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Pandemics, notably the recent COVID-19 outbreak, have impacted both publichealth and the global economy. A profound understanding of disease progressionand efficient response strategies is thus needed to prepare for potentialfuture outbreaks. In this paper, we emphasize the potential of Agent-BasedModels (ABM) in capturing complex infection dynamics and understanding theimpact of interventions. We simulate realistic pharmaceutical, behavioral, anddigital interventions that mirror challenges in real-world policy adoption andsuggest a holistic combination of these interventions for pandemic response.Using these simulations, we study the trends of emergent behavior on alarge-scale population based on real-world socio-demographic and geo-censusdata from Kings County in Washington. Our analysis reveals the pivotal role ofthe initial 100 days in dictating a pandemic's course, emphasizing theimportance of quick decision-making and efficient policy development. Further,we highlight that investing in behavioral and digital interventions can reducethe burden on pharmaceutical interventions by reducing the total number ofinfections and hospitalizations, and by delaying the pandemic's peak. We alsoinfer that allocating the same amount of dollars towards extensive testing withcontact tracing and self-quarantine offers greater cost efficiency compared tospending the entire budget on vaccinations.

First 100 days of pandemic; an interplay of pharmaceutical, behavioral and digital interventions -- A study using agent based modeling