Author: Cyril Rakovski
Estimation of disease prevalences has been an extensively studied research subject. These are constantly changing quantities as diseases have genetic, environmental and random components and these population characteristics change due to immigration, genetic drift, mutation, environmental exposure changes, lifestyle changes and population aging. We propose a new statistical measure, Disease Disequilibrium (DD), that reflects the simultaneous under or over occurrence of two or more diseases in the population compared to the expected joint prevalence under the assumption of independence. The idea of DD is very similar to the Linkage Disequilibrium (LD) of the human genome and partially related to the idea of analyzing Familial Aggregation to ascertain the presence of a deleterious genetic disease component. LD is manifested by presence of correlations across closely positioned multiple genes due to common genetic ancestry. Large values of DD will be attributable to common genetic, environmental/lifestyle risk factors in the population. We propose to implement a large scale computational study and map the DD values (create a complete DD map) for all subsets of diseases. This information can be invaluable for Public Health and Medicine as it will uncover hidden unexpected relationships among multiple human disorders that can lead to better screening, diagnosis, public health campaign messages as well as finding new applications of already existing drugs.