000151995 001__ 151995
000151995 005__ 20251017144633.0
000151995 0247_ $$2doi$$a10.1038/s41598-022-19931-w
000151995 0248_ $$2sideral$$a143297
000151995 037__ $$aART-2022-143297
000151995 041__ $$aeng
000151995 100__ $$aLe Treut, Guillaume
000151995 245__ $$aA high-resolution flux-matrix model describes the spread of diseases in a spatial network and the effect of mitigation strategies
000151995 260__ $$c2022
000151995 5060_ $$aAccess copy available to the general public$$fUnrestricted
000151995 5203_ $$aPropagation of an epidemic across a spatial network of communities is described by a variant of the SIR model accompanied by an intercommunity infectivity matrix. This matrix is estimated from fluxes between communities, obtained from cell-phone tracking data recorded in the USA between March 2020 and February 2021. We apply this model to the SARS-CoV-2 pandemic by fitting just one global parameter representing the frequency of interaction between individuals. We find that the predicted infections agree reasonably well with the reported cases. We clearly see the effect of “shelter-in-place” policies introduced at the onset of the pandemic. Interestingly, a model with uniform transmission rates produces similar results, suggesting that the epidemic transmission was deeply influenced by air travel. We then study the effect of alternative mitigation policies, in particular restricting long-range travel. We find that this policy is successful in decreasing the epidemic size and slowing down the spread, but less effective than the shelter-in-place policy. This policy can result in a pulled wave of infections. We express its velocity and characterize the shape of the traveling front as a function of the epidemiological parameters. Finally, we discuss a policy of selectively constraining travel based on an edge-betweenness criterion.
000151995 536__ $$9info:eu-repo/grantAgreement/ES/MINECO-FEDER/PGC2018-094684-B-C21
000151995 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttps://creativecommons.org/licenses/by/4.0/deed.es
000151995 590__ $$a4.6$$b2022
000151995 591__ $$aMULTIDISCIPLINARY SCIENCES$$b22 / 73 = 0.301$$c2022$$dQ2$$eT1
000151995 592__ $$a0.973$$b2022
000151995 593__ $$aMultidisciplinary$$c2022$$dQ1
000151995 594__ $$a7.5$$b2022
000151995 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000151995 700__ $$aHuber, Greg
000151995 700__ $$aKamb, Mason
000151995 700__ $$aKawagoe, Kyle
000151995 700__ $$aMcGeever, Aaron
000151995 700__ $$aMiller, Jonathan
000151995 700__ $$aPnini, Reuven
000151995 700__ $$aVeytsman, Boris
000151995 700__ $$0(orcid)0000-0001-7276-2942$$aYllanes, David
000151995 773__ $$g12 (2022), 15946 [10 pp.]$$pSci. rep. (Nat. Publ. Group)$$tScientific reports (Nature Publishing Group)$$x2045-2322
000151995 8564_ $$s3396745$$uhttps://zaguan.unizar.es/record/151995/files/texto_completo.pdf$$yVersión publicada
000151995 8564_ $$s2526417$$uhttps://zaguan.unizar.es/record/151995/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000151995 909CO $$ooai:zaguan.unizar.es:151995$$particulos$$pdriver
000151995 951__ $$a2025-10-17-14:27:18
000151995 980__ $$aARTICLE