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. 2011 Jul 26;29(33):5512-8.
doi: 10.1016/j.vaccine.2011.05.044. Epub 2011 May 30.

The optimal number of routine vaccines to order at health clinics in low or middle income countries

Jayant Rajgopal  1 , Diana L Connor, Tina-Marie Assi, Bryan A Norman, Sheng-I Chen, Rachel R Bailey, Adrienne R Long, Angela R Wateska, Kristina M Bacon, Shawn T Brown, Donald S Burke, Bruce Y Lee
Affiliations

The optimal number of routine vaccines to order at health clinics in low or middle income countries

Jayant Rajgopal et al. Vaccine. .

Abstract

In a low or middle income country, determining the correct number of routine vaccines to order at a health clinic can be difficult, especially given the variability in the number of patients arriving, minimal vaccination days and resource (e.g., information technology and refrigerator space) constraints. We developed a spreadsheet model to determine the potential impact of different ordering policies, basing orders on the arrival rates seen in the previous 1, 3, 6, or 12 sessions, or on long-term historical averages (where these might be available) along with various buffer stock levels (range: 5-50%). Experiments varied patient arrival rates (mean range: 1-30 per session), arrival rate distributions (Poisson, Normal, and Uniform) and vaccine vial sizes (range: 1-dose to 10-dose vials). It was found that when the number of doses per vial is small and the expected number of patients is low, the ordering policy has a more significant impact on the ability to meet demand. Using data from more prior sessions to determine arrival rates generally equates to a better ability to meet demand, although the marginal benefit is relatively small after more than 6 sessions are averaged. As expected, the addition of more buffer is helpful in obtaining better performance; however, this advantage also has notable diminishing returns. In general, the long-term demand rate, the vial sizes of the vaccines used and the method of determining the patient arrival rate all have an effect on the ability of a clinic to maximize the demand that is met.

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Figures

Figure 1
Figure 1
Schematic for various ordering policies
Figure 2
Figure 2
Effect of various averaging procedures on the percentage of met demand
Figure 3
Figure 3
Change in percentage of met demand by varying buffer capacities
See this image and copyright information in PMC

References

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