Considering COVID-19 pandemic reaction and response analogies in an agent-based modeling framework for water distribution system contamination response

Contamination events in water distribution systems are emergencies which can cause distress in the population and require fast handling of the responsible utility manager. Various models have been built to explore the reactions of all relevant stakeholders during a contamination event or other emergencies and disasters utilizing agent-based modeling. None of them considers the social background and the possibly related psychological states of the affected population. This study proposes to use recent findings during the COVID-19 pandemic outbreak and draw analogies regarding response and reaction to a disaster on a major scale for implementing it in an agent-based model framework for reacting to a contamination event in a water network. A hydraulic simulation is coupled with an agent-based model which consists of consumer agents and a utility manager. Upon detection of anomalies in the water quality, the utility manager places mobile sensor equipment to emulate "contact tracing," determine endangered areas in the water network, and warn the consumer agents in real time about the geographical spread of the event through, e.g., social media. The consumer agents' actions are determined according to their social backgrounds, location in the water network, and possible symptoms from ingesting contaminated water by utilizing a fuzzy logic system. Results on an example application suggest that placing mobile equipment and warning consumers in real time is essential as a proper response to a contamination event. Furthermore, social background factors like age or employment status of the population can play a vital role in the response of consumer agents to a water quality contamination event in a water distribution system.