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   <dc:title>Estimates of the global, regional, and national morbidity,&#xd;
                mortality, and aetiologies of lower respiratory infections in&#xd;
                195 countries, 1990-2016: a systematic analysis for the Global&#xd;
                Burden of Disease Study 2016</dc:title>
   <dc:creator>Bassat Orellana, Quique</dc:creator>
   <dc:creator>García-Basteiro, Alberto L.</dc:creator>
   <dc:creator>GBD 2016 Lower Respiratory Infections Collaborators</dc:creator>
   <dc:subject>Infeccions respiratòries</dc:subject>
   <dc:subject>Mortalitat</dc:subject>
   <dc:subject>Respiratory infections</dc:subject>
   <dc:subject>Mortality</dc:subject>
   <dcterms:abstract>Background: Lower respiratory infections are a leading cause of morbidity and mortality around the world. The Global&#xd;
Burden of Diseases, Injuries, and Risk Factors (GBD) Study 2016, provides an up-to-date analysis of the burden of&#xd;
lower respiratory infections in 195 countries. This study assesses cases, deaths, and aetiologies spanning the past&#xd;
26 years and shows how the burden of lower respiratory infection has changed in people of all ages.&#xd;
Methods: We used three separate modelling strategies for lower respiratory infections in GBD 2016: a Bayesian&#xd;
hierarchical ensemble modelling platform (Cause of Death Ensemble model), which uses vital registration, verbal&#xd;
autopsy data, and surveillance system data to predict mortality due to lower respiratory infections; a compartmental&#xd;
meta-regression tool (DisMod-MR), which uses scientific literature, population representative surveys, and healthcare data to predict incidence, prevalence, and mortality; and modelling of counterfactual estimates of the population&#xd;
attributable fraction of lower respiratory infection episodes due to Streptococcus pneumoniae, Haemophilus influenzae&#xd;
type b, influenza, and respiratory syncytial virus. We calculated each modelled estimate for each age, sex, year, and&#xd;
location. We modelled the exposure level in a population for a given risk factor using DisMod-MR and a spatiotemporal Gaussian process regression, and assessed the effectiveness of targeted interventions for each risk factor in&#xd;
children younger than 5 years. We also did a decomposition analysis of the change in LRI deaths from 2000–16 using&#xd;
the risk factors associated with LRI in GBD 2016.&#xd;
Findings: In 2016, lower respiratory infections caused 652 572 deaths (95% uncertainty interval [UI] 586475–720 612)&#xd;
in children younger than 5 years (under-5s), 1 080958 deaths (943 749–1 170638) in adults older than 70 years, and&#xd;
2 377697 deaths (2145584–2512809) in people of all ages, worldwide. Streptococcus pneumoniae was the leading cause&#xd;
of lower respiratory infection morbidity and mortality globally, contributing to more deaths than all other aetiologies&#xd;
combined in 2016 (1 189937 deaths, 95% UI 690 445–1770 660). Childhood wasting remains the leading risk factor for&#xd;
lower respiratory infection mortality among children younger than 5 years, responsible for 61·4% of lower respiratory&#xd;
infection deaths in 2016 (95% UI 45·7–69·6). Interventions to improve wasting, household air pollution, ambient&#xd;
particulate matter pollution, and expanded antibiotic use could avert one under-5 death due to lower respiratory&#xd;
infection for every 4000 children treated in the countries with the highest lower respiratory infection burden.&#xd;
Interpretation: Our findings show substantial progress in the reduction of lower respiratory infection burden, but this&#xd;
progress has not been equal across locations, has been driven by decreases in several primary risk factors, and might&#xd;
require more effort among elderly adults. By highlighting regions and populations with the highest burden, and the&#xd;
risk factors that could have the greatest effect, funders, policy makers, and programme implementers can more&#xd;
effectively reduce lower respiratory infections among the world’s most susceptible populations.</dcterms:abstract>
   <dcterms:issued>2019-06-05T14:06:29Z</dcterms:issued>
   <dcterms:issued>2019-06-05T14:06:29Z</dcterms:issued>
   <dcterms:issued>2018-11-01</dcterms:issued>
   <dcterms:issued>2019-05-27T08:58:40Z</dcterms:issued>
   <dc:type>info:eu-repo/semantics/article</dc:type>
   <dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
   <dc:relation>Reproducció del document publicat a: http://dx.doi.org/10.1016/S1473-3099(18)30310-4</dc:relation>
   <dc:relation>Lancet Infectious Diseases, 2018, vol. 18, num. 11, p. 1191-1210</dc:relation>
   <dc:relation>http://dx.doi.org/10.1016/S1473-3099(18)30310-4</dc:relation>
   <dc:rights>cc by (c) Troeger et al., 2018</dc:rights>
   <dc:rights>http://creativecommons.org/licenses/by/3.0/es/</dc:rights>
   <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
   <dc:publisher>Elsevier Inc.</dc:publisher>
   <dc:source>Articles publicats en revistes (ISGlobal)</dc:source>
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