Environmental correlates of Aedes aegypti abundance in the West Valley region of San Bernardino County, California, USA, from 2017 to 2023: an ecological modeling study

ByStoryAI

Aug 18, 2025

Environmental correlates of Aedes aegypti abundance in the West Valley region of San Bernardino County, California, USA, from 2017 to 2023: an ecological modeling study

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Environmental correlates of Aedes aegypti abundance in the West Valley region of San Bernardino County, California, USA, from 2017 to 2023: an ecological modeling study – Parasites & Vectors

Our study on Ae. aegypti mosquito abundance from 2017 to 2023 in the WVMVCD (part of San Bernardino County) in southern California revealed several key findings. We found that surface water, temperature, seasonality, and geographical location were predictors associated with mosquito abundance. Clusters of high mosquito abundance were concentrated in the central and southern regions of the study area. These findings emphasize the need to consider both temperature and seasonal cues in predicting mosquito populations to improve vector control strategies. Persistent hotspots may require targeted, intensive interventions, while areas with fluctuating patterns suggest the need for adaptive approaches, such as novel approaches to resource allocation. The study also found a decrease in global autocorrelation over time, suggesting a transition from tightly clustered to more dispersed patterns of mosquito abundance and temporal variability in Ae aeEgypti abundance and abundance. The findings have important implications for vector control efforts through traditional resource allocation methods, whether through traditional mosquito control methods, or through novel approaches. The results also suggest that some of these spatial and temporal patterns are driven by micro-environmental factors such as water availability, ambient temperature, and human activity.

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Our study on Ae. aegypti mosquito abundance from 2017 to 2023 in the WVMVCD (part of San Bernardino County) in southern California revealed several key findings. We observed a significant increase in Ae. aegypti abundance over the study period, from an average of 0.52 mosquitoes per trap in 2017 to an average of 19.60 mosquitoes in 2023, with yearly increases corresponding to summer months. We found that surface water, temperature, seasonality, and geographical location were predictors associated with mosquito abundance. Additionally, spatial clustering of high mosquito abundance was concentrated in the central and southern regions of the study area—though clusters did shift over time.

In our analysis, surface water was associated with Ae. aegypti abundance. Conversely, precipitation was not associated with abundance. The region is semi-arid, with very little precipitation in an average year. The lack of a clear relationship between precipitation and Ae. aegypti abundance could be explained by the ecology of this species. This mosquito often breeds in small artificial containers located around human dwellings, meaning seasonal patterns in population dynamics might be more influenced by variations in peridomestic water availability than changes in precipitation. Heavy rains could likewise have a negative effect on larval abundance, since intense rainfall may flush the larval habitat, thereby affecting the adult mosquito population [34,35,36]. We also note that in this setting, surface water does not come from precipitation alone, since patterns in surface water over time did not align with precipitation. We hypothesize that much of this surface water is from residential yard watering and agricultural irrigation, which increases during prolonged periods of the dry season without precipitation. While surface water availability may serve as a potential predictor of Ae. aegypti distribution, its influence is dependent on additional environmental and anthropogenic factors.

We found that average temperature was also an important factor with regard to the abundance of Ae. aegypti mosquitoes. In our model, average temperature significantly influences Ae. aegypti abundance, but it is important to note that seasonal factors, including photoperiod, could modulate the effect of temperature on mosquitoes. The interaction between temperature and season highlights the complexity of mosquito population dynamics, where optimal conditions depend on multiple environmental factors [37]. While warmer temperatures during peak season generally promote mosquito development, extreme heat can reduce habitat suitability. Longer daylight hours in summer enhance mosquito activity and reproduction, whereas shorter daylight hours in cooler months suppress it, even when temperatures remain favorable [38]. These findings emphasize the need to consider both temperature and seasonal cues in predicting mosquito populations to improve vector control strategies.

Geographical location plays a crucial role in Ae. aegypti abundance (Fig. 6A). We did not find a significant association between built area and mosquito abundance in our model, likely because most traps were placed in urban areas. However, using spatial analysis, we identified localized spatial clustering of Ae. aegypti abundance in various locations across the study area. For example, the spatial correlogram analysis showed that Ae. aegypti populations are highly localized, and the Getis-Ord Gi* analysis revealed spatio-temporal shifts in Ae. aegypti abundance, with initial hotspots concentrated in the southern part of the study area in 2017 gradually expanding and relocating to central and northern regions in subsequent years. This localized clustering aligns with the well-documented limited flight range of Ae. aegypti, which typically disperse only short distances from breeding sites—often less than 200 m—highlighting the importance of fine-scale spatial analysis in detecting meaningful patterns [39]. Our regression analyses suggest that some of these spatial and temporal patterns are driven by micro-environmental factors such as water availability, ambient temperature, and human activity [40].

Many of these hot spots were observed in residential areas and near public spaces such as parks and schools, likely due to the presence of suitable breeding sites and human hosts. Clusters of high mosquito abundance were also noted in proximity to commercial areas, including real estate developments, fire sprinkler system businesses, junk removal services, and major roads (e.g., Highways 210 and 110). Cold spots, while less frequent, were observed in some locations, including near a senior center. The distribution of both hot spots and cold spots varied throughout the study period, with some areas showing persistent patterns and others demonstrating changes over time. This shift in the spatial distribution was also reflected in a decrease in global spatial autocorrelation over time, as measured by Moran’s I, suggesting a transition from tightly clustered to more dispersed patterns of mosquito abundance across the district.

The spatial and temporal variability in Ae. aegypti abundance has important implications for vector control strategies. Persistent hotspots may require targeted, intensive interventions, while areas with fluctuating patterns suggest the need for adaptive, flexible approaches. Understanding these dynamics is integral to optimizing resource allocation in mosquito control efforts, whether through traditional methods, novel techniques like sterile insect release, or integrated vector management strategies. This knowledge can guide decision-makers in prioritizing high-risk areas, adjusting intervention timing and intensity, and potentially improving the cost-effectiveness of control measures. Ultimately, these insights contribute to more efficient and sustainable vector management. While our study does not assess mosquito infection or human case data, the characterization of spatial and temporal patterns of Ae. aegypti abundance provides a foundation for proactive vector surveillance, which is an essential component of public health preparedness in urban environments.

The spatial and temporal patterns we observed in Ae. aegypti abundance reflect the complex dynamics of this species’ expansion into new environments. Aedes aegypti has been expanding in the southwestern parts of the United States in recent years [41], a trend of particular concern given the large population in California, the relatively frequent travel-related Aedes-borne diseases, and the recent occurrence of locally transmitted dengue in the region [42]. This highlights the importance of proactive vector surveillance, even in the absence of widespread local transmission. The relationships that we observed, which differ somewhat from what is normally seen in tropical and subtropical regions of the world where the mosquito is endemic (and normally more common in the rainy season) [13, 43, 44], highlight potential challenges for public health and vector control agencies. Heightened surveillance that includes ecological research into the environmental, meteorological, and geographical correlates of Ae. aegypti abundance is important for understanding seasonal, inter-annual, and geographical patterns in abundance. As this species moves into new environments, identifying consistent environmental predictors of its presence and abundance may remain challenging until it reaches equilibrium with local environmental conditions.

This study has both limitations and strengths. Our assessment of mosquito abundance is limited to locations and time periods when trapping occurred (February to November). Over time, trapping efforts expanded geographically, coinciding with an increase in Ae. aegypti abundance. While our model accounted for trapping intensity, we were unable to assess abundance in areas and time periods without trapping. Additionally, trapping itself may influence Ae. aegypti abundance, as mosquitoes removed from the environment are not replaced immediately [28]. Moreover, the use of cluster trapping—deploying additional traps around high-count sites to identify potential mosquito sources—may have contributed to localized increases in mosquito abundance in certain instances. Overall, the observed reduction in the proportion of traps yielding zero Ae. aegypti is however most likely due to the spatial expansion of the mosquito population across the district. Over time, Ae. aegypti became more widespread and ubiquitous, as reflected by higher detection rates and a declining number of traps with no mosquito captures. Nonetheless, we believe the trapped mosquitoes provide a reliable representation of abundance in the surrounding environment. Our analyses incorporated Earth observation data, primarily derived from satellite imagery. These data can be affected by cloud cover, potentially leading to incomplete surface water measurements [45]. However, unlike tropical regions, where cloud cover can persist for weeks or months, this issue is relatively minor in this arid part of North America. There were relatively few periods during the study when Earth observation data were unavailable. We were also unable to directly incorporate photoperiod into the model, as daylight exposure varies by trap location and is not routinely measured; however, seasonal variation in daylight length is partially captured through the inclusion of day of year and temperature.

Despite these limitations, this study has several notable strengths. The use of Earth observation sensors (e.g., satellite systems) allowed for remote monitoring of environmental conditions at fine spatial and temporal resolutions across much of the study period [46]. Such high-resolution, long-term monitoring would have been cost-prohibitive and logistically challenging using only ground-based methods. As the availability and accessibility of Earth observation data continue to grow, their integration into vector-borne disease surveillance systems in this and other settings is expected to expand [47]. Additionally, the extensive surveillance data collected over a 7-year period represents a key strength of this study. The depth and breadth of the spatial and temporal dataset facilitated a robust analysis of mosquito distribution patterns, revealing both long-term trends and localized variations. Recognizing the value of predictive modeling in forecasting vector abundance, we are currently exploring advanced approaches—such as machine learning algorithms and spatio-temporal models—as part of our ongoing and future research efforts.

Finally, as the threat of Aedes-borne diseases in this region increases, vector control agencies have moved toward the implementation of different novel interventions [42]. In the WVMVCD, sterile insect release is currently being incorporated into vector control efforts [48, 49]. Recent work indicated a reduction in Ae. aegypti abundance by up to 65% following the optimization of integrated vector management strategies through adoption of the target sterile insect technique and In2Care Mosquito Stations in selected sites in the area in 2024 [50]. The model presented here, which accounts for environmental factors influencing Ae. aegypti abundance, can be adapted to assess the relative impact of this intervention while accounting for spatial and temporal variability.

Source: Parasitesandvectors.biomedcentral.com | View original article

Source: https://parasitesandvectors.biomedcentral.com/articles/10.1186/s13071-025-06967-w