Age and multi-model growth estimation of white grunt, Haemulon plumieri, in the southern Gulf of Mexico from otolith macrostructure analysis

Oribe-Pérez, Iván Ali; Velázquez‐Abunader, Iván; Poot-López, Gaspar Román

doi:10.1016/j.rsma.2020.101069

Cited by 4 publications

(3 citation statements)

References 26 publications

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“…PG models provide a simpler alternative for modelling the number of cumulative positive cases, hospitalizations and other pandemic variables. Growth curves are used in a wide range of research areas, such as fishery research (Oliveira Zardin et al 2019 ; Oribe-Pérez et al 2020 ), biology (Sun et al 2020 ), or other infectious disease outbreaks (Horimoto et al 1997 ; Roberts and Saha 1999 ; Viboud et al 2016 ; Ghazvini et al 2019 ). Specifically, Logistic, Gompertz, Rosenzweig, and Richards models have been used to model the spread of outbreaks such as A/H1N1 and Ebola in (Liu et al 2015 ).…”

Section: Related Literaturementioning

confidence: 99%

Hospital preparedness during epidemics using simulation: the case of COVID-19

Garcia-Vicuña

Esparza²,

Giménez

2021

Cent Eur J Oper Res

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This paper presents a discrete event simulation model to support decision-making for the short-term planning of hospital resource needs, especially Intensive Care Unit (ICU) beds, to cope with outbreaks, such as the COVID-19 pandemic. Given its purpose as a short-term forecasting tool, the simulation model requires an accurate representation of the current system state and high fidelity in mimicking the system dynamics from that state. The two main components of the simulation model are the stochastic modeling of patient admission and patient flow processes. The patient arrival process is modelled using a Gompertz growth model, which enables the representation of the exponential growth caused by the initial spread of the virus, followed by a period of maximum arrival rate and then a decreasing phase until the wave subsides. We conducted an empirical study concluding that the Gompertz model provides a better fit to pandemic-related data (positive cases and hospitalization numbers) and has superior prediction capacity than other sigmoid models based on Richards, Logistic, and Stannard functions. Patient flow modelling considers different pathways and dynamic length of stay estimation in several healthcare stages using patient-level data. We report on the application of the simulation model in two Autonomous Regions of Spain (Navarre and La Rioja) during the two COVID-19 waves experienced in 2020. The simulation model was employed on a daily basis to inform the regional logistic health care planning team, who programmed the ward and ICU beds based on the resulting predictions.

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Section: Related Literaturementioning

confidence: 99%

Hospital preparedness during epidemics using simulation: the case of COVID-19

Garcia-Vicuña

Esparza²,

Giménez

2021

Cent Eur J Oper Res

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“…Therefore, growth population models suppose a simpler alternative to model the accumulated number of infected people. Growth curves are found in a wide range of areas, such as fishery research [34,35], biology [36] or other infectious disease outbreaks [37][38][39][40]. Specifically, Logistic, Gompertz, Rosenzweig, and Richards models have been already used to model the spread of outbreaks such as A/H1N1 and Ebola in [41].…”

Section: Related Literaturementioning

confidence: 99%

Hospital preparedness in epidemics by using simulation. The case of COVID-19

Garcia-Vicuña

Esparza²,

Giménez

2020

Preprint

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This paper presents a discrete event simulation model to support the decision-making concerned with the short-term planning of the necessary hospital resources, especially Intensive Care Unit (ICU) beds, to face outbreaks, as the SARS-CoV-2. Being used as a short-term forecasting tool, the simulation model requires an accurate representation of the current system state and high fidelity in mimicking the system dynamics from that state. The two main components of the simulation model are the stochastic modeling of the admission of new patients and the patient flow through the hospital facilities. For the patient arrival process, we analyze different models based on growth curves of the twenty most affected countries (until June 15) and propose the use of the Gompertz curve. The length of stay is divided into several stages, each one modeled separately. We analyze the starting of the simulation model, which requires different procedures depending on the information available about the patients currently hospitalized. We also report the use of this simulation model during the COVID-19 outbreak in the Autonomous Community of Navarre, in Spain. Every day, the research team informed the regional logistic team in charge of planning the health resources, who programmed the ward and ICU beds based on the resulting predictions.

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“…In addition, studies related to the reproduction of this species have been carried out in Jamaica (Munro et al, 1973), USA (Murie & Parkyn, 1999), Venezuela (Palazón-Fernández, 2007, and Brasil (Hoffmann et al, 2017;Shinozaki et al, 2013;Silva, 2015;Souza, 2008). However, biological information of this species in the southern Gulf of Mexico is scarce, mainly focused on its growth and mortality, genetic differentiation among populations, and lengthweight relationships (Domínguez-Viveros & Avila-Martínez, 1996;Oribe-Pérez et al, 2020;Poot-López et al, 2017;Villegas-Hernández et al, 2014). Only one published study has addressed reproductive traits for H. plumierii on the Campeche Bank (northern coast off the Yucatán Peninsula) (Darcy, 1983), such as those relating to spawning seasonality and sexual maturity; however this reference is more than 30 years old.…”

Section: Introductionmentioning

confidence: 99%