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Real time effectiveness of COVID-19 control strategies
COVID-19 Research Area(s): Epidemiology & Public Health, Healthcare Delivery & Policy
Main objectives: We will estimate the effectiveness of current COVID19 control strategies in near-real-time, and project the effectiveness of proposed control strategies.
Time to impact: 3 weeks - 6 months.
Significance: Estimating the strength of control measures from data is crucial to understanding how we can relax distancing measures: Can we re-open schools? Can we focus measures on those most at risk? As we change our control approaches, we need to monitor their success, based on the imperfect data available.
Deliverables: (1) Statistical test for when we can expect to see the effects of a change in policy and in which data stream; (2) Bayesian estimation of the strength of control measures; (3) Projected effects of new control measures; when they will be visible in data; and (4) Determination of effective measures based on comparisons between locations. Models and documented code will be available in R and/or python.