scholarly journals Influenza Vaccine Match with Circulating Strains and Indicators of Influenza Strain Impact - Canada 1980 to 1992

1998 ◽  
Vol 9 (3) ◽  
pp. 143-148 ◽  
Author(s):  
Edward Ellis ◽  
John M Weber ◽  
Wilf Cuff ◽  
Susan G Mackenzie
Keyword(s):  
Influenza Vaccine ◽  
Ecological Study ◽  
Influenza Season ◽  
National Laboratory ◽  
Mortality Rates ◽  
Mortality Data ◽  
Influenza Strain ◽  
Previous Season ◽  
Vaccine Antigens ◽  
Excess Deaths

OBJECTIVES: To determine the similarity between influenza vaccine antigens and viruses associated with laboratory-confirmed infections by virus type/subtype, strain and influenza season; to correlate pneumonia and influenza hospitalization and mortality rates with the number of laboratory-confirmed influenza infections in an influenza season; and to develop predictive indicators of the likely incidence of current strains in the following season.DESIGN: Ecological study using national laboratory, pneumonia and influenza hospitalization and mortality data.SETTING: Canada, influenza seasons from 1980 to 1992.POPULATION STUDIED: Individuals with laboratory-confirmed influenza infections, pneumonia and influenza hospitalizations or deaths.INTERVENTION: Influenza immunization.MAIN RESULTS: Similarity of circulating strains and vaccine antigens was 99% for A(H1N1), 65% for A(H3N2) and 65% for B strains. During outbreaks, pneumonia and influenza hospitalization, and mortality rates increased 19% or less and 21% or less for A(H1N1), respectively; 28% or less and 51% or less for A(H3N2), and 19% or less and 16% or less for B strains. There were usually fewer than 25 laboratory-confirmed A(H1N1) infections with a particular strain in a season if there had been more than 25 infections with similar strains the previous season. For A(H3N2), the figure was 100, and for B it was 150.CONCLUSIONS: Matches were excellent for A(H1N1) and good for A(H3N2) plus B strains. Hospitalization and mortality rates increased substantially during outbreaks, eg, estimated 1609 excess deaths during a widespread A(H3N2) outbreak. This study identifies relationships that provide some ability to predict the incidence of a particular influenza strain in a coming season based on the incidence of strains similar to it in the previous season.

Influenza Vaccine Effectiveness Among Children for the 2017–2018 Season

2019 ◽  
Vol 9 (4) ◽  
pp. 468-473 ◽  
Author(s):  
Lauren N Powell ◽  
Rodolfo E Bégué
Keyword(s):  
Influenza Vaccine ◽  
Influenza A ◽  
Influenza Season ◽  
Vaccine Effectiveness ◽  
Influenza B ◽  
Immunization Registry ◽  
Previous Season ◽  
Waning Immunity ◽  
Small Benefit ◽  
Susceptible Populations

Abstract Background The 2017–2018 influenza season was of high severity. Circulating influenza strains change periodically, making it important to determine vaccine effectiveness on an annual basis, especially for susceptible populations. The primary aim of our study was to estimate the effectiveness of the influenza vaccine among children. Secondary aims were to assess the effect of previous season vaccination and intraseasonal waning of immunity. Methods Children 6 months to 17 years of age tested for influenza during the 2017–2018 season were included. Clinical charts were reviewed, and immunization status was confirmed via the Louisiana Immunization Registry. Influenza vaccine effectiveness (IVE) was estimated in a test-negative design by comparing vaccination status of influenza-positive vs influenza-negative cases. Results A total of 3595 children were included, 26% of whom tested positive for influenza, mostly type A (79%); 15% had received an influenza vaccine prior to illness: 8% among the influenza-positive and 17% among influenza-negative cases (P <.0001). IVE for the 2017–2018 influenza season was 52% overall (95% confidence interval, 38%–62%), 49% for influenza A, and 60% for influenza B. While receiving current year (2017–2018) vaccine had the most effect, receiving the previous year (2016–2017) vaccine had a small benefit and no interference. We found no evidence of waning immunity of the vaccine for the 2017–2018 season. Conclusions IVE was moderate for children. Previous year vaccination had a small but significant benefit and there was no evidence of waning immunity in our cohort. Ongoing national and local surveillance is important to understand the benefit of influenza vaccination.

scholarly journals Challenges of Making Effective Influenza Vaccines

2020 ◽  
Vol 7 (1) ◽  
pp. 495-512
Author(s):  
Sigrid Gouma ◽  
Elizabeth M. Anderson ◽  
Scott E. Hensley
Keyword(s):  
Influenza Vaccine ◽  
Seasonal Influenza ◽  
Influenza Season ◽  
Viral Evolution ◽  
Influenza Vaccines ◽  
Antigen Production ◽  
Production Processes ◽  
Vaccine Antigens ◽  
History Of ◽  
Viral Vaccines

Seasonal influenza vaccines prevent influenza-related illnesses, hospitalizations, and deaths. However, these vaccines are not as effective as other viral vaccines, and there is clearly room for improvement. Here, we review the history of seasonal influenza vaccines, describe challenges associated with producing influenza vaccine antigens, and discuss the inherent difficulties of updating influenza vaccine strains each influenza season. We argue that seasonal influenza vaccines can be dramatically improved by modernizing antigen production processes and developing models that are better at predicting viral evolution. Resources should be specifically dedicated to improving seasonal influenza vaccines while developing entirely new vaccine platforms.

Excess Mortality During the COVID-19 Pandemic in Guatemala

2021 ◽  
pp. e1-e8
Author(s):  
Kevin Martinez-Folgar ◽  
Diego Alburez-Gutierrez ◽  
Alejandra Paniagua-Avila ◽  
Manuel Ramirez-Zea ◽  
Usama Bilal
Keyword(s):  
Excess Mortality ◽  
Generalized Additive Model ◽  
Additive Model ◽  
Mortality Rates ◽  
Place Of Death ◽  
Mortality Data ◽  
Registration System ◽  
Health Crisis ◽  
Vital Registration System ◽  
Excess Deaths

Objectives. To describe excess mortality during the COVID-19 pandemic in Guatemala during 2020 by week, age, sex, and place of death. Methods. We used mortality data from 2015 to 2020, gathered through the vital registration system of Guatemala. We calculated weekly mortality rates, overall and stratified by age, sex, and place of death. We fitted a generalized additive model to calculate excess deaths, adjusting for seasonality and secular trends and compared excess deaths to the official COVID-19 mortality count. Results. We found an initial decline of 26% in mortality rates during the first weeks of the pandemic in 2020, compared with 2015 to 2019. These declines were sustained through October 2020 for the population younger than 20 years and for deaths in public spaces and returned to normal from July onward in the population aged 20 to 39 years. We found a peak of 73% excess mortality in mid-July, especially in the population aged 40 years or older. We estimated a total of 8036 excess deaths (95% confidence interval = 7935, 8137) in 2020, 46% higher than the official COVID-19 mortality count. Conclusions. The extent of this health crisis is underestimated when COVID-19 confirmed death counts are used. (Am J Public Health. Published online ahead of print September 23, 2021: e1–e8. https://doi.org/10.2105/AJPH.2021.306452 )

scholarly journals Successes and Failures of the Live-attenuated Influenza Vaccine: Can We Do Better?

2019 ◽  
Vol 70 (6) ◽  
pp. 1029-1037 ◽  
Author(s):  
Laura Matrajt ◽  
M Elizabeth Halloran ◽  
Rustom Antia
Keyword(s):  
Influenza Vaccine ◽  
Mathematical Models ◽  
Vaccine Strain ◽  
Influenza Season ◽  
Mechanistic Explanation ◽  
Vaccine Effectiveness ◽  
Challenge Strain ◽  
Influenza Strain ◽  
Live Attenuated Influenza Vaccine ◽  
The World

Abstract Background The effectiveness of the live-attenuated influenza vaccine (LAIV) can vary widely, ranging from 0% to 50%. The reasons for these discrepancies remain largely unclear. Methods We use mathematical models to explore how the efficacy of LAIV is affected by the degree of mismatch with the currently circulating influenza strain and interference with pre-existing immunity. The models incorporate 3 key antigenic distances: the distances between the vaccine strain, pre-existing immunity, and the challenge strain. Results Our models show that an LAIV that is matched with the currently circulating strain is likely to have only modest efficacy. Our results suggest that the efficacy of the vaccine would be increased (optimized) if, rather than being matched to the circulating strain, it is antigenically slightly further from pre-existing immunity than the circulating strain. The models also suggest 2 regimes in which LAIV that is matched to circulating strains may be protective: in children before they have built immunity to circulating strains and in response to novel strains (such as antigenic shifts) which are at substantial antigenic distance from previously circulating strains. We provide an explanation for the variation in vaccine effectiveness between studies and countries of vaccine effectiveness observed during the 2014–2015 influenza season. Conclusions LAIV is offered to children across the world; however, its effectiveness significantly varies between studies. Here, we propose a mechanistic explanation to understand these differences. We further propose a way to select the LAIV strain that would have a higher chance of being protective.

scholarly journals Early estimates of the excess mortality associated with the 2008-9 influenza season in Portugal

2009 ◽  
Vol 14 (18) ◽  
Author(s):  
P J Nogueira ◽  
B Nunes ◽  
A Machado ◽  
E Rodrigues ◽  
V Gómez ◽  
...  
Keyword(s):  
Excess Mortality ◽  
Total Population ◽  
Influenza Season ◽  
Statistical Modelling ◽  
Mortality Data ◽  
Age Group ◽  
Gender And Age ◽  
Influenza Activity ◽  
The Impact ◽  
Excess Deaths

The aim of this study was to estimate the excess mortality associated with the influenza activity registered in Portugal between week 49 of 2008 and week 5 of 2009. For this purpose available mortality data from the Portuguese Daily Mortality Monitoring (VDM) System were used. Several estimates of excess deaths associated with the recent recorded influenza activity were determined through statistical modelling (cyclic regression) for the total population and disaggregated by gender and age group. The results show that the impact of the 2008-9 influenza season was 1,961 excess deaths, with approximately 82% of these occurring in the age group of 75 years and older.

scholarly journals Covid-19 and excess mortality rates not comparable across countries

2021 ◽  
Author(s):  
Gabrielle E Kelly ◽  
Stefano Petti ◽  
Norman Noah
Keyword(s):  
Excess Mortality ◽  
Spatial Clustering ◽  
Mortality Rates ◽  
Mortality Data ◽  
Published Data ◽  
Death Rates ◽  
Government Response ◽  
Health Measures ◽  
Specific Mortality ◽  
Excess Deaths

Abstract: Evidence that more people in some countries and fewer in others are dying because of the pandemic, than is reflected by reported Covid-19 mortality rates, is derived from mortality data. Worldwide, mortality data is used to estimate the full extent of the effects of the Covid-19 pandemic, both direct and indirect; the possible short fall in the number of cases reported to the WHO; and to suggest explanations for differences between countries. Excess mortality data is largely varying across countries and is not directly proportional to Covid-19 mortality. Using publicly available databases, deaths attributed to Covid-19 in 2020 and all deaths for the years 2015-2020 were tabulated for 36 countries together with economic, health, demographic, and government response stringency index variables. Residual death rates in 2020 were calculated as excess deaths minus death rates due to Covid-19 where excess deaths were observed deaths in 2020 minus the average for 2015-2019. For about half the countries, residual deaths were negative and for half, positive. The absolute rates in some countries were double those in others. In a regression analysis, the stringency index (p=0.026) was positively associated with residual mortality. There was no evidence of spatial clustering of residual mortality. The results show that published data on mortality from Covid-19 cannot be directly comparable across countries, likely due to differences in Covid-19 death reporting. In addition, the unprecedented public health measures implemented to control the pandemic may have produced either increased or reduced excess deaths due to other diseases. Further data on cause-specific mortality is required to determine the extent to which residual mortality represents non-Covid-19 deaths and to explain differences between countries.

scholarly journals Is the decline in neonatal mortality in northern Ghana, 1996–2012, associated with the decline in the age of BCG vaccination? An ecological study

BMJ Open ◽  
2018 ◽  
Vol 8 (12) ◽  
pp. e023752 ◽  
Author(s):  
Paul Welaga ◽  
Cornelius Debpuur ◽  
Peter Aaby ◽  
Abraham Hodgson ◽  
Daniel K Azongo ◽  
...  
Keyword(s):  
Neonatal Mortality ◽  
Ecological Study ◽  
Mortality Rates ◽  
Northern Ghana ◽  
Trend Test ◽  
Mortality Data ◽  
Bcg Vaccination ◽  
Randomised Control Trials ◽  
Home Deliveries ◽  
Delivery Place

ObjectiveTo examine the association between early Bacille Calmette-Guerin (BCG) vaccination and neonatal mortality in northern Ghana.MethodsThis ecological study used vaccination and mortality data from the Navrongo Health and Demographic Surveillance System. First, we assessed and compared changes in neonatal mortality rates (NMRs) and median BCG vaccination age from 1996 to 2012. Second, we compared the changes in NMR and median BCG vaccination age from 2002 to 2012 by delivery place when data on delivery place were available.ResultsNeonatal mortality rates declined from 46 to 12 per 1000 live births between 1996 and 2012 (trend test: p<0.001). Within the same period, median BCG vaccination age declined from 46 to 4 days (trend test: p<0.001). Among home deliveries, BCG vaccination age declined from 39 days in 2002 to 7 days in 2012 (trend test: p<0.001) and neonatal mortality declined by 24/1000 (trend test: p<0.001). Among health facility deliveries, BCG vaccination age was stable around 3 days from 2002 to 2012 (trend test: p=0.49) and neonatal mortality declined by 9/1000 (trend test: p=0.04). In a small study of children whose vaccination cards were inspected within the first 28 days of life, the HR for BCG-vaccinated compared with BCG-unvaccinated children was 0.55 (95% CI 0.12 to 2.40).ConclusionThe data support the hypothesis that early BCG vaccination may be associated with a decrease in neonatal mortality. However, as suggested by WHO, randomised control trials are required to address the question of whether there is indeed a causal association between early BCG vaccination and neonatal mortality.

scholarly journals Trends in diabetes mortality identified from death certificates in Colombia, 1979-2017

2021 ◽  
Vol 45 ◽  
pp. 1
Author(s):  
Pablo Chaparro-Narváez ◽  
Nelson J. Alvis-Zakzuk ◽  
Diana Díaz-Jiménez ◽  
Carlos Castañeda-Orjuela
Keyword(s):  
Regression Models ◽  
Ecological Study ◽  
Age Groups ◽  
Mortality Rates ◽  
Mortality Data ◽  
Joinpoint Regression ◽  
Primary And Secondary Prevention ◽  
Mortality Trends ◽  
Joinpoint Regression Analysis ◽  
Annual Mortality

Objective. To describe the mortality trends of diabetes mellitus (DM) in Colombia, by sex and age group, from 1979 to 2017. Methods. We carried out an ecological study using mortality data from the Colombian National Administrative Department of Statistics. Crude and age-standardized annual mortality rates per 100 000 people were estimated. Trends of standardized rates were described by sex and age groups. Joinpoint regression models were performed to study mortality trends. Results. Throughout the whole period, the total number of DM recorded deaths in Colombia was 200 650, 58% (116 316) in women (p<0.05). The age-standardized mortality rates (ASMR) by sex increased from 13.2 to 26.6 deaths per 100 000 in women and from 10.1 to 22.7 in men from 1979 to 1999. We observed a decrease from 26.6 to 15.4 per 100 000 in women, and from 22.7 to 15.9 in men for the period 1999-2017. The joinpoint regression analysis showed that the average annual percentage change of the period did not vary in both sexes (men: -0.2%, 95% CI –1.0 to 1.4%; women: 0.7%, 95% CI –0.1 to 1.6%). Conclusions. The DM mortality showed a decreasing trend after 2000 in women and 2004 in men. Primary and secondary prevention programs must continue to be strengthened for an earlier diagnosis of diabetes.

scholarly journals Excess mortality in England and Wales during the first wave of the COVID-19 pandemic

2020 ◽  
Author(s):  
Evangelos Kontopantelis ◽  
Mamas A Mamas ◽  
John Deanfield ◽  
Miqdad Asaria ◽  
Tim Doran
Keyword(s):  
Excess Mortality ◽  
Age Groups ◽  
Mortality Rates ◽  
Mortality Data ◽  
List Type ◽  
Age Group ◽  
The West ◽  
England And Wales ◽  
West Midlands ◽  
Excess Deaths

AbstractBackgroundDeaths during the COVID-19 pandemic result directly from infection and exacerbation of other diseases and indirectly from deferment of care for other conditions, and are socially and geographically patterned. We quantified excess mortality in regions of England and Wales during the pandemic, for all causes and for non-COVID-19 associated deaths.MethodsWeekly mortality data for 1 Jan 2010 to 1 May 2020 for England and Wales were obtained from the Office of National Statistics. Mean-dispersion negative binomial regressions were used to model death counts based on pre-pandemic trends and exponentiated linear predictions were subtracted from: i) all-cause deaths; and ii) all-cause deaths minus COVID-19 related deaths for the pandemic period (07-13 March to 25 April to 8 May).FindingsBetween 7 March and 8 May 2020, there were 47,243 (95%CI: 46,671 to 47,815) excess deaths in England and Wales, of which 9,948 (95%CI: 9,376 to 10,520) were not associated with COVID-19. Overall excess mortality rates varied from 49 per 100,000 (95%CI: 49 to 50) in the South West to 102 per 100,000 (95%CI: 102 to 103) in London. Non-COVID-19 associated excess mortality rates ranged from −1 per 100,000 (95%CI: −1 to 0) in Wales (i.e. mortality rates were no higher than expected) to 26 per 100,000 (95%CI: 25 to 26) in the West Midlands.InterpretationThe COVID-19 pandemic has had markedly different impacts on the regions of England and Wales, both for deaths directly attributable to COVID-19 infection and for deaths resulting from the national public health response.FundingNoneSummary boxWhat is already known on the subjectThe number of deaths due to COVID-19 have been quantified by the Office of National StatisticsThese have also been reported across age groups and regionsWhat this study addsWe report the number of excess deaths, using weekly mortality data from 1/1/2010We also quantify the number of excess deaths, excluding COVID-19 associated deaths, which can be attributed to COVID-19 directly (but not coded as such) or indirectly (due to other urgent but unmet health need)Highest excess mortality, excluding COVID-19 deaths, was observed in the West Midlands, followed by London and the North WestAlthough males had larger excess mortality rates than females across all age groups, female excess mortality rates excluding COVID-19 were higher in the 85+ age group, indicating a large undocumented impact of the virus on older females (direct and/or indirect)The three provided appendices will be updated weekly on the BMJ-JECH website, to provide up-to-date information of excess mortality by region, sex and age group

Inequalities and Impact of Socioeconomic-Cultural Factors in Suicide Rates Across Italy

Crisis ◽  
2011 ◽  
Vol 32 (4) ◽  
pp. 178-185 ◽  
Author(s):  
Maurizio Pompili ◽  
Marco Innamorati ◽  
Monica Vichi ◽  
Maria Masocco ◽  
Nicola Vanacore ◽  
...  
Keyword(s):  
Suicide Rate ◽  
Age Groups ◽  
Premature Death ◽  
Mortality Rates ◽  
Mortality Data ◽  
Italian Population ◽  
Comprehensive Overview ◽  
Suicide Rates ◽  
Younger Age ◽  
Age And Sex

Background: Suicide is a major cause of premature death in Italy and occurs at different rates in the various regions. Aims: The aim of the present study was to provide a comprehensive overview of suicide in the Italian population aged 15 years and older for the years 1980–2006. Methods: Mortality data were extracted from the Italian Mortality Database. Results: Mortality rates for suicide in Italy reached a peak in 1985 and declined thereafter. The different patterns observed by age and sex indicated that the decrease in the suicide rate in Italy was initially the result of declining rates in those aged 45+ while, from 1997 on, the decrease was attributable principally to a reduction in suicide rates among the younger age groups. It was found that socioeconomic factors underlined major differences in the suicide rate across regions. Conclusions: The present study confirmed that suicide is a multifaceted phenomenon that may be determined by an array of factors. Suicide prevention should, therefore, be targeted to identifiable high-risk sociocultural groups in each country.

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