9 research outputs found
Mean annual and monthly <i>Aedes albopictus</i> eggs abundance projected by the forecasting model over the period 2009–2013 for the three regions located in the southern (region A), middle (region B) and northern part (region C) of Balkan countries.
<p>The central statistics (percentile p50) and the associated error bars (percentiles p10 and p90) of each barplot were calculated from 100 bootstrap models projections, averaged over the three regions of interest.</p
Goodness-of-fit assessment for the forecasting model applied to the validation and calibration sites, based on 100 bootstrap model projections.
<p>a) according to the monitoring week of the year and b) according to the week of model initialization.</p
Forecasting the spatial and seasonal dynamic of <i>Aedes albopictus</i> oviposition activity in Albania and Balkan countries
<div><p>The increasing spread of the Asian tiger mosquito, <i>Aedes albopictus</i>, in Europe and US raises public health concern due to the species competence to transmit several exotic human arboviruses, among which dengue, chikungunya and Zika, and urges the development of suitable modeling approach to forecast the spatial and temporal distribution of the mosquito. Here we developed a dynamical species distribution modeling approach forecasting <i>Ae</i>. <i>albopictus</i> eggs abundance at high spatial (0.01 degree WGS84) and temporal (weekly) resolution over 10 Balkan countries, using temperature times series of Modis data products and altitude as input predictors. The model was satisfactorily calibrated and validated over Albania based observed eggs abundance data weekly monitored during three years. For a given week of the year, eggs abundance was mainly predicted by the number of eggs and the mean temperature recorded in the preceding weeks. That is, results are in agreement with the biological cycle of the mosquito, reflecting the effect temperature on eggs spawning, maturation and hatching. The model, seeded by initial egg values derived from a second model, was then used to forecast the spatial and temporal distribution of eggs abundance over the selected Balkan countries, weekly in 2011, 2012 and 2013. The present study is a baseline to develop an easy-handling forecasting model able to provide information useful for promoting active surveillance and possibly prevention of <i>Ae</i>. <i>albopictus</i> colonization in presently non-infested areas in the Balkans as well as in other temperate regions.</p></div
Statistical model selection for the Core, Init and Max modeling components, based on based on Akaike information criterion (AIC), Spearman correlation coefficient (COR), root mean square error (RMSE) and dispersion parameter (DISP).
<p>Statistical model selection for the Core, Init and Max modeling components, based on based on Akaike information criterion (AIC), Spearman correlation coefficient (COR), root mean square error (RMSE) and dispersion parameter (DISP).</p
Location of the sampling sites.
<p>a) 16 sites used for model calibration are located in Middle Albania (Tirana-Dajti mount); b) 10 sites used for model validation are located in North Albania (Malesia e Madhe–Vermosh). Information sources are open source information from: <a href="http://asig.gov.al/" target="_blank">http://asig.gov.al/</a> <a href="https://landsatlook.usgs.gov/viewer.html" target="_blank">https://landsatlook.usgs.gov/viewer.html</a>.</p
Conditional effects of selected predictors (x-axis) on the egg abundances (y-axis) in the the final Core zero-inflated negative binomial model.
<p>Conditional effects of selected predictors (x-axis) on the egg abundances (y-axis) in the the final Core zero-inflated negative binomial model.</p
Spatial and temporal experimental semi-variograms calculated from the final Core model residuals, highlighting low autocorrelation in model residuals (the black line indicated the smoothed trend).
<p>Spatial and temporal experimental semi-variograms calculated from the final Core model residuals, highlighting low autocorrelation in model residuals (the black line indicated the smoothed trend).</p
Parameters, standard deviation and significance for the best Core (zero inflated negative binomial model; zeroinf-nb), Init (GLM negative binomial model; glm-nb) and Max models (GLM negative binomial model; glm-nb).
<p>Parameters, standard deviation and significance for the best Core (zero inflated negative binomial model; zeroinf-nb), Init (GLM negative binomial model; glm-nb) and Max models (GLM negative binomial model; glm-nb).</p
Annual mean percentiles of 10% (p10), 50% (p50) and 90% (p90) of <i>Aedes albopictus</i> eggs abundance projected by the forecasting model over Balkan countries in year 2012.
<p>The darker the color the more projected abundance by the model.</p