Our unique strength is our epidemiology and econometric models of the historical demographic and socio-economic profile of each country and the use of these models to forecast the epidemiology, demographic and socio-economic landscape of these countries.
Our forecasts range from epidemiology (disease or health condition), affordable market and price sensitivity to healthcare expenditure, macroeconomics and prevention, and help clients to optimize different stages of their business planning, whether new product entry, pricing, health economics, or R&D strategy etc.
Our forecasts are derived through combing health and epidemiology parameters with demographic and socioeconomic factors. The key drivers of the overall model are education and birth rates. Education is projected by using the current education profile of the adult population and then modifying that year by year taking into account the profile of those exiting the education system each year as well as the education profile of those who die each year.
An Education Index is then used to drive the projected trends in urbanisation, occupation profile, productivity per worker and household size. Time series trends drives birth rates, death rates and education enrollments.
Epidemiology forecasts are dependent on the changes in disease rates and the population age profile. The forecast of disease rate by age and gender is driven by the relationship in actual historical rate changes, the change in causal (aeitiological) agents, expected contributory lifestyle changes, urbanization and natural history of the disease within country, ethnic group and across geographies. These rates are then applied to the forecasted population by age and gender (and where available urban and rural) to derive the number of people with the disease. The prevalent population is linked to their incomes and expenditure and this enables us to forecast the affordable market by price.
The user is expected to use these forecasts as a base point – if the past relationships and trends continue then this is what will happen. That means they are a defensible base line – all changes can be related back to a past trend or relationship (and then ultimately source data) rather than the opinion of an individual.
In working form, the key projections are run to 2050 to see the long term impact of the projected trends. However, we only publish 20 years beyond latest actual, with confidence obviously being higher for 10 year forecasts.
We have a large historic database dating back 30 years, which ‘feeds’ into our models. The healthcare expenditure, demographic and socioeconomic data is primarily from published government sources of each country. It is ‘supported’ by data from other agencies as this helps check the consistency of the interpretation of the data. Governments typically engage in a census and by-census at regular intervals and we supplement that with information from inter year samples, annual labour force studies, annual household income expenditure surveys etc. By using multiple sources of data from different agencies within the same government we are able to develop a more complete picture of what the demographic and socio-economic landscape is like and the dynamics taking place within it. The epidemiology data is from government sources, disease registries, published medical journals and other well recognized sources.
To check on the overall voracity of the data from a government we also examine certain headline relationships, such as water consumption per capita, to ensure the reported levels of population etc make sense. Similarly we look for consistency of relationships across countries of similar affluence and education levels and to the extent that there are differences the possible reasons are investigated.
The database is harmonized as much as possible to facilitate modeling and hence consistency of forecasting process.
The database is updated at least once a year, and for many countries there are interim updates with the release of labour force surveys, household income and expenditure surveys etc, throughout the year. When updating, we always check the consistency of the most recent data with the preceding series for the same variable. We acquire the source document (or online database) for all data that we include in the database thereby allowing items to be back-checked when necessary.
The database includes the following variables – although for some countries not all data is available:
Age by gender – modeled to 1 year age steps.
Births by age of mother.
Deaths by age and gender.
Number of Households; proportion by number of persons in them; number of urban and rural households and average number of persons in each.
Education profile of the adult population.
Enrollment profile of school age population covering primary, secondary, vocational and tertiary.
Number of employed persons by gender, occupation profile and industry sector employed in.
GDP and GDP per capita and deflator.
Distribution of households by income.
Expenditure of both average household and by income group
Total Health Expenditure, public and private health expenditure, total pharmaceutical expenditure
Disease rates and number of people by age and gender with a number of key diseases
Population with a disease, by age and gender, able to afford a treatment of a specific price
Are proprietary to Global Demographics Healthcare Ltd.
Are based on our own comprehensive database.
Use recognized statistical (mainly econometric in style), epidemiological and evidence based medicine methods and processes.
Are transparent- explained to users and not a ‘black box’.
Are ‘constrained’ – meaning that they continuously check that different data items fit together.
Are well tested and continuously improved as more data becomes available.