Abstract: Techniques for geospatial-temporal pathogen tracing include: obtaining, from multiple mobile devices in association with a first time, first contact tracing data including at least first geospatial traffic data and first values of a set of attributes associated with a pathogen; obtaining, from the multiple mobile devices in association with a second time, second contact tracing data including at least second geospatial traffic data and second values of the set of attributes associated with the pathogen; and applying at least the first contact tracing data and the second contact tracing data to a machine learning model, to obtain actionable intelligence associated with the pathogen.

Abstract: Techniques for geospatial-temporal pathogen tracing in zero knowledge include: generating, by a first user device, a first proximity token for contact tracing; receiving, by the first user device, a second proximity token from a second user device; generating, by the first user device, a hash based on the first proximity token and the second proximity token; generating, by the first user device using a prover function of a preprocessing zero knowledge succinct non-interactive argument of knowledge (pp-zk-SNARK), a cryptographic proof attesting that an individual associated with the first user device tested positive for a pathogen; transmitting, by the first user device, first publicly verifiable exposure data including at least the cryptographic proof and the hash to a public registry; and applying at least the first publicly verifiable exposure data and second publicly verifiable exposure data to a machine learning model, to obtain actionable intelligence associated with the pathogen.