In order to effectively control spread of coronavirus 2019 (COVID-19), it is essential that jurisdictions have the capacity to rapidly trace close contacts of each and every case. Best practice guidance on how to implement such programs is urgently needed. We describe the early experience in the City and County of San Francisco (CCSF), where the City’s Department of Health expanded contact tracing capability in anticipation of changes in San Francisco’s ‘shelter in place’ order between April and June 2020. Important prerequisites to successful scale-up included a rapid expansion of the COVID-19 response workforce, expansion of testing capability, and other containment resources. San Francisco’s scale-up offers a model for how other jurisdictions can rapidly mobilize a workforce. We underscore the importance of an efficient digital case management system, effective training, and expansion of supportive service programs for those in quarantine or isolation, and metrics to ensure continuous performance improvement.

In today's climate of government outsourcing and multiple stakeholder involvement in public sector management and service delivery, it is more important than ever to rethink and redesign the structure of how policy decisions are made, implemented, monitored, and adapted to new realities. The traditional command-and-control approach is now less effective because an increasing amount of responsibility to deliver public goods and services falls on networks of nongovernment agencies. Even though public administrators are seeking new decision-making models in an increasingly more complex environment, the public sector currently only sparsely utilizes Mediated Modeling (MM). There is growing evidence, however, that by employing MM and similar tools, public interest networks can be better equipped to deal with their long-term viability while maintaining the short-term needs of their clients. However, it may require a shift in organizational culture within and between organizations to achieve the desired results. This paper explores the successes and barriers to implementing MM and similar tools in the public sector and offers insights into utilizing them through a review of case studies and interdisciplinary literature. We aim to raise a broader interest in MM and similar tools among public sector administrators at various administrative levels. We focus primarily, but not exclusively, on those cases operating at the interface of ecology and socio-economic systems.

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