Methodology We use a three-step methodology to develop, evaluate, and refine an emergency response plan: Create a schematic Gather data for our scenarios Perform simulation runs, analyze them, and prepare documentation The first step in our methodology is to sketch out the emergency response plan. When we have sufficient detail, we can create a schematic of the process. We typically raise a lot of questions and uncover a lot of inconsistencies during this step. The second step is to gather the required data. We’ll treat some of these values as constants—the number of clients, the timing of surges and lulls in client arrivals, distances between staging areas and the clinic, and the time it takes to vaccinate a client, for example. We’ll vary some of the other data over the course of our analysis—for example, the number of vaccination stations, the number of shuttle buses, the capacity of orientation rooms, the number of families who have a sick family member, etc. A complete set of data is called a scenario. In the third step, our goal is to arrive at an appropriate balance between costs and service levels—better service levels usually cost more. In order to achieve this balance, we construct scenarios in a systematic way and carry out simulation runs on each of the scenarios. In a simulation run, we move families through the schematic. Each family stops at each “block” in the schematic, waits for every family member to be served, and then moves to the next block. The simulator collects statistics relating to the families, the services, and the resources that provide the services. This type of dynamic simulation is a powerful analysis technique and it enables us to see aspects of process performance that we can’t see using simpler tools, such as spreadsheets. We conduct our simulation analysis in three steps: Simulate a no-wait scenario—see how the process would behave if we had enough of everything so that families never had to wait Scale back critical resources—to find the lowest levels that provide satisfactory service Reduce other resources—so that they are in line with critical resource levels We constructed a no-wait scenario for our community. Our community’s planners were most worried about the number of vaccinators they could muster, so we treated vaccination stations as our critical resource. The no-wait scenario showed us that we would need as many as 31 vaccination stations over the 10-day period of operation in order to provide no-wait service. We wanted to reduce the number of vaccination stations, but we knew that it would affect operations. In particular, we were concerned about: Lengthening the amount of time families would spend in the clinic Elevating clinic populations and making security more difficult Increasing clinic operating hours Increasing transportation costs Increased demands upon staging area parking lots   The following two graphs show how “time in clinic” and clinic population are affected by reducing the number of vaccination stations in the clinic. Planners saw that if they reduced the number of vaccination stations to 25 and there were surges in client arrivals, like the ones that we envisioned, then clinic populations would approach 1,300 families would be in the clinic for as long as 3.5 hours the clinic would have to operate 20 hours per day staging areas would have to operate 22 hours per day Based upon this data, our community decided to plan for 28 vaccination stations—this would enable them to deal with surges in client arrivals at a cost they were willing to afford. After planners decided on 28 vaccination stations, we went back to the model and determined the appropriate levels of other staging area resources (security, triage, contact evaluation, sick evaluation, form distribution, and shuttle buses) and other clinic resources (security, orientation rooms, form review, medical screening, and form collection). The report that we prepared documented the community’s mass vaccination process, resource requirements (both professional and volunteer), transportation costs, and the service levels that the community could expect. Our report showed what would happen if the clinic were understaffed and gave the planners the confidence and credibility to obtain commitments for the resources that they would need.