Optimal Covid-19 vaccine stations location and allocation strategies

Abstract

PurposeThis study proposes strategies for vaccine center allocation for coronavirus disease (COVID) vaccine by determining the number of vaccination stations required for the vaccination drive, location of vaccination station, assignment of demand group to vaccination station, allocation of the scarce medical professional teams to station and number of optimal days a vaccination station to be functional in a week.Design/methodology/approachThe authors propose a mixed-integer nonlinear programming model. However, to handle nonlinearity, the authors devise a heuristic and then propose a two-stage mixed-integer linear programming (MILP) formulation to optimize the allocation of vaccination centers or stations to demand groups in the first stage and the allocation of vaccination centers to cold storage links in the second stage. The first stage optimizes the cost and average distance traveled by people to reach the vaccination center, whereas the second stage optimizes the vaccine’s holding and storage and transportation cost by efficiently allocating cold storage links to the centers.Findings The model is studied for the real-world case of Chandigarh, India. The results obtained validate that the proposed approach can immensely help government agencies and policymaking body for a successful vaccination drive. The model tries to find a tradeoff between loss due to underutilized medical teams and the distance traveled by a demand group to get the vaccination.Originality/value To the best of our knowledge, there are hardly any studies on a vaccination program at such a scale due to sudden outbreaks such as Covid-19.

A robust optimization problem for drone-based equitable pandemic vaccine distribution with uncertain supply

“…Additional distribution problems for COVID-19 vaccines involving tactical decisions can also be found in Kumar et al. [34] , Rahman et al. [50] .…”

“… [27] Demand, lead time Stochastic Kumar et al. [34] - - Rahman et al. [50] Vaccine loss CCP Balcik et al.…”

Enhancing Mass Vaccination Programs with Queueing Theory and Spatial Optimization

“…Queueing theory is foundational to operations research and has been applied to many facets of healthcare operations, including the triage process in emergency care departments, 9 staffing needs in operating rooms, 10 hospital bed management, 11,12 and outpatient scheduling. 13 Additionally, it has been applied to COVID-19 vaccine distribution and capacity planning, 7,[14][15][16][17][18] as well as the containment of disease outbreaks, bioterrorist attacks, and other public health emergencies. [19][20][21][22] Mass dog vaccination campaigns (MDVCs) are held annually in Arequipa, Peru to address the re-emergence of canine rabies in the region; 23 they have important parallels with early pandemic vaccination and testing programs in that success depends, in part, on strategically placing and optimally allocating resources across a discrete number of fixed-location facility sites.…”