Epidemiology and Trends of Pertussis among Infants: United States, 2000–2015

Abstract Background Pertussis, a cyclic respiratory disease, causes the greatest morbidity and mortality among infants, particularly those too young to be vaccinated. Following a resurgence of pertussis in the 1990s, a recommendation was made in 2012 to vaccinate during every pregnancy in order to prevent infant disease. We describe pertussis trends from 2000–2015 among U.S. infants aged <1 year. Methods We analyzed infant pertussis cases reported through the National Notifiable Diseases Surveillance System from 2000 to 2015. Incidence rates (cases per 100,000 population) among various age groups (<2, 2– <4, 4– <6, and 6–<12 months) were calculated using National Center for Health Statistics population estimates as denominators. Negative binomial regression was used to estimate the annual average percent change with a linear trend; P < 0.05 was significant. Results From 2000 to 2015, 48,909 infant pertussis cases and 255 deaths were reported; infants aged <2 months accounted for 38.7% of cases. The age distribution of infant cases was stable from 2000 to 2009 but changed from 2010 to 2015 (Fig. 1), as the proportion of cases aged 4–<12 months increased annually on average by 4.7% (P < 0.001). Annual incidence was highest among <2 month olds; however, rates increased among older infants (Fig. 2): 7% average annual increase among infants aged 4–<6 months and 11% among infants aged 6–<12 months (P < 0.001 for each). The proportion of infants hospitalized decreased over time in each age group (P < 0.001 for all) with the largest annual average declines among 4–<6 (−5.1%) and 6–<12 month (−5.9%) olds. For all age groups, hospitalization rates were relatively stable, but non-hospitalization rates increased (P < 0.05 for all). The case–fatality ratio (CFR) was highest among <2 month olds (1.6%); CFRs decreased over time among <2 and 2–< 4 month olds (P < 0.05 for each). Conclusion Pertussis incidence remains highest among infants aged <4 months, although the age distribution appears to be changing. Decreasing proportions of infants hospitalized may suggest a true decline in disease severity or an increase in reporting of less severe disease. Ongoing monitoring of infant pertussis is needed to better understand the impact of vaccinating pregnant women to prevent pertussis in young infants. Disclosures All authors: No reported disclosures.

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Serotype Replacement After the Introduction of the 13-valent Pneumococcal Conjugate Vaccine in Ontario, Canada, 2007-2018

University of Toronto Journal of Public Health ◽

10.33137/utjph.v1i1.33816 ◽

2020 ◽

Vol 1 (1) ◽

Author(s):

Allison H Yeung ◽

Shinthuja Wijayasri ◽

Sarah E Wilson ◽

Tara M Harris ◽

Sarah A Buchan ◽

...

Keyword(s):

Public Health ◽

Severe Disease ◽

Age Groups ◽

Pneumococcal Vaccination ◽

Case Fatality ◽

Vaccination Programs ◽

Hospitalization Rates ◽

Age Related ◽

Serotype Replacement ◽

Vaccine Type

Introduction: Invasive pneumococcal disease (IPD) is a disease of public health significance in Ontario, Canada, where publicly funded pneumococcal vaccination programs target children, older adults, and people at high risk of disease. Since the implementation of pneumococcal conjugate vaccines (PCV), serotype replacement has been documented, where non-PCV serotypes replace the niche created by the reduction in vaccine-preventable serotypes. Our objective was to determine whether there has been serotype replacement or a change in IPD severity in Ontario since implementation of the childhood 13-valent (PCV13) program by assessing IPD burden over a 12-year period (2007-2018). Methods: We included all confirmed IPD cases reported in Ontario’s integrated Public Health Information System (iPHIS) and defined the pre-PCV13 era (January 2007-December 2010) and post-PCV13 era (January 2011-December 2018). We grouped IPD serotypes according to associated vaccine type: PCV13; 23-valent polysaccharide vaccine (unique PPV23); and non-vaccine-preventable (NVP). We used population data to calculate incidence and hospitalization rates (per 100,000 population) by age group, vaccine type, and era. Results: In the post-PCV13 era, PCV13-specific incidence and hospitalization rates decreased, while the incidence and hospitalizations due to unique PPV23 and NVP serotypes increased; this was consistent across all age groups. The greatest decrease in incidence (RR=0.4) and hospitalizations (RR=0.4) was observed in children <5 years with PCV13 serotypes. There were no distinct age-related trends observed for case fatality ratios; the highest CFR was observed in adults ≥65 years. Conclusion: A shift in serotype distribution was seen across all age groups; IPD incidence and hospitalization rates due to PCV13 serotypes decreased after PCV13 implementation, but this reduction was offset by the increasing burden and severity of unique PPV23 and NVP serotypes. As IPD continues to be a severe disease, continued surveillance is required to better understand the growing burden of these serotypes and emergence of non-vaccine-preventable serotypes.

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Estimating effective infection fatality rates during the course of the COVID-19 pandemic in Germany

BMC Public Health ◽

10.1186/s12889-021-11127-7 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Christian Staerk ◽

Tobias Wistuba ◽

Andreas Mayr

Keyword(s):

Age Distribution ◽

Age Groups ◽

Case Fatality ◽

Time Dependent ◽

Temporary Increase ◽

International Studies ◽

Age Group ◽

Fatality Rate ◽

Substantial Fraction ◽

Second Wave

Abstract Background The infection fatality rate (IFR) of the Coronavirus Disease 2019 (COVID-19) is one of the most discussed figures in the context of this pandemic. In contrast to the case fatality rate (CFR), the IFR depends on the total number of infected individuals – not just on the number of confirmed cases. In order to estimate the IFR, several seroprevalence studies have been or are currently conducted. Methods Using German COVID-19 surveillance data and age-group specific IFR estimates from multiple international studies, this work investigates time-dependent variations in effective IFR over the course of the pandemic. Three different methods for estimating (effective) IFRs are presented: (a) population-averaged IFRs based on the assumption that the infection risk is independent of age and time, (b) effective IFRs based on the assumption that the age distribution of confirmed cases approximately reflects the age distribution of infected individuals, and (c) effective IFRs accounting for age- and time-dependent dark figures of infections. Results Effective IFRs in Germany are estimated to vary over time, as the age distributions of confirmed cases and estimated infections are changing during the course of the pandemic. In particular during the first and second waves of infections in spring and autumn/winter 2020, there has been a pronounced shift in the age distribution of confirmed cases towards older age groups, resulting in larger effective IFR estimates. The temporary increase in effective IFR during the first wave is estimated to be smaller but still remains when adjusting for age- and time-dependent dark figures. A comparison of effective IFRs with observed CFRs indicates that a substantial fraction of the time-dependent variability in observed mortality can be explained by changes in the age distribution of infections. Furthermore, a vanishing gap between effective IFRs and observed CFRs is apparent after the first infection wave, while an increasing gap can be observed during the second wave. Conclusions The development of estimated effective IFR and observed CFR reflects the changing age distribution of infections over the course of the COVID-19 pandemic in Germany. Further research is warranted to obtain timely age-stratified IFR estimates, particularly in light of new variants of the virus.

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Evolution of case fatality rates in the second wave of coronavirus in England: effects of false positives, a Variant of Concern and vaccination.

10.1101/2021.04.14.21255385 ◽

2021 ◽

Author(s):

James A Ackland ◽

Graeme J Ackland ◽

David J Wallace

Keyword(s):

False Positive ◽

Age Groups ◽

Case Fatality ◽

Potential Effect ◽

Time To Death ◽

New Variant ◽

Government Data ◽

The Uk ◽

Second Wave ◽

Over Time

Objective: To track the statistical case fatality rate (CFR) in the second wave of the UK coronavirus outbreak, and to understand its variations over time. Design: Publicly available UK government data and clinical evidence on the time between first positive PCR test and death are used to determine the relationships between reported cases and deaths, according to age groups and across regions in England. Main Outcome Measures: Estimates of case fatality rates and their variations over time. Results: Throughout October and November 2020, deaths in England can be broadly understood in terms of CFRs which are approximately constant over time. The same CFRs prove a poor predictor of deaths when applied back to September, when prevalence of the virus was comparatively low, suggesting that the potential effect of false positive tests needs to be taken into account. Similarly, increasing CFRs are needed to match cases to deaths when projecting the model forwards into December. The growth of the S gene dropout VOC in December occurs too late to explain this increase in CFR alone, but at 33% increased mortality, it can explain the peak in deaths in January. On our analysis, if there were other factors responsible for the higher CFRs in December and January, 33% would be an upper bound for the higher mortality of the VOC. From the second half of January, the CFRs for older age groups show a marked decline. Since the fraction of the VOC has not decreased, this decline is likely to be the result of the rollout of vaccination. However, due to the rapidly decreasing nature of the raw cases data (likely due to a combination of vaccination and lockdown), any imprecisions in the time-to-death distribution are greatly exacerbated in this time period, rendering estimates of vaccination effect imprecise. Conclusions: The relationship between cases and deaths, even when controlling for age, is not static through the second wave of coronavirus in England. An apparently anomalous low case-fatality ratio in September can be accounted for by a modest 0.4% false-positive fraction. The large jump in CFR in December can be understood in terms of a more deadly new variant B1.1.7, while a decline in January correlates with vaccine roll-out, suggesting that vaccine reduce the severity of infection, as well as the risk.

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Spatial and temporal trends in social vulnerability and COVID-19 incidence and death rates in the United States

PLoS ONE ◽

10.1371/journal.pone.0248702 ◽

2021 ◽

Vol 16 (3) ◽

pp. e0248702

Author(s):

Brian Neelon ◽

Fedelis Mutiso ◽

Noel T. Mueller ◽

John L. Pearce ◽

Sara E. Benjamin-Neelon

Keyword(s):

Social Vulnerability ◽

Primary Care Physicians ◽

Negative Binomial ◽

Temporal Trends ◽

The United States ◽

Social Vulnerability Index ◽

Crossover Effect ◽

Death Rates ◽

The Impact ◽

Over Time

Background Socially vulnerable communities may be at higher risk for COVID-19 outbreaks in the US. However, no prior studies examined temporal trends and differential effects of social vulnerability on COVID-19 incidence and death rates. Therefore, we examined temporal trends among counties with high and low social vulnerability to quantify disparities in trends over time. Methods We conducted a longitudinal analysis examining COVID-19 incidence and death rates from March 15 to December 31, 2020, for each US county using data from USAFacts. We classified counties using the Social Vulnerability Index (SVI), a percentile-based measure from the Centers for Disease Control and Prevention, with higher values indicating more vulnerability. Using a Bayesian hierarchical negative binomial model, we estimated daily risk ratios (RRs) comparing counties in the first (lower) and fourth (upper) SVI quartiles, adjusting for rurality, percentage in poor or fair health, percentage female, percentage of smokers, county average daily fine particulate matter (PM2.5), percentage of primary care physicians per 100,000 residents, daily temperature and precipitation, and proportion tested for COVID-19. Results At the outset of the pandemic, the most vulnerable counties had, on average, fewer cases per 100,000 than least vulnerable SVI quartile. However, on March 28, we observed a crossover effect in which the most vulnerable counties experienced higher COVID-19 incidence rates compared to the least vulnerable counties (RR = 1.05, 95% PI: 0.98, 1.12). Vulnerable counties had higher death rates starting on May 21 (RR = 1.08, 95% PI: 1.00,1.16). However, by October, this trend reversed and the most vulnerable counties had lower death rates compared to least vulnerable counties. Conclusions The impact of COVID-19 is not static but can migrate from less vulnerable counties to more vulnerable counties and back again over time.

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Empirically Treated Pneumocystis Carinii Pneumonia in London, 1983–1989

International Journal of STD & AIDS ◽

10.1177/095646249200300411 ◽

1992 ◽

Vol 3 (4) ◽

pp. 285-287 ◽

Cited By ~ 5

Author(s):

E J Beck ◽

P D French ◽

M H Helbert ◽

D S Robinson ◽

F M Moss ◽

...

Keyword(s):

Pneumocystis Carinii Pneumonia ◽

Lymphocyte Count ◽

Severe Disease ◽

Pneumocystis Carinii ◽

Fatal Outcome ◽

Case Fatality ◽

Medical Intervention ◽

Arterial Oxygen ◽

Oxygen Gradient ◽

Over Time

For 227 episodes of Pneumocystis carinii pneumonia (PCP) treated at St Mary's between 1983 and 1989, factors predictive of fatal outcome were age, haemoglobin levels, peripheral lymphocyte count and alveolar-arterial oxygen gradient. Case fatality for the 47 empirically-treated episodes was significantly higher compared with the 180 cytologically proven episodes (55% vs 18%, χ2 = 25.7, P<0.0001). Case fatality for episodes which could not be bronchoscoped was significantly higher compared with bronchoscopy negative cases (66% vs 25%, χ2 = 4.5, P<0.05). Predictive factors for fatal outcome differed significantly for cases which could not be bronchoscoped and cytologically proven cases: haemoglobin level (10.7 g/dl vs 12.0 g/dl, P<0.001), lymphocyte count (0.64 × 109/l vs 0.87×109/l, P=0.05) and oxygen gradient (77.7 mmHg vs 58.9 mmHg, P<0.02). Such differences were not observed between bronchoscopy negative and cytologically proven cases. Case fatality decreased significantly over time ( b = –0.39, SE=0.14, P<0.05). Total and non-fatal first time episodes displayed an inverse relationship between oxygen gradient and time ( r = −0.22, P<0.006 and r = −0.24, P<0.01, respectively). Mean oxygen gradient of fatal episodes for sequential years increased significantly from 73 mmHg in 1983 to 102 mmHg in 1989 ( r = 0.92, P<0.01). This suggests that medical intervention as well as presentation with less severe disease both contributed to improved case fatality over time.

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B Part of It School Leaver protocol: an observational repeat cross-sectional study to assess the impact of a meningococcal serogroup B (4CMenB) vaccine programme on carriage ofNeisseria meningitidis

BMJ Open ◽

10.1136/bmjopen-2018-027233 ◽

2019 ◽

Vol 9 (5) ◽

pp. e027233 ◽

Cited By ~ 3

Author(s):

Helen S Marshall ◽

Mark McMillan ◽

Ann Koehler ◽

Andrew Lawrence ◽

Jenny MacLennan ◽

...

Keyword(s):

Controlled Trial ◽

Age Groups ◽

Case Fatality ◽

Cluster Randomised Controlled Trial ◽

Cross Sectional Study ◽

Sectional Study ◽

School Students ◽

Cross Sectional ◽

The Impact ◽

Carriage Prevalence

IntroductionInvasive meningococcal disease is uncommon but associated with a high-case fatality rate. Carriage prevalence of the causative bacteria,Neisseria meningitidis, is high in adolescents. A large (n=34 500) cluster randomised controlled trial (RCT) to assess the impact of a meningococcal B (MenB) vaccine on meningococcal carriage was implemented in the state of South Australia (SA) for year 10, 11 and 12 senior school students in 2017–2018. This study will assess the impact of MenB vaccine (4CMenB) on carriage prevalence in school leavers in SA, 1 and 2 years after implementation of the cluster RCT in adolescents. Measuring the impact of population programmes on carriage can assist in informing future meningococcal immunisation programmes such as targeted age groups and use of catch-up campaigns.Methods and analysisThis repeat cross-sectional study will assess carriage prevalence in 2018 and 2019. All school leavers who attended year 12 in any school in SA in 2018 or 2019 will be invited to participate in this study. An oropharyngeal swab will be taken from each participating student and a risk factor questionnaire completed by the student following informed consent. Students will attend clinics at SA universities, technical colleges, and metropolitan, rural and remote government council clinics. Confirmed vaccination history will allow a comparison in carriage prevalence between vaccinated and unvaccinated school leavers. A sample size of 4096 students per year will provide 80% power to detect a 20% difference in carriage prevalence of disease-causing meningococci (defined as genogroup A, B, C, W, X or Y) between years.Ethics and disseminationThe study was approved by the Women’s and Children’s Health Network Human Research Ethics Committee. Results will be published in international peer review journals and presented at national and international conferences.Trial registration numberNCT03419533; Pre-results

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Incorporating calendar effects to predict influenza seasonality in Milwaukee, Wisconsin

Epidemiology and Infection ◽

10.1017/s0950268819001511 ◽

2019 ◽

Vol 147 ◽

Cited By ~ 3

Author(s):

Ryan B. Simpson ◽

Tania M. Alarcon Falconi ◽

Aishwarya Venkat ◽

Kenneth H. H. Chui ◽

Jose Navidad ◽

...

Keyword(s):

Public Schools ◽

Negative Binomial ◽

Age Groups ◽

Influenza Surveillance ◽

Influenza B ◽

Sporting Events ◽

Seasonal Incidence ◽

Calendar Effects ◽

Holiday Effects ◽

The Impact

Abstract Social outings can trigger influenza transmission, especially in children and elderly. In contrast, school closures are associated with reduced influenza incidence in school-aged children. While influenza surveillance modelling studies typically account for holidays and mass gatherings, age-specific effects of school breaks, sporting events and commonly celebrated observances are not fully explored. We examined the impact of school holidays, social events and religious observances for six age groups (all ages, ⩽4, 5–24, 25–44, 45–64, ⩾65 years) on four influenza outcomes (tests, positives, influenza A and influenza B) as reported by the City of Milwaukee Health Department Laboratory, Milwaukee, Wisconsin from 2004 to 2009. We characterised holiday effects by analysing average weekly counts in negative binomial regression models controlling for weather and seasonal incidence fluctuations. We estimated age-specific annual peak timing and compared influenza outcomes before, during and after school breaks. During the 118 university holiday weeks, average weekly tests were lower than in 140 school term weeks (5.93 vs. 11.99 cases/week, P < 0.005). The dampening of tests during Winter Break was evident in all ages and in those 5–24 years (RR = 0.31; 95% CI 0.22–0.41 vs. RR = 0.14; 95% CI 0.09–0.22, respectively). A significant increase in tests was observed during Spring Break in 45–64 years old adults (RR = 2.12; 95% CI 1.14–3.96). Milwaukee Public Schools holiday breaks showed similar amplification and dampening effects. Overall, calendar effects depend on the proximity and alignment of an individual holiday to age-specific and influenza outcome-specific peak timing. Better quantification of individual holiday effects, tailored to specific age groups, should improve influenza prevention measures.

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Evaluation of community coalition training effects on youth hospital-admitted injury incidence in Victoria, Australia: 2001–2017

Injury Prevention ◽

10.1136/injuryprev-2019-043386 ◽

2019 ◽

Vol 26 (5) ◽

pp. 463-470 ◽

Cited By ~ 1

Author(s):

Janneke Berecki-Gisolf ◽

Bosco Rowland ◽

Nicola Reavley ◽

Barbara Minuzzo ◽

John Toumbourou

Keyword(s):

Risk Factors ◽

Injury Risk ◽

Negative Binomial ◽

Hospital Admissions ◽

Intervention Strategy ◽

Age Groups ◽

Negative Binomial Regression ◽

Population Based ◽

Injury Incidence ◽

The Impact

BackgroundInjuries are one of the three leading causes of morbidity and mortality for young people internationally. Although community risk factors are modifiable causes of youth injury, there has been limited evaluation of community interventions. Communities That Care (CTC) offers a coalition training process to increase evidence-based practices that reduce youth injury risk factors.MethodUsing a non-experimental design, this study made use of population-based hospital admissions data to evaluate the impact on injuries for 15 communities that implemented CTC between 2001 and 2017 in Victoria, Australia. Negative binomial regression models evaluated trends in injury admissions (all, unintentional and transport), comparing CTC and non-CTC communities across different age groups.ResultsStatistically significant relative reductions in all hospital injury admissions in 0–4 year olds were associated with communities completing the CTC process and in 0–19 year olds when communities began their second cycle of CTC. When analysed by subgroup, a similar pattern was observed with unintentional injuries but not with transport injuries.ConclusionThe findings support CTC coalition training as an intervention strategy for preventing youth hospital injury admissions. However, future studies should consider stronger research designs, confirm findings in different community contexts, use other data sources and evaluate intervention mechanisms.

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The return of the historic influenza A H1N1 virus and its impact on the population of the United Kingdom

Journal of Hygiene ◽

10.1017/s0022172400070571 ◽

1982 ◽

Vol 89 (1) ◽

pp. 89-100 ◽

Cited By ~ 6

Author(s):

P. Chakraverty ◽

P. Cunningham ◽

M. S. Pereira

Keyword(s):

United Kingdom ◽

Influenza A ◽

Antigenic Variation ◽

Adult Population ◽

Age Distribution ◽

Age Groups ◽

The United Kingdom ◽

Influenza A H1n1 ◽

Older Adult Population ◽

The Impact

SUMMARYThe epidemiology in the United Kingdom of the influenza A H1N1 subtype which returned in 1977 after an absence of 20 years is described for the four winter seasons from 1977/8 to 1980/1. The age distribution of virus isolates and the evidence for antigenic variation is presented. The impact in the susceptible age groups year by year is shown by the change in the population with specific antibody. There was the expected increase of antibody in those under the age of 21 but also evidence for a significant amount of infection or re-infection in the older adult population.

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Experimental Blunt Injury to the Larynx

Annals of Otology Rhinology & Laryngology ◽

10.1177/000348949210100312 ◽

1992 ◽

Vol 101 (3) ◽

pp. 270-274 ◽

Cited By ~ 9

Author(s):

Shiann Yann Lee

Keyword(s):

Sex Difference ◽

Thyroid Cartilage ◽

Age Distribution ◽

Age Groups ◽

Central Zone ◽

Fracture Line ◽

Blunt Injury ◽

Clinical Experiences ◽

Laryngeal Trauma ◽

The Impact

This article deals with the fracture line distribution and severity of laryngeal trauma. Laryngeal trauma was experimentally inflicted on 100 human laryngeal specimens with the impact of a 2.0-kg weight falling by gravity from a height of 100 cm. According to the previous pilot experiment and clinical experiences, the author classified the severity of fracture into four grades. The results showed no significant sex difference in the severity of fracture with reference to age distribution, especially severe injury in older age groups. The pattern of fracture lines of the laryngeal cartilage was observed and traced in four selected locations, including the thyroid notch, central zone of the thyroid cartilage, cricothyroid region, and cricoid. The distributions of fracture lines are illustrated. The experiment is described in detail.

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