Background Despite the use of numerous methods of control measures, mosquito populations and mosquito-borne diseases are still increasing globally. Evidence-based action thresholds to initiate or intensify control activities have been identified as essential in reducing mosquito populations to required levels at the correct/optimal time. This systematic review was conducted to identify different mosquito control action thresholds existing across the world and associated surveillance and implementation characteristics. Methodology/Principal findings Searches for literature published from 2010 up to 2021 were performed using two search engines, Google Scholar and PubMed Central, according to PRISMA guidelines. A set of inclusion/exclusion criteria were identified and of the 1,485 initial selections, only 87 were included in the final review. Thirty inclusions reported originally generated thresholds. Thirteen inclusions were with statistical models that seemed intended to be continuously utilized to test the exceedance of thresholds in a specific region. There was another set of 44 inclusions that solely mentioned previously generated thresholds. The inclusions with “epidemiological thresholds” outnumbered those with “entomological thresholds”. Most of the inclusions came from Asia and those thresholds were targeted toward Aedes and dengue control. Overall, mosquito counts (adult and larval) and climatic variables (temperature and rainfall) were the most used parameters in thresholds. The associated surveillance and implementation characteristics of the identified thresholds are discussed here. Conclusions/Significance The review identified 87 publications with different mosquito control thresholds developed across the world and published during the last decade. Associated surveillance and implementation characteristics will help organize surveillance systems targeting the development and implementation of action thresholds, as well as direct awareness towards already existing thresholds for those with programs lacking available resources for comprehensive surveillance systems. The findings of the review highlight data gaps and areas of focus to fill in the action threshold compartment of the IVM toolbox.

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The purpose of this study was to perform descriptive and inferential analyses to better understand the presence of the abundant mosquito species Aedes atlanticus and Aedes infirmatus in St. Johns County, northeastern Florida. Historical surveillance data (2010-2019) obtained from Anastasia Mosquito Control District of St. Johns County, St. Augustine, FL, was organized to graph temporal mosquito abundance trends and inverse distance weighted (IDW) interpolation was used to map spatial distribution patterns of mosquitoes. Precipitation and habitat composition were investigated as spatiotemporal predictors of mosquito abundance using Pearson’s correlation statistics. There were considerable and inconsistent fluctuations in the population abundance of Ae. atlanticus and Ae. infirmatus across and within individual surveillance seasons during the last decade. Precipitation was significantly associated with total county-wide mosquito population counts by season (Ae. atlanticus, R = 0.810, p = 0.005; Ae. infirmatus, R = 0.850, p = 0.002), while the association with weekly mosquito population trends was inconsistently significant across species, lag time, and years. The proportion of surrounding land covered by upland forest, water, and agriculture was associated with species abundance at the spatial level of individual trap sites. Overall, the results identify that Ae. atlanticus and Ae. infirmatus share a spatiotemporal relationship and are similarly impacted by rainfall and habitat type. Findings of the study might help to inform improved surveillance by integrating IDW estimation maps with current district resources and improved knowledge of species’ ecology.

The distribution of mosquito communities is predicted by complex micro- and macrohabitat systems. While macrohabitat variables are significant in modeling the distribution of individual mosquito species, the distribution of mosquito communities in disturbed urban and semi-urban environmental gradients was overlooked in most of the previous models. In our study, we used conditional Markov Random Fields (CRF) to evaluate spatial co-occurrence patterns between mosquito vectors of eastern equine encephalitis (EEEV) and west Nile virus (WNV) in a disturbed urban environment in Saint John’s County, Florida. We aimed to 1) quantify the strength and direction of spatial unconditional and conditional correlations between mosquito assemblages in disturbed environments, and 2) evaluate whether the strength of correlations between mosquito assemblages is conditional on landscape or climate variables. We leveraged the longitudinal surveillance effort using Biogents sentinel traps (BGS) conducted by Anastasia Mosquito Control Districts in disturbed urban environments during 2017-2020. The distribution of high mosquito abundance, especially Aedes albopictus, Ae. aegypti, Ae. vexans, Ae. taeniorhynchus, Culex nigripalpus, Cx. salinarius, and Cx. quinquefasciatus, were conditionally correlated with other EEEV and WNV vector species in reduced woody and herbaceous wetlands and evergreen forests (-54.44%), and in urban developed landscapes (3.44%) during 2019 and 2020. Moreover, conditional correlations between mosquito species pairs were positively associated with increased total precipitation and in areas with high average minimum and maximum temperatures. Our results show that the micro- and macrohabitat characteristics demonstrated spatial effects on distribution and correlations between species pairs of EEEV and WNV mosquito vectors across disturbed environments. Our findings could be used to better understand the joint effects of drivers on mosquito diversity at a specific locality, interspecific interactions among mosquito assemblages, and how this diversity changes across environmental gradients.