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http://hdl.handle.net/11422/26731
| Type: | Dissertação |
| Title: | A multivariate approach for correcting reporting delas in infectious disease surveillance |
| Author(s)/Inventor(s): | Santos, Guilherme dos |
| Advisor: | Gonçalves, Kelly Cristina Mota |
| Co-advisor: | Bastos, Leonardo Soares |
| Abstract: | Frequentemente, o monitoramento em tempo real de epidemias enfrenta um problema preocupante: os atrasos na notificação de casos e mortes. Esses atrasos podem ocorrer devido a problemas logísticos, confirmação laboratorial e outros motivos. A habilidade de corrigir esses atrasos é essencial para a tomada de decisões com o objetivo de conter uma epidemia. Em alguns casos, a epidemia pode estar associada a mais de uma doença, como é o caso de dengue e chikungunya, por exemplo. Neste trabalho, propomos um modelo multivariado para corrigir os atrasos de notificação e acomodar os casos como dengue e chikungunya. O modelo é estimado usando o método INLA (Integrated Nested Laplace Approximation) com o objetivo de obter resultados mais rapidamente. |
| Abstract: | Frequently, real-time tracking of epidemics is faced with a concerning issue, the reporting delays of cases and deaths. Delays might occur due to logistical problems, laboratory confirmation, and other reasons. Being able to correct the delay is essential to decision making with the goal of containing an epidemic. In some cases, the epidemic might be associated with more than one disease, Dengue and Chikungunya are common examples of this phenomenon. We propose a multivariate model to correct reporting delays and accommodate the above-mentioned cases. The model is estimated using the Integrated Nested Laplace Approximation method with the aim of providing faster results. |
| Keywords: | Inferência bayesiana Dengue Chikungunya Bayesian inference |
| Subject CNPq: | CNPQ::CIENCIAS EXATAS E DA TERRA::PROBABILIDADE E ESTATISTICA |
| Program: | Programa de Pós-Graduação em Estatística |
| Production unit: | Instituto de Matemática |
| Publisher: | Universidade Federal do Rio de Janeiro |
| Issue Date: | 3-Apr-2023 |
| Publisher country: | Brasil |
| Language: | eng |
| Right access: | Acesso Aberto |
| Appears in Collections: | Estatística |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| GSantos.pdf | 2.71 MB | Adobe PDF | View/Open |
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