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Decision-makers need signals for action as the coronavirus disease 2019 (COVID-19) pandemic progresses. Our aim was to demonstrate a novel use of statistical process control to provide timely and interpretable displays of COVID-19 data that inform local mitigation and containment strategies. Healthcare and other industries use statistical process control to study variation and disaggregate data for purposes of understanding behavior of processes and systems and intervening on them. We developed control charts at the county and city/neighborhood level within one state (California) to illustrate their potential value for decision-makers. We found that COVID-19 rates vary by region and subregion, with periods of exponential and non-exponential growth and decline. Such disaggregation provides granularity that decision-makers can use to respond to the pandemic. The annotated time series presentation connects events and policies with observed data that may help mobilize and direct the actions of residents and other stakeholders. Policy-makers and communities require access to relevant, accurate data to respond to the evolving COVID-19 pandemic. Control charts could prove valuable given their potential ease of use and interpretability in real-time decision-making and for communication about the pandemic at a meaningful level for communities.

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Background The scale of the COVID-19 pandemic has required rapid development of both governmental and institutional policies and protocols to minimize transmission. We describe our institution's implementation of a symptom monitoring program with this goal. Methods We developed a symptom monitoring tool based on our return-to-work guidelines using a Qualtrics survey tool. We implemented this for healthcare workers (HCWs) and provided individualized real time guidance and linkage to COVID-19 testing if indicated. Results During the period from April 2nd to April 17th, 2020, 9446 HCWs had enrolled in the symptom tracking survey, with 5,035 HCWs completing the survey daily at the end of this period. 1,318 HCWs had been identified as being symptomatic with an indication for SARS-CoV-2 testing and were directed to the hotline to have this ordered. Of these, 82% reported not currently staying home from work due to illness or quarantine when first reporting symptoms. Discussion and Conclusions A survey based symptom monitoring tool can be rapidly designed and implemented, and incorporated with a testing strategy. Our results show the potential for quick uptake, and effectiveness in identifying and addressing presenteeism. We report our large academic institution's experience as a model to be adapted for use in this and future pandemics.