West Nile virus (WNV; family Flaviviridae) has been an annual public health concern in the continental United States since its introduction in 1999. It is particularly difficult to determine when and where human infections will occur because WNV is highly focal and amplifies in bird-mosquito cycles with incidental spillover to humans. WNV is transmitted by female mosquitoes in the genus Culex, most commonly Cx. tarsalis, Cx. pipiens, and Cx. quinquefasciatus. The mosquitoes’ capacity to transmit WNV depends on the environment, particularly temperature, resulting in seasonal cycles with most human cases occurring between July and September. WNV prevention is predominantly through vector management, consisting of a combination of larval and adult control. Integrated vector management programs in California conduct surveillance to monitor mosquito abundance and mosquito infection prevalence as a means for targeting control strategies, but these estimates are not adjusted for biases that could be induced by short-term variation in weather. This dissertation investigates the complicated relationship between environmental factors, entomological surveillance observations, and human WNV disease.Chapter 1 focused on the relationship between entomological surveillance indicators and risk for human WNV disease. In particular, we evaluated the ability of the vector index (VI), the product of mosquito abundance and infection prevalence, to predict periods of above-average WNV incidence. We used receiver operating characteristic (ROC) curves to identify the VI threshold that maximized sensitivity and specificity of these predictions and found that these thresholds were highly dependent on the dominant vector species in an area and the trap type used for targeting surveillance. We also used statistical models with observed entomological surveillance and human disease data aggregated to different spatial scales to examine the effect of spatial scale on the ability of the VI to predict human WNV disease incidence. These results found cities to be the best balance between being small enough to be operationally relevant but large enough to have adequate predictive accuracy during high-risk periods. Chapter 2 considered short-term weather variability as a potential source of bias in entomological surveillance that may affect estimates of WNV disease risk. We collected mosquitoes and gathered weather data from 10 field sites equipped with devices to record mosquito counts, temperature, and wind speed every 15 minutes in the rice-growing region of northern California. We used the 15-minute mosquito data to estimate four outcomes for the primary WNV vector in the study area, Cx. tarsalis: the total overnight count, the onset time of evening host-seeking activity, the median time of nightly host-seeking activity, and the hour of peak host-seeking activity. We related each of these outcomes to the wind speed and temperature recorded at a range of times in the afternoon leading to the host-seeking night through statistical models and found both wind speed and temperature at 20:00, or just prior to the onset of host-seeking, to be the best predictors of all four outcomes. These predictable factors will help guide the timing of vector control applications to maximize their effects on the local vector population, thus reducing the overall risk of WNV transmission. Chapter 3 applied spatio-temporal predictive models that accounted for ecological factors and were capable of highlighting gaps in surveillance coverage for estimating risk of WNV transmission. We used a generalized additive model (GAM) to model the nonlinear weekly seasonal trends of Cx. tarsalis abundance in a range of land use types using trap count data for the years 2008-2020 collected by 20 Central Valley mosquito and vector control districts in California. Overall, the model captured strong seasonal patterns in abundance, modified by local land use and ephemeral spatio-temporal anomalies. Models maintained a similar predictive accuracy for out-of-sample data compared to that for the training data set. To determine the ability of the model to extrapolate from known surveillance locations, we then used the GAM to predict weekly Cx. tarsalis abundance at unmeasured locations across a 2.5-km grid of the Central Valley. We found that these predictions were most accurate when the nearest observed trap was within 2 km and one week prior. Taken together, these three chapters provide a basis for improving WNV risk estimation through entomological surveillance. These chapters will inform efforts to prevent human WNV disease through a more complete understanding of the link between WNV vector dynamics and the risk of human disease, improving the ability to predict risk and target mosquito control.

Wave kinematics are involved in most processes that coastal engineers study. Knowledge of fluid velocities and accelerations are necessary for the study of wave loading of structures through the use of the O'Brien-Morison equation. Knowledge of the kinematics near the sea bed are necessary for studies of sediment transport processes. For this reason, it is important that wave measurements be interpreted as accurately as possible.

West Nile virus (WNV) can cause a potentially fatal neuroinvasive mosquito-borne disease. The virus is maintained in an enzootic cycle between birds and Culex mosquitoes but can spillover to cause infections in horses and humans. Approximately 80% of human infections are asymptomatic, but 20% develop a febrile illness and <1% result in a neuroinvasive disease which can result in long-term physical and mental disabilities. During periods of high risk for human infections, insecticides are used to rapidly reduce the abundance of infectious mosquitoes in proximity to humans, thereby reducing zoonotic transmission risk. However, the degree to which mosquito populations are reduced following insecticide applications is highly variable and difficult to measure in operational settings. New vector control strategies, like ivermectin (IVM), a drug that increases mosquito mortality when ingested, are under investigation to improve the specificity of control strategies. This dissertation assesses the spatio-temporal impacts of aerial applications of insecticides and bird-delivered ivermectin on Culex mosquito populations and WNV transmission dynamics.In Chapter 1, we developed generalized additive models to estimate the duration and magnitude of reduction in abundance of Culex (Cx.) tarsalis and Cx. pipiens, the primary WNV vectors in California, following application of aerial adulticides in Sacramento and Yolo counties from 2006-2017. Aerial applications are utilized during periods of epidemic risk to rapidly reduce the abundance of infectious mosquitoes in proximity to humans. The efficacy of these applications for reducing Culex mosquito abundance is difficult to assess for single events due to stochastic variation in trapping success as well as natural variation in mosquito abundance due to season, land use, and weather. Peridomestic Cx. pipiens populations were reduced to a greater extent compared with Cx. tarsalis after both single and repeated spray events, likely due to the species’ focal distribution within urbanized areas. In contrast, impacts of aerial sprays on Cx. tarsalis populations are likely diluted by the species’ large dispersal ability and the broad distributions of productive larval habitat present in the study area. In Chapter 2, we conducted a randomized field trial to investigate the impacts of a novel WNV control strategy, IVM-treated backyard chickens, on mosquito population and WNV transmission dynamics. We placed eight flocks (4 treated and 4 untreated) of six chickens each in backyards across Davis, California for the WNV season (Jun-Sep 2019). We detected a reduction in WNV seroconversions in treated flocks, paired with increased mortality in wild Cx. tarsalis feeding on treated chickens and a reduction in parity in female mosquitoes near treated flocks, suggest that there was a reduction in WNV transmission around treated vs. untreated flocks resulting from ivermectin-administration. We did not detect a difference in abundance or WNV infection rates in mosquitoes. In Chapter 3, we developed a spatially implicit dynamical model of WNV transmission in the presence of IVM-treated birdfeeders to assess the feasibility and efficacy of treating backyard birds with IVM to reduce local WNV transmission. Using field-collected data on birdfeeder usage and nocturnal roosting habits of common backyard birds to parameterize the model, we estimated that reductions up to 83.9% in infectious mosquito-days and 61.3% in infections in competent birds could be obtained under ideal conditions. Both the probability of IVM-induced mosquito mortality and the number of treated lots strongly affect the magnitude of reduction while the spatial distribution of treated lots within a neighborhood did not. Increasing the total number of treated birds in a neighborhood, irrespective of WNV competency, reduced WNV transmission intensity, indicating that IVM deployment should target a wide variety of common backyard bird species. Taken together, the results of this dissertation provide new insights into the efficacy of existing and novel methods of vector control for reducing mosquito abundance and WNV transmission. An improved understanding of these processes will inform future vector control strategies, providing more efficient and targeted approaches to prevent arboviral transmission.

Aedes aegypti, the primary vector for dengue virus (DENV), as well as other viruses such as chikungunya, Zika, and yellow fever, is well-adapted to urban environments and has become established across tropical, subtropical, and some temperate regions, including parts of the continental United States. With no effective treatments available for dengue, prevention relies primarily on vector control. Early warning systems that would allow vector control interventions to be targeted and timely would mitigate the disease burden, reduce the duration of outbreaks, and lower associated costs.Entomological surveillance has the potential to provide timely and spatially accurate risk estimates, yet metrics for Ae. aegypti abundance and DENV prevalence in Ae. aegypti have thus far not been consistent and effective predictors of dengue risk. The high spatial and temporal variability of dengue transmission complicates the use of entomological data for risk prediction. Additionally, the spatial and temporal dimensions of vector control coverage necessary for effective interventions remain poorly understood. This dissertation aims to define spatial and temporal scales and effort required for both surveillance and control of Ae. aegypti informed by realistic scenarios, including a major DENV-2 outbreak in Iquitos, routine entomological surveillance in Miami-Dade County, Florida, and a large-scale study of sequential ultra-low volume (ULV) indoor pyrethroid spray applications in Iquitos. Chapter 1 characterizes the major DENV-2 outbreak in Iquitos, including variation in abundance and DENV prevalence in Ae. aegypti and their lagged associations with dengue cases in humans. We identified Ae. aegypti DENV prevalence as the entomological metric that best predicted dengue risk, with the strongest association at a one-week lag. Chapter 2 focused on determining the surveillance effort required for early detection of dengue transmission in both endemic and non-endemic settings through simulations informed by real data from entomological surveillance during the dengue outbreak in Iquitos. Results showed that sample sizes of 320 and 1,600 Ae. aegypti females could provide an 80% DENV detection probability in endemic and non-endemic settings, respectively. The surveillance effort necessary to achieve optimal sample sizes varied markedly by season, collection method, and the epidemiological context. Chapter 3 assessed the temporal and spatial effects of ultra-low volume (ULV) indoor insecticide sprays on Ae. aegypti populations. We disentangled the impact of sprays within a household from those in neighboring households and compared the effect of the most recent spray with the cumulative effect of multiple sprays on the number of Ae. aegypti in a household. Our findings suggest that the reduction of Ae. aegypti in a household is primarily determined by time elapsed since the last spray intervention within that household, with no significant additional reduction provided by neighboring houses being sprayed or by multiple past sprays in the same household. Taken together, my research provides evidence to optimize entomological surveillance, early warning systems, and vector control strategies for more effective dengue prevention.

The mosquito Aedes aegypti is the primary vector of many viruses that cause a major burden on human health worldwide, including dengue, Zika, yellow fever, and chikungunya viruses. Currently, a widely adopted vaccine is available only for yellow fever virus, and thus mitigating the burden of diseases caused by these viruses predominantly relies on avoiding mosquito bites and controlling mosquito populations. Mosquito-borne virus transmission risk models can help mosquito control decision-makers efficiently use limited resources and reduce the use of chemical insecticides that can lead to resistance and therefore less effective control. As the Zika virus (ZIKV) pandemic emerged in 2016, estimates for ZIKV transmission risk were based on proxy evidence from closely related dengue virus. To improve risk estimates, we first studied how temperature affects ZIKV extrinsic incubation period (EIP). We concluded that, in agreement with findings for other mosquito-borne viruses, ZIKV EIP decreased as temperature increased and ZIKV EIP was relatively shorter than for dengue virus across temperatures. We then sought to further improve ZIKV risk estimates by studying thermal preferences of Ae. aegypti mosquitoes in the laboratory and in the field. Current mosquito-borne pathogen risk models primarily use temperatures from weather stations or thermal imagery as a proxy for the temperatures mosquitoes experience; however, such approaches do not account for the range of local environments or microclimates available to adult mosquitoes nor the microhabitats mosquitoes select and therefore may lead to an inaccurate estimate of risk. In the lab, Ae. aegypti generally preferred the coldest temperatures available (<20°C) and avoided the hottest temperatures (>31°C) on a gradient ranging from 17.5°C to 36.5°C. However, mosquitoes reared at cooler temperatures (22°C) were larger and rested at warmer temperatures compared to mosquitoes reared at warm temperatures (26°C and 30°C). In the field, female Ae. aegypti were found resting at temperatures that were increasingly cooler than ambient as ambient air temperature increased. Accordingly bias in air-temperature-based models of Zika virus transmission risk is expected to be greatest at the hottest temperatures, and overall, accounting for Ae. aegypti thermal preferences yielded lower estimates for Zika virus transmission risk compared to models based on air temperatures alone. Taken together, the results of these studies can be used to improve prediction of mosquito-borne pathogen risk and inform mosquito control decisions.

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