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Intra- and interseasonal autoregressive prediction of dengue outbreaks using local weather and regional climate for a tropical environment in Colombia.

Eastin MD, Delmelle E, Casas I, Wexler J, Self C - Am. J. Trop. Med. Hyg. (2014)

Bottom Line: Dengue fever transmission results from complex interactions between the virus, human hosts, and mosquito vectors-all of which are influenced by environmental factors.Time series of epidemiological and meteorological data for the urban environment of Cali, Colombia are analyzed from January of 2000 to December of 2011.Significant dengue outbreaks generally occur during warm-dry periods with extreme daily temperatures confined between 18°C and 32°C--the optimal range for mosquito survival and viral transmission.

View Article: PubMed Central - PubMed

Affiliation: Department of Geography and Earth Sciences, University of North Carolina, Charlotte, North Carolina; Department of Social Sciences, Louisiana Tech University, Ruston, Louisiana mdeastin@uncc.edu.

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Reported and predicted interseasonal dengue incidence rates from 2001 to 2011. The reported population-adjusted monthly dengue incidence rates (DPOP) for Cali during the model development period (2001–2010) are shown by vertical light grey lines, whereas reported rates during the model verification period (2011) are denoted by vertical medium grey lines. Also shown are monthly predictions by the best interseasonal autoregressive model not using weather parameters (model 3; dashed dark grey) and the best model using lagged weather parameters (model 4; solid black) during both subperiods. The thin dashed black lines denote the 95% confidence interval for model 4 during the verification period.
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Figure 8: Reported and predicted interseasonal dengue incidence rates from 2001 to 2011. The reported population-adjusted monthly dengue incidence rates (DPOP) for Cali during the model development period (2001–2010) are shown by vertical light grey lines, whereas reported rates during the model verification period (2011) are denoted by vertical medium grey lines. Also shown are monthly predictions by the best interseasonal autoregressive model not using weather parameters (model 3; dashed dark grey) and the best model using lagged weather parameters (model 4; solid black) during both subperiods. The thin dashed black lines denote the 95% confidence interval for model 4 during the verification period.

Mentions: Figure 8 shows the reported and model 3-predicted DPOP during the development (2001–2010) period. Overall, the model performed well (R2 = 0.846), but again, it significantly underpredicted dengue incidence just before and during the three most severe outbreaks. Next, all possible combinations of the potential interseasonal meteorological predictors were fitted with an AR(1) model using transfer functions (24 total models) and evaluated. Performance statistics are shown in Table 6 for the best model (hereafter model 4), which incorporates RHAVG, L18DAYS, and N4 information based on initial 4- to 6-month lags. The full prediction (transfer) equation is


Intra- and interseasonal autoregressive prediction of dengue outbreaks using local weather and regional climate for a tropical environment in Colombia.

Eastin MD, Delmelle E, Casas I, Wexler J, Self C - Am. J. Trop. Med. Hyg. (2014)

Reported and predicted interseasonal dengue incidence rates from 2001 to 2011. The reported population-adjusted monthly dengue incidence rates (DPOP) for Cali during the model development period (2001–2010) are shown by vertical light grey lines, whereas reported rates during the model verification period (2011) are denoted by vertical medium grey lines. Also shown are monthly predictions by the best interseasonal autoregressive model not using weather parameters (model 3; dashed dark grey) and the best model using lagged weather parameters (model 4; solid black) during both subperiods. The thin dashed black lines denote the 95% confidence interval for model 4 during the verification period.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4155567&req=5

Figure 8: Reported and predicted interseasonal dengue incidence rates from 2001 to 2011. The reported population-adjusted monthly dengue incidence rates (DPOP) for Cali during the model development period (2001–2010) are shown by vertical light grey lines, whereas reported rates during the model verification period (2011) are denoted by vertical medium grey lines. Also shown are monthly predictions by the best interseasonal autoregressive model not using weather parameters (model 3; dashed dark grey) and the best model using lagged weather parameters (model 4; solid black) during both subperiods. The thin dashed black lines denote the 95% confidence interval for model 4 during the verification period.
Mentions: Figure 8 shows the reported and model 3-predicted DPOP during the development (2001–2010) period. Overall, the model performed well (R2 = 0.846), but again, it significantly underpredicted dengue incidence just before and during the three most severe outbreaks. Next, all possible combinations of the potential interseasonal meteorological predictors were fitted with an AR(1) model using transfer functions (24 total models) and evaluated. Performance statistics are shown in Table 6 for the best model (hereafter model 4), which incorporates RHAVG, L18DAYS, and N4 information based on initial 4- to 6-month lags. The full prediction (transfer) equation is

Bottom Line: Dengue fever transmission results from complex interactions between the virus, human hosts, and mosquito vectors-all of which are influenced by environmental factors.Time series of epidemiological and meteorological data for the urban environment of Cali, Colombia are analyzed from January of 2000 to December of 2011.Significant dengue outbreaks generally occur during warm-dry periods with extreme daily temperatures confined between 18°C and 32°C--the optimal range for mosquito survival and viral transmission.

View Article: PubMed Central - PubMed

Affiliation: Department of Geography and Earth Sciences, University of North Carolina, Charlotte, North Carolina; Department of Social Sciences, Louisiana Tech University, Ruston, Louisiana mdeastin@uncc.edu.

Show MeSH
Related in: MedlinePlus