Aedes aegypti is the primary urban vector for several important arboviruses, including dengue, chikungunya, yellow fever, and Zika viruses. Traditional dengue virus (DENV) surveillance relies on passive reporting of human cases, which often underestimates transmission due to asymptomatic or unreported infections. This study evaluated the utility of monitoring DENV in Ae. aegypti mosquitoes to improve detection of local dengue transmission and inform vector control strategies during the 2024 dengue epidemic in Puerto Rico. Mosquito surveillance was conducted in 15 neighborhoods within the San Juan metropolitan area where confirmed dengue cases had been recently reported. Adult female Ae. aegypti were collected weekly using Autocidal Gravid Ovitraps (AGO traps) placed within a 200 m radius of index cases. Pools of 1–20 mosquitoes were tested for DENV RNA and serotype using RT-PCR. Surveillance continued for up to 91 days in study areas, depending on virus detection. A total of 29,354 female Ae. aegypti were collected, of which 29,211 females were pooled (1–20 specimens per pool) into 3878 pools and analyzed. DENV was detected in 49 pools across 11 neighborhoods, with serotypes DENV-1, DENV-2, and DENV-3 identified. Multiple serotypes were sometimes detected in mosquitoes from the same neighborhood. Minimum infection rates and vector indices were higher during the epidemic than in previous inter-epidemic periods, and mosquito densities exceeded thresholds considered protective against outbreaks. Entomo-virological surveillance detected a greater variety and evenness of serotypes than passive human surveillance. These findings suggest that entomo-virological surveillance can complement passive case surveillance, providing a more comprehensive detection of DENV circulation. Integrating mosquito-based and human surveillance can improve outbreak detection, guide vector control, and aid in reducing dengue burden in affected communities.

The representativeness and timeliness of sentinel surveillance for endemic and emerging arboviral and respiratory diseases in low-resource settings are understudied. We compared laboratory-confirmed epidemic dengue, non-epidemic dengue, Zika, chikungunya, and COVID-19 (pre-Omicron and Omicron periods) cases reported in Puerto Rico’s Sentinel Enhanced Dengue Surveillance System (SEDSS) with island-wide trends reported by the Department of Health’s passive disease surveillance system (PADSS). We plotted trends over time to assess representativeness and used lagged cross-correlations to determine whether SEDSS reporting preceded PADSS. SEDSS trends were representative of island-wide trends for all pathogens. SEDSS preceded reporting in PADSS by up to three, eight, and two weeks for epidemic dengue, Zika, and pre-Omicron COVID-19, respectively. Increasing case trends for chikungunya occurred at broadly similar times in both systems, while temporal concordance was lower for non-epidemic dengue. In Puerto Rico, sentinel surveillance was representative of island-wide trends and could provide early warning for dengue epidemics and emerging diseases, such as Zika and COVID-19.