other lessons valuable for future preparedness. While a fundamental difficulty in planning for the next pandemic remains their unpredictability and infrequency, this uncertainty can be mitigated, in part, by optimizing the handling of the much more predictable occurrence of seasonal influenza. Improvements in antivirals and novel vaccine formulations are critical in lessening the impact of both pandemic and seasonal influenza.

scholarly journals Racial Disparities in Mortality During the 1918 Influenza Pandemic in United States Cities

2021 ◽  
Author(s):  
Martin Eiermann ◽  
Elizabeth Wrigley-Field ◽  
James J. Feigenbaum ◽  
Jonas Helgertz ◽  
Elaine Hernandez ◽  
...  
Keyword(s):  
United States ◽  
Racial Disparities ◽  
Early Life ◽  
Racial Inequality ◽  
Influenza Pandemic ◽  
The United States ◽  
Careful Examination ◽  
Unexpected Result ◽  
1918 Influenza ◽  
Socio Demographic Factors

The 1918 influenza pandemic stands out because of the unusual age pattern of high mortality. In the United States, another feature merits scientific scrutiny: against a historical backdrop of extreme racial health inequality, the pandemic produced strikingly small ratios of nonwhite to white influenza and pneumonia mortality. We provide the most complete account to date of these racial disparities in 1918, showing that, across U.S. cities, they were almost uniformly small. We examine four potential explanations for this unexpected result, including [1] socio-demographic factors like segregation, [2] city-level implementation of non-pharmaceutical interventions (NPIs), [3] exposure to the milder spring 1918 “herald wave,” and [4] early-life exposures to other influenza strains resulting in differential immunological vulnerability to the 1918 flu. While we find little evidence for 1-3, we offer suggestive evidence that racial variation in early-life exposure to the 1889-1892 influenza pandemic shrunk racial disparities during the 1918 pandemic. We also raise the possibility that differential behavioral responses to the herald wave may have protected nonwhite urban populations. By providing a comprehensive description and careful examination of the potential drivers of racial inequality in mortality during the 1918 pandemic, our study provides a framework to consider interactions between the natural history of particular microbial agents and the social histories of the populations they infect.

scholarly journals Racial, Economic and Health Inequality and COVID-19 Infection in the United States

2020 ◽  
Author(s):  
Vida Abedi ◽  
Oluwaseyi Olulana ◽  
Venkatesh Avula ◽  
Durgesh Chaudhary ◽  
Ayesha Khan ◽  
...  
Keyword(s):  
United States ◽  
New York ◽  
Health Care Access ◽  
Urban Areas ◽  
Death Rate ◽  
The United States ◽  
Preliminary Evidence ◽  
Cross Sectional Study ◽  
Cross Sectional ◽  
The Impact

AbstractBackgroundThere is preliminary evidence of racial and social-economic disparities in the population infected by and dying from COVID-19. The goal of this study is to report the associations of COVID-19 with respect to race, health and economic inequality in the United States.MethodsWe performed a cross-sectional study of the associations between infection and mortality rate of COVID-19 and demographic, socioeconomic and mobility variables from 369 counties (total population: 102,178,117 [median: 73,447, IQR: 30,761-256,098]) from the seven most affected states (Michigan, New York, New Jersey, Pennsylvania, California, Louisiana, Massachusetts).FindingsThe risk factors for infection and mortality are different. Our analysis shows that counties with more diverse demographics, higher population, education, income levels, and lower disability rates were at a higher risk of COVID-19 infection. However, counties with higher disability and poverty rates had a higher death rate. African Americans were more vulnerable to COVID-19 than other ethnic groups (1,981 African American infected cases versus 658 Whites per million). Data on mobility changes corroborate the impact of social distancing.InterpretationThe observed inequality might be due to the workforce of essential services, poverty, and access to care. Counties in more urban areas are probably better equipped at providing care. The lower rate of infection, but a higher death rate in counties with higher poverty and disability could be due to lower levels of mobility, but a higher rate of comorbidities and health care access.

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