| dc.creator | Lalwani, Soniya | |
| dc.creator | Sahni, Gunjan | |
| dc.creator | Mewara, Bhawna | |
| dc.creator | Kumar, Rajesh | |
| dc.date.accessioned | 2020-07-29T19:18:26Z | |
| dc.date.available | 2020-07-29T19:18:26Z | |
| dc.date.created | 2020-05-30 | |
| dc.identifier.issn | 0960-0779 | spa |
| dc.identifier.other | https://www.sciencedirect.com/science/article/pii/S0960077920303386?via%3Dihub | spa |
| dc.identifier.uri | http://hdl.handle.net/20.500.12010/11362 | |
| dc.format.extent | 8 páginas | spa |
| dc.format.mimetype | application/pdf | spa |
| dc.publisher | Chaos, Solitons & Fractals | eng |
| dc.source | reponame:Expeditio Repositorio Institucional UJTL | spa |
| dc.source | instname:Universidad de Bogotá Jorge Tadeo Lozano | spa |
| dc.subject | SIRD Model | spa |
| dc.subject | Pandemic | spa |
| dc.subject | Lockdown | spa |
| dc.subject | Silent Carriers | spa |
| dc.title | Predicting optimal lockdown period with parametric approach using three-phase maturation SIRD model for COVID-19 pandemic | spa |
| dc.type.local | Artículo | spa |
| dc.subject.lemb | Síndrome respiratorio agudo grave | spa |
| dc.subject.lemb | COVID-19 | spa |
| dc.subject.lemb | SARS-CoV-2 | spa |
| dc.subject.lemb | Coronavirus | spa |
| dc.rights.accessrights | info:eu-repo/semantics/openAccess | spa |
| dc.type.hasversion | info:eu-repo/semantics/acceptedVersion | spa |
| dc.identifier.doi | https://doi.org/10.1016/j.chaos.2020.109939 | spa |
| dc.description.abstractenglish | This paper proposes a three-phase Susceptible-Infected-Recovered-Dead (3P-SIRD) model to calculate an optimal lockdown period for some specific geographical regions that will be favorable to break not only the transmission chain but also will help country’s economy to recover and support infrastructure in a fight against COVID-19. Proposed model is novel since it additionally includes parameters i.e. silent carriers, sociability of newly infected person and unregistered died coronavirus infected people along with the infection rate, suspected rate and death rate. These parameters contribute a lot to figure out the more clear model, along with essential parameters. The model takes the testing rate of suspected people into consideration and this rate varies with respect to phase of the epidemic growth. Proposed 3P-SIRD model is divided into three-phases based on the awareness and sustainability of disease. Time is divided into different periods as rate of infection and recovery fluctuates region to region. The model is tested on China data and is efficient enough to propose a model very close to their actual figures of infected people, recovered people, died and active cases. The model predicts the optimal lockdown period as 73 days for China which is very close to their actual lockdown period (77 days). Further, the model is implemented to predict the optimal lockdown period of India and Italy. | spa |
