Exploratory space-time analysis of reported dengue cases during an outbreak in Florida, Puerto Rico, 1991-1992.

TLDR

GIS technologies offer potential for dengue surveillance, though surveillance data limitations constrain spatial analyses. The study mapped 377 laboratory‑confirmed dengue cases in Florida, Puerto Rico, using GIS, generating weekly case maps and applying K‑function, Barton and David, and Knox tests to assess spatial clustering and spatio‑temporal patterns. Rapid epidemic spread over seven weeks, with significant household clustering within three days, yet overall spatial patterns mirrored the population distribution, indicating that control should target entire municipalities rather than only surrounding houses.

Abstract

The spatial and temporal distributions of dengue cases reported during a 1991-1992 outbreak in Florida, Puerto Rico (population = 8,689), were studied by using a Geographic Information System. A total of 377 dengue cases were identified from a laboratory-based dengue surveillance system and georeferenced by their residential addresses on digital zoning and U.S. Geological Survey topographic maps. Weekly case maps were generated for the period between June and December 1991, when 94.2% of the dengue cases were reported. The temporal evolution of the epidemic was rapid, affecting a wide geographic area within seven weeks of the first reported cases of the season. Dengue cases were reported in 217 houses; of these 56 (25.8%) had between two and six reported cases. K-function analysis was used to characterize the spatial clustering patterns for all reported dengue cases (laboratory-positive and indeterminate) and laboratory-positive cases alone, while the Barton and David and Knox tests were used to characterize spatio-temporal attributes of dengue cases reported during the 1991-1992 outbreak. For both sets of data significant case clustering was identified within individual households over short periods of time (three days or less), but in general, the cases had spatial pattern characteristics much like the population pattern as a whole. The rapid temporal and spatial progress of the disease within the community suggests that control measures should be applied to the entire municipality, rather than to the areas immediately surrounding houses of reported cases. The potential for incorporating Geographic Information System technologies into a dengue surveillance system and the limitations of using surveillance data for spatial studies are discussed.