8 November 2018
adapted slightly from the story by CIRES Communications
The Global Burden of Disease (GBD) is a critical resource for informed policymaking, with the goal of providing a tool to quantify health loss from hundreds of diseases, injuries, and risk factors, so that health systems worldwide can be improved and disparities can be eliminated.
GBD research incorporates both the prevalence of a given disease or risk factor and the relative harm it causes. The tools allow decision-makers to compare the effects of different diseases, such as malaria versus cancer, and then use that information at home. Collected and analyzed by a consortium of more than 2,300 researchers in more than 130 countries, the data capture premature death and disability from more than 300 diseases and injuries in 195 countries, by age and sex, from 1990 to the present. This method allows comparisons over time, across age groups, and among populations. Policymakers in Brazil, China, India, Indonesia, Mexico, Saudi Arabia, the United Kingdom, and other countries worldwide are collaborating with GBD researchers to adopt this approach for measuring their population's health and determining how it varies by different regions, socioeconomic status, or ethnic groups in their country. Every year GBD produces multiple peer-reviewed studies: Global Burden of Disease (GBD) Publications.
GBD's update for the year 2017 was published in The Lancet early November 2018. Among 84 assessed risks, the report includes an update for premature deaths worldwide due to ambient ozone pollution. GBD estimates 472 thousand premature deaths worldwide due to ambient ozone pollution, an increase of 20 percent from the year 2007 (392 thousand deaths). Estimates of worldwide premature deaths due to ambient particulate matter are much higher: 2,940 thousand deaths in 2017, an increase of 22 percent from 2007. Of all premature deaths in 2017 due to ambient ozone and ambient particulate matter, ozone accounted for 14 percent.
CSD scientists Kai-Lan Chang and Owen Cooper contributed to the ambient ozone mortality estimates by producing a new global map of surface ozone concentrations based on all available surface ozone observations (provided by the Tropospheric Ozone Assessment Report (TOAR)) and output from six global atmospheric chemistry models. This product, a fusion of observations and the best-performing models, provides a more accurate ozone field than can be achieved by any individual model. This work is a collaboration between CSD / CIRES and the University of North Carolina Chapel Hill (Dr. J. Jason West and Dr. Marc Serre), with support from the NASA Health and Air Quality Applied Sciences Team.
Chang, K.-L., O.R. Cooper, J.J. West, M.L. Serre, M.G. Schultz, M. Lin, V. Marécal, B. Josse, M. Deushi, K. Sudo, J. Liu, and C.A. Keller, A new method (M3Fusion v1) for combining observations and multiple model output for an improved estimate of the global surface ozone distribution, Geoscientific Model Development, doi:10.5194/gmd-12-955-2019, 2019.
We have developed a new statistical approach (M3Fusion) for combining surface ozone observations from thousands of monitoring sites around the world with the output from multiple atmospheric chemistry models to produce a global surface ozone distribution with greater accuracy than can be provided by any individual model. The ozone observations from 4766 monitoring sites were provided by the Tropospheric Ozone Assessment Report (TOAR) surface ozone database, which contains the world's largest collection of surface ozone metrics. Output from six models was provided by the participants of the Chemistry-Climate Model Initiative (CCMI) and NASA's Global Modeling and Assimilation Office (GMAO). We analyze the 6-month maximum of the maximum daily 8 h average ozone value (DMA8) for relevance to ozone health impacts. We interpolate the irregularly spaced observations onto a fine-resolution grid by using integrated nested Laplace approximations and compare the ozone field to each model in each world region. This method allows us to produce a global surface ozone field based on TOAR observations, which we then use to select the combination of global models with the greatest skill in each of eight world regions; models with greater skill in a particular region are given higher weight. This blended model product is bias corrected within 2° of observation locations to produce the final fused surface ozone product. We show that our fused product has an improved mean squared error compared to the simple multi-model ensemble mean, which is biased high in most regions of the world.
GBD 2017 Risk Factor Collaborators (a team of approximately 600), Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017, The Lancet, doi:10.1016/S0140-6736(18)32225-6, 2018.
The Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017) provides a comprehensive assessment of risk factor exposure and attributable burden of disease. By providing estimates over a long time series, this study can monitor risk exposure trends critical to health surveillance and inform policy debates on the importance of addressing risks in context.