Updating research methods that have been widely used for 60 years
For the past six decades, researchers have been using the same techniques to measure death rates in areas where little data exists. Known as model life table methods, these approaches borrow heavily from patterns that scientists have observed in areas with plentiful data—mostly high- and middle-income areas.
Model life table methods are commonly used to estimate mortality in countries where few deaths are officially registered in government data systems. These systems are called vital registration systems, and they typically monitor births and deaths that occur in a country. While South Africa, Cabo Verde, Namibia, and Botswana have comprehensive vital registration systems, few other countries in sub-Saharan Africa currently collect these data on a country-wide basis.
Researchers developed model life tables as a way of dealing with data challenges, but the method is not ideal. Even though model life tables have long been accepted as the gold standard in academia, and researchers have made improvements to model life table methods over time, the core assumption – that mortality patterns in countries with the highest resources are similar to countries with the fewest resources – is problematic. For example, mortality patterns estimated for Burkina Faso in 2015 could be borrowed from places such as Germany in the 1970s and Argentina in the 1980s, which may not capture key differences among these populations.
In GBD 2023, researchers developed a new method to model mortality rates for different age groups directly from observed data, rather than relying on model life table methods. This allows the data to more directly influence the estimated patterns and trends. For places with little available data, the model integrates information from similar locations and from past trends. The updated methods also leverage data from factors that affect mortality – such as socioeconomic status and development assistance for health – in producing estimates that are as accurate as possible.
New model emphasizes high-quality, local data
GBD researchers and their collaborators around the world have developed a new, more scientifically accurate technique that places data from sub-Saharan African countries front and center when generating GBD mortality estimates instead of relying on outdated methods that impose patterns from higher income countries on lower-income countries. Examples of these high-quality data that the model prioritizes include health and demographic surveillance data collected by groups such as the South Africa Medical Research Council/Wits-Agincourt Unit, part of the Wits Health Consortium in South Africa at the University of the Witwatersrand. Researchers in the Wits-Agincourt Unit gather data on mortality and other health-related indicators from sites in nine countries in sub-Saharan Africa, including South Africa, Mozambique, Kenya, Uganda, Tanzania, Malawi, Ethiopia, Ghana, and Burkina Faso.
The South Africa Medical Research Council/Wits-Agincourt Unit originally started collecting data from communities in South Africa in the 1990s, and has expanded to other countries over the years, incorporating increasingly detailed data over time to provide important insights for scientists and decision-makers. For example, in addition to collecting data on deaths, the University gathers information about people’s health from hospital and clinic records. This rich and informative data gives policymakers valuable knowledge for saving lives and improving health.
Another vital source of data that the new GBD methods prioritize are nationally representative surveys that collect data from mothers and birthing people about the lives – and deaths, when applicable – of their children in sub-Saharan Africa. These data, known as complete birth histories, shed light on the higher rates of death that were occurring in some sub-Saharan African countries among children and young women. The new GBD mortality method allowed data from these surveys to be used for children aged 5–14 years, which was not possible with previous methods.
Promising efforts to expand data collection in sub-Saharan Africa
Beyond the four countries that have comprehensive information on births and deaths in sub-Saharan Africa, there are other nations in the region that are laying the groundwork for vital registration systems, such as Ethiopia. In July 2025, the Ethiopian Public Health Institute (EPHI), which is part of the government, launched a pilot program – known as a sample registration system – to monitor deaths that occur at the regional and national levels. IHME and EPHI have been formally partnering on burden of disease research since 2017.
As countries expand and strengthen their data collection, the world will gain an even better understanding of health trends. The scientific process involves attempting to get closer to the truth. Advancements in statistical methods allow scientists to improve their understanding of how many people are dying around the world, thereby alerting the global community to areas where additional resources may be needed to prevent these deaths.
