1 / 14

A. Townsend Peterson, Carmen Martinez-Campos, Yoshinori Nakazawa, Enrique Martinez-Meyer

Time-specific ecological niche modeling predicts spatial dynamics of vector insects and human dengue cases. A. Townsend Peterson, Carmen Martinez-Campos, Yoshinori Nakazawa, Enrique Martinez-Meyer.

more
Download Presentation

A. Townsend Peterson, Carmen Martinez-Campos, Yoshinori Nakazawa, Enrique Martinez-Meyer

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Time-specific ecological niche modeling predicts spatial dynamics of vector insects and human dengue cases A. Townsend Peterson, Carmen Martinez-Campos, Yoshinori Nakazawa, Enrique Martinez-Meyer Peterson, A. T., C. Martínez-Campos, Y. Nakazawa, and E. Martínez-Meyer. 2005. Time-specific ecological niche modeling predicts spatial dynamics of vector insects and human dengue cases. Transactions of the Royal Society of Tropical Medicine and Hygiene 99:647-655.

  2. Dengue Is caused by a virus from the genus Flavovirus. Transmitted by a mosquito (Aedes aegypti). Tropical and subtropical regions of the world. Create time specific ecological niche models that help us understand the spatial and temporal dynamics of the mosquitoes. Predict future outbreaks.

  3. Data Mosquitoes Point-occurrence of Aedes aegypti drawn from larval surveys (Laboratorio de Entomologia, InDRE) Monthly samples from eastern and southern Mexico. Data from April to December 1995. InDRE: Instituto de Diagnostico y Referencia Epidemiologica.

  4. Environmental data Monthly maximum value composites of NDVI for 1995. From AVHRR. Topographic variables from USGS Hydro-1k: DEM, slope, aspect and topographic index.

  5. Methods All points all NDVI

  6. Methods MODIS NDVI Data1 Month1 Model1 Data2 Month2 Model2 DATA Data3 Month3 Model3 Data4 Month4 Model4 Data5 Month5 Model5 Include information about conditions from previous months: NDVI(t) - NDVI(t-1) NDVI(t) - NDVI(t-2)

  7. Time specific predictions Time specific model

  8. Methods: Transmission cycle Human case data drawn from cases tested by InDRE. • Incubation in mosquito • Infection of human • Incubation in human • 7 days for taking sera after onset of symptoms. • (Total: 18days)

  9. Methods: Future • Models for each month • Models projected to all other months • Average of models from two previous months (t-1 and t-2) projected to the current (t) • June  August • July  August • Overlay of occurrences (t) • August • Evaluate predictions

  10. Predict future distribution Average models from previous months

  11. Predict future distribution

  12. Predict future distribution * Strong significance + Marginally significant X Not significant

  13. Predict future outbreaks

  14. Conclusions Time-specific models seem to perform better. Recover the spatial and temporal dynamics of the disease through ENM. Predict areas where an outbreak is more likely to occur. -- Inclusion of human population data/variables.

More Related