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Optimizing vaccine distribution via mobile clinics: a case study on COVID-19 vaccine distribution to long-term care facilities.
Shukla, Samta; Fressin, Francois; Un, Michelle; Coetzer, Henriette; Chaguturu, Sreekanth K.
  • Shukla S; CVS Health, Woonsocket, RI, USA. Electronic address: Samta.Shukla@CVSHealth.com.
  • Fressin F; CVS Health, Woonsocket, RI, USA.
  • Un M; CVS Health, Woonsocket, RI, USA.
  • Coetzer H; CVS Health, Woonsocket, RI, USA.
  • Chaguturu SK; CVS Health, Woonsocket, RI, USA; Department of General Medicine, Massachusetts General Hospital, Boston, MA, USA.
Vaccine ; 40(5): 734-741, 2022 01 31.
Article in English | MEDLINE | ID: covidwho-1586267
ABSTRACT

BACKGROUND:

People living in clustered communities with health comorbidities are highly vulnerable to COVID-19 infection. Rapid vaccination of vulnerable populations is critical to reducing fatalities and mitigating strain on healthcare systems. We present a case study on COVID-19 vaccine distribution via mobile vans to residents/staff of 47,907 long-term care facilities (LTCFs) across the United States that relied on algorithms to optimize vaccine distribution.

METHODS:

We developed a modeling framework for vaccine distribution to high-risk populations in a supply-constrained environment. Our framework decomposed this challenge as two separate problems an assignment problem where we optimally mapped each LTCF to select CVS stores responsible for distributing vaccines; and a scheduling problem where we developed an algorithm to assign available resources efficiently.

RESULTS:

We assigned 1,214 retail stores as depots for vaccine distribution to LTCFs throughout the United States. Forty-one percent of matched depot-LTCF pairs were within 5 miles of a depot, 74% were within 20 miles, and only 8% mapped to depots farther than 50 miles away. Our two-step approach ensured that the first LTCF vaccination dose was distributed within 9 days after the program start date in 76% of states, and greater than 90% of doses were administered in the minimum amount of time.

CONCLUSIONS:

We demonstrate that algorithmic approaches are instrumental in maximizing vaccine distribution efficiency. Our learning and framework may be of use to other organizations, including communities where mobile clinics can be established to efficiently distribute vaccines and other healthcare resources in a variety of scenarios.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Vaccines / COVID-19 Type of study: Case report / Prognostic study Topics: Long Covid / Vaccines Limits: Humans Country/Region as subject: North America Language: English Journal: Vaccine Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Vaccines / COVID-19 Type of study: Case report / Prognostic study Topics: Long Covid / Vaccines Limits: Humans Country/Region as subject: North America Language: English Journal: Vaccine Year: 2022 Document Type: Article