title: Deconstructing the differences: a comparison of GBD 2010 and CHERG's approach to estimating the mortality burden of diarrhea, pneumonia, and their etiologies.
abstract: BACKGROUND
  Pneumonia and diarrhea are leading causes of death for children under five (U5). It is challenging to estimate the total number of deaths and cause-specific mortality fractions. Two major efforts, one led by the Institute for Health Metrics and Evaluation (IHME) and the other led by the World Health Organization (WHO)/Child Health Epidemiology Reference Group (CHERG) created estimates for the burden of disease due to these two syndromes, yet their estimates differed greatly for 2010.
  
  
  METHODS
  This paper discusses three main drivers of the differences: data sources, data processing, and covariates used for modelling. The paper discusses differences in the model assumptions for etiology-specific estimates and presents recommendations for improving future models.
  
  
  RESULTS
  IHME's Global Burden of Disease (GBD) 2010 study estimated 6.8 million U5 deaths compared to 7.6 million U5 deaths from CHERG. The proportional differences between the pneumonia and diarrhea burden estimates from the two groups are much larger; GBD 2010 estimated 0.847 million and CHERG estimated 1.396 million due to pneumonia. Compared to CHERG, GBD 2010 used broader inclusion criteria for verbal autopsy and vital registration data. GBD 2010 and CHERG used different data processing procedures and therefore attributed the causes of neonatal death differently. The major difference in pneumonia etiologies modeling approach was the inclusion of observational study data; GBD 2010 included observational studies. CHERG relied on vaccine efficacy studies.
  
  
  CONCLUSIONS
  Greater transparency in modeling methods and more timely access to data sources are needed. In October 2013, the Bill & Melinda Gates Foundation (BMGF) hosted an expert meeting to examine possible approaches for better estimation. The group recommended examining the impact of data by systematically excluding sources in their models. GBD 2.0 will use a counterfactual approach for estimating mortality from pathogens due to specific etiologies to overcome bias of the methods used in GBD 2010 going forward.
authors.affiliation: Strategic Analysis, Research and Training Program, University of Washington, Seattle, WA, USA. kovacs2@uw.edu.
authors.forename: Stephanie D
authors.initials: SD
authors.lastname: Kovacs
authors.affiliation: London School of Hygiene & Tropical Medicine, Melbourne, Australia. kim.mulholland@lshtm.ac.uk.|Murdoch Childrens Research Institute, Melbourne, Australia. kim.mulholland@lshtm.ac.uk.|Menzies School of Health Research, Charles Darwin University, Darwin, Australia. kim.mulholland@lshtm.ac.uk.
authors.forename: Kim
authors.initials: K
authors.lastname: Mullholland
authors.affiliation: Bill & Melinda Gates Foundation, Seattle, WA, USA. Julia.Bosch@gatesfoundation.org.
authors.forename: Julia
authors.initials: J
authors.lastname: Bosch
authors.affiliation: University of Edinburgh, Edinburgh, Scotland. harry.campbell@ed.ac.uk.
authors.forename: Harry
authors.initials: H
authors.lastname: Campbell
authors.affiliation: Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA. forouzan@uw.edu.
authors.forename: Mohammad H
authors.initials: MH
authors.lastname: Forouzanfar
authors.affiliation: Bill & Melinda Gates Foundation, Seattle, WA, USA. Ibrahim.khalil@gatesfoundation.org.
authors.forename: Ibrahim
authors.initials: I
authors.lastname: Khalil
authors.affiliation: Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA. stevelim@uw.edu.
authors.forename: Stephen
authors.initials: S
authors.lastname: Lim
authors.affiliation: Institute of International Programs, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. liliu@jhsph.edu.
authors.forename: Li
authors.initials: L
authors.lastname: Liu
authors.affiliation: Strategic Analysis, Research and Training Program, University of Washington, Seattle, WA, USA. maleys@uw.edu.
authors.forename: Stephen N
authors.initials: SN
authors.lastname: Maley
authors.affiliation: Department of Health Statistics and Informatics, World Health Organization, Geneva, Switzerland. Mathersc@who.int.
authors.forename: Colin D
authors.initials: CD
authors.lastname: Mathers
authors.affiliation: Strategic Analysis, Research and Training Program, University of Washington, Seattle, WA, USA. alastair.matheson@gmail.com.
authors.forename: Alastair
authors.initials: A
authors.lastname: Matheson
authors.affiliation: Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA. mokdaa@uw.edu.
authors.forename: Ali H
authors.initials: AH
authors.lastname: Mokdad
authors.affiliation: Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. klobrien@jhsph.edu.
authors.forename: Kate
authors.initials: K
authors.lastname: O'Brien
authors.affiliation: Division of Viral Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA. uap2@cdc.gov.
authors.forename: Umesh
authors.initials: U
authors.lastname: Parashar
authors.affiliation: Strategic Analysis, Research and Training Program, University of Washington, Seattle, WA, USA. ttss@uw.edu.
authors.forename: Torin T
authors.initials: TT
authors.lastname: Schaafsma
authors.affiliation: Bill & Melinda Gates Foundation, Seattle, WA, USA. duncan.steele@gatesfoundation.org.
authors.forename: Duncan
authors.initials: D
authors.lastname: Steele
authors.affiliation: Strategic Analysis, Research and Training Program, University of Washington, Seattle, WA, USA. hawes@u.washington.edu.
authors.forename: Stephen E
authors.initials: SE
authors.lastname: Hawes
authors.affiliation: Bill & Melinda Gates Foundation, Seattle, WA, USA. john.grove@gatesfoundation.org.
authors.forename: John T
authors.initials: JT
authors.lastname: Grove
mesh_terms: D002648:Child; D002662:Child Health Services; D002675:Child, Preschool; D003968:Diarrhea, Infantile / Q000209:etiology / Q000401:mortality* / Q000517:prevention & control; D005260:Female; D014943:Global Health; D006801:Humans; D007223:Infant; D007226:Infant Mortality; D007231:Infant, Newborn; D008297:Male; D008403:Mass Screening / Q000379:methods; D015233:Models, Statistical; D011014:Pneumonia / Q000209:etiology / Q000401:mortality* / Q000517:prevention & control; D012044:Regression Analysis