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An SIR-type epidemiological model that integrates social distancing as a dynamic law based on point prevalence and socio-behavioral factors
| dc.contributor.author | Cabrera-Hernández, Maritza | |
| dc.contributor.author | Cordova-Lepe, Fernando | |
| dc.contributor.author | Gutiérrez-Jara, Juan P. | |
| dc.contributor.author | Vogt-Geisse, Katia | |
| dc.date.accessioned | 2021-12-30T14:55:29Z | |
| dc.date.available | 2021-12-30T14:55:29Z | |
| dc.date.issued | 2021 | |
| dc.identifier.uri | http://repositorio.ucm.cl/handle/ucm/3687 | |
| dc.description.abstract | Modeling human behavior within mathematical models of infectious diseases is a key component to understand and control disease spread. We present a mathematical compartmental model of Susceptible–Infectious–Removed to compare the infected curves given by four different functional forms describing the transmission rate. These depend on the distance that individuals keep on average to others in their daily lives. We assume that this distance varies according to the balance between two opposite thrives: the self-protecting reaction of individuals upon the presence of disease to increase social distancing and their necessity to return to a culturally dependent natural social distance that occurs in the absence of disease. We present simulations to compare results for different society types on point prevalence, the peak size of a first epidemic outbreak and the time of occurrence of that peak, for four different transmission rate functional forms and parameters of interest related to distancing behavior, such as: the reaction velocity of a society to change social distance during an epidemic. We observe the vulnerability to disease spread of close contact societies, and also show that certain social distancing behavior may provoke a small peak of a first epidemic outbreak, but at the expense of it occurring early after the epidemic onset, observing differences in this regard between society types. We also discuss the appearance of temporal oscillations of the four different transmission rates, their differences, and how this oscillatory behavior is impacted through social distancing; breaking the unimodality of the actives-curve produced by the classical SIR-model. | es_CL |
| dc.language.iso | en | es_CL |
| dc.rights | Atribución-NoComercial-SinDerivadas 3.0 Chile | * |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/cl/ | * |
| dc.source | Scientific Reports, 11, 10170 | es_CL |
| dc.subject | Epidemiology | es_CL |
| dc.subject | Applied mathematics | es_CL |
| dc.title | An SIR-type epidemiological model that integrates social distancing as a dynamic law based on point prevalence and socio-behavioral factors | es_CL |
| dc.type | Article | es_CL |
| dc.ucm.indexacion | Scopus | es_CL |
| dc.ucm.indexacion | Isi | es_CL |
| dc.ucm.uri | www.nature.com/articles/s41598-021-89492-x | es_CL |
| dc.ucm.doi | doi.org/10.1038/s41598-021-89492-x | es_CL |
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Excepto si se señala otra cosa, la licencia de la publicación se describe como Atribución-NoComercial-SinDerivadas 3.0 Chile