Here we summarize two new views that are available for each chart. For a more detailed walk-through, check out this video tutorial.
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?
Estimates are only as strong as the evidence they are built on. The Global Burden of Disease (GBD) study produces millions of estimates of health around the globe, estimates that are informing real-world policy and implementation. That means that they have to be built on good data, and a lot of it.
How do we quantify the health impacts of a risk factor such as pollution, which is pervasive, difficult to detect, and often underreported? Richard Fuller, environmentalist and President of Pure Earth, is taking on the challenge.
At the US Senate on April 17, 2018, Professor Ali Mokdad presented findings about health in the US at a briefing for Senate health staff. The goal of the presentation was to raise awareness about how Global Burden of Disease (GBD) data could be a valuable resource for them, and how states can use GBD data to advocate for money to address different health problems.
Everyone deserves to live a long life in full health. Inspired and fueled by this idea, the Global Burden of Disease study, or GBD, seeks to answer the question of what sickens and kills people of all ages around the world.
What do the largest development bank, largest global public health agency, and largest funder of primary biomedical research have in common? Well, among other things, their use of IHME’s work for decision-making.
In his 2017 National Day Rally speech, Singapore’s Prime Minister Lee Hsien Loong expressed his commitment to tackling an important challenge facing the country: Singaporeans are living some of the longest lives in the world, but, particularly in old age, they are not always healthy ones.
Precision maps reveal significant health and education disparities within African nations.
In Rwanda, IHME’s collaborators are using GBD data as they tackle the growing burden of non-communicable diseases (NCDs) and improve care for people living with disabilities.
Ukraine has revamped its health system using the Global Burden of Disease (GBD) study to better address the health problems of its people. The Ministry of Health of Ukraine is also working with IHME to improve the science behind the estimates.
According to Harvard Business Review, people often make great decisions not while actively trying. These “aha!” moments can lead to brilliant, unexpected ideas or solutions. In 1993, a man in Seattle had such an “aha!” moment reading a study about diarrhea. Nearly 25 years later, that moment, unquestionably, helped change the course of global health.
The Global Burden of Disease study (GBD) has been compared to many landmark events: the advent of the encyclopedia, the mapping of the human genome, and the first landing on the moon.