SAIFR:2145

Model-data Fusion and Forecasting for Mosquito-borne Diseases

(2020). Model-data Fusion and Forecasting for Mosquito-borne Diseases. ICTP South American Institute for Fundamental Research. https://scivideos.org/index.php/ictp-saifr/2145

Model-data Fusion and Forecasting for Mosquito-borne Diseases. ICTP South American Institute for Fundamental Research, Mar. 04, 2020, https://scivideos.org/index.php/ictp-saifr/2145 

          @misc{ scivideos_SAIFR:2145,
            doi = {},
            url = {https://scivideos.org/index.php/ictp-saifr/2145},
            author = {},
            keywords = {ICTP-SAIFR, IFT, UNESP},
            language = {en},
            title = {Model-data Fusion and Forecasting for Mosquito-borne Diseases},
            publisher = { ICTP South American Institute for Fundamental Research},
            year = {2020},
            month = {mar},
            note = {SAIFR:2145 see, \url{https://scivideos.org/index.php/ictp-saifr/2145}}
          }
Carrie Manore
Talk numberSAIFR:2145
Source RepositoryICTP – SAIFR
Collection
Talk Type Conference
Subject

Abstract

Mosquito-borne diseases have been emerging and re-emerging in the Americas, causing millions of human illnesses. Recent examples include Zika virus and chikungunya. In order to quantify the impact of past outbreaks and predict the course of future outbreaks, it is necessary to merge models with heterogeneous data streams. We present both statistical and mechanistic modeling for mosquito-borne disease spread coupled with data including demographics, internet data, human case counts, weather, and satellite to predict risk. Wehighlight the relative usefulness of our data streams and models depending on the question we are answering and its scale.