Table 1.

Description of 3 Institutional Models to Estimate Influenza Respiratory Mortality, Multiple Countries

Research Group	Envelope	Sources of Data	Age Groups, years	Indicators	Extrapolation Methodology
CDCa	All respiratory causes of death	EMRs from 33 countries or territories. Annual respiratory deaths from 14 countries. WHO GHE RI deaths, 2015. United Nations and US Census Population Estimates 2015.b Study period: 1999–2015.	<65, 65–74, ≥75, all	WHO GHE RI deaths (2015) as a proxy to account for differences in MMR	Bayesian hierarchical model with multiplier:  • Estimate country-specific influenza-associated respiratory EMR for 33 countries using time series log-linear regression models with vital death records and influenza surveillance data.  • Extrapolate estimates to countries without data. Countries divided into 3 ADs using WHO GHE RI mortality rates.  • Country-specific MRR generated from WHO GHE RI deaths  • Random average country-specific mortality rate from a contributing country multiplied by country/specific MMR to calculate country-specific mortality rate distributions
GLaMORc	All respiratory causes of death	EMRs from 33 countries or territories. Study period: 2002–2011.	<65, ≥65, all	10 country-specific indicators: WHO Region; age group all-cause mortality rates; physician density; obesity; population density; major infectious diseases; gross national income per capita; rural population; population age structure; latitude	Multiple imputation method for extrapolation:  • Two-step approach with a data creation step (stage 1) followed by a hierarchical regression modeling step to project burden for all countries (stage 2).  • For data creation, used statistical correlations between country-specific indicators and contributing country mortality estimates to create distribution of possible mortality values.
IHMEd	LRI deaths	LRI mortality data from 10,312 site-year vital registration, 915 site-year verbal autopsy, and 928 site-year surveillance data, between 1980 and 2016.	23 age groups: 0–6 days, 7–27 days, 28–364 days, 1–4 years, and every 5 years up to 99	13 covariates involved in the modeling process of LRI mortality: pneumococcal conjugate vaccine coverage; indoor air pollution; LRI summary exposure variable; mean BMI; smoking prevalence; DTP3 vaccine coverage; health-care access and quality index; education per capita; LDI per capita; sociodemographic index; alcohol liters per capita; outdoor air pollution (PM2.5); water and sanitation summary exposure value	Counterfactual approach to attribute influenza Estimate of LRI deaths. Attribution of specific pathogens (influenza) by:  • Systematic review to estimate prevalence of influenza virus in patients with LRI;  • Calculation of PAF using proportion influenza positive and OR of LRI given the presence of influenza virus;  • Attributable fraction adjusted by the viral: bacterial pneumonia CFR ratio.

Abbreviations: AD, analytical divisions; BMI, body mass index; CDC, US Centers for Disease Control and Prevention; CFR, case-fatality rate; DPT3, diphtheria-tetanus-pertussis; EMR, excess mortality estimates; GHE, Global Health Estimates; GLaMOR, Global Pandemic Mortality Project; IHME, Institute for Health Metrics and Evaluation; LDI, lag-distributed income; LRI, lower respiratory tract infection; MMR, mortality risk between countries; MRR, mortality rate ratio; OR, odds ratio; PAF, population attributable fraction; PM_2.5, particulate matter with an aerodynamic diameter less than or equal to 2.5 μm; RI, respiratory tract infection; URI, respiratory tract infection; WHO, World Health Organization.

^aIuliano et al. (6).

^bUN World Population Prospects (26).

^cPaget et al. (7).

^dGlobal Burden of Disease 2016 LRI Collaborators. (8).