The Use of Automated Traps to Assess the Efficacy of Insecticide Barrier Treatments Against Abundant Mosquitoes in Remote Environments

Commercially available ‘smart’ trap technology has not yet been widely used to evaluate interventions against mosquitoes despite potential benefits. These benefits include the ability to capture data continuously at fine temporal scales without the human resources usually required for conventional trap deployment. Here, we used a commercially available smart trap (BG-Counter, Biogents) to assess the efficacy of an insecticide barrier treatment (BiFlex AquaMax) in reducing mosquito nuisance in a logistically challenging coastal environment in Queensland, Australia. Adoption of smart trap technology permitted us to conduct a uniquely detailed assessment of barrier treatments, ultimately allowing us to demonstrate significant reductions in mosquito collections from treated properties over all temporal scales. On average, daily mosquito collections from treated properties were reduced by 74.6% for the duration of the post-treatment period (56 d). This observation was supported by similar reductions (73.3%) in mosquito collections across all hours of the day. It was further found that underlying mosquito population dynamics were comparable across all study sites as evidenced by the high congruence in daily collection patterns among traps (Pearson r = 0.64). Despite limitations related to trap costs and replication, the results demonstrate that smart traps offer new precision tools for the assessment of barrier treatments and other mosquito control interventions.

Predictive model for microclimatic temperature and its use in mosquito population modeling

Mosquitoes transmit several infectious diseases that pose significant threat to human health. Temperature along with other environmental factors at breeding and resting locations play a role in the organismal development and abundance of mosquitoes. Accurate analysis of mosquito population dynamics requires information on microclimatic conditions at breeding and resting locations. In this study, we develop a regression model to characterize microclimatic temperature based on ambient environmental conditions. Data were collected by placing sensor loggers at resting and breeding locations such as storm drains across Houston, TX. Corresponding weather data was obtained from National Oceanic and Atmospheric Administration website. Features extracted from these data sources along with contextual information on location were used to develop a Generalized Linear Model for predicting microclimate temperatures. We also analyzed mosquito population dynamics for Aedes albopictus under ambient and microclimatic conditions using system dynamic (SD) modelling to demonstrate the need for accurate microclimatic temperatures in population models. The microclimate prediction model had an R2 value of ~ 95% and average prediction error of ~ 1.5 °C indicating that microclimate temperatures can be reliably estimated from the ambient environmental conditions. SD model analysis indicates that some microclimates in Texas could result in larger populations of juvenile and adult Aedes albopictus mosquitoes surviving the winter without requiring dormancy.

Fine-scale estimation of key life-history parameters of malaria vectors: implications for next-generation vector control technologies

Background Mosquito control has the potential to significantly reduce malaria burden on a region, but to influence public health policy must also show cost-effectiveness. Gaps in our knowledge of mosquito population dynamics mean that mathematical modelling of vector control interventions have typically made simplifying assumptions about key aspects of mosquito ecology. Often, these assumptions can distort the predicted efficacy of vector control, particularly next-generation tools such as gene drive, which are highly sensitive to local mosquito dynamics. Methods We developed a discrete-time stochastic mathematical model of mosquito population dynamics to explore the fine-scale behaviour of egg-laying and larval density dependence on parameter estimation. The model was fitted to longitudinal mosquito population count data using particle Markov chain Monte Carlo methods. Results By modelling fine-scale behaviour of egg-laying under varying density dependence scenarios we refine our life history parameter estimates, and in particular we see how model assumptions affect population growth rate (Rm), a crucial determinate of vector control efficacy. Conclusions Subsequent application of these new parameter estimates to gene drive models show how the understanding and implementation of fine-scale processes, when deriving parameter estimates, may have a profound influence on successful vector control. The consequences of this may be of crucial interest when devising future public health policy. Graphic abstract

La Crosse virus spread within the mosquito population in Knox County, TN

In Appalachia, La Crosse virus (LACV) is a leading pediatric arbovirus and public health concern for children under 16 years. LACV is transmitted via the bite of an infected Aedes mosquito. Thus, it is imperative to understand the dynamics of the local vector population in order to assess risk and transmission. Using entomological data collected from Knox County, Tennessee in 2013, we formulate an environmentally-driven system of ordinary differential equations to model mosquito population dynamics over a single season. Further, we include infected compartments to represent LACV transmission within the mosquito population. Findings suggest that the model, with dependence on degree days and accumulated precipitation, can closely describe field data. This model confirms the need to include these environmental variables when planning control strategies.

The Ecological Structure of Mosquito Population Dynamics: Insights from India

Understanding the temporal dynamics (including the start, duration and end) of malaria transmission is key to optimising various control strategies, enabling interventions to be deployed at times when they can have the most impact. This temporal profile of malaria risk is intimately related to the dynamics of the mosquito populations underlying transmission. However, many outstanding questions remain surrounding these dynamics, including the specific drivers and their dependence on the ecological structure of a setting. Here we collate mosquito time-series catch data from across India in order to better understand these dynamics and the factors shaping them. Our analyses reveal pronounced heterogeneity in mosquito population dynamics, both within (across different locations) and between (in the same location) species complexes. Despite this variation, we show that these time-series can be clustered into a small number of categories characterised by distinct temporal properties and driven by a largely unique set of environmental factors. Exploration of these categories highlights that an interplay of species complex-specific factors and the ecological structure of the local environment together shape the temporal dynamics (including timing and extent of seasonality) of mosquito populations. The results of these analyses are then integrated with spatial predictions of species presence/absence in order to generate predictive maps of mosquito population seasonality across India, to inform the planning and timing of malaria control efforts.SignificanceEffective planning and control of malaria requires an understanding of the underlying mosquito population dynamics that determine the temporal profile of malaria risk. Here, we collate a database of monthly mosquito catch data spanning 40 years and 117 unique locations across India to explore the factors shaping these dynamics. Our analyses reveal pronounced heterogeneity in mosquito population dynamics, both within (across different locations) and across (in the same location) species complexes: this heterogeneity is driven by an interplay between species complex-specific factors and the ecological structure of the local environment. Despite this variation, the temporal patterns of mosquito abundance across these different locations can be categorised into a small number of clusters, each characterised by distinct temporal properties and each of which is influenced by a largely unique set of environmental factors. Based on these results, we create a tool to predict mosquito population seasonality in a given location, to inform the planning and timing of control efforts.

Parasitism of Aedes Albopictus by Ascogregarina Taiwanensis Lowers Its Competitive Ability Against Aedes Triseriatus.

Background: Mosquitoes are carriers for many diseases that significantly impact the human population such as dengue, malaria and La Crosse virus. When multiple mosquito species are present, the competition between species may alter disease spread. Two mosquito species, Aedes albopictus and Aedes triseriatus, both inhabit areas where La Crosse Encephalitis Virus is found. Infection of Aedes albopictus by the parasite Ascogregarina taiwanensis can decrease the mosquito’s fitness and impact its initial competitive advantage over Aedes triseriatus. The decrease in fitness occurs through the impact of Ascogregarina taiwanensis on female fecundity, larval development rate, and larval mortality. Methods: In this paper, we examine the effects of parasitism of Ascogregarina taiwanensis on Aedes albopictus and Aedes triseriatus population dynamics and competition. We build a compartmental model using parameters based on published literature, simulate the dynamics of the system, and analyze the effect of parasitism on competition between the mosquito species. Results: We show that increased levels of parasitism in Aedes albopictus will decrease the initial competitive advantage of the species over Aedes triseriatus and increase the survivorship of Aedes triseriatus. An understanding of how population dynamics are affected by this parasite can inform future mosquito control and mosquito-borne disease mitigation efforts. Conclusions: Mosquito population dynamics are affected by many factors, including abiotic factors (e.g. temperature and humidity) and competition between mosquito species. This is especially true when multiple mosquito species are vying to live in the same area. An understanding of mosquito population dynamics is vital to preventing spread of these diseases.

Inter-annual variability of the effects of intrinsic and extrinsic drivers affecting West Nile virus vector Culex pipiens population dynamics in Northeastern Italy

Background: Vector-borne infectious diseases (VBDs) represent a major public health concern worldwide. Among VBDs, West Nile Virus (WNV) showed an increasingly wider spread in temperate regions of Europe, including Italy. During the last decade, WNV outbreaks have been recurrently reported in mosquitoes, horses, wild birds, and humans, showing great variability in the temporal and spatial distribution pattern. Due to the complexity of the environment-host-vector-pathogen interaction and the incomplete understanding of the epidemiological pattern of the disease, WNV occurrences can be hardly predictable. The analyses of ecological drivers responsible for the earlier WNV reactivation and transmission are pivotal; in particular, variations in the vector population dynamics may represent a key point of the recent success of WNV and, more in general, of the VBDs.Methods: We investigated the variations of Culex pipiens population abundance using environmental, climatic and trapping data obtained over nine years (2010 to 2018) through the WNV entomological surveillance program implemented in northeastern Italy. An Information Theoretic approach (IT-AICc) and model-averaging algorithms were implemented to examine the relationship between the seasonal mosquito population growth rates and both intrinsic (e.g. intraspecific competition) and extrinsic (e.g. environmental and climatic variables) predictors, to identify the most significant combinations of variables outlining the Cx. pipiens population dynamics.Results: Population abundance (proxy for intraspecific competition) and length of daylight were the predominant factors regulating the mosquito population dynamics; however, also other drivers encompassing environmental and climatic variables had a significant impact, although sometimes counterintuitive and not univocal. The analyses of the single-year datasets, and the comparison with the results obtained from the overall model (all data available from 2010 to 2018), highlighted remarkable differences in coefficients magnitude, sign, and significance. These outcomes indicate that different combinations of factors might have distinctive, and sometimes divergent, effects on mosquito population dynamics. Conclusions: A more realistic acquaintance of the intrinsic and extrinsic mechanism of mosquito population fluctuations in relation to continuous changes in environmental and climatic conditions is paramount to properly reinforce VBDs risk-based surveillance activities, to plan targeted density control measures and to implement effective early detection programs.

Inter-annual variability of the effects of intrinsic and extrinsic drivers affecting West Nile virus vector Culex pipiens population dynamics in northeastern Italy

Background: Vector-borne infectious diseases (VBDs) represent a major public health concern worldwide. Among VBDs, West Nile Virus (WNV) showed an increasingly wider spread in temperate regions of Europe, including Italy. During the last decade, WNV outbreaks have been recurrently reported in mosquitoes, horses, wild birds, and humans, showing great variability in the temporal and spatial distribution pattern. Due to the complexity of the environment-host-vector-pathogen interaction and the incomplete understanding of the epidemiological pattern of the disease, WNV occurrences can be hardly predictable. The analyses of ecological drivers responsible for the earlier WNV reactivation and transmission are pivotal; in particular, variations in the vector population dynamics may represent a key point of the recent success of WNV and, more in general, of the VBDs.Methods: We investigated the variations of Culex pipiens population abundance using environmental, climatic and trapping data obtained over nine years (2010 to 2018) through the WNV entomological surveillance program implemented in northeastern Italy. An Information Theoretic approach (IT-AIC c ) and model-averaging algorithms were implemented to examine the relationship between the seasonal mosquito growth rates and both intrinsic (e.g. intraspecific competition) and extrinsic (e.g. environmental and climatic variables) predictors, to identify the most significant combinations of variables outlining the Cx. pipiens population dynamics. Results: Population density (proxy for intraspecific competition) and length of daylight were the predominant factors regulating the mosquito population dynamics; however, also other drivers encompassing environmental and climatic variables had a significant impact, although sometimes counterintuitive and not univocal. The analyses of the single-year datasets, and the comparison with the results obtained from the overall model (all data available from 2010 to 2018), highlighted remarkable differences in coefficients magnitude, sign, and significance. These outcomes indicate that different combinations of factors might have distinctive, and sometimes divergent, effects on mosquito population dynamics. Conclusions: A more realistic acquaintance of the intrinsic and extrinsic mechanism of mosquito population fluctuations in relation to continuous changes in environmental and climatic conditions is paramount to properly reinforce VBDs risk-based surveillance activities, to plan targeted density control measures and to implement effective early detection programs.