Tiered social distancing policies and epidemic control

Tiered social distancing policies have been adopted by many governments to mitigate the harmful consequences of COVID-19. Such a number well-established features, i.e. they are short-term, adaptive (to changing epidemiological conditions), and based on multiplicity indicators prevailing epidemic activity. Here, we use ideas from Behavioural Epidemiology represent tiered in an SEIRS model using composite information index including multiple current past activity mimicking those used during COVID-19 pandemic, such as transmission intensity, infection incidence hospitals’ occupancy. In its turn, dynamics is assumed endogenously inform governmental interventions. The resulting described hereditary system showing noteworthy property, dependency endemic levels variables initial conditions. This consequence need normalize different pool them into single index. Simulations suggest rich spectrum possible results. These include policy suggestions identify pitfalls undesired outcomes, worsening control, that can arise following types approaches responses.