Diseases carried by mosquitoes and other arthropods endanger human health globally. Though costly, surveillance efforts are vital for disease control and prevention This paper describes an approach for strategically configuring targeted disease surveillance sites across a study area. The methodology combines risk index mapping and spatial optimization modelling. The risk index is used to identify demand for surveillance, and the maximum covering location problem is used to select a specified number of candidate surveillance sites that covers the maximum amount of risk. The approach is demonstrated using a case study where optimal locations for sentinel surveillance sites are selected for the purposes of detecting eastern equine encephalitis virus in a county in the state of Florida. Optimal sentinel sites were selected under a number of scenarios that modelled different target populations (horses or humans), coverage distances (0.5, 1.0, and 1.5 km), and numbers of sites to select (1-12). Sentinel site selections for the horse and human models displayed different spatial patterns, with horse sites located largely in the west-central region and human ones in the north-central. Minor amounts of spatial overlap between the horse and human sites were observed, especially as coverage distances and numbers of sites were increased. Additionally, a near linear increase in risk coverage was observed as sites were incrementally added to the scenarios. This finding suggests that the number of sentinel sites within the ranges explored should be based on the maximum that can be funded, since they provide similar levels of benefit.

Eastern equine encephalitis virus (EEEV) is the most pathogenic arbovirus endemic to the United States. Studies have demonstrated Florida’s role as a regional reservoir for the virus and its ability to support year-round transmission. Previous research has developed risk index models for mapping locations most at risk for EEEV transmission. We compared vector abundance, vector feeding behavior, potential host species, and fauna presence at high versus low–moderate risk sites during the winter and spring. Predicted high-risk sites had a significantly greater abundance of mosquitoes overall, including Culiseta melanura (Coquillett) (Diptera: Culicidae), the primary enzootic vector of EEEV. Twenty host species were identified from Cs. melanura bloodmeals, with the majority taken from avian species. Culiseta melanura largely fed upon the Northern Cardinal (Cardinalis cardinalis (Passeriformes: Cardinalidae)), which accounted for 20–24.4% of the bloodmeals obtained from this species in years 1 and 2, respectively. One EEEV-positive mosquito pool (Cs. melanura) and nine EEEV seropositive sentinel chickens were confirmed during winter-spring collections from high-risk sites; no seropositive chickens nor mosquito pools were found at the low–moderate risk sites. These results suggest that high-risk sites for EEEV activity are characterized by habitats that support populations of Cs. melanura and which may also provide ample opportunities to feed upon Northern Cardinals. The overall low level of mosquito populations during the winter also suggests that control of Cs. melanura populations in winter at high-risk sites may prove effective in reducing EEEV transmission during the peak summer season.