Bloque 1

Viernes 29 enero 2020 (9:15 – 11:45am)

Modera: Pedro Gajardo / Fernando Mardones, Universidad Técnica Federico Santa María / Pontificia Universidad Católica de Chile

9:15 – 9:45 Forecasting COVID-19 Chile’s second outbreak by a generalized SIR model with constant time delays and a fitted positivity rate

Expositor: Patricio Cumsille ( Facultad de Ciencias, Universidad del Biobio; Centro de Biotecnología y Bioingeniería Universidad de Chile

Resumen: The COVID-19 disease has forced countries to make a considerable collaborative effort between scientists and governments to provide indicators to suitable follow-up the pandemic’s consequences. Mathematical modeling plays a crucial role in quantifying indicators describing diverse aspects of the pandemic. Consequently, this work aims to develop a clear, efficient, and reproducible methodology for parameter optimization, whose implementation is illustrated using data from three representative regions from Chile and a suitable generalized SIR model together with a fitted positivity rate. Our results reproduce the general trend of the infected’s curve, distinguishing the reported and real cases. Finally, our methodology is robust, and it allows us to forecast a second outbreak of COVID-19 and the infection fatality rate of COVID-19 qualitatively according to the reported dead cases.

9:45 – 10:15 · Desarrollo de un modelo lagrangeano de tiempos de residencia y riesgos en ambientes y clases para covid19 en la RM con información EOD

Expositor: Tabita Catalán ( DIM/CMM Universidad de Chile

Co-autores: Axel Osses (CMM-UCh), Carla Castillo (UDD), Héctor Ramírez (CMM-UCh), Pedro Gajardo (UTFSM)

Resumen: Se diseña y se genera información y modelación para desarrollar un modelo lagrangeano de tipo SEIR usando tiempos de residencia y riesgos por ambientes y clases. Los ambientes y clases son seleccionados inspirándose en la estructura de las encuestas origen-destino EOD. El modelo es aplicado para evaluar estrategias de salida y rebrotes de covid19 en el caso de la Región Metropolitana de Santiago. La metodología permite parametrizar el plan paso a paso y modelar situaciones que otros modelos no permiten como uso de mascarillas en el transporte público, riesgo en comercio y áreas de esparcimiento, reducción de trabajo/estudio presencial, etc. El mismo estudio puede extenderse a otras regiones donde esté disponible la encuesta origen-destino y pueden actualizarse sus parámetros con la actualización de la encuesta.

10:15 – 10:45 · Una estimación de la seroprevalencia del Covid-19 en Chile

Expositor: Antoine Brault ( DIM/CMM Universidad de Chile

Resumen: Actualmente, no hay estudio de seroprevalencia publicado para determinar el porcentaje de personas que se han infectado con el Covid-19 en Chile. Utilizamos los datos de muertos y de hospitalizados para estimar esta proporción por regiones.

10:45 – 11:15 · Assessing the short-run effects of lockdown policies on economic activity, with an application to the Santiago Metropolitan Region, Chile

Expositor: Constanza Fosco ( Centro de Investigación para la Gestión Integrada del Riesgo de Desastres (CIGIDEN), Grupo Interdisciplinar de Sistemas Complejos (GISC), Universidad Carlos III, Madrid

Co-autores: Felipe Zurita, CIGIDEN e Instituto de Economía UC

Resumen: This paper develops a methodology for the assessment of the short-run effects of lockdown policies on economic activity. The methodology combines labor market data with simulation of an agent-based model. We apply our methodology to the Santiago Metropolitan Region, Chile. We recover the model parameters from observed data, taking into account the recurring policy adjustments that characterized the study window. The model is used to build counterfactual scenarios. We estimate an 8 percent output loss in the first 5 months of the pandemic from the policy that was put in place, achieving a 56 percent reduction in the total number of infections. At the same time, with an output loss to 10.5 percent of GDP, the drop in infections would have reached 92 percent.

11:15 – 11:45 · Sobre la asociación entre nivel socioeconómico, edad y letalidad en el Gran Santiago

Expositor: Gonzalo Mena (, Department of Statistics, University of Oxford, UK

Co-autores: Pamela P. Martinez, Ayesha S. Mahmud, Pablo A. Marquet, Caroline O. Buckee,  Mauricio Santillana. Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan, School of Public Health, Boston, Massachusetts, US; Department of Microbiology, University of Illinois at Urbana Champaign, Illinois, US; Department of Statistics, University of Illinois at Urbana Champaign, Illinois, US; Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana Champaign, Illinois, US;  Department of Demography, University of California Berkeley, US; Departamento de Ecologıa, Facultad de Ciencias Biologicas, Pontificia Universidad Catolica de Chile, Chile; Instituto de Ecolog´ıa y Biodiversidad (IEB), Chile; The Santa Fe Institute, Santa Fe, New Mexico, US; Instituto de Sistema Complejos de Valparaıso (ISCV), Valparaıso, Chile; Centro de Cambio Global UC, Pontificia Universidad Catolica de Chile, Santiago, Chile; Computational Health Informatics Program, Boston Children’s Hospital, US; Department of Pediatrics, Harvard Medical School, US.

Resumen: The current coronavirus disease 2019 (COVID-19) pandemic has impacted dense urban populations particularly hard. Here, we provide an in-depth characterization of disease incidence and mortality patterns, and their dependence on demographic and socioeconomic strata in Santiago, a highly segregated city and the capital of Chile. We find that among all age groups, there is a strong association between socioeconomic status and both mortality –measured either by direct COVID-19 attributed deaths or excess deaths– and public health capacity. Specifically, we show that behavioral factors like human mobility, as well as health system factors such as testing volumes, testing delays, and test positivity rates are associated with disease outcomes. These robust patterns suggest multiple possibly interacting pathways that can explain the observed disease burden and mortality differentials: (i) in lower socioeconomic status municipalities, human mobility was not reduced as much as in more affluent municipalities; (ii) testing volumes in these locations were insufficient early in the pandemic and public health interventions were applied too late to be effective; (iii) test positivity and testing delays were much higher in less affluent municipalities, indicating an impaired capacity of the health-care system to contain the spread of the epidemic; and (iv) infection fatality rates appear much higher in the lower end of the socioeconomic spectrum. Together, these findings highlight the exacerbated consequences of health-care inequalities in a large city of the developing world, and provide practical methodological approaches useful for characterizing COVID-19 burden and mortality in other segregated urban centers.


Bloque 2

Viernes 29 enero 2020 (12:00 – 14:30)

Modera: Mauricio Lima / Eduardo Undurraga Pontificia Universidad Católica de Chile

12:00 – 12:30 · On the effectiveness of communication strategies as non-pharmaceutical interventions to tackle epidemics

Expositora: Alejandro Bernardin (, Computational Biology Lab, Fundación Ciencia & Vida

Co-autores: Alejandro Martinez, Tomas Perez-Acle. Computational Biology Lab, Fundación Ciencia & Vida; Centro Interdisciplinario de Neurociencia de Valparaíso, Universidad de Valparaíso; Facultad de Ingeniería y Tecnología, Universidad San Sebastián

Resumen: In this work we show how communication strategies, both global and local, can affect the spread of an infectious disease. To do so, we implemented an agent-based simulation coupling infectious and information dynamics. As a result, we show the importance of informing the population on a daily basis highlighting the role that communication between people plays during the pandemic.

12:30 – 13:00 ·Assessing the effects of rapid testing and quarantine on the dynamics of the COVID-19 pandemic

Expositor: Samuel Ropert (, Computational Biology Lab, Fundación Ciencia & Vida

Co-autores: Alejandro Bernardin, Tomas Perez-Acle. Computational Biology Lab, Fundación Ciencia & Vida; Centro Interdisciplinario de Neurociencia de Valparaíso, Universidad de Valparaíso; Facultad de Ingeniería y Tecnología, Universidad San Sebastián

Resumen: In this work we studied the influence of non-pharmaceutical interventions relying on rapid testing and quarantine, on the dynamics of the COVID-19 pandemic. To do so, we developed a set of SEIR-TQ computational models using both ODEs and an agent-based model. Our models suggest that iterative testing over 10% of the population could effectively suppress the spread of COVID-19. Moreover, using this strategy, a drastic reduction in the number of superspreaders can also be achieved. The importante of the delay between testing and quarantine is strongly enforced.

13:00 – 13:30 · Análisis no-lineal de la dinámica del SARS-CoV-2

Expositora: Ignacio Acevedo (, DIM/CMM Universidad de Chile

Co-autores: Javier Monreal, Alejandro Maass, CMM Universidad de Chile, Mauricio Canals, Escuela de Salud Pública, Universidad de Chile

Resumen: Estudiamos y analizamos el grado de complejidad de la dinámica generada por la actual pandemia del COVID19. Se emplean diferentes métodos no-lineales para caracterizar el atractor y la caoticidad del sistema, obteniendo interesantes resultados para distintos grupos de poblaciones.

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13:30 – 14:00 · Iniciativa SHIELD y la dinamica viral de SARS-CoV-2

Expositora: Pamela Martinez (, University of Illinois at Urbana Champaign, Illinois, US; Harvard T.H. Chan School of Public Health

Co-autores: Rebecca Smith, Christopher Brooke, University of Illinois at Urbana Champaign

Resumen: Entender la dinámica viral de SARS-CoV-2 dentro del huésped es fundamental para poder evaluar diferentes métodos de detección del virus. La Universidad de Illinois ha implementado un estudio longitudinal para poder evaluar la respuesta de tres tipos de tests en el tiempo: PCR nasal, PCR de saliva, y tests antigénicos. Mostrare resultados preliminares de este estudio y las consecuencias para una detección masiva y temprana de SARS-CoV-2.

14:00 – 14:30 · Sobre una ley dinámica para la tasa de contagio

Expositor: Fernando Cordova (, Universidad Católica del Maule

Resumen A un modelo por compartimentos tipo SEIR se le suma una ecuación para la tasa de contagio. Algunos patrones de primeras olas, mesetas y segunda o terceras olas en la curva de activos son observandos. Además, se presenta una hiper sensibilidad a ciertos parámetros sociales.