6533b871fe1ef96bd12d1970
RESEARCH PRODUCT
Stochastic sampling effects favor manual over digital contact tracing.
Marco MancastroppaMarco MancastroppaRaffaella BurioniRaffaella BurioniAlessandro VezzaniClaudio Castellanosubject
0301 basic medicinePhysics - Physics and SocietyComputer scienceEpidemiologyScienceComplex networksFOS: Physical sciencesGeneral Physics and AstronomyPhysics and Society (physics.soc-ph)Tracingcomputer.software_genreGeneral Biochemistry Genetics and Molecular BiologyArticleSpecimen Handling03 medical and health sciences0302 clinical medicineHumans030212 general & internal medicineQuantitative Biology - Populations and EvolutionPandemicsCondensed Matter - Statistical Mechanicsstochastic modelProtocol (science)Stochastic ProcessesMultidisciplinaryStatistical Mechanics (cond-mat.stat-mech)Stochastic processDiagnostic Tests RoutineSARS-CoV-2QPopulations and Evolution (q-bio.PE)Sampling (statistics)COVID-19General ChemistryComplex networkModels TheoreticalNetwork dynamics030104 developmental biologyFOS: Biological sciencesScalabilityQuarantineData miningContact TracingcomputerContact tracingAlgorithmsdescription
Isolation of symptomatic individuals, tracing and testing of their nonsymptomatic contacts are fundamental strategies for mitigating the current COVID-19 pandemic. The breaking of contagion chains relies on two complementary strategies: manual reconstruction of contacts based on interviews and a digital (app-based) privacy-preserving contact tracing. We compare their effectiveness using model parameters tailored to describe SARS-CoV-2 diffusion within the activity-driven model, a general empirically validated framework for network dynamics. We show that, even for equal probability of tracing a contact, manual tracing robustly performs better than the digital protocol, also taking into account the intrinsic delay and limited scalability of the manual procedure. This result is explained in terms of the stochastic sampling occurring during the case-by-case manual reconstruction of contacts, contrasted with the intrinsically prearranged nature of digital tracing, determined by the decision to adopt the app or not by each individual. The better performance of manual tracing is enhanced by heterogeneity in agent behavior: superspreaders not adopting the app are completely invisible to digital contact tracing, while they can be easily traced manually, due to their multiple contacts. We show that this intrinsic difference makes the manual procedure dominant in realistic hybrid protocols.
year | journal | country | edition | language |
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2020-10-07 | Nature communications |