RESUMEN
We determined abundance of Aedes aegypti mosquitoes and presence of dengue virus (DENV) in females collected from premises of laboratory-confirmed dengue patients over a 12-month period (March 2007 to February 2008) in Merida, Mexico. Backpack aspiration from 880 premises produced 1,836 females and 1,292 males indoors (predominantly from bedrooms) and 102 females and 108 males from patios/backyards. The mean weekly indoor catch rate per home peaked at 7.8 females in late August. Outdoor abundances of larvae or pupae were not predictive of female abundance inside the home. DENV-infected Ae. aegypti females were recovered from 34 premises. Collection of DENV-infected females from homes of dengue patients up to 27 days after the onset of symptoms (median, 14 days) shows the usefulness of indoor insecticide application in homes of suspected dengue patients to prevent their homes from becoming sources for dispersal of DENV by persons visiting and being bitten by infected mosquitoes.
Asunto(s)
Aedes/fisiología , Aedes/virología , Virus del Dengue/aislamiento & purificación , Adolescente , Adulto , Animales , Niño , Preescolar , Dengue/epidemiología , Femenino , Vivienda , Humanos , Lactante , Masculino , México/epidemiología , Control de Mosquitos , Densidad de Población , Lluvia , Estaciones del Año , Temperatura , Factores de TiempoRESUMEN
OBJECTIVE: Novel, inexpensive solutions are needed for improved management of vector-borne and other diseases in resource-poor environments. Emerging free software providing access to satellite imagery and simple editing tools (e.g. Google Earth) complement existing geographic information system (GIS) software and provide new opportunities for: (i) strengthening overall public health capacity through development of information for city infrastructures; and (ii) display of public health data directly on an image of the physical environment. METHODS: We used freely accessible satellite imagery and a set of feature-making tools included in the software (allowing for production of polygons, lines and points) to generate information for city infrastructure and to display disease data in a dengue decision support system (DDSS) framework. FINDINGS: Two cities in Mexico (Chetumal and Merida) were used to demonstrate that a basic representation of city infrastructure useful as a spatial backbone in a DDSS can be rapidly developed at minimal cost. Data layers generated included labelled polygons representing city blocks, lines representing streets, and points showing the locations of schools and health clinics. City blocks were colour-coded to show presence of dengue cases. The data layers were successfully imported in a format known as shapefile into a GIS software. CONCLUSION: The combination of Google Earth and free GIS software (e.g. HealthMapper, developed by WHO, and SIGEpi, developed by PAHO) has tremendous potential to strengthen overall public health capacity and facilitate decision support system approaches to prevention and control of vector-borne diseases in resource-poor environments.