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Mosquito-borne diseases are an increasing global health challenge, threatening over 40% of the world's population. Despite major advances in malaria control since 2000, recent progress has stalled. Additionally, the risk of Aedes -borne arboviruses is rapidly growing, with the unprecedented spread of dengue and chikungunya viruses, outbreaks of yellow fever and the 2015 epidemic of Zika virus in Latin America. To counteract this growing problem, diverse and innovative mosquito control technologies are currently under development. Conceptually, these span an impressive spectrum of approaches, from invasive transgene cassettes with the potential to crash mosquito populations or reduce the vectorial capacity of a population, to low-cost alterations in housing design that restrict mosquito entry. This themed issue will present articles providing insight into the breadth of mosquito control research, while demonstrating the requirement for an interdisciplinary approach. The issue will highlight mosquito control technologies at varying stages of development and includes both opinion pieces and research articles with laboratory and field-based data on control strategy development. This article is part of the theme issue ‘Novel control strategies for mosquito-borne diseases'.

Gene drives are selfish genetic elements that can be re-designed to invade a population and they hold tremendous potential for the control of mosquitoes that transmit disease. Much progress has been made recently in demonstrating proof of principle for gene drives able to suppress populations of malarial mosquitoes, or to make them refractory to the Plasmodium parasites they transmit. This has been achieved using CRISPR-based gene drives. In this article, I will discuss the relative merits of this type of gene drive, as well as barriers to its technical development and to its deployment in the field as malaria control. This article is part of the theme issue ‘Novel control strategies for mosquito-borne diseases'.

Mosquito-borne diseases are a major burden on human health worldwide and their eradication through vector control methods remains challenging. In particular, the success of vector control interventions for targeting diseases such as malaria is under threat, in part due to the evolution of insecticide resistance, while for other diseases effective control solutions are still lacking. The rate at which mosquitoes encounter and bite humans is a key determinant of their capacity for disease transmission. Future progress is strongly reliant on improving our understanding of the mechanisms leading to a mosquito bite. Here, we review the biological factors known to influence the attractiveness of mosquitoes to humans, such as body odour, the skin microbiome, genetics and infection by parasites. We identify the knowledge gaps around the relative contribution of each factor, and the potential links between them, as well as the role of natural selection in shaping vector–host–parasite interactions. Finally, we argue that addressing these questions will contribute to improving current tools and the development of novel interventions for the future. This article is part of the theme issue ‘Novel control strategies for mosquito-borne diseases'.

Automating mosquito control is a pivotal advancement in the pest control industry with the primary objective of mitigating the prevalence of vector-borne diseases. Recent progress in pest control robotics has enabled the automation of mosquito activity restrictions. However, existing robotic solutions have exhibited limitations in effectively addressing mosquito control while lacking a sensitive strategy for maximizing area coverage with crowded areas as a priority. In response to these challenges, this article proposes a novel human-first approach for complete coverage path planning (HFA-CCPP) that leverages the Glasius Bio-inspired Neural Network (GBNN) to cover areas that simulate and consider human activity patterns systematically. In this study, a mosquito-capturing robot, Dragonfly, is demonstrated with HFA-CCPP. This article provides an in-depth exploration of the technical intricacies of the proposed solution. The efficacy of the proposed technique is evaluated in terms of total area coverage and times taken to cover the high human activity region in simulation and real-world environments by comparing results with traditional GBNN. Across all scenarios, the proposed HFA-CCPP surpasses the traditional method by delivering efficient area coverage with minimal time for human-dense area coverage and efficiency in mosquito trapping. This finding stands as a newfound direction in automated mosquito control, holding great potential for curbing vector-borne diseases.

In sub-Saharan Africa, most transmission of mosquito-transmitted diseases, such as malaria or dengue, occurs within or around houses. Preventing mosquito house entry and reducing mosquito production around the home would help reduce the transmission of these diseases. Based on recent research, we make key recommendations for reducing the threat of mosquito-transmitted diseases through changes to the built environment. The mnemonic, DELIVER , recommends the following best practices: (i) D oors should be screened, self-closing and without surrounding gaps; (ii) E aves, the space between the wall and roof, should be closed or screened; (iii) houses should be L ifted above the ground; (iv) I nsecticide-treated nets should be used when sleeping in houses at night; (v) houses should be V entilated, with at least two large-screened windows to facilitate airflow; (vi) E nvironmental management should be conducted regularly inside and around the home; and (vii) R oofs should be solid, rather than thatch. DELIVER is a package of interventions to be used in combination for maximum impact. Simple changes to the built environment will reduce exposure to mosquito-transmitted diseases and help keep regions free from these diseases after elimination. This article is part of the theme issue ‘Novel control strategies for mosquito-borne diseases'.

Aedes aegypti is a mosquito species known for its role in transmitting dengue fever, a viral disease prevalent in tropical and subtropical regions. Recognizable by its white markings and preference for urban habitats, this mosquito breeds in standing water near human dwellings. A promising approach to combat the proliferation of mosquitoes is the use of smart traps, equipped with advanced technologies to attract, capture, and monitor them. The most significant results include 97% accuracy in detecting Aedes aegypti, 100% accuracy in identifying bees, and 90.1% accuracy in classifying butterflies in the laboratory. Field trials successfully validated and identified areas for continued improvement. The integration of technologies such as Internet of Things (IoT), cloud computing, big data, and artificial intelligence has the potential to revolutionize pest control, significantly improving mosquito monitoring and control. The application of machine learning (ML) algorithms and computer vision for the identification and classification of Aedes aegypti is a crucial part of this process. This article proposes the development of a smart trap for selective control of winged insects, combining IoT devices, high-resolution cameras, and advanced ML algorithms for insect detection and classification. The intelligent system features the YOLOv7 algorithm (You Only Look Once v7) that is capable of detecting and counting insects in real time, combined with LoRa/LoRaWan connectivity and IoT system intelligence. This adaptive approach is effective in combating Aedes aegypti mosquitoes in real time.

Different challenges are presented by the variety of malaria transmission environments present in the world today. In each setting, improved control for reduction of morbidity is a necessary first step towards the long-range goal of malaria eradication and a priority for regions where the disease burden is high. For many geographic areas where transmission rates are low to moderate, sustained and well-managed application of currently available tools may be sufficient to achieve local elimination. The research needs for these areas will be to sustain and perhaps improve the effectiveness of currently available tools. For other low-to-moderate transmission regions, notably areas where the vectors exhibit behaviours such as outdoor feeding and resting that are not well targeted by current strategies, new interventions that target predictable features of the biology/ecologies of the local vectors will be required. To achieve elimination in areas where high levels of transmission are sustained by very efficient vector species, radically new interventions that significantly reduce the vectorial capacity of wild populations will be needed. Ideally, such interventions should be implemented with a one-time application with a long-lasting impact, such as genetic modification of the vectorial capacity of the wild vector population.

Aedes aegypti is the main vector of arboviral diseases such as dengue, chikungunya and Zika. A key feature for disease transmission modeling and vector control planning is adult mosquito dispersal. We studied Ae aegypti adult dispersal by conducting a mark-capture study of naturally occurring Ae. aegypti from discarded containers found along a canal that divided two residential communities in Donna, Texas, USA. Stable isotopes were used to enrich containers with either 13 C or 15 N. Adult mosquitoes were collected outdoors in the yards of households throughout the communities with BG Sentinel 2 traps during a 12-week period. Marked mosquito pools with stable isotopes were used to estimate the mean distance travelled using three different approaches (Net, Strip or Circular) and the probability of detecting an isotopically marked adult at different distances from the larval habitat of origin. We consistently observed, using the three approaches that male (Net: 220 m, Strip: 255 m, Circular: 250 m) Ae. aegypti dispersed further in comparison to gravid (Net: 135 m, Strip: 176 m, Circular: 189 m) and unfed females (Net: 192 m, Strip: 213 m, Circular: 198 m). We also observed that marked male capture probability slightly increased with distance, while, for both unfed and gravid females, such probability decreased with distance. Using a unique study design documenting adult dispersal from natural larval habitat, our results suggest that Ae. aegypti adults disperse longer distances than previously reported. These results may help guide local vector control authorities in their fight against Ae. aegypti and the diseases it transmits, suggesting coverage of 200 m for the use of insecticides and innovative vector control tools.

In southern Zambia, malaria transmission is low, with outdoor biting Anopheles mosquitoes playing a significant role in malaria transmission. Locals cook in outdoor, open-walled kitchen shelters, exposing them to these outdoor biting vectors and malaria. Volatile pyrethroid spatial emanators (SE) operate through a mode of action which could provide local protection around these kitchens. In this study, SE devices containing the pyrethroid transfluthrin were deployed to local kitchens, where human landing collection (HLC) was utilized to determine differences in host-landing rates associated with protection. Forty-one households from two villages were enrolled in the study in clusters of five (or six) and randomly assigned a treatment by cluster. Local mosquito collectors were recruited and trained to conduct HLCs from 18:00-06:00 once per week for 15 weeks. SE and placebo devices were replaced monthly. Following collection, mosquitoes were returned to the lab for morphological identification. Results were analyzed in R with negative binomial generalized linear mixed models (GLMM) considering all-night and per-hour capture. A total of 3021 mosquitoes were collected during the follow-up period, with Anopheles species composing roughly half of all specimens. Anopheles activity was lower in SE protected kitchens based on all night and hourly comparisons. Mosquito activity was highest in the middle of the night, and SE was not significantly associated with protection between 18:00-21:00. SE usage appeared to reduce mosquito host-seeking activity by approximately 65-70%, with this efficacy appearing to diminish gradually over time to approximately 20-25% four weeks after opening, at which point they were replaced. Culicine mosquito behavior was not significantly impacted by the SE. The SE device provided protection to individuals within protected kitchen structures overnight and during most hours of the night. The number of mosquitoes was lowest during the early collection hours between 18:00-21:00, a period in which the SE devices did not significantly impact mosquito host-seeking behavior. This result has implications for this use-case and should be further explored.

Autodissemination traps are among the most innovative strategies for suppressing mosquito vector populations. These traps are particularly effective against Aedes aegypti due to the species' skip oviposition behavior, where eggs from a single clutch are distributed across multiple breeding sites. Evaluating the efficacy of different densities of In2Care stations under large-scale field conditions is crucial for understanding their potential impact on Ae. aegypti populations. A total of 3,250 In2Care stations were deployed in Goiânia, the 10th largest city in Brazil, with an estimated population of 1.45 million. The field study lasted 14 months, with each station serviced bi-monthly. To assess the impact of In2Care, ovitraps were installed and inspected weekly to measure changes in the number of positive ovitraps and the average number of eggs laid by Ae. aegypti females in intervention areas compared to control neighborhoods. Over the course of the study, 666,204 eggs were sampled. The density of In2Care stations varied across neighborhoods, ranging from 220 to 555 stations per km2. In the high-density area (~555 stations per km2), the Ovitrap Positivity Index (OPI) decreased from 56.9% to 31.5%, while the average number of eggs per positive paddle dropped from 41.2 to 18.1-representing a 56% reduction in egg counts. Conversely, in the low- and medium-density, no significant effect was observed. The recommended density of In2Care is about 2500 stations per Km2. Our results demonstrated stations density 4.5 times lower than the recommended density is able to reduce the frequency of positive ovitraps and the number of eggs collected on them. entomological indexes. Additional fieldwork in other entomological and epidemiological settings are needed to evaluate whether the In2Care density of ~555 units/Km2 observed for Goiânia was site-dependent or if it has borader applicability. Our results show that In2Care stations can effectively suppress Ae. aegypti populations over large geographic areas, with efficacy likely influenced by trap density.