About: In order to anticipate a future trends in the development of the novel coronavirus COVID-19 epidemic starting early at march 13, in the french overseas department Mayotte, we study in this paper a deterministic and stochastic epidemic model through several possible states: susceptible, exposed, infected including symptomatics and asymptomatics cases, simple or mild removed, severe removed (including hospitalized) and death cases. We first fit the constant transmission rate parameter to the epidemic data in Mayotte during an early exponential growth phase using an algorithm with a package of software R and based on a Likewook Maximum estimator. Thus, after the intervention and control measures imposed by the gouvernement, we introduce a simple temporally varying and exponentially decreasing transmission rate with a control parameter. This allows us to understand wheter these interventions are having the desired impact of controlling the epidemic by pointing out some percentages to maintain control which is critical in Mayotte given the fragility of its health infrastructure and the significant fraction of the population without access to water.

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: In order to anticipate a future trends in the development of the novel coronavirus COVID-19 epidemic starting early at march 13, in the french overseas department Mayotte, we study in this paper a deterministic and stochastic epidemic model through several possible states: susceptible, exposed, infected including symptomatics and asymptomatics cases, simple or mild removed, severe removed (including hospitalized) and death cases. We first fit the constant transmission rate parameter to the epidemic data in Mayotte during an early exponential growth phase using an algorithm with a package of software R and based on a Likewook Maximum estimator. Thus, after the intervention and control measures imposed by the gouvernement, we introduce a simple temporally varying and exponentially decreasing transmission rate with a control parameter. This allows us to understand wheter these interventions are having the desired impact of controlling the epidemic by pointing out some percentages to maintain control which is critical in Mayotte given the fragility of its health infrastructure and the significant fraction of the population without access to water. Goto Sponge NotDistinct Permalink

An Entity of Type : fabio:Abstract, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	abstract
value	In order to anticipate a future trends in the development of the novel coronavirus COVID-19 epidemic starting early at march 13, in the french overseas department Mayotte, we study in this paper a deterministic and stochastic epidemic model through several possible states: susceptible, exposed, infected including symptomatics and asymptomatics cases, simple or mild removed, severe removed (including hospitalized) and death cases. We first fit the constant transmission rate parameter to the epidemic data in Mayotte during an early exponential growth phase using an algorithm with a package of software R and based on a Likewook Maximum estimator. Thus, after the intervention and control measures imposed by the gouvernement, we introduce a simple temporally varying and exponentially decreasing transmission rate with a control parameter. This allows us to understand wheter these interventions are having the desired impact of controlling the epidemic by pointing out some percentages to maintain control which is critical in Mayotte given the fragility of its health infrastructure and the significant fraction of the population without access to water.
subject	Exponentials Statistical parameters Island countries of the Indian Ocean
part of	Analysis of the COVID-19 epidemic in french overseas department Mayotte based on a modified deterministic and stochastic SEIR model
is abstract of	Analysis of the COVID-19 epidemic in french overseas department Mayotte based on a modified deterministic and stochastic SEIR model
is hasSource of	covid:ann/target/66caca7c467018cebb753aa3a01e8bc4a6fa9927 covid:ann/target/aca7c9c50a095e705acd56104695bd9b411f9fbe covid:ann/target/c3c7f1aa46b34d18d76b9c895e5de0727f9fcc97 covid:ann/target/e02aa8c2737c015b27278c9e30873f926efb7e54 covid:ann/target/6c5f0191ba5978518d09e52e82f0905804eb8114 »more»

Faceted Search & Find service v1.13.91 as of Mar 24 2020

Alternative Linked Data Documents: Sponger | ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2025 OpenLink Software