Abstract

The COVID-19 outbreak put healthcare systems across the globe under immense pressure to meet the unprecedented demand for critical supplies and personal protective equipment (PPE). The traditional cost-effective supply chain paradigm failed to respond to the increased demand, putting healthcare workers (HCW) at a much higher infection risk relative to the general population. Recognizing PPE shortages and high infection risk for HCWs, the World Health Organization (WHO) recommends allocations based on ethical principles. In this paper, we model the infection risk for HCWs as a function of usage and use it as the basis for distribution planning that balances government procurement decisions, hospitals’ PPE usage policies, and WHO ethical allocation guidelines. We propose an infection risk model that integrates PPE allocation decisions with disease progression estimates to quantify infection risk among HCWs. The proposed risk function is used to derive closed-form allocation decisions under WHO ethical guidelines in both deterministic and stochastic settings. The modelling is then extended to dynamic distribution planning. Although nonlinear, we reformulate the resulting model to make it solvable using off-the-shelf software. The risk function successfully accounts for virus prevalence in space and in time and leads to allocations that are sensitive to the differences between regions. Comparative analysis shows that the allocation policies lead to significantly different levels of infection risk, especially under high virus prevalence. The best-outcome allocation policy that aims to minimize the total infected cases outperforms other policies under this objective and that of minimizing the maximum number of infections per period.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.