Browsing by Autor "Juan Manuel Cordovez"

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Causal Inference Unveils How Forest Coverage Mitigates Excess of Snakebite Cases During Rainfall Seasons in Colombia
(RELX Group (Netherlands), 2025) Juan Manuel Gutiérrez; Carlos Bravo-Vega; Juan Manuel Cordovez
Estimating and forecasting the burden and spread of SARS-CoV2 first wave in Colombia
(2021) Jaime E. Cascante Vega; Juan Manuel Cordovez; Mauricio Santos‐Vega
A bstract Following the rapid dissemination of COVID-19 cases in Colombia in 2020, large-scale non-pharmaceutical interventions (NPIs) were implemented as national emergencies in most of the municipalities of the country starting by a lockdown on March 20th of 2020. Using combinations of meta-population models SEAIIRD (Susceptible-Exposed-Asymptomatic-Infected-Recovered-Diseased) which describes the disease dynamics in the different localities, with movement data that accounts for the number of commuters between units and statistical inference algorithms could be an effective approach to both nowcast and forecast the number of cases and deaths in the country. Here we used an iterated filtering (IF) framework to fit the parameters of our model to the reported data across municipalities from march to late October in locations with more than 50 reported deaths and cases historically. Since the model is high dimensional (6 state variable by municipality) inference on those parameters is highly non-trivial, so we used an Ensemble-Adjustment-Kalman-Filter (EAKF) to estimate time variable system states and parameters. Our results show that the model is capable of capturing the evolution of the outbreak in the country and providing estimates of the epidemiological parameters in time. These estimates could become the base for planning future interventions as well as evaluate the impact of NPIs on the effective reproductive number (ℛ eff ) and the key epidemiological parameters, such as the contact rate or the reporting rate. Our approach demonstrates that real-time, publicly available ensemble forecasts can provide robust short-term predictions of reported COVID-19 deaths in Colombia. This model has the potential to be used as a forecasting and prediction tool to evaluate disease dynamics and to develop a real time surveillance system for management and control.
Estudio sobre los efectos de virtualizar el campus como estrategia para minimizar los contagios por SARS-COV-2 producidos en los espacios académicos
(Universidad de Los Andes, 2020) Juan Manuel Cordovez
The effect of non-pharmacological interventions to contain the spread of SARS-CoV-2 have caused negative impacts, especially in education. Re-opening schools and universities is regarded as a high risk scenario. This paper seeks to understand, with the help of mathematical modeling, possible mechanisms through which the virus could spread in an academic environment and to quantify contagions attributable to participating in academic activities. To simulate the dynamics of contagion at the University, an agent-based mathematical model that incorporated stochastic differential equations was built using academic data for the University´s 2020-2 semester. The model suggests that hybrid-attendance combined with epidemiological surveillance can produce very safe operating conditions without significantly contributing towards more COVID infections in the city of Bogotá.
Mathematical model of oncolytic virotherapy with Myxoma virus infection in cancer cells
(Wiley, 2020) Sofia Ortegon; Lina S. Franco; Grant McFadden; Juan Manuel Cordovez
Oncolytic virotherapy is an innovative alternative to more conventional cancer therapies that is based on the ability of oncolytic viruses to specifically target and kill tumor cells. This therapy can activate the innate and adaptive immune response of the body achieving the destruction of cancer cells by the immune system. Myxoma virus is a poxvirus that infects in European rabbits, can also replicate in a variety of human cancer cells lines, which makes it an ideal candidate for oncolytic virotherapy. However, the dynamic mechanisms between the virus and the cancer cells are not completely understood. Mathematical models are useful tools to provide relevant insights about the dynamics that govern the interplay between normal and cancer cells and their viral parasites. In this study murine melanoma cancer cells were infected with a Myxoma virus expressing GFP (vMyx GFP) at low multiplicity of infection and pictures were taken in a fluorescence microscope every 30 minutes to determine infected cells. To understand the process of infection, namely the susceptible to infected conversion rates and the spatial effects of cell culture, we developed a mathematical model parameterized with the experiments described above that spatially explicitly simulates the process of infection. The model is an stochastic spatially explicit SI formulation that considers cancer cells and viral particles. With the model we were able to quantify and better understand this complex network of interactions. We were able to estimate important parameters concerning infection, proliferation and spatial dependency. We hope that the model will contribute to accelerate the development of a functional and effective oncolytic virotherapy with Myxoma virus. Support or Funding Information Office of the vice‐presidency of research at los Andes University
Ventilation‐perfusion ratio: A Mathematical Approach for Gas Exchange in the Lungs
(Wiley, 2019) Alejandro Pizano; Paola Calvacci; Felipe Girón; Juan Manuel Cordovez
Chronic pulmonary diseases and respiratory infections remained as one of the most morbid and deadliest diseases in the world. Airway and environment play an important role in the etiology of these pathologies. The balance between oxygen and carbon dioxide exchange is the pillar of the respiratory system. The ventilation ‐ perfusion ratio (VPR) determines the efficiency of gas exchange in different areas of the lung. For a long time the lung was assumed to be divided in three regions that would have homogenous VPR. Recently it was established that the VPR changes in a more heterogeneous fashion. The aim of this project is to understand the gas exchange in each alveoli using a mathematical model that produce the VPR architecture based on airways architecture. The model assumed mass balance, the ideal gas law and diffusional forces. Parameters for the model were determined according to data obtained in the literature and their correspondent mathematical calculus. The model was implemented in MATLAB (The MathWorks®, Inc.)and the equations were solved to steady state. The model predicted gas concentrations and flows in different lung segments. We were able to model healthy an pathological situations. In addition, we also simulated environmental influence in the small airways. The mathematical model was helpful to understand the gas exchange dynamics. It could be used to predict the interaction between ventilation and perfusion under different conditions, giving the possibility to estimate the efficacy of medical intervention. It can also shed some light on how to prevent anddecrease the incidence of lung diseases. Support or Funding Information Department of Biomedical Engineering, Universidad de los Andes, Bogota, Colombia This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .