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With the widespread use of collaborative governance mechanisms for mitigating water pollution, an opportunity exists to test alternative institutional designs based on collaborative governance theory using computer simulation models, particularly when there is a clear relationship between governance networks, observable resource allocation decisions, and measurable outcomes. This is especially the case for wicked problems like nonpoint source water pollution where there are compelling questions regarding how best to design policies, allocate funds, and build administrative capacity to meet water quality standards. We present an agent-based model (ABM) of water governance for the Lake Champlain Basin to simulate the impacts of alternative collaborative governance arrangements on the development of suites of water quality projects. The ABM is connected or coupled with land use and phosphorus load accumulation models that are informed by existing hydrologic models, project datasets, and state-set load reduction targets. We find that regionally arranged collaborative governance in water quality project planning and implementation can lead to better water quality outcomes, thereby affirming one of the central premises of collaborative governance regime theory. We also find that externally mandated collaboration, as opposed to voluntary, self-initiated collaboration, can lead to better water quality outcomes, adding to our understanding of which type of collaborative governance arrangement is best suited to the specific contexts of this case. Further, without adequate administrative capacity in the form of human resources located in central network actors to manage project funds, “administrative bottlenecks” may form and money can go unspent. This research demonstrates the efficacy of using simulations of alternative institutional design for theory testing and tuning, and policy prototyping.

BACKGROUND: School vaccination rates in California have fallen as more parents opt for personal belief exemptions (PBEs) for their children. Our goals were to (1) spatially analyze PBE patterns over time, (2) determine correlates of PBEs, and (3) examine their spatial overlap with personal medical exemptions (PMEs).METHODS: PBE and PME data for California kindergarten classes from the 2001/2002 to 2013/2014 school years were matched to the locations of schools. Nonspatial clustering algorithms were implemented to group 5147 schools according to their trends in PBE percentages among kindergartners. Cluster assignments were mapped and hotspot analysis was performed to find areas in California where schools sharing trends in PBEs over time were colocated. Schools were further associated both with school-level data on minority enrollment and free and reduced price lunch participation and with charter/private and rural/urban status. Spatial regression was implemented to determine which school-level variables were correlated with PBE rates in the 2013/2014 school year.RESULTS: Distinct spatial patterns are observed in California when PBE cluster assignments are mapped. Results indicate that schools belonging to the "high PBE" cluster are spatially buffered from those in "low PBE" areas by "medium PBE" schools. Further, PBE rates are positively associated with the percentage of white students, charter status, and private schools.CONCLUSIONS: Hotspots of high PBE schools are in some cases colocated with schools that have elevated PME rates, prompting concern that herd immunity is diminished for school populations where students have no choice but to remain unvaccinated. WHAT'S KNOWN ON THIS SUBJECT:An increasing number of children are unvaccinated at entry into public schools, potentially endangering children who cannot be vaccinated for medical reasons and threatening herd immunity. Voluntary exemptions from immunizations vary geographically and by parental characteristics. WHAT THIS STUDY ADDS:We find that exemption behavior is highest in peripheral areas of cities and that specific types of student populations are associated with high exemption rates. Additionally, there is spatial overlap between clusters of high personal exemption and medical exemption populations. Dr Carrel conceptualized and designed the study, performed statistical and spatial analysis, and drafted the initial manuscript; Mr Bitterman developed the dataset, carried out spatial and statistical analyses, and reviewed and revised the manuscript; and both authors approved the final manuscript as submitted.www.pediatrics.org/cgi

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