Weather variables at Muñoz-Marin International Airport in 2008, San Juan, Puerto Rico.

<p>Panel A shows mean monthly temperature and adjusted temperature. Adjusted temperature is the average of daily mean temperature for 21 days before mosquito sampling. Panel B shows monthly rainfall and adjusted rainfall. Adjusted rainfall is the accumulated rainfall during the third and second weeks before each mosquito sampling, which was conducted every three weeks.</p

Temporal changes in rainfall, mosquitoes, and dengue.

<p>Panel A shows changes in adjusted rainfall (mm), number of <i>Aedes aegypti</i> females per BG-Sentinel trap per day, number of eggs per CDC ovitrap per day, and adjusted dengue incidence (cases per 100000 inhabitants) in “El Comandante” (EC) and Panel B shows these parameters in “Villa Carolina” (VC), San Juan city, Puerto Rico from October 2007 to December 2008.</p

Relationships between mosquitoes and rainfall.

<p>Panel A presents the number of female <i>Ae. aegypti</i> per BG-Sentinel trap per day versus adjusted rainfall (mm) for each sampling date in “El Comandante” (EC) and “Villa Carolina” (VC), San Juan city, Puerto Rico, and Panel B shows the number of eggs per CDC ovitrap per day versus adjusted rainfall in each neighborhood. The corresponding correlation coefficients and Type I error probabilities are presented next to the location.</p

Map of the study areas.

<p>The map shows the municipalities of San Juan city, Puerto Rico and the location of the airport in relation to the two neighborhoods investigated. Each neighborhood is composed of two adjacent census tracts.</p

Composition and abundance of adult mosquito species captured in BG traps.

<p>Composition and abundance of adult mosquito species captured in BG traps.</p

Relationships between dengue incidence and mosquitoes.

<p>Panel A presents dengue incidence (cases per 100000 inhabitants) as a function of the number of female <i>Ae. aegypti</i> per BG-Sentinel trap per day for each sampling date in “El Comandante” (EC) and “Villa Carolina” (VC), San Juan city, Puerto Rico, and Panel B shows dengue incidence as a function of the number of eggs per CDC ovitrap per day in each neighborhood. The corresponding correlation coefficients and Type I error probabilities are presented next to the location.</p

Meteorologically Driven Simulations of Dengue Epidemics in San Juan, PR

<div><p>Meteorological factors influence dengue virus ecology by modulating vector mosquito population dynamics, viral replication, and transmission. Dynamic modeling techniques can be used to examine how interactions among meteorological variables, vectors and the dengue virus influence transmission. We developed a dengue fever simulation model by coupling a dynamic simulation model for <i>Aedes aegypti</i>, the primary mosquito vector for dengue, with a basic epidemiological Susceptible-Exposed-Infectious-Recovered (SEIR) model. Employing a Monte Carlo approach, we simulated dengue transmission during the period of 2010–2013 in San Juan, PR, where dengue fever is endemic. The results of 9600 simulations using varied model parameters were evaluated by statistical comparison (r²) with surveillance data of dengue cases reported to the Centers for Disease Control and Prevention. To identify the most influential parameters associated with dengue virus transmission for each period the top 1% of best-fit model simulations were retained and compared. Using the top simulations, dengue cases were simulated well for 2010 (r² = 0.90, p = 0.03), 2011 (r² = 0.83, p = 0.05), and 2012 (r² = 0.94, p = 0.01); however, simulations were weaker for 2013 (r² = 0.25, p = 0.25) and the entire four-year period (r² = 0.44, p = 0.002). Analysis of parameter values from retained simulations revealed that rain dependent container habitats were more prevalent in best-fitting simulations during the wetter 2010 and 2011 years, while human managed (i.e. manually filled) container habitats were more prevalent in best-fitting simulations during the drier 2012 and 2013 years. The simulations further indicate that rainfall strongly modulates the timing of dengue (e.g., epidemics occurred earlier during rainy years) while temperature modulates the annual number of dengue fever cases. Our results suggest that meteorological factors have a time-variable influence on dengue transmission relative to other important environmental and human factors.</p></div

Ensemble model validation statistics for the top 1% of simulations for San Juan County, PR parameterized for the entire time period (2010–2013) and individual years.

<p>Bold indicates significance at p<0.05 and * indicates significance at p<0.01. O = observed, P = predicted, <i>S</i> = standard deviation, a = slope, b = intercept, MAE = mean average error, RMSE = route-mean-square error, s = systematic, u = unsystematic, d = Willmott’s index of agreement.</p><p>Ensemble model validation statistics for the top 1% of simulations for San Juan County, PR parameterized for the entire time period (2010–2013) and individual years.</p

Simulated and reported weekly total dengue fever cases (2010–2013).

<p>The model ensemble mean (black line) replicated inter-annual variability in reported DF cases (red line) accurately, however, intra-annual variability is not simulated as well. Dashed gray lines are the ensemble minimum and maximum.</p

Conceptual diagram of modeled dengue ecology.

<p>Suns bordering an arrow indicate that the process is temperature dependent and a habitat/container symbol bordering an arrow indicates the process is habitat/precipitation dependent. Water is added to a habitat through precipitation or manual filling and is lost due to spilling and evaporation which is regulated by temperature. After hatching, the mosquitoes develop through their larval and pupal stages before emerging as adults. The adults blood feed, develop eggs, and then lay them in a water habitat. Upon blood feeding, adults can contract the virus from an infectious human. Those mosquitoes can then expose a susceptible human to the virus during a subsequent blood meal.</p