Age-specific mortality during the 1918 influenza pandemic: unravelling the mystery of high young adult mortality.

The worldwide spread of a novel influenza A (H1N1) virus in 2009 showed that influenza remains a significant health threat, even for individuals in the prime of life. This paper focuses on the unusually high young adult mortality observed during the Spanish flu pandemic of 1918. Using historical records from Canada and the U.S., we report a peak of mortality at the exact age of 28 during the pandemic and argue that this increased mortality resulted from an early life exposure to influenza during the previous Russian flu pandemic of 1889-90. We posit that in specific instances, development of immunological memory to an influenza virus strain in early life may lead to a dysregulated immune response to antigenically novel strains encountered in later life, thereby increasing the risk of death. Exposure during critical periods of development could also create holes in the T cell repertoire and impair fetal maturation in general, thereby increasing mortality from infectious diseases later in life. Knowledge of the age-pattern of susceptibility to mortality from influenza could improve crisis management during future influenza pandemics

Stillbirth Risk during the 1918 Influenza Pandemic in Arizona, USA.

INTRODUCTION: Influenza pandemic of 1918 was the most devastating pandemics to date, affecting approximately one-third of the population worldwide. Prior works have documented the impact of the 1918 influenza pandemic on pregnant mothers and pregnancy outcomes like birth defects, miscarriages or preterm births, but the impact of infection on stillbirth is not studied well. OBJECTIVE: To assess the stillbirth risk due to the 1918 influenza pandemic in Arizona, USA. METHODS: We conducted a retrospective study to assess the impact of the 1918 influenza pandemic on stillbirth risk. We manually retrieved 21,334 birth records for the Maricopa County of Arizona state for the years 1915-1925 from a publicly available genealogy database. Logistic regression using SAS statistical software was done to assess the impact of influenza on the risk of stillbirth. Additionally, the study evaluated the risk of stillbirth with advanced maternal age. RESULTS: The results did not show a significant impact of a pandemic on stillbirth risk. January 1920 experienced the highest rate of stillbirths with 59 stillbirths per 1000 births, 9-10 months later, the deadly second pandemic wave. There was also a higher rate of stillbirth in July 1919, with 49 stillbirths per 1000 births. Additionally, there was a significant association between stillbirth and advanced maternal age (P-value 0.0096, at 0.05 level of significance) with stillbirth risk of 1.42 (95% Confidence interval: 1.17, 1.72) in younger women (\u3c35 yrs.) compared to older women (≥35 yrs.). The results showed that the risk of stillbirth is least if the age of the mother is approximately 26 years at the time of pregnancy. DISCUSSION: Though the results did not show a significant impact of the pandemic on stillbirth risk, the study did observe a higher rate of stillbirth in July 1919, consistent with natality decline reported in the previous study in the same month in Arizona. Also, the results are in line with prior work and found that there is a high risk of stillbirths with advanced maternal age

Send Only Your Serious Cases: Delivering Flu to Toronto: An Anthropological Analysis of the 1918 -1919 Influenza Epidemic in Toronto, Ontario, Canada.

This project looks at the 1918-19 pandemic influenza experience in Toronto, Ontario, Canada. Based on historical records (most notably death registries and archival material) this work strives to understand the social, biological, and environmental conditions that facilitated the spread of this virulent microorganism throughout the city. Grounded in the anthropological frameworks of evolutionary medicine, political economy and syndemics, this dissertation is designed to present a qualitative historical account of the pandemic in one of Canada\u27s largest cities. This piece adds to the growing body of literature aimed at documenting one of the most catastrophic events of the 20th century. It also explores how epidemics are shaped by and in turn shape history. Many of the key findings of this work stem from the relationship between the Great War and the H1N1 strain responsible for Spanish flu. Soldiers appear to have brought the disease to Toronto and the conditions generated by the prolonged conflict in all likelihood increased individual susceptibility (via. increased stress, sustained food shortages and promotion of status incongruity). It is important to note however, that the effects of the war were not all detrimental to the population of Toronto. Sustained investment in the military effort promoted the development of informal networks of care, which were paramount in the city\u27s effort to curtail influenza mortality. This dissertation generates as many questions as it answers, with the main message being that an analysis of infectious disease experiences must be cognizant of the two-way linkages between culture and biology

Influenza interaction with cocirculating pathogens, and its impact on surveillance, pathogenesis and epidemic profile: a key role for mathematical modeling

ABSTRACT Evidence is mounting that influenza virus, a major contributor to the global disease burden, interacts with other pathogens infecting the human respiratory tract. Taking into account interactions with other pathogens may be critical to determining the real influenza burden and the full impact of public health policies targeting influenza. That necessity is particularly true for mathematical modeling studies, which have become critical in public health decision-making, despite their usually focusing on lone influenza virus acquisition and infection, thereby making broad oversimplifications regarding pathogen ecology. Herein, we review evidence of influenza virus interaction with bacteria and viruses, and the modeling studies that incorporated some of these. Despite the many studies examining possible associations between influenza and Streptococcus pneumoniae, Staphylococcus aureus, Haemophilus influenzae, Neisseria meningitides , respiratory syncytial virus, human rhinoviruses, human parainfluenza viruses, etc., very few mathematical models have integrated other pathogens alongside influenza. A notable exception is the recent modeling of the pneumococcus-influenza interaction, which highlighted potential influenza-related increased pneumococcal transmission and pathogenicity. That example demonstrates the power of dynamic modeling as an approach to test biological hypotheses concerning interaction mechanisms and estimate the strength of those interactions. We explore how different interference mechanisms may lead to unexpected incidence trends and misinterpretations. Using simple transmission models, we illustrate how existing interactions might impact public health surveillance systems and demonstrate that the development of multipathogen models is essential to assess the true public health burden of influenza, and help improve planning and evaluation of control measures. Finally, we identify the public health needs, surveillance, modeling and biological challenges, and propose avenues of research for the coming years. Author Summary Influenza is a major pathogen responsible for important morbidity and mortality burdens worldwide. Mathematical models of influenza virus acquisition have been critical to understanding its epidemiology and planning public health strategies of infection control. It is increasingly clear that microbes do not act in isolation but potentially interact within the host. Hence, studying influenza alone may lead to masking effects or misunderstanding information on its transmission and severity. Herein, we review the literature on bacterial and viral species that interact with the influenza virus, interaction mechanisms, and mathematical modeling studies integrating interactions. We report evidence that, beyond the classic secondary bacterial infections, many pathogenic bacteria and viruses probably interact with influenza. Public health relevance of pathogen interactions is detailed, showing how potential misreading or a narrow outlook might lead to mistaken public health decisionmaking. We describe the role of mechanistic transmission models in investigating this complex system and obtaining insight into interactions between influenza and other pathogens. Finally, we highlight benefits and challenges in modeling, and speculate on new opportunities made possible by taking a broader view: including basic science, clinical relevance and public health

Mortality and transmissibility patterns of the 1957 influenza pandemic in Maricopa County, Arizona

abstract: Background While prior studies have quantified the mortality burden of the 1957 H2N2 influenza pandemic at broad geographic regions in the United States, little is known about the pandemic impact at a local level. Here we focus on analyzing the transmissibility and mortality burden of this pandemic in Arizona, a setting where the dry climate was promoted as reducing respiratory illness transmission yet tuberculosis prevalence was high. Methods Using archival death certificates from 1954 to 1961, we quantified the age-specific seasonal patterns, excess-mortality rates, and transmissibility patterns of the 1957 H2N2 pandemic in Maricopa County, Arizona. By applying cyclical Serfling linear regression models to weekly mortality rates, the excess-mortality rates due to respiratory and all-causes were estimated for each age group during the pandemic period. The reproduction number was quantified from weekly data using a simple growth rate method and assumed generation intervals of 3 and 4 days. Local newspaper articles published during 1957–1958 were also examined. Results Excess-mortality rates varied between waves, age groups, and causes of death, but overall remained low. From October 1959-June 1960, the most severe wave of the pandemic, the absolute excess-mortality rate based on respiratory deaths per 10,000 population was 16.59 in the elderly (≥65 years). All other age groups exhibit very low excess-mortality and the typical U-shaped age-pattern was absent. However, the standardized mortality ratio was greatest (4.06) among children and young adolescents (5–14 years) from October 1957-March 1958, based on mortality rates of respiratory deaths. Transmissibility was greatest during the same 1957–1958 period, when the mean reproduction number was estimated at 1.08–1.11, assuming 3- or 4-day generation intervals with exponential or fixed distributions. Conclusions Maricopa County exhibited very low mortality impact associated with the 1957 influenza pandemic. Understanding the relatively low excess-mortality rates and transmissibility in Maricopa County during this historic pandemic may help public health officials prepare for and mitigate future outbreaks of influenza.The electronic version of this article is the complete one and can be found online at: https://bmcinfectdis.biomedcentral.com/articles/10.1186/s12879-016-1716-

PLoS One

Infectious diseases and underlying medical conditions common to Africa may affect influenza frequency and severity. We conducted a systematic review of published studies on influenza and the following co-infections or co-morbidities that are prevalent in Africa: dengue, malaria, measles, meningococcus, Pneumocystis jirovecii pneumonia (PCP), hemoglobinopathies, and malnutrition. Articles were identified except for influenza and PCP. Very few studies were from Africa. Sickle cell disease, dengue, and measles co-infection were found to increase the severity of influenza disease, though this is based on few studies of dengue and measles and the measles study was of low quality. The frequency of influenza was increased among patients with sickle cell disease. Influenza infection increased the frequency of meningococcal disease. Studies on malaria and malnutrition found mixed results. Age-adjusted morbidity and mortality from influenza may be more common in Africa because infections and diseases common in the region lead to more severe outcomes and increase the influenza burden. However, gaps exist in our knowledge about these interactions.26068416PMC4466242851

Streptococcus pneumoniae Coinfection Is Correlated with the Severity of H1N1 Pandemic Influenza

Initial reports in May 2009 of the novel influenza strain H1N1pdm estimated a case fatality rate (CFR) of 0.6%, similar to that of seasonal influenza. In July 2009, however, Argentina reported 3056 cases with 137 deaths, representing a CFR of 4.5%. Potential explanations for increased CFR included virus reassortment or genetic drift, or infection of a more vulnerable population. Virus genomic sequencing of 26 Argentinian samples representing both severe and mild disease indicated no evidence of reassortment, mutations associated with resistance to antiviral drugs, or genetic drift that might contribute to virulence. Furthermore, no evidence was found for increased frequency of risk factors for H1N1pdm disease.We examined nasopharyngeal swab samples (NPS) from 199 cases of H1N1pdm infection from Argentina with MassTag PCR, testing for 33 additional microbial agents. The study population consisted of 199 H1N1pdm-infected subjects sampled between 23 June and 4 July 2009. Thirty-nine had severe disease defined as death (n = 20) or hospitalization (n = 19); 160 had mild disease. At least one additional agent of potential pathogenic importance was identified in 152 samples (76%), including Streptococcus pneumoniae (n = 62); Haemophilus influenzae (n = 104); human respiratory syncytial virus A (n = 11) and B (n = 1); human rhinovirus A (n = 1) and B (n = 4); human coronaviruses 229E (n = 1) and OC43 (n = 2); Klebsiella pneumoniae (n = 2); Acinetobacter baumannii (n = 2); Serratia marcescens (n = 1); and Staphylococcus aureus (n = 35) and methicillin-resistant S. aureus (MRSA, n = 6). The presence of S. pneumoniae was strongly correlated with severe disease. S. pneumoniae was present in 56.4% of severe cases versus 25% of mild cases; more than one-third of H1N1pdm NPS with S. pneumoniae were from subjects with severe disease (22 of 62 S. pneumoniae-positive NPS, p = 0.0004). In subjects 6 to 55 years of age, the adjusted odds ratio (OR) of severe disease in the presence of S. pneumoniae was 125.5 (95% confidence interval [CI], 16.95, 928.72; p<0.0001).The association of S. pneumoniae with morbidity and mortality is established in the current and previous influenza pandemics. However, this study is the first to demonstrate the prognostic significance of non-invasive antemortem diagnosis of S. pneumoniae infection and may provide insights into clinical management

Modeling rapidly disseminating infectious disease during mass gatherings

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