Mathematical Modelling of Syndemics
A mathematical model is a simplified representation using mathematical language to describe natural, mechanical or social system dynamics. In the early 20th century, epidemiologists became increasingly interested in the use of mathematical modelling procedures to project possible patterns in the spread of infectious diseases, including potential outcomes of an epidemic. To achieve these goals, epidemiological modelers unite several types of information and analytic capacity, including: 1) mathematical equations and computational algorithms; 2) computer technology; 3) epidemiological knowledge about infectious disease dynamics, including information about specific pathogens and disease vectors; and 4) research data on social conditions and human behavior. Mathematical modelling in epidemiology is now being applied to syndemics. Abu-Raddad, Patnaik, and Kublin (2006), for example, used modelling to quantify the syndemic effects of malaria and HIV in sub-Saharan Africa based on research in Kisumu, Kenya. These researchers point out that infection with HIV facilitates disease progression in individuals exposed to malaria. At the same time, immune reaction to malaria doubles the infectious level of HIV infected individual. In short, in typical syndemic fashion, each of these diseases amplifies the effects of the other. Using mathematical modelling, Abu-Raddad and co-workers found that 5% of HIV infections (or 8,500 cases of HIV since 1980) in Kisumu are the result of the higher HIV infectiousness of malaria-infected HIV patients. Additionally, their model attributed 10% of adult malaria episodes (or almost one million excess malaria infections since 1980) to the greater susceptibility of HIV infected individuals to malaria. Their model also suggests that HIV has contributed to the wider geographic spread of malaria in Africa, a process previously thought to be the consequence primarily of global warming. Other researchers (e.g., Herring and Sattenspiel 2007) also have begun to apply mathematical modelling to syndemics. Modelling offers an enormously useful tool for anticipating future syndemics, including eco-syndemic, based on information about the spread of various diseases across the planet and the consequent co-infections and disease interactions that will result.
In this regard, Jeremy Lauer and colleges (2003) have developed PopMod, a longitudinal population tool that models distinct and possibly interacting diseases. Unlike other life-table population models, PopMod is specifically designed to not assume the statistical independence of the diseases of interest. The PopMod has several intended purposes, including describing the time evolution of population health for standard demographic purposes (such as estimating healthy life expectancy in a population), and providing a standard measure of effectiveness for health interventions and cost-effectiveness analysis. PopMod is used as one of the standard tools of the World Health Organization’s (WHO) CHOICE (Choosing Interventions that are Cost-Effective) program, an initiative designed to provide national health policy makers in the WHO’s 14 epidemiological sub-regions around the world with findings on a range of health intervention costs and effects.
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