Examinando por Autor "Ospina J"

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    Algebraic analysis of social networks for bio-surveillance: the cases of SARS-Beijing-2003 and AH1N1 influenza-Mexico-2009.
    (SPRINGER-VERLAG BERLIN, 2011-01-01) Hincapié D; Ospina J; Hincapié D; Ospina J; Universidad EAFIT. Departamento de Ciencias; Lógica y Computación
    Algebraic analysis of social networks exhibited by SARS-Beijing-2003 and AH1N1 flu-Mexico-2009 was realized. The main tools were the Tutte polynomials and Maple package Graph-Theory. The topological structures like graphs and networks were represented by invariant polynomials. The evolution of a given social network was represented like an evolution of the algebraic complexity of the corresponding Tutte polynomial. The reduction of a given social network was described like an involution of the algebraic complexity of the associated Tutte polynomial. The outbreaks of SARS and AH1N1 Flu were considered like represented by a reduction of previously existing contact networks via the control measures executed by health authorities. From Tutte polynomials were derived numerical indicators about efficiency of control measures.
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    The dynamics of shrinking and expanding drug-loaded microspheres: A semi-empirical approach
    (ELSEVIER SCIENCE BV, 2014-07-16) Simon L; Ospina J; Willits RK; Simon L; Ospina J; Willits RK; Universidad EAFIT. Departamento de Ciencias; Lógica y Computación
    The dynamics of shrinking and expanding drug-loaded microspheres were studied using a diffusion equation in spherical coordinates. A movable boundary condition was incorporated as a convection term in the original model. The resulting convective-diffusive problem was solved using Laplace transform techniques with the Bromwich integral and the residue theorem. Analytical solutions were derived for the general case of shrinking or expanding microspheres and three particular kinetics expressions: linear growth, exponential swelling and exponential shrinking. Simulations show that microspheres with fast-swelling kinetics released their therapeutic cargo at a relatively slow rate in the first two cases. Ninety-nine percent of the medication was delivered at four times the effective time constant. In line with laboratory studies using bovine serum albumin, an increase in the shrinking rate led to a fast release of the medication from its carrier. The method was applied to analyze insulin transport through spherical Ca-alginate beads. A good agreement was noted between predicted and experimental data. The theoretical effective time constant was 114.0 min.
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    Three-dimensional analyses of a perforated cylindrical drug delivery device
    (ELSEVIER SCIENCE BV, 2015-03-15) Simon L; Ospina J; Simon L; Ospina J; Universidad EAFIT. Departamento de Ciencias; Lógica y Computación
    A closed-formed solution of a perforated drug-delivery model was developed. Laplace transforms were applied to the governing equation, which included diffusion through the tubular device and mass transfer across a rectangular cut. A first-order estimate for the fraction of drug released, in terms of the Laplace variable, was derived after employing suitable boundary and initial conditions. The effective time constant for the process was calculated. The residue theorem and the Zakian method were proposed as two reliable approaches to recover the solution in the time domain. Simulations show that the drug was released faster at higher Sherwood numbers. Ninety-eight percent (98%) of the loading dose was delivered after a period corresponding to four time constants. This analytical platform can aid in the design of implants for long-term delivery applications. (C) 2015 Elsevier B.V. All rights reserved.
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    Using Phenomenological Models to Characterize Transmissibility and Forecast Patterns and Final Burden of Zika Epidemics.
    (Public Library of Science,, 2016-05-31) Chowell G; Hincapie-Palacio D; Ospina J; Pell B; Tariq A; Dahal S; Moghadas S; Smirnova A; Simonsen L; Viboud C; Chowell G; Hincapie-Palacio D; Ospina J; Pell B; Tariq A; Dahal S; Moghadas S; Smirnova A; Simonsen L; Viboud C; Universidad EAFIT. Departamento de Ciencias; Lógica y Computación
    BACKGROUND: The World Health Organization declared the ongoing Zika virus (ZIKV) epidemic in the Americas a Public Health Emergency of International Concern on February 1, 2016. ZIKV disease in humans is characterized by a "dengue-like" syndrome including febrile illness and rash. However, ZIKV infection in early pregnancy has been associated with severe birth defects, including microcephaly and other developmental issues. Mechanistic models of disease transmission can be used to forecast trajectories and likely disease burden but are currently hampered by substantial uncertainty on the epidemiology of the disease (e.g., the role of asymptomatic transmission, generation interval, incubation period, and key drivers). When insight is limited, phenomenological models provide a starting point for estimation of key transmission parameters, such as the reproduction number, and forecasts of epidemic impact. METHODS: We obtained daily counts of suspected Zika cases by date of symptoms onset from the Secretary of Health of Antioquia, Colombia during January-April 2016. We calibrated the generalized Richards model, a phenomenological model that accommodates a variety of early exponential and sub-exponential growth kinetics, against the early epidemic trajectory and generated predictions of epidemic size. The reproduction number was estimated by applying the renewal equation to incident cases simulated from the fitted generalized-growth model and assuming gamma or exponentially-distributed generation intervals derived from the literature. We estimated the reproduction number for an increasing duration of the epidemic growth phase. RESULTS: The reproduction number rapidly declined from 10.3 (95% CI: 8.3, 12.4) in the first disease generation to 2.2 (95% CI: 1.9, 2.8) in the second disease generation, assuming a gamma-distributed generation interval with the mean of 14 days and standard deviation of 2 days. The generalized-Richards model outperformed the logistic growth model and provided forecasts within 22% of the actual epidemic size based on an assessment 30 days into the epidemic, with the epidemic peaking on day 36. CONCLUSION: Phenomenological models represent promising tools to generate early forecasts of epidemic impact particularly in the context of substantial uncertainty in epidemiological parameters. Our findings underscore the need to treat the reproduction number as a dynamic quantity even during the early growth phase, and emphasize the sensitivity of reproduction number estimates to assumptions on the generation interval distribution.