Stopping the pandemic requires enforceable, proactive, time-bound and zonal physical restrictions.

A proposal to stop pandemic calls for drastic restrictions

This op-ed was published in The Star-Ledger (NJ.com) on March 25. It was written by Alok Baveja, a professor of supply chain management at Rutgers Business School, and Ajai Kapoor of Goldratt Consulting. The op-ed was based on a research paper done by Baveja and Kapoor.

In the last two weeks, the COVID-19 pandemic has moved from a foreign news story to a palpable reality in neighborhoods throughout our nation. Faced with this calamity, efforts are being made on a war footing, at every level, to control its spread through a variety of measures, such as ramping up testing, curfews, stay-in-place orders and voluntary social distancing. Despite these efforts, the fear in society has escalated, driven by the uncertainty of the timeline and impact of this crisis.

Confronted with the challenge of finding an implementable, time-bound solution, we have derived an action plan using the well-tested methodology called the Theory of Constraints. Applying this approach, our analysis has shown that the right goal is to stop the pandemic, not just slow it down. The slow-down approach does not have a timeline, increasing the stress on the healthcare system, reducing business and consumer spending, destabilizing financial markets and ultimately resulting in lost confidence among citizens. On the other hand, stopping the pandemic will promote widespread alignment around a time-bounded plan.

Achieving this goal requires enforceable, proactive, time-bound and zonal physical restrictions, and cannot rely exclusively on voluntary measures. Finding the right size for these pro-active clusters/zones is essential. The clusters should be self-contained for medical, purchasing and social needs. While we recommend these cluster zones be designed at state government level in consultation with counties and municipalities, we think the right size should be around 1 million people, with exceptions made for larger clusters in case of bigger metropolitan areas. Based on modeling, the transmission dynamics within a cluster of 1 million population size, we estimate the time to stop the virus or have it run its course within the cluster to be around 90 days.

Our proposal:

  • Define proactive, “self-sufficient” clusters of about 1 million people, using administrative and geographical boundaries wherever possible.
  • Stop all air, train and bus passenger travel across clusters for 90 days
  • Allow the flow of goods across clusters
  • Cross-cluster travel of people should be allowed only with recent proof of negative testing
  • Within a cluster, adopt consistent curfews, stay-in-place orders, social-distancing, work-from-home, closure of schools, etc.

This plan has some key features. First, it’s enforceable. Second, a time-bound of 90 days will improve planning for communities, businesses and government agencies. Also, the fiscal support/aid required by businesses and families during this time period will now be quantifiable. Third, a cluster strategy will reduce the chance of spread to other clusters. Fourth, and perhaps most importantly, a time-bound plan will help restore consumer, business and investor confidence.

One of the downsides of our proposed plan is the curtailment of people’s travel. Therefore, we recommend ramping up the testing infrastructure, which will allow for more flexibility in the cross-cluster travel of people. This improved flexibility will play a major role in securing citizens’ cooperation for the duration of the plan.

We hope our proposed plan helps drive a more focused, proactive response to this crisis while there is still a small window of time to stop the pandemic. 

Dr. Alok Baveja is a professor of supply chain management at Rutgers Business School and has expertise in quantitative, resource-allocation modeling for public and private enterprises.

Dr. Ajai Kapoor is a partner at Goldratt Consulting with more than 20 years of experience in applying the Theory of Constraints methodology to public and private enterprises.

 

 

 

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