The Advisory Committee on Immunization Practices (ACIP) has developed new new recommendations for vaccine allocation.
The target groups and priorities are different from those in the previously released Guidance on Allocating and Targeting Pandemic Influenza Vaccine.
Although the current version can be modified to take these into account, we will be releasing a new version of our Vaccine Allocation Model with new defaults to reflect the new recommendations.
If you have any questions, please let me know at firstname.lastname@example.org.
As part of our collaboration with the Montgomery County, Maryland, Advanced Practice Center for Public Health Emergency Preparedness and Response, we have developed a Vaccine Allocation Model.
The Vaccine Allocation Model is intended to help public health officials determine how many persons in different target groups can receive treatment if the number of vaccinations available is limited. This can be done on a local, state, or national scale.
The Vaccine Allocation Model is a Microsoft Excel workbook that can be used either in the advance planning stages of a vaccination campaign or for support during a vaccination campaign.
It is based on information published in the Guidance on Allocating and Targeting Pandemic Influenza Vaccine.
I would like to thank Rachel Abbey at Montgomery County, Maryland, and Hiro Toiya at the Hawaii State Department of Health for their feedback on draft versions of the model.
To download the model and the user’s guide, visit http://www.isr.umd.edu/Labs/CIM/projects/clinic/vam.html.
Please send any comments or suggestions to me at email@example.com.
NYU’s Center for Catastrophe Preparedness & Response has been developing an agent-based disaster simulation model.
The tool is called Planning with Large Agent-Networks against Catastrophes (PLAN C). According to its web site, PLAN C is designed to help “emergency managers, urban planners and public health officials to prepare and evaluate Pareto-optimal plans to respond to urban catastrophic situations.”
The Pareto-optimal part of the description refers to its ability to search for plans that optimize multiple objectives, including the number of casualties, economic impact, and time to recovery. “In this context, planning can be seen as the problem of adjusting the controllable parameters in the interaction between different classes of agents (hospitals, persons, on-site responders, ambulances, etc.) and available resources, in order to moderate the negative consequences of a catastrophic event.”
The 40-page information package available online contains an overview brochure and copies of their publications, including applications to scenarios such as a sarin release, food poisoning, and a smallpox outbreak.
(Thanks to Rachel Abbey for the tip.)