In the United States, federalism involves policy decisions at the local, state and federal levels. Management of ecological or health systems is guided by the allocation of management authority between different levels of government agencies. Allocating regulatory authority at the federal level can help coordinate efforts to fight the spread of pests and diseases. But federal authority is often characterized by “one size fits all” policies that force uniform restrictions across several states leading to inefficient use of scarce resources. Comparing the relative values of alternate policies can be difficult as decision makers may have different objectives. What features of pest and infectious disease systems would favor a patchwork of several uncoordinated state policies rather than a coordinated but uniform federal policy?
As a unifying framework, we consider two-patch models with a pest species and an infectious disease that managers seek to control. For example, the two patches may represent the spatial extent of potentially invaded habitat or a susceptible human population. In the pest scenario, pests spread between patches based on the number of pests in a patch. In an infectious disease scenario, a two-patch SIR-type model is considered with several types of control actions.
Results/Conclusions
Various numerical simulations and corresponding optimization results will be shown to illustrate the issues of different types of governance. The ‘best’ options can depend on the amount of knowledge shared between the ‘players’, like one state knowing about the actual extent of the pest invasion in its neighboring state. In a disease outbreak scenario, the transmission and the disease death rates can be strong drivers of decisions. Additionally, results can depend on whether states have the same (e.g. minimize cases) versus different (e.g. minimize cases versus minimize deaths) objectives.