The duration of protection that COVID-19 vaccines provide is still uncertain (Murray & Piot, 2021). Therefore, a possible future scenario is that the entire population will need an extra dose of a vaccine. Yearly recurring flu vaccinations take place at general practices (GP), so this might also be the case for COVID-19 vaccinations. General practitioners indicate that this would not be efficient. In fact, many general practitioners don’t want to execute any vaccinations, because their main job is to provide primary healthcare (Buckley, 2021). On the one hand, when considering the insights of general practitioners, the question arises whether it is desirable for GPs to take care of the vaccinations. On the other hand, immunization of an entire country is a huge operation, so it is important to know which contribution GPs can make to accomplish this task. To answer this question, the required performance of the system must be investigated. Therefore, the main research question is: What is the required performance of the vaccination system to keep the vaccination rate above a sufficient level and minimize virus spread, given uncertainties in vaccine supply and negative social influence regarding vaccinations? This research explores the interactions the concepts of social influence, service level (i.e. the ease of getting vaccinated) and willingness to vaccinate. Several experiments were run wherein negative social influence influences willingness to vaccinate in varying degrees. The same applies to the service level of the vaccination system, which is expressed in waiting times, vaccination speed and canceled appointments. Uncertain deliveries impacts the vaccination speed and the number of canceled appointments in a negative way. A lower average willingness to vaccinate leads to lower vaccination rate and stimulates virus spread. The minimum vaccination rate to achieve herd immunity is assumed to be 70% (Lippi & Henry, 2021). Since an epidemic and willingness to vaccinate of a population are driven by social interactions, an Agent-Based Modeling (ABM) approach was chosen to conduct this research. Based on the findings of this research the following lessons learned have been formulated. First, it is recommended to focus on higher vaccination capacities in order to reduce the vaccination times and limit infections. Despite the fact that vaccinations can be executed more efficiently by GGDs and that many GPs are not willing to take care of vaccinations, the additional force of the GPs can be useful. Provided that they accept to spend 1 hour per day for 37 days, GPs can take care of 11% of the vaccinations. Therefore, the options should be discussed with them in order to convince them to take part in the vaccination campaign. Besides the 11% of the population that GPs can possibly vaccinate, another 89% percent of the population should be vaccinated. Therefore, re-establishment of (some of) the current mass vaccination sites would be a useful option to enable GGDs to work efficiently. Second, this research shows that the minimal required performance of the vaccination system to keep the vaccination rate above a sufficient level is low. That indicates that the willingness to vaccinate in the Netherlands is robust. Enormous increases in negative social influence, delays and low service levels didn’t cause significant disruptions of the willingness to vaccinate. Even in situations with 40% chance of delayed vaccine supplies and high values of negative social influence, the vaccination rate remains above 70%. However, it is still important take the effects of social influence and low service levels into account, because they might be stronger when the willingness to vaccinate is lower. That will possibly be the case when we are not in a crisis situation anymore. Suggestions for further research are making improvements in the model and investigating the actual importance of social influence on vaccination decision making. The last suggestion is to conduct experiments with the model proposed in this research, with the amount of patients that currently receive an influenza vaccination, instead of the entire population. With those experiments, it can be evaluated to what extent GPs can take care of the vaccinations when the number of patients is equal to the number of people that already visit the GP for a vaccination every year.