When we think of predictive analytics in insurance, perhaps it calls to mind weather risks, earthquake exposures or other types of disasters, but newly-reported research indicates that a form of predictive analytics will be of great use to health insurers, who should be able to geographically localize the spread of diseases, and in turn, better assess health risks.
According to a ScienceDaily story, a computer model of the spread of West Nile virus was able to predict areas where human cases would be concentrated, especially around Sacramento in 2005. A computerized epidemiological model of the spread of the mosquito-borne virus in 17 counties of California in 2005 successfully predicted where 81.6 percent of human cases of the disease would arise and defined high-risk areas where the risk of infection turned out to be 39 times higher than in low-risk areas, according to newly published research.
The DYCAST software used in those predictions is now open-source and is being applied to other diseases, says the report. The software doesn’t just track the geography of actual cases. DYCAST is based on a number of parameters, including how far mosquitoes and infected birds are likely to fly. Key time parameters include how long the virus needs to incubate in mosquitoes before they become infectious and the lifespan of infected birds.
The model allowed the California Department of Public Health to provide early warnings to an area stretching from the Bay Area through Sacramento to the Nevada line, as well as regions in southern California, says ScienceDaily.
As this kind of multi-parameter technology is developed for other diseases, especially serious ones, it should be interesting to see how the insurance community reacts. Obviously, being able to accurately predict future disease patterns could be a major factor in setting health insurance rates, especially as health insurers feel pressure from both consumers and government to be more focused in assessing risks and assigning premiums. To a certain extent, insurers have always been able to localize areas where some diseases occur more frequently, but this new technology promises a much more accurate and precise type of risk assessment.
Much as auto insurance rates may be significantly affected by the area in which the insured lives and/or works, health insurance premiums could rise or fall depending on the disease risk profiles that are sure to emerge as this approach becomes mainstream. It is the logical extension to the furious increases in information available to insurers for evaluating risks of all kinds—including risk of death.
There are sure to be objections to health insurers segmenting geographical areas based on such data, yet it certainly makes sense to do so when evaluating risk. The depth and thoroughness of the West Nile research demonstrates a scientific rigor that will be hard for anyone to argue with.
Ara C. Trembly (www.aratremblytechnology.com) is the founder of Ara Trembly, The Tech Consultant, and a longtime observer of technology in insurance and financial services.
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