Population dynamics of Aedes aegypti and dengue as influenced by weather and human behavior in San Juan, Puerto Rico

Abstract

Previous studies on the influence of weather on Aedes aegypti dynamics in Puerto Rico suggested that rainfall was a significant driver of immature mosquito populations and dengue incidence, but mostly in the drier areas of the island. We conducted a longitudinal study of Ae. aegypti in two neighborhoods of the metropolitan area of San Juan city, Puerto Rico where rainfall is more uniformly distributed throughout the year. We assessed the impacts of rainfall, temperature, and human activities on the temporal dynamics of adult Ae. aegypti and oviposition. Changes in adult mosquitoes were monitored with BG-Sentinel traps and oviposition activity with CDC enhanced ovitraps. Pupal surveys were conducted during the drier and wetter parts of the year in both neighborhoods to determine the contribution of humans and rains to mosquito production. Mosquito dynamics in each neighborhood was compared with dengue incidence in their respective municipalities during the study. Our results showed that: 1. Most pupae were produced in containers managed by people, which explains the prevalence of adult mosquitoes at times when rainfall was scant; 2. Water meters were documented for the first time as productive habitats for Ae. aegypti; 3. Even though Puerto Rico has a reliable supply of tap water and an active tire recycling program, water storage containers and discarded tires were important mosquito producers; 4. Peaks in mosquito density preceded maximum dengue incidence; and 5. Ae. aegypti dynamics were driven by weather and human activity and oviposition was significantly correlated with dengue incidence.

Figure 1. Map of the study areas.

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.

Figure 2. Weather variables at Muñoz-Marin International Airport in 2008, San Juan, Puerto Rico.

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.

Figure 3. Aedes aegypti pupae per type of container.

Percentage of all pupae found in pupal surveys conducted during the “drier” (Panel A) and rainy (Panel B) periods, respectively, in neighborhoods “El Comandante” (EC) and “Villa Carolina” (VC), San Juan city, Puerto Rico. Numbers on top of bars indicate how many containers of each type were found with pupae.

Figure 4. Temporal changes in rainfall, mosquitoes, and dengue.

Panel A shows changes in adjusted rainfall (mm), number of Aedes aegypti 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.

Figure 5. Relationships between mosquitoes and rainfall.

Panel A presents the number of female Ae. aegypti 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.

Figure 6. Relationships between dengue incidence and mosquitoes.

Panel A presents dengue incidence (cases per 100000 inhabitants) as a function of the number of female Ae. aegypti 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.