Health Modeling

Health Modeling

Anticipating the incidence and prevalence of human health conditions worldwide is critical information. With such data, advocates, public policy agencies, and NGOs have a greater chance of developing campaigns that can truly improve the lives of millions. Our custom health models aim to serve precisely this need.

UNICEF

Our cooperation with UNICEF involves forecasting population density, age, pregnancies, and births in Mozambique at the 100×100 meter level for the entire country. This data will provide additional granularity allowing for improved insights and planning for upcoming programs and initiatives.

Population.io

Population.io allows individuals to visualize their relative place in national and global populations by computing a user’s life expectancy and illustrating how long the user would live in different countries. Population.io is based on the UN World Population Prospects, as well as methods created by Samir K. C., Professor at the Asian Demographic Research Institute of Shanghai University and World Population Project Leader at the International Institute for Applied Systems Analysis.

The Next Frontier

One of our advisors, Professor Jesus Crespo Cuaresma of the Vienna University of Economics and Business is working on an emerging concept for measuring life expectancy which aims to standardize life expectancy across varying living conditions across the globe by considering the remaining amount of life available to a particular individual and population. He is also working on a new approach for forecasting demographic data which uses a rolling window of previous activity as the basis for forward projections.

More Accurate Life Expectancy Data

As an extension of Population.io, WDL has created a global health model based on data from IHME and UN data which computes individual life expectancies when different health risk factors and diseases are introduced. First, “death rates” are computed based on prevalence and mortality data. Next, these rates are used to create “life tables” for persons affected by different diseases. Finally, life expectancies are extracted as a primary output.