Systems Approach to Localize Tipping Points for the Emergency Services in Face of the COVID-19 Pandemic

When it comes to the COVID-19 pandemic [1], various issues and problems arise for institutions and critical infrastructures. Institutions such as first responders can be affected by COVID-19 by temporary or permanent loss of their essential staff and resources and therefore loss of their carrying capacity. The gradual and partial loss of carrying capacity in combination with increased demand on first responder systems can potentially push these system towards their tipping point, and thus cause even more loss of capacity to respond to emergency situations. In addition to the increased mental and emotional pressure burdened on first responders due to the presence and dangers of the virus, emergency personnel such as police officers can experience increased workload and stress during the pandemic as well as exposure to symptomatic or asymptomatic individuals affected by COVID-19. By assessing the dynamic carrying capacity of the first responder systems and their interaction with the general population they provide service to, the resiliency of first responder systems can be assessed in face of various scenarios. The resiliency of first responder systems can be increased by designing extra capacity and preventing the system from coming into the proximity of its tipping point, which could result in partial or major collapse in performance of the system. Therefore, protecting the emergency personnel and these indispensable institutions as well as maintaining the capacity to respond to the majority of the emergency calls is paramount. Since the police force, hospitals, fire departments, and other care institutions are structures consisting of a wide range of individuals and operate in an ever-changing environment, this paper attempts to assess the resilience and capacity of such institutions via simulations to find and localize their tipping points. To enable such simulations, the model developed by Vierlboeck, Nilchiani, and Edwards [2] was extended with further branches to allow for simulations of sub-systems and loads thereof. For this paper, the police force of New York City (NYC) was chosen as a case study. To assess the police force performance, the capabilities and capacities of the sub-system were evaluated by testing its function under different circumstances and with different influencing factors such as fatigue [3] and the influence of the Yerkes-Dodsen Law [4]. This way, it was possible to assess the performance of the emergency personnel and provide information that could potentially be used for regulatory measures and decisions. The conducted evaluations and simulations studied the existing system's resiliency and its proximity to the system tipping point as the reduction of a number of emergency personnel is inevitable due to sickness caused by COVID-19. The baseline simulations showed performance drops under high loads which leaves the system in a more delicate state and vulnerable, with a higher tendency to collapse. Testing different scenarios, it was found that overall the system can tolerate a certain degree of changes in temporary demand. However, extended stress and increased demand on the emergency infrastructure systems can push them towards their tipping point and therefore cause irreversible damage.