Racial and ethnic minority groups have been omitted from CDC guidelines intended to prioritize vaccination for those at highest risk.
One year after we published our first COVID-19 model, we take a look back at progress made, lessons learned, and how the world has changed.
When we look exclusively at high-income countries and territories with populations of 10 million or more, the US ranks first for its high levels of gun violence.
Listen to IHME director Dr. Chris Murray discuss the future of the COVID-19 pandemic.
Dr. Mokdad discusses the importance of ensuring vaccine access to any individual irrespective of their citizenship status, creating a national vaccination plan that heavily involves participation at the local level, details on the COVID-19 virus mutations, and more.
La vacilación ante la vacuna y otros riesgos de comportamiento reducen la probabilidad de inmunidad colectiva.
Vaccine hesitancy and other behavioral risks reduce the likelihood of herd immunity.
Maps of mask usage globally, and specifically in the United States, since April 20, 2020
Maps of vaccine confidence globally and specifically in the United States.
This week, IHME has decided not to release new projections due to significant delays in death reporting during and following the holidays.
20 figures from studies that our researchers and collaborators published in journals in 2020, as well as data visualizations, infographics, GIFs and designs from other IHME-affiliated projects.
With many locations at or past their initial peak in daily deaths, on May 4, we released an adaptation of our model of the initial peak in deaths that links that model to our emerging understanding of disease transmission dynamics. This new hybrid approach between our initial statistical model and a more traditional disease transmission model will enable the exploration of changes in transmission intensity if – or as the data increasingly suggest, when – social distancing mandates are eased and/or human mobility patterns rise.
The White House recently referenced a new COVID-19 forecasting model created by Dr. Christopher Murray and researchers in Washington state that predicts the state-by-state impact of the coronavirus pandemic on health systems in the United States. That model is our model.
Why do GBD researchers bother to use new and potentially unfamiliar metrics instead of tried-and-true, older ways of discussing disease, like prevalence and incidence? To illustrate how GBD metrics complement other population health metrics, let’s consider some standard public health metrics, and how GBD-specific metrics build on them.
As part of a recent bipartisan push to enact new anti-tobacco legislation in the state, the Arkansas Center for Health Improvement (ACHI) used data from the Global Burden of Disease study and the Institute for Health Metrics and Evaluation (IHME) to highlight the steep cost of tobacco use in Arkansas.
At the United Nations Population Fund (UNFPA), health innovators are using Global Burden of Disease (GBD) metrics to improve child health, increase access to family planning services, and make childbirth safer.
On April 4, 2019, the Indonesian Ministry of National Development Planning, known as Bappenas, and the Ministry of Health unveiled findings from a new provincial-level study of burden of disease, which they are using to guide national planning and priority setting.
As a world leader promoting the health of children and mothers, UNICEF and its partners work to save the lives of millions of the world’s most vulnerable, in part by having hyper-local data at their fingertips. Recently, UNICEF and its partners started using maps from the Local Burden of Disease (LBD) project, an initiative led by the Institute for Health Metrics and Evaluation (IHME), in one of their flagship data dashboards, the Equitable Impact Sensitive Tool (EQUIST).
Every day we encounter and use mathematical models. From producing weather predictions for the week, to calculating a country’s GDP, to estimating the impact of vaccinations, models help us process, represent, and understand the data that describe the workings of the world around us.
Underwriters Laboratories focused on home and workplace safety, publishes a Safety Index, an algorithm-based data science initiative to foster safe conditions through scientific applications addressing safety, security, and sustainability challenges. Data is integral to the Safety Index, and UL utilizes data from the Global Burden of Disease study (GBD).
We use more 90,000 data sources in the Global Burden of Disease. Why do we use estimates instead of simply presenting the data points?
As part of its Big Four agenda, the government of Kenya is committed to providing universal health coverage by 2022. Global Burden of Disease (GBD) collaborators in Kenya are shedding light on ways that the study can help the country reach this goal.
Knowing what someone died of can be complicated. We often talk and think about death as a singular event. We say, “he died of cancer” or “she died of old age.” In reality, a series of domino effects are often occurring inside the body that lead to someone’s death.
The Global Burden of Disease (GBD) study relies on a lot of data – over 90,000 data sources, in fact. Each of these data sources has their own distinct way of collecting information and measuring health. How do we make these sources speak the same language?