116 research outputs found

    Epidemiology and risk factors for pneumonia severity and mortality in Bangladeshi children <5 years of age before 10-valent pneumococcal conjugate vaccine introduction

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    Abstract Background Pneumonia is the leading infectious cause of morbidity and mortality in young children in Bangladesh. We present the epidemiology of pneumonia in Bangladeshi children <5 years before 10-valent pneumococcal conjugate vaccine introduction and investigate factors associated with disease severity and mortality. Methods Children aged 2–59 months admitted to three Bangladeshi hospitals with pneumonia (i.e., cough or difficulty breathing and age-specific tachypnea without danger signs) or severe pneumonia (i.e., cough or difficulty breathing and ≥1 danger signs) were included. Demographic, clinical, laboratory, and vaccine history data were collected. We assessed associations between characteristics and pneumonia severity and mortality using multivariable logistic regression. Results Among 3639 Bangladeshi children with pneumonia, 61% had severe disease, and 2% died. Factors independently associated with severe pneumonia included ages 2–5 months (adjusted odds ratio [aOR] 1.60 [95% CI: 1.26–2.01]) and 6–11 months (aOR 1.31 [1.10–1.56]) relative to 12–59 months, low weight for age (aOR 1.22 [1.04–1.42]), unsafe drinking water source (aOR 2.00 [1.50–2.69]), higher paternal education (aOR 1.34 [1.15–1.57]), higher maternal education (aOR 0.74 [0.64–0.87]), and being fully vaccinated for age with pentavalent vaccination (aOR 0.64 [0.51–0.82]). Increased risk of pneumonia mortality was associated with age <12 months, low weight for age, unsafe drinking water source, lower paternal education, disease severity, and having ≥1 co-morbid condition. Conclusions Modifiable factors for severe pneumonia and mortality included low weight for age and access to safe drinking water. Improving vaccination status could decrease disease severity

    Case-control vaccine effectiveness studies: Preparation, design, and enrollment of cases and controls.

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    Case-control studies are commonly used to evaluate effectiveness of licensed vaccines after deployment in public health programs. Such studies can provide policy-relevant data on vaccine performance under 'real world' conditions, contributing to the evidence base to support and sustain introduction of new vaccines. However, case-control studies do not measure the impact of vaccine introduction on disease at a population level, and are subject to bias and confounding, which may lead to inaccurate results that can misinform policy decisions. In 2012, a group of experts met to review recent experience with case-control studies evaluating the effectiveness of several vaccines; here we summarize the recommendations of that group regarding best practices for planning, design and enrollment of cases and controls. Rigorous planning and preparation should focus on understanding the study context including healthcare-seeking and vaccination practices. Case-control vaccine effectiveness studies are best carried out soon after vaccine introduction because high coverage creates strong potential for confounding. Endpoints specific to the vaccine target are preferable to non-specific clinical syndromes since the proportion of non-specific outcomes preventable through vaccination may vary over time and place, leading to potentially confusing results. Controls should be representative of the source population from which cases arise, and are generally recruited from the community or health facilities where cases are enrolled. Matching of controls to cases for potential confounding factors is commonly used, although should be reserved for a limited number of key variables believed to be linked to both vaccination and disease. Case-control vaccine effectiveness studies can provide information useful to guide policy decisions and vaccine development, however rigorous preparation and design is essential

    Case-control vaccine effectiveness studies: Data collection, analysis and reporting results.

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    The case-control methodology is frequently used to evaluate vaccine effectiveness post-licensure. The results of such studies provide important insight into the level of protection afforded by vaccines in a 'real world' context, and are commonly used to guide vaccine policy decisions. However, the potential for bias and confounding are important limitations to this method, and the results of a poorly conducted or incorrectly interpreted case-control study can mislead policies. In 2012, a group of experts met to review recent experience with case-control studies evaluating vaccine effectiveness; we summarize the recommendations of that group regarding best practices for data collection, analysis, and presentation of the results of case-control vaccine effectiveness studies. Vaccination status is the primary exposure of interest, but can be challenging to assess accurately and with minimal bias. Investigators should understand factors associated with vaccination as well as the availability of documented vaccination status in the study context; case-control studies may not be a valid method for evaluating vaccine effectiveness in settings where many children lack a documented immunization history. To avoid bias, it is essential to use the same methods and effort gathering vaccination data from cases and controls. Variables that may confound the association between illness and vaccination are also important to capture as completely as possible, and where relevant, adjust for in the analysis according to the analytic plan. In presenting results from case-control vaccine effectiveness studies, investigators should describe enrollment among eligible cases and controls as well as the proportion with no documented vaccine history. Emphasis should be placed on confidence intervals, rather than point estimates, of vaccine effectiveness. Case-control studies are a useful approach for evaluating vaccine effectiveness; however careful attention must be paid to the collection, analysis and presentation of the data in order to best inform evidence-based vaccine policies

    First results from the AugerPrime Radio Detector

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    Update of the Offline Framework for AugerPrime

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    Combined fit to the spectrum and composition data measured by the Pierre Auger Observatory including magnetic horizon effects

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    The measurements by the Pierre Auger Observatory of the energy spectrum and mass composition of cosmic rays can be interpreted assuming the presence of two extragalactic source populations, one dominating the flux at energies above a few EeV and the other below. To fit the data ignoring magnetic field effects, the high-energy population needs to accelerate a mixture of nuclei with very hard spectra, at odds with the approximate E2^{-2} shape expected from diffusive shock acceleration. The presence of turbulent extragalactic magnetic fields in the region between the closest sources and the Earth can significantly modify the observed CR spectrum with respect to that emitted by the sources, reducing the flux of low-rigidity particles that reach the Earth. We here take into account this magnetic horizon effect in the combined fit of the spectrum and shower depth distributions, exploring the possibility that a spectrum for the high-energy population sources with a shape closer to E2^{-2} be able to explain the observations

    Event-by-event reconstruction of the shower maximum XmaxX_{\mathrm{max}} with the Surface Detector of the Pierre Auger Observatory using deep learning

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