Cost effective reproduction number based strategies for reducing deaths from COVID-19

Abstract In epidemiology, the effective reproduction number $R_{e}$ R e is used to characterize growth rate of an epidemic outbreak. If $R_{e} >1$ > 1 , worsens, and if $R_{e}< 1$ < then it subsides eventually dies out. this paper, we investigate properties for a modified SEIR model COVID-19 in city Houston, TX USA, which population divided into low-risk high-risk subpopulations. The response two types control measures (testing distancing) applied different subpopulations characterized. A nonlinear cost measures, include effects diminishing returns. Lowest-cost combinations reducing instantaneous given value are computed. We propose three heuristic strategies mitigating that targeted at exhibit tradeoffs between strategy implementation costs deaths. also consider variants each type strategy: basic strategies, only controls on without regard subpopulation; prioritizing maximize subpopulation. Results showed types, most cost-effective involved setting target applying sufficient attain value. This led begin with strict distancing entire population, later followed by increased testing. Strategies individuals were less than emphasize reduction spreading disease. shows delaying start past certain point greatly worsens outcomes. conclude can be valuable real-time indicator determining strategies.