Epidemiological Processes in the Biological and Social Sciences: Stochastic Hierarchical Complex Dynamic Network-centric Models

The recent advent of rapid technological changes, scientific developments, and educational expansions have created complex heterogeneities, environmental uncertainties, and socio-economic-ecological inequalities globally. The innovative beneficial resources upgrade and update the existing varieties of structural features such as hereditary, random environmental, spatial and atmospheric perturbations in human population dynamics processes and predator-prey systems. The highly interconnected system under operating random environmental conditions is represented by nonlinear nonstationary large-scale multi-level hierarchical network-centric dynamic processes of Ito-Doob and finite Markovian types with network-centric structural perturbations. For instance, complex spatial, behavioral, and epidemiological structures in human populations vary from citizen to visitor; practicing and adhering to different disease preventive measures at sites in meta-populations; and different ages, stages and resistance levels to infections, respectively. An advantage of the presented results in simple algebraic system parameters form is easy verification and application to planning, prevention, policies, stabilization, monitoring and diseases management.