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Smartphone-based earthquake early warning systems implemented by citizenscience initiatives are characterized by a significant variability in theirsmartphone network geometry. This has an direct impact on the earthquakedetection capability and performance of the system. Here, a simulationframework based on the Monte Carlo method is implemented for making inferenceon relevant quantities of the earthquake detection such as the detectiondistance from the epicentre, the detection delay and the warning time forpeople exposed to high ground shaking levels. The framework is applied toHaiti, which has experienced deadly earthquakes in the past decades, and to thenetwork of the Earthquake Network citizen science initiative, which is popularin the country. It is discovered that relatively low penetrations of theinitiative among the population allow to offer a robust early warning service,with warning times up to 12 second for people exposed to intensities between7.5 and 8.5 of the modified Mercalli scale.

A simulation framework for statistical inference on the alerting  capabilities of smartphone-based earthquake early warning systems. With a  case study on the Earthquake Network system in Haiti