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Dengue on islands: a Bayesian approach to understanding the global ecology of dengue viruses.

Feldstein LR, Brownstein JS, Brady OJ, Hay SI, Johansson MA - Trans. R. Soc. Trop. Med. Hyg. (2015)

Bottom Line: Minimum temperature was strongly associated with suitability for DENV transmission.Increased population size and precipitation were associated with increased outbreak frequency, but did not capture all of the variability.Wealth and connectivity, in contrast, had no discernable effects.

View Article: PubMed Central - PubMed

Affiliation: Children's Hospital Informatics Program, Boston Children's Hospital, 1 Autumn St., Boston, MA 02215, USA Center for Statistics and Quantitative Infectious Diseases, Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington; USA.

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pSuit and pSuitpOut estimates for training and testing islands. (A) and (B) show the estimated pSuit (point) and 95% credible interval (line) for each island, in the training and testing datasets, respectively. White points are islands with no known history of dengue outbreaks, blue points are islands with evidence of at least one outbreak. (C) and (D) show the estimated pSuitpOut for each training and testing island, respectively. The colors indicate no outbreaks (white), and an increasing number of consecutive years with outbreaks from 1 (yellow) to 10 (dark green).
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TRV012F3: pSuit and pSuitpOut estimates for training and testing islands. (A) and (B) show the estimated pSuit (point) and 95% credible interval (line) for each island, in the training and testing datasets, respectively. White points are islands with no known history of dengue outbreaks, blue points are islands with evidence of at least one outbreak. (C) and (D) show the estimated pSuitpOut for each training and testing island, respectively. The colors indicate no outbreaks (white), and an increasing number of consecutive years with outbreaks from 1 (yellow) to 10 (dark green).

Mentions: To assess the model's ability to identify suitable islands for dengue transmission we compared pSuit predictions to the data for both training and testing islands (Figures 2 and 3A). Of the 74 training islands with evidence of local surveillance or dengue outbreaks, the model predicted 60 to be suitable and 14 to be unsuitable. Three islands classified as suitable had no evidence of dengue transmission (Figure 3A). Two of these, Badu and Cocos, have small population sizes and thus are unlikely to have observed outbreaks (estimated pObs= 0.27 and 0.23, respectively). The third island, Bahrain, was unique in the dataset as it had a large population and high temperatures, but the lowest humidity and precipitation among any of the islands. None of the islands classified as unsuitable had evidence of dengue outbreaks. The overall accuracy of pSuit for the training islands was 96% (57 of 60 islands predicted to be suitable had observed outbreaks and 14 of 14 islands predicted to be unsuitable had no evidence of transmission).Figure 2.


Dengue on islands: a Bayesian approach to understanding the global ecology of dengue viruses.

Feldstein LR, Brownstein JS, Brady OJ, Hay SI, Johansson MA - Trans. R. Soc. Trop. Med. Hyg. (2015)

pSuit and pSuitpOut estimates for training and testing islands. (A) and (B) show the estimated pSuit (point) and 95% credible interval (line) for each island, in the training and testing datasets, respectively. White points are islands with no known history of dengue outbreaks, blue points are islands with evidence of at least one outbreak. (C) and (D) show the estimated pSuitpOut for each training and testing island, respectively. The colors indicate no outbreaks (white), and an increasing number of consecutive years with outbreaks from 1 (yellow) to 10 (dark green).
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4401210&req=5

TRV012F3: pSuit and pSuitpOut estimates for training and testing islands. (A) and (B) show the estimated pSuit (point) and 95% credible interval (line) for each island, in the training and testing datasets, respectively. White points are islands with no known history of dengue outbreaks, blue points are islands with evidence of at least one outbreak. (C) and (D) show the estimated pSuitpOut for each training and testing island, respectively. The colors indicate no outbreaks (white), and an increasing number of consecutive years with outbreaks from 1 (yellow) to 10 (dark green).
Mentions: To assess the model's ability to identify suitable islands for dengue transmission we compared pSuit predictions to the data for both training and testing islands (Figures 2 and 3A). Of the 74 training islands with evidence of local surveillance or dengue outbreaks, the model predicted 60 to be suitable and 14 to be unsuitable. Three islands classified as suitable had no evidence of dengue transmission (Figure 3A). Two of these, Badu and Cocos, have small population sizes and thus are unlikely to have observed outbreaks (estimated pObs= 0.27 and 0.23, respectively). The third island, Bahrain, was unique in the dataset as it had a large population and high temperatures, but the lowest humidity and precipitation among any of the islands. None of the islands classified as unsuitable had evidence of dengue outbreaks. The overall accuracy of pSuit for the training islands was 96% (57 of 60 islands predicted to be suitable had observed outbreaks and 14 of 14 islands predicted to be unsuitable had no evidence of transmission).Figure 2.

Bottom Line: Minimum temperature was strongly associated with suitability for DENV transmission.Increased population size and precipitation were associated with increased outbreak frequency, but did not capture all of the variability.Wealth and connectivity, in contrast, had no discernable effects.

View Article: PubMed Central - PubMed

Affiliation: Children's Hospital Informatics Program, Boston Children's Hospital, 1 Autumn St., Boston, MA 02215, USA Center for Statistics and Quantitative Infectious Diseases, Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington; USA.

Show MeSH
Related in: MedlinePlus