Global mortality estimates for the 2009 Influenza Pandemic from the GLaMOR project: a modeling study

Abstract

Background: Assessing the mortality impact of the 2009 influenza A H1N1 virus (H1N1pdm09) is essential for optimizing public health responses to future pandemics. The World Health Organization reported 18,631 laboratory-confirmed pandemic deaths, but the total pandemic mortality burden was substantially higher. We estimated the 2009 pandemic mortality burden through statistical modeling of mortality data from multiple countries.

Methods and findings: We obtained weekly virology and underlying cause-of-death mortality time series for 2005-2009 for 20 countries covering ∼35% of the world population. We applied a multivariate linear regression model to estimate pandemic respiratory mortality in each collaborating country. We then used these results plus ten country indicators in a multiple imputation model to project the mortality burden in all world countries. Between 123,000 and 203,000 pandemic respiratory deaths were estimated globally for the last 9 mo of 2009. The majority (62%-85%) were attributed to persons under 65 y of age. We observed a striking regional heterogeneity, with almost 20-fold higher mortality in some countries in the Americas than in Europe. The model attributed 148,000-249,000 respiratory deaths to influenza in an average pre-pandemic season, with only 19% in persons <65 y. Limitations include lack of representation of low-income countries among single-country estimates and an inability to study subsequent pandemic waves (2010-2012).

Conclusions: We estimate that 2009 global pandemic respiratory mortality was ∼10-fold higher than the World Health Organization's laboratory-confirmed mortality count. Although the pandemic mortality estimate was similar in magnitude to that of seasonal influenza, a marked shift toward mortality among persons <65 y of age occurred, so that many more life-years were lost. The burden varied greatly among countries, corroborating early reports of far greater pandemic severity in the Americas than in Australia, New Zealand, and Europe. A collaborative network to collect and analyze mortality and hospitalization surveillance data is needed to rapidly establish the severity of future pandemics. Please see later in the article for the Editors' Summary.

Conflict of interest statement

LS has provided consultancy services to GlaxoSmithKline (GSK) and served on expert advisory boards for GSK, Roche, Pfizer, Merck, and Novartis. LS and RJT have an ownership interest in Sage Analytica, a consultancy in epidemiology and bioinformatics. DMF has provided consultancy services for GSK, Novartis, and MedImmune relating to influenza epidemiology and vaccine effectiveness and has been supported to attend international influenza meetings. WJP has served on an influenza advisory board for GSK.

Figures

Figure 1. Schematic illustration of the matching method based on country indicators.

BMI, body mass index; Resp. disease, respiratory disease.

Figure 2. Output of the data creation phase for multiple imputation and matching for one randomly selected country per region.

Eastern Med, Eastern Mediterranean; Imp, multiple imputation method; Match, matching method.

Figure 3. Pandemic excess mortality estimates for Stage 1 countries, by age and outcome (respiratory, cardiorespiratory, and all cause).

Data are grouped into four geographical regions.

Figure 4. Examples of regional heterogeneity in pandemic mortality impact: Mexico (high burden) and France (low burden).

In Mexico, a substantial H1N1pdm09 respiratory mortality burden (red areas above gray background mortality) occurred among children, young adults, and middle-aged persons (

Figure 5. Pandemic respiratory mortality rates projected to all world countries with the Stage 2 multiple imputation model, stratified by age.

(A) Under 65 y and (B) all ages. Numbers in map legend are pandemic mortality rates per 100,000 persons.

Figure 6. Sensitivity analysis of global and regional pandemic respiratory mortality rates.

The Stage 2 model was run multiple times, each time removing one Stage 1 country, for (A) all ages and (B)

Figure 7. Age distribution of projected global and regional respiratory mortality, for both pandemic and seasonal influenza mortality estimates.

East.Med, Eastern Mediterranean.

Figure 8. Comparison of GLaMOR mortality estimates to those of Dawood et al.

GLaMOR all-age respiratory mortality estimated directly from all-age multiple imputation (open circles) and by proportional extrapolation of the

Figure 9. Comparison of Stage 1 modeled pandemic respiratory mortality rates, by age, to published estimates for Mexico, Australia, US, China, and France by authors using various modeling strategies.

Asterisks indicate significance at the p<0.05 level.

Figure 10. Comparison of Stage 1 modeled pandemic all-age mortality rates, by cause, to published estimates for Mexico, Australia, US, China, and France by authors using various modeling strategies.

Asterisks indicate significance at the p<0.05 level.