The 1918-1920 influenza pandemic in Peru

Respiratory pandemics, urban planning and design: A multidisciplinary rapid review of the literature

COVID-19 is the most recent respiratory pandemic to necessitate better knowledge about city planning and design. The complex connections between cities and pandemics, however challenge traditional approaches to reviewing literature. In this article we adopted a rapid review methodology. We review the historical literature on respiratory pandemics and their documented connections to urban planning and design (both broadly defined as being concerned with cities as complex systems). Our systematic search across multidisciplinary databases returned a total of 1323 sources, with 92 articles included in the final review. Findings showed that the literature represents the multi-scalar nature of cities and pandemics - pandemics are global phenomena spread through an interconnected world, but require regional, city, local and individual responses. We characterise the literature under ten themes: scale (global to local); built environment; governance; modelling; non-pharmaceutical interventions; socioeconomic factors; system preparedness; system responses; underserved and vulnerable populations; and future-proofing urban planning and design. We conclude that the historical literature captures how city planning and design intersects with a public health response to respiratory pandemics. Our thematic framework provides parameters for future research and policy responses to the varied connections between cities and respiratory pandemics.

Global variation in early epidemic growth rates and reproduction number of seasonal influenza

INTRODUCTION

Little is known about global variation in early epidemic growth rates and effective reproduction numbers (R_e) of seasonal influenza. We aimed to estimate global variation in R_e of influenza type A and B during a single period.

METHODS

Country influenza detection time series from September 2017 through January 2019 were obtained from an international database. Type A and B epidemics by country were selected based on R_e estimates for a five-week moving window advanced by week. Associations of R_e with absolute latitude, Human Development Index, percent of the population aged <15 years and percent living rurally in each country were assessed.

RESULTS

Time series were included for 119 of 169 available countries. There were 100 countries with influenza A and 79 with B epidemics. Median R_e for both influenza A and B epidemics was 1.23 (ranges: A 1.10, 1.60; B 1.06, 1.58). R_e of influenza B, but not A, was independently associated with absolute latitude, increasing by 0.022 (95% CI 0.002, 0.043) per 10 degrees.

CONCLUSIONS

R_e of influenza A and B were similar. Only R_e of influenza B was associated with country characteristics; increasing with distance from the equator. The approach may be suitable for continuous R_e surveillance.

The beginning and ending of a respiratory viral pandemic-lessons from the Spanish flu

The COVID‐19 pandemic goes into its third year and the world population is longing for an end to the pandemic. Computer simulations of the future development of the pandemic have wide error margins and predictions on the evolution of new viral variants of SARS‐CoV‐2 are uncertain. It is thus tempting to look into the development of historical viral respiratory pandemics for insight into the dynamic of pandemics. The Spanish flu pandemic of 1918 caused by the influenza virus H1N1 can here serve as a potential model case. Epidemiological observations on the shift of influenza mortality from very young and old subjects to high mortality in young adults delimitate the pandemic phase of the Spanish flu from 1918 to 1920. The identification and sequencing of the Spanish flu agent allowed following the H1N1 influenza virus after the acute pandemic phase. During the 1920s H1N1 influenza virus epidemics with substantial mortality were still observed. As late as 1951, H1N1 strains of high virulence evolved but remained geographically limited. Until 1957, the H1N1 virus evolved by accumulation of mutations (‘antigenic drift’) and some intratypic reassortment. H1N1 viruses were then replaced by the pandemic H2N2 influenza virus from 1957, which was in 1968 replaced by the pandemic H3N2 influenza virus; both viruses were descendants from the Spanish flu agent but showed the exchange of entire gene segments (‘antigenic shift’). In 1977, H1N1 reappeared from an unknown source but caused only mild disease. However, H1N1 achieved again circulation in the human population and is now together with the H3N2 influenza virus an agent of seasonal influenza winter epidemics.

Clinical data to be used as a foundation to combat Covid-19 vaccine hesitancy

The coronavirus has become the paramount subject in peoples' lives, affecting and disrupting virtually every aspect of society, as the pandemic casts a shadow over the world. The facts, myths, and conspiracy theories centered on the Covid-19 pandemic have dominated social media accounts, local and national newspapers, as well as television programs. Strategies need to be evolved to counter Covid-19 vaccine hesitancy and mitigate health disparities in at-risk populations. Overcoming misinformation and distrust will require an interdisciplinary approach to deal with Covid-19. The purpose of this review is to offer a factual basis to all healthcare providers to assist in framing strategies to mitigate vaccine hesitancy and achieve herd immunity to combat the deadly Covid-19 pandemic. First an overview of the discovery of the viruses and their molecular structures will be presented. Secondly, a historical perspective is offered, comparing the differences between the 1918 flu pandemic and the current covid-19 pandemic. Lastly, an overview for proposed techniques and methods to counter and or mitigate covid-19 vaccine misinformation that may be used by an interdisciplinary team will be offered narratively and graphically.

Archival Big Data and the Spanish Flu in Copenhagen

Purpose

The Spanish Flu 1918–1920 saw a high degree of excess mortality among young and healthy adults. The purpose of this paper is a further exploration of the hypothesis that high mortality risk during The Spanish Flu in Copenhagen was associated with early life exposure to The Russian Flu 1889–1892.

Design/methodology/approach

Based on 37,000 individual-level death records in a new unique database from The Copenhagen City Archives combined with approximate cohort-specific population totals interpolated from official censuses of population, the author compiles monthly time series on all-cause mortality rates 1916–1922 in Copenhagen by gender and one-year birth cohorts. The author then analyses birth cohort effects on mortality risk during The Spanish Flu using regression analysis.

Findings

The author finds support for hypotheses relating early life exposure to The Russian Flu to mortality risk during The Spanish Flu. Some indications of possible gender heterogeneity during the first wave of The Spanish Flu – not found in previous studies – should be a topic for future research based on data from other countries.

Originality/value

Due to lack of individual-level death records with exact dates of birth and death, previous studies on The Spanish Flu in Denmark and many other countries have relied on data with lower birth cohort resolutions than the one-year birth cohorts used in this study. The analysis in this paper illustrates how archival Big Data can be used to gain new insights in studies on historical pandemics.

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.

Systematic analysis of infectious disease outcomes by age shows lowest severity in school-age children

The COVID-19 pandemic has ignited interest in age-specific manifestations of infection but surprisingly little is known about relative severity of infectious disease between the extremes of age. In a systematic analysis we identified 142 datasets with information on severity of disease by age for 32 different infectious diseases, 19 viral and 13 bacterial. For almost all infections, school-age children have the least severe disease, and severity starts to rise long before old age. Indeed, for many infections even young adults have more severe disease than children, and dengue was the only infection that was most severe in school-age children. Together with data on vaccine response in children and young adults, the findings suggest peak immune function is reached around 5-14 years of age. Relative immune senescence may begin much earlier than assumed, before accelerating in older age groups. This has major implications for understanding resilience to infection, optimal vaccine scheduling, and appropriate health protection policies across the life course.

Spatiotemporal Patterns and Diffusion of the 1918 Influenza Pandemic in British India

The factors that drive spatial heterogeneity and diffusion of pandemic influenza remain debated. We characterized the spatiotemporal mortality patterns of the 1918 influenza pandemic in British India and studied the role of demographic factors, environmental variables, and mobility processes on the observed patterns of spread. Fever-related and all-cause excess mortality data across 206 districts in India from January 1916 to December 1920 were analyzed while controlling for variation in seasonality particular to India. Aspects of the 1918 autumn wave in India matched signature features of influenza pandemics, with high disease burden among young adults, (moderate) spatial heterogeneity in burden, and highly synchronized outbreaks across the country deviating from annual seasonality. Importantly, we found population density and rainfall explained the spatial variation in excess mortality, and long-distance travel via railroad was predictive of the observed spatial diffusion of disease. A spatiotemporal analysis of mortality patterns during the 1918 influenza pandemic in India was integrated in this study with data on underlying factors and processes to reveal transmission mechanisms in a large, intensely connected setting with significant climatic variability. The characterization of such heterogeneity during historical pandemics is crucial to prepare for future pandemics.

Age-Specific Excess Mortality Patterns During the 1918-1920 Influenza Pandemic in Madrid, Spain

Although much progress has been made to uncover age-specific mortality patterns of the 1918 influenza pandemic in populations around the world, more studies in different populations are needed to make sense of the heterogeneous death impact of this pandemic. We assessed the absolute and relative magnitudes of 3 pandemic waves in the city of Madrid, Spain, between 1918 and 1920, on the basis of age-specific all-cause and respiratory excess death rates. Excess death rates were estimated using a Serfling model with a parametric bootstrapping approach to calibrate baseline death levels with quantified uncertainty. Excess all-cause and pneumonia and influenza mortality rates were estimated for different pandemic waves and age groups. The youngest and oldest persons experienced the highest excess mortality rates, and young adults faced the highest standardized mortality risk. Waves differed in strength; the peak standardized mortality risk occurred during the herald wave in spring 1918, but the highest excess rates occurred during the fall and winter of 1918/1919. Little evidence was found to support a “W”-shaped, age-specific excess mortality curve. Acquired immunity may have tempered a protracted fall wave, but recrudescent waves following the initial 2 outbreaks heightened the total pandemic mortality impact.

The 1918 influenza pandemic in Montevideo: The southernmost capital city in the Americas

BACKGROUND

Few studies have addressed the impact and dynamics of the 1918-1919 influenza pandemic in temperate regions of South America.

OBJECTIVE

To identify key factors for influenza onset, spread, and mortality in Montevideo and Uruguay in 1918-1919.

METHODS

An analysis of official national records of the public health system of Uruguay was performed.

RESULTS

From November to December of 1918 (spring), a total of 131 deaths due to influenza occurred in Montevideo and a total of 296 deaths accounted from July to September of 1919 (winter) in the same city. The total deaths attributed to influenza in Uruguay in 1918 and 1919 were 926 and 1089, respectively. In contrast, the mean annual mortality attributed to influenza in Uruguay from 1908 to 1917 was 50.9. A pattern of age-shift in mortality in the two pandemic waves studied was observed.

CONCLUSIONS

The results of studies revealed that Montevideo was first hit by the devastating second wave of the pandemic of 1918, arriving Montevideo at the end of the spring of that year. The third wave arrived by July 1919, in the winter season, and in the capital city was as severe as the second one.

A review of the 1918 herald pandemic wave: importance for contemporary pandemic response strategies

Mounting epidemiological evidence supports the occurrence of a mild herald pandemic wave in the spring and summer of 1918 in North America and Europe, several months before the devastating autumn outbreak that killed an estimated 2% of the global population. These epidemiological findings corroborate the anecdotal observations of contemporary clinicians who reported widespread influenza outbreaks in spring and summer 1918, with sporadic occurrence of unusually severe clinical manifestations in young adults. Initially seen as controversial, these findings were eventually confirmed by retrospective identification of influenza specimens collected from U.S. soldiers who died from acute respiratory infections in May-August 1918. Other studies found that having an episode of influenza illness during the spring herald wave was highly protective in the severe autumn wave. Here, we conduct a systematic review of the clinical, epidemiological, and virological evidence supporting the global occurrence of mild herald waves of the 1918 pandemic and place these historic observations in the context of pandemic preparedness. Taken together, historic experience with the 1918 and subsequent pandemics shows that increased severity in second and later pandemic waves may be the rule rather than the exception. Thus, a sustained pandemic response in the first years following a future pandemic is critical; conversely, multiwave pandemic patterns allow for more time to rollout vaccines and antivirals.

We could learn much more from 1918 pandemic-the (mis)fortune of research relying on original death certificates

PURPOSE

The analysis of historical death certificates has enormous potential for understanding how the health of populations was shaped by diseases and epidemics and by the implementation of specific interventions. In Brazil, the systematic archiving of mortality records was initiated only in 1944-hence the analysis of death registers before this time requires searching for these documents in public archives, notaries, parishes, and especially ancient cemeteries, which are often the only remaining source of information about these deaths. This article describes an effort to locate original death certificates in Brazil and document their organization, accessibility, and preservation.

METHODS

To this end, we conducted an exploratory study in 19 of the 27 Brazilian states, focusing on the period surrounding the 1918 influenza pandemic (1913-1921). We included 55 cemeteries, 22 civil archives, and one military archive.

RESULTS

Apart from few exceptions, the results show the absence of a curatorial policy for the organization, access or even physical preservation of this material, frequently leading to unavailability, deterioration, and ultimately its complete loss.

CONCLUSIONS

This study indicates the need to promote the preservation of a historical heritage that is a key to understanding historical epidemiological patterns and human responses to global health threats.

Disparities in influenza mortality and transmission related to sociodemographic factors within Chicago in the pandemic of 1918

Social factors have been shown to create differential burden of influenza across different geographic areas. We explored the relationship between potential aggregate-level social determinants and mortality during the 1918 influenza pandemic in Chicago using a historical dataset of 7,971 influenza and pneumonia deaths. Census tract-level social factors, including rates of illiteracy, homeownership, population, and unemployment, were assessed as predictors of pandemic mortality in Chicago. Poisson models fit with generalized estimating equations (GEEs) were used to estimate the association between social factors and the risk of influenza and pneumonia mortality. The Poisson model showed that influenza and pneumonia mortality increased, on average, by 32.2% for every 10% increase in illiteracy rate adjusted for population density, homeownership, unemployment, and age. We also found a significant association between transmissibility and population density, illiteracy, and unemployment but not homeownership. Lastly, analysis of the point locations of reported influenza and pneumonia deaths revealed fine-scale spatiotemporal clustering. This study shows that living in census tracts with higher illiteracy rates increased the risk of influenza and pneumonia mortality during the 1918 influenza pandemic in Chicago. Our observation that disparities in structural determinants of neighborhood-level health lead to disparities in influenza incidence in this pandemic suggests that disparities and their determinants should remain targets of research and control in future pandemics.

Death patterns during the 1918 influenza pandemic in Chile

Scarce information about the epidemiology of historical influenza pandemics in South America prevents complete understanding of pandemic patterns throughout the continent and across different climatic zones. To fill gaps with regard to spatiotemporal patterns of deaths associated with the 1918 influenza pandemic in Chile, we reviewed archival records. We found evidence that multiple pandemic waves at various times of the year and of varying intensities occurred during 1918-1921 and that influenza-related excess deaths peaked during July-August 1919. Pandemic-associated mortality rates were elevated for all age groups, including for adults >50 years of age; elevation from baseline was highest for young adults. Overall, the rate of excess deaths from the pandemic was estimated at 0.94% in Chile, similar to rates reported elsewhere in Latin America, but rates varied ≈10-fold across provinces. Patterns of death during the pandemic were affected by variation in host-specific susceptibility, population density, baseline death rate, and climate.

WITHDRAWN: Intense Seasonal A/H1N1 Influenza in Mexico, Winter 2013-2014

The Publisher regrets that this article is an accidental duplication of an article that has already been published, http://dx.doi.org/10.1016/j.arcmed.2014.11.005. The duplicate article has therefore been withdrawn. The full Elsevier Policy on Article Withdrawal can be found at http://www.elsevier.com/locate/withdrawalpolicy.

Intense seasonal A/H1N1 influenza in Mexico, winter 2013-2014

BACKGROUND AND AIMS

A recrudescent wave of pandemic influenza A/H1N1 affected Mexico during the winter of 2013-2014 following a mild 2012-2013 A/H3N2 influenza season.

METHODS

We compared the demographic and geographic characteristics of hospitalizations and inpatient deaths for severe acute respiratory infection (SARI) and laboratory-confirmed influenza during the 2013-2014 influenza season compared to previous influenza seasons, based on a large prospective surveillance system maintained by the Mexican Social Security health care system.

RESULTS

A total of 14,236 SARI hospitalizations and 1,163 inpatient deaths (8.2%) were reported between October 1, 2013 and March 31, 2014. Rates of laboratory-confirmed A/H1N1 hospitalizations and deaths were significantly higher among individuals aged 30-59 years and lower among younger age groups for the 2013-2014 A/H1N1 season compared to the previous A/H1N1 season in 2011-2012 (χ(2) test, p <0.001). The reproduction number for the winter 2013-2014 influenza season in central Mexico was estimated at 1.3-1.4, in line with that reported for the 2011-2012 A/H1N1 season but lower than during the initial waves of pandemic A/H1N1 activity in 2009.

CONCLUSIONS

We documented a substantial increase in the number of A/H1N1-related hospitalizations and deaths during the period from October 2013-March 2014 in Mexico and a proportionate shift of severe disease to middle-aged adults, relative to the preceding A/H1N1 2011-2012 season. In the absence of clear antigenic drift in globally circulating A/H1N1 viruses in the post-2009 pandemic period, the gradual change in the age distribution of A/H1N1 infections observed in Mexico suggests a slow build-up of immunity among younger populations, reminiscent of the age profile of past pandemics.

The evolution of pandemic influenza: evidence from India, 1918-19

Background

The 1918–19 ‘Spanish’ Influenza was the most devastating pandemic in recent history, with estimates of global mortality ranging from 20 to 50 million. The focal point of the pandemic was India, with an estimated death toll of between 10 and 20 million. We will characterize the pattern of spread, mortality, and evolution of the 1918 influenza across India using spatial or temporal data.

Methods

This study estimates weekly deaths in 213 districts from nine provinces in India. We compute statistical measures of the severity, speed, and duration of the virulent autumn wave of the disease as it evolved and diffused throughout India. These estimates create a clear picture of the spread of the pandemic across India.

Results

Analysis of the timing and mortality patterns of the disease reveals a striking pattern of speed deceleration, reduction in peak-week mortality, a prolonging of the epidemic wave, and a decrease in overall virulence of the pandemic over time.

Conclusions

The findings are consistent with a variety of possible causes, including the changing nature of the dominant viral strain and the timing and severity of the monsoon. The results significantly advance our knowledge of this devastating pandemic at its global focal point.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2334-14-510) contains supplementary material, which is available to authorized users.

Estimates of the reproduction number for seasonal, pandemic, and zoonotic influenza: a systematic review of the literature

BACKGROUND

The potential impact of an influenza pandemic can be assessed by calculating a set of transmissibility parameters, the most important being the reproduction number (R), which is defined as the average number of secondary cases generated per typical infectious case.

METHODS

We conducted a systematic review to summarize published estimates of R for pandemic or seasonal influenza and for novel influenza viruses (e.g. H5N1). We retained and summarized papers that estimated R for pandemic or seasonal influenza or for human infections with novel influenza viruses.

RESULTS

The search yielded 567 papers. Ninety-one papers were retained, and an additional twenty papers were identified from the references of the retained papers. Twenty-four studies reported 51 R values for the 1918 pandemic. The median R value for 1918 was 1.80 (interquartile range [IQR]: 1.47-2.27). Six studies reported seven 1957 pandemic R values. The median R value for 1957 was 1.65 (IQR: 1.53-1.70). Four studies reported seven 1968 pandemic R values. The median R value for 1968 was 1.80 (IQR: 1.56-1.85). Fifty-seven studies reported 78 2009 pandemic R values. The median R value for 2009 was 1.46 (IQR: 1.30-1.70) and was similar across the two waves of illness: 1.46 for the first wave and 1.48 for the second wave. Twenty-four studies reported 47 seasonal epidemic R values. The median R value for seasonal influenza was 1.28 (IQR: 1.19-1.37). Four studies reported six novel influenza R values. Four out of six R values were <1.

CONCLUSIONS

These R values represent the difference between epidemics that are controllable and cause moderate illness and those causing a significant number of illnesses and requiring intensive mitigation strategies to control. Continued monitoring of R during seasonal and novel influenza outbreaks is needed to document its variation before the next pandemic.

Spatial-temporal excess mortality patterns of the 1918-1919 influenza pandemic in Spain

Background

The impact of socio-demographic factors and baseline health on the mortality burden of seasonal and pandemic influenza remains debated. Here we analyzed the spatial-temporal mortality patterns of the 1918 influenza pandemic in Spain, one of the countries of Europe that experienced the highest mortality burden.

Methods

We analyzed monthly death rates from respiratory diseases and all-causes across 49 provinces of Spain, including the Canary and Balearic Islands, during the period January-1915 to June-1919. We estimated the influenza-related excess death rates and risk of death relative to baseline mortality by pandemic wave and province. We then explored the association between pandemic excess mortality rates and health and socio-demographic factors, which included population size and age structure, population density, infant mortality rates, baseline death rates, and urbanization.

Results

Our analysis revealed high geographic heterogeneity in pandemic mortality impact. We identified 3 pandemic waves of varying timing and intensity covering the period from Jan-1918 to Jun-1919, with the highest pandemic-related excess mortality rates occurring during the months of October-November 1918 across all Spanish provinces. Cumulative excess mortality rates followed a south–north gradient after controlling for demographic factors, with the North experiencing highest excess mortality rates. A model that included latitude, population density, and the proportion of children living in provinces explained about 40% of the geographic variability in cumulative excess death rates during 1918–19, but different factors explained mortality variation in each wave.

Conclusions

A substantial fraction of the variability in excess mortality rates across Spanish provinces remained unexplained, which suggests that other unidentified factors such as comorbidities, climate and background immunity may have affected the 1918–19 pandemic mortality rates. Further archeo-epidemiological research should concentrate on identifying settings with combined availability of local historical mortality records and information on the prevalence of underlying risk factors, or patient-level clinical data, to further clarify the drivers of 1918 pandemic influenza mortality.

Substantial Morbidity and Mortality Associated with Pandemic A/H1N1 Influenza in Mexico, Winter 2013-2014: Gradual Age Shift and Severity

BACKGROUND

A recrudescent wave of pandemic influenza A/H1N1 is underway in Mexico in winter 2013-14, following a mild 2012-13 A/H3N2 influenza season. Mexico previously experienced several waves of pandemic A/H1N1 activity in spring, summer and fall 2009 and winter 2011-2012, with a gradual shift of influenza-related hospitalizations and deaths towards older ages. Here we describe changes in the epidemiology of the 2013-14 A/H1N1 influenza outbreak, relative to previous seasons dominated by the A/H1N1 pandemic virus. The analysis is intended to guide public health intervention strategies in near real time.

METHODS

We analyzed demographic and geographic data on hospitalizations with severe acute respiratory infection (SARI), laboratory-confirmed A/H1N1 influenza hospitalizations, and inpatient deaths, from a large prospective surveillance system maintained by the Mexican Social Security medical system during 01-October 2013 to 31-Jan 2014. We characterized the age and regional patterns of influenza activity relative to the preceding 2011-2012 A/H1N1 influenza epidemic. We also estimated the reproduction number (R) based on the growth rate of daily case incidence by date of symptoms onset.

RESULTS

A total of 7,886 SARI hospitalizations and 529 inpatient-deaths (3.2%) were reported between 01-October 2013 and 31-January 2014 (resulting in 3.2 laboratory-confirmed A/H1N1 hospitalizations per 100,00 and 0.52 laboratory-confirmed A/H1N1-positive deaths per 100,000). The progression of daily SARI hospitalizations in 2013-14 exceeded that observed during the 2011-2012 A/H1N1 epidemic. The mean age of laboratory-confirmed A/H1N1 patients in 2013-14 was 41.1 y (SD=20.3) for hospitalizations and 49.2 y (SD=16.7) for deaths. Rates of laboratory-confirmed A/H1N1 hospitalizations and deaths were significantly higher among individuals aged 30-59 y and lower among younger age groups for the ongoing 2013-2014 epidemic, compared to the 2011-12 A/H1N1 epidemic (Chi-square test, P<0.001). The reproduction number of the winter 2013-14 wave in central Mexico was estimated at 1.3-1.4 which is slightly higher than that reported for the 2011-2012 A/H1N1 epidemic.

CONCLUSIONS

We have documented a substantial and ongoing increase in the number of A/H1N1-related hospitalizations and deaths during the period October 2013-January 2014 and a proportionate shift of severe disease to middle aged adults, relative to the preceding A/H1N1 2011-2012 epidemic in Mexico. In the absence of clear antigenic drift in globally circulating A/H1N1 viruses in the post-pandemic period, the gradual change in the age distribution of A/H1N1 infections observed in Mexico suggests a slow build-up of immunity among younger populations, reminiscent of the age profile of past pandemics.

The influenza pandemic of 1918-1919 in Sri Lanka: its demographic cost, timing, and propagation

Background

As an island and a former British colony, Sri Lanka is a case of special interest for the study of 1918–1919 influenza pandemic because of its potential for isolation from as well as integration into the world epidemiologic system.

Objectives

To estimate population loss attributable to the influenza pandemic and weekly district-level excess mortality from the pandemic to analyze its spread across the island.

Methods

To measure population loss, we estimated a population growth model using a panel of 100 district-level observations on population for five consecutive censuses from 1891 to 1931, allowing for a one-time drop in population in 1918–1919. To estimate weekly excess mortality from the pandemic, we estimated a seasonally adjusted weekly time series of district-specific mortality estimates from vital registration records, ranked them, and plotted the ranks on weekly maps to create a picture of the geographic pattern of propagation across Sri Lanka.

Results

Total loss of population from the influenza pandemic was 307 000 or approximately 6·7% of the population. The pandemic peaked in two discrete (northern and southern) regions in early October of 1918 and in a third (central) region in early March 1919.

Conclusions

The population loss estimate is significantly higher than earlier estimates of mortality from the pandemic in Sri Lanka, suggesting underreporting of influenza-attributable deaths and a role for influenza-related fertility declines. The spatial pattern of peak mortality indicates the presence of two distinct entry points and three distinct epidemiologic regions, defined by population density and ethnicity, in colonial Sri Lanka.

Influenza associated mortality in Southern China, 2010-2012

OBJECTIVE

Influenza caused substantial morbidity and mortality worldwide. The mortality burden caused by influenza has been under evaluation; however, data assessing this burden have been relatively sparse in tropical or subtropical regions. We estimated influenza-associated mortality in Guangzhou, China and assessed the excess mortality due to different influenza virus subtypes.

METHODS

We estimated influenza-associated excess mortality due to all-cause, pneumonia and influenza, cardiorespiratory disease and other influenza-associated diagnoses from weekly numbers of deaths and influenza surveillance data through negative binomial regression model during 2010-2012.

RESULTS

Estimates derived from the model indicated that influenza resulted in 14.72 (95% confidence interval (CI), 12.12-17.31) deaths per 100,000 population per year from all-cause death among all ages group. Most deaths (84.2%) occurred among people aged ≥65 years. B virus caused 5.84 (95%CI, 4.10-7.58) deaths per 100,000 population for all-cause death, which was higher than A (H3N2) (4.89, 95%CI, 3.19-6.59) or A(H1N1)pdm09 (3.99, 95%CI, 2.32-5.66).

CONCLUSIONS

Influenza is responsible for a substantial mortality especially among people aged ≥65 years and influenza B virus caused the highest influenza-associated mortality. The results highlight the need for seasonal influenza vaccination programs in subtropical areas to decrease excess mortality.

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.

A geographic analysis of population density thresholds in the influenza pandemic of 1918-19

BACKGROUND

Geographic variables play an important role in the study of epidemics. The role of one such variable, population density, in the spread of influenza is controversial. Prior studies have tested for such a role using arbitrary thresholds for population density above or below which places are hypothesized to have higher or lower mortality. The results of such studies are mixed. The objective of this study is to estimate, rather than assume, a threshold level of population density that separates low-density regions from high-density regions on the basis of population loss during an influenza pandemic. We study the case of the influenza pandemic of 1918-19 in India, where over 15 million people died in the short span of less than one year.

METHODS

Using data from six censuses for 199 districts of India (n=1194), the country with the largest number of deaths from the influenza of 1918-19, we use a sample-splitting method embedded within a population growth model that explicitly quantifies population loss from the pandemic to estimate a threshold level of population density that separates low-density districts from high-density districts.

RESULTS

The results demonstrate a threshold level of population density of 175 people per square mile. A concurrent finding is that districts on the low side of the threshold experienced rates of population loss (3.72%) that were lower than districts on the high side of the threshold (4.69%).

CONCLUSIONS

This paper introduces a useful analytic tool to the health geographic literature. It illustrates an application of the tool to demonstrate that it can be useful for pandemic awareness and preparedness efforts. Specifically, it estimates a level of population density above which policies to socially distance, redistribute or quarantine populations are likely to be more effective than they are for areas with population densities that lie below the threshold.

Mortality from the influenza pandemic of 1918-19 in Indonesia

The influenza pandemic of 1918-19 was the single most lethal short-term epidemic of the twentieth century. For Indonesia, the world's fourth most populous country, the most widely used estimate of mortality from that pandemic is 1.5 million. We estimated mortality from the influenza pandemic in Java and Madura, home to the majority of Indonesia's population, using panel data methods and data from multiple quinquennial population counts and two decennial censuses. The new estimates suggest that, for Java alone, population loss was in the range of 4.26-4.37 million, or more than twice the established estimate for mortality for all of Indonesia. We conclude that the standing estimates of mortality from influenza in Java and Indonesia need to be revised upward significantly. We also present new findings on geographic patterns of population loss across Java, and pre-pandemic and post-pandemic population growth rates.

Age- and sex-specific mortality associated with the 1918-1919 influenza pandemic in Kentucky

Background. The reasons for the unusual age-specific mortality patterns of the 1918–1919 influenza pandemic remain unknown. Here we characterize pandemic-related mortality by single year of age in a unique statewide Kentucky data set and explore breakpoints in the age curves.

Methods. Individual death certificates from Kentucky during 1911–1919 were abstracted by medically trained personnel. Pandemic-associated excess mortality rates were calculated by subtracting observed rates during pandemic months from rates in previous years, separately for each single year of age and by sex.

Results. The age profile of excess mortality risk in fall 1918 was characterized by a maximum among infants, a minimum at ages 9–10 years, a maximum at ages 24–26 years, and a second minimum at ages 56–59 years. The excess mortality risk in young adults had been greatly attenuated by winter 1919. The age breakpoints of mortality risk did not differ between males and females.

Conclusions. The observed mortality breakpoints in male and female cohorts born during 1859–1862, 1892–1894, and 1908–1909 did not coincide with known dates of historical pandemics. The atypical age mortality patterns of the 1918–1919 pandemic cannot be explained by military crowding, war-related factors, or prior immunity alone and likely result from a combination of unknown factors.

Epidemiological characterization of a fourth wave of pandemic A/H1N1 influenza in Mexico, winter 2011-2012: age shift and severity

BACKGROUND AND AIMS

A substantial recrudescent wave of pandemic influenza A/H1N1 affected the Mexican population from December 1, 2011-March 20, 2012 following a 2-year period of sporadic transmission.

METHODS

We analyzed demographic and geographic data on all hospitalizations with severe acute respiratory infection (SARI) and laboratory-confirmed A/H1N1 influenza, and inpatient deaths, from a large prospective surveillance system maintained by a Mexican social security medical system during April 1, 2009-March 20, 2012. We also estimated the reproduction number (R) based on the growth rate of the daily case incidence by date of symptoms onset.

RESULTS

A total of 7569 SARI hospitalizations and 443 in-patient deaths (5.9%) were reported between December 1, 2011, and March 20, 2012 (1115 A/H1N1-positive inpatients and 154 A/H1N1-positive deaths). The proportion of laboratory-confirmed A/H1N1 hospitalizations and deaths was higher among subjects ≥60 years of age (χ(2) test, p <0.0001) and lower among younger age groups (χ(2) test, p <0.04) for the 2011-2012 pandemic wave compared to the earlier waves in 2009. The reproduction number of the winter 2011-2012 wave in central Mexico was estimated at 1.2-1.3, similar to that reported for the fall 2009 wave, but lower than that of spring 2009.

CONCLUSIONS

We documented a substantial increase in the number of SARI hospitalizations during the period December 2011-March 2012 and an older age distribution of laboratory-confirmed A/H1N1 influenza hospitalizations and deaths relative to 2009 A/H1N1 pandemic patterns. The gradual change in the age distribution of A/H1N1 infections in the post-pandemic period is consistent with a build-up of immunity among younger populations.

The 1918-19 influenza pandemic in Boyacá, Colombia

Timing of pandemic onset and prior immunity of populations varied by region.

To quantify age-specific excess-mortality rates and transmissibility patterns for the 1918–20 influenza pandemic in Boyacá, Colombia, we reviewed archival mortality records. We identified a severe pandemic wave during October 1918–January1919 associated with 40 excess deaths per 10,000 population. The age profile for excess deaths was W shaped; highest mortality rates were among infants (<5 y of age), followed by elderly persons (>60 y) and young adults (25–29 y). Mean reproduction number was estimated at 1.4–1.7, assuming 3- or 4-day generation intervals. Boyacá, unlike cities in Europe, the United States, or Mexico, experienced neither a herald pandemic wave of deaths early in 1918 nor a recrudescent wave in 1920. In agreement with reports from Mexico, our study found no death-sparing effect for elderly persons in Colombia. We found regional disparities in prior immunity and timing of introduction of the 1918 pandemic virus across populations.

Recrudescent wave of pandemic A/H1N1 influenza in Mexico, winter 2011-2012: Age shift and severity

BACKGROUND

A substantial recrudescent wave of pandemic influenza A/H1N1 that began in December 2011 is ongoing and has not yet peaked in Mexico, following a 2-year period of sporadic transmission. Mexico previously experienced three pandemic waves of A/H1N1 in 2009, associated with higher excess mortality rates than those reported in other countries, and prompting a large influenza vaccination campaign. Here we describe changes in the epidemiological patterns of the ongoing 4th pandemic wave in 2011-12, relative to the earlier waves in 2009. The analysis is intended to guide public health intervention strategies in near real time.

METHODS

We analyzed demographic and geographic data on all hospitalizations with acute respiratory infection (ARI) and laboratory-confirmed A/H1N1 influenza, and inpatient deaths, from a large prospective surveillance system maintained by the Mexican Social Security medical system during 01-April 2009 to 10-Feb 2012. We characterized the age and regional patterns of A/H1N1-positive hospitalizations and inpatient-deaths relative to the 2009 A/H1N1 influenza pandemic. We also estimated the reproduction number (R) based on the growth rate of the daily case incidence by date of symptoms onset.

RESULTS

A total of 5,795 ARI hospitalizations and 186 inpatient-deaths (3.2%) were reported between 01-December 2011 and 10-February 2012 (685 A/H1N1-positive inpatients and 75 A/H1N1-positive deaths). The nationwide peak of daily ARI hospitalizations in early 2012 has already exceeded the peak of ARI hospitalizations observed during the major fall pandemic wave in 2009. The mean age was 34.3 y (SD=21.3) among A/H1N1 inpatients and 43.5 y (SD=21) among A/H1N1 deaths in 2011-12. The proportion of laboratory-confirmed A/H1N1 hospitalizations and deaths was higher among seniors >=60 years of age (Chi-square test P<0.001) and lower among younger age groups (Chi-square test, P<0.03) for the 2011-2012 pandemic wave, compared to the earlier waves in 2009. The reproduction number of the winter 2011-12 wave in central Mexico was estimated at 1.2-1.3, similar to that reported for the fall 2009 wave, but lower than that of spring 2009.

CONCLUSIONS

We have documented a substantial and ongoing increase in the number of ARI hospitalizations during the period December 2011-February 2012 and an older age distribution of laboratory-confirmed A/H1N1 influenza hospitalizations and deaths, relative to 2009 A/H1N1 pandemic patterns. The gradual change in the age distribution of A/H1N1 infections in the post-pandemic period is reminiscent of historical pandemics and indicates either a gradual drift in the A/H1N1 virus, and/or a build-up of immunity among younger populations.

The perils of using annual all-cause mortality data to estimate pandemic influenza burden

Measuring the burden of historic pandemics is not straightforward and often must be based on suboptimal mortality data. For example, the critical 1918 pandemic global burden estimate was based on excess in annual all-cause mortality--calculated as the difference between deaths during 1918-1920 and the surrounding 3-year periods. One intriguing result was a ∼ 40-fold between-country variation in pandemic mortality burden: ∼ 0.2% of Danes died, compared to ∼ 8% of populations in some Indian provinces (Murray et al., 2006 [16]). Using the same methodology and data source we explore the robustness of this methodology for different age-groups. For infants the country estimates varied 100-fold, from 15 to 1500 excess deaths/10,000 population, while for adults ≥ 45 years estimates ranged from -70 to 170/10,000 population. In contrast, estimates for children, 1-14 years, and adults aged 15-44 years, were far more stable. We next used detailed mortality data from Copenhagen to compare such estimates to the more precise estimates obtained from monthly mortality time series data and respiratory deaths. We found that the all-cause annual method substantially underestimated due to an unexplained depression in all-cause mortality in Denmark in 1918 and deaths caused by other epidemic diseases during the baseline periods. We conclude that country estimates for infants and older adults were highly variable by the Murray method due to substantial variability in annual all-cause mortality. A more precise 1918 pandemic burden estimate would be gotten from either focusing analysis on persons age 1-44 who suffered 95% of all pandemic deaths and had a substantial rise over their baseline mortality level, or if possible focus analysis on annual respiratory deaths. For less severe pandemics, including the ongoing 2009 H1N1 pandemic, the use of all-cause mortality data requires careful consideration of excess deaths in defined pandemic periods and a focus on age groups known to be at risk.