Estimating and forecasting the burden and spread of SARS-CoV2 first wave in Colombia

Following the rapid dissemination of COVID-19 cases in Colombia in 2020, large-scale nonpharmaceutical 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-RecoveredDiseased) 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...

• Autores: Cascante Vega, Jaime Enrique
• Fecha de publicación: 2020
• Institución: Universidad de los Andes
• Repositorio: Séneca: repositorio Uniandes
• Idioma: eng
• OAI Identifier: oai:repositorio.uniandes.edu.co:1992/50947
• Acceso en línea: http://hdl.handle.net/1992/50947
• Palabra clave: COVID-19 (Enfermedad); Pandemias; Ingeniería
• Rights: openAccess
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/