bioRxiv Science⌕ Search

bioRxiv · 10.1101/2025.10.20.683413

Social Perspectives on Larvicide-Based Mosquito Control in Urban Quebec

Abstract

The spreading of Bacillus thuringiensis israelensis (Bti) in urban waterways, as a biological larvicide to control biting insect populations and mitigate disease transmission, has been subject to scientific scrutiny due to its potential environmental impacts. Public and political discussions have revealed recurring opinions that reflect broader social perspectives. While scientific research on Bti progresses, knowledge of public understanding and perspectives, which are important for decision-making, remains limited. The main objective of this research was to identify and compare the social perspectives of Quebec citizens, primarily in the city of Gatineau, regarding the use of Bti for mosquito and black fly control in aquatic environments. We used Q methodology, a mixed approach combining both quantitative and qualitative methods to identify social perspectives related to the use of Bti. Our analysis revealed three social perspectives, which account for 51% of the explained variance. They reflect the broader range of opinion within citizens, and are described as "The critical environmentalist", "The diligent mosquito hunter", and "The Bti enthusiast". Each accounting for 29%, 12% and 10% of the explained variance, respectively. The common thread across all three perspectives is the minimal public awareness and understanding of Bti and its environmental implications. Providing a first characterization of social perspectives in North America regarding larvicides, this research contributes to a more comprehensive understanding of public opinion and informs the development of inclusive and transparent policies.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Sotelo, F., Levesque, A., Larouche, M., Dupras, J., Turgeon, K.. 2025-10-22. Social Perspectives on Larvicide-Based Mosquito Control in Urban Quebec. https://doi.org/10.1101/2025.10.20.683413

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Evaluating Large Language Models as Tools to Navigate Researchers in Rapidly Evolving Research Landscapes: A Case Study in Cancer Drug Response Prediction

Large Language Models (LLMs) have emerged as promising tools for assisting researchers in automating and accelerating the synthesis of literature reviews. However, their reliability is a significant concern due to issues like factual inaccuracies and hallucinations. The key question is whether LLMs can reliably provide comprehensive, up-to-date overviews and analyses. This study evaluates the performance of three leading LLMs (OpenAI's ChatGPT, Google's Gemini, and DeepSeek) on the complex task of generating a comprehensive survey paper on deep learning for cancer Drug Response Prediction (DRP). By testing both standard and Deep Research (DR) / Deep Think (DT) modes of LLMs with prompts of varying detail, this paper assesses key academic dimensions, including reference management, content quality, and analytical depth. Key findings reveal that while DR modes of LLMs significantly improve reliability by eliminating hallucinations, performance variations exist across models and prompts. A trade-off between reference quantity and integration quality was observed, and even the best-performing models lacked the analytical depth of human experts, often requiring extensive human supervision. The study concludes that LLMs currently serve as powerful assistive tools but still cannot replace the critical validation and synthesis provided by human researchers. Choosing the best LLM to use depends on the task in hand, while several strategies can be implemented to improve the produced output.

scientific communication and education↗

Leveraging a hybrid cross-disciplinary training model to accelerate global bioinformatics capacity

Disparities in formal bioinformatics training exacerbate the global skills gap, impeding the democratized application of advanced genomic technologies. To bridge this divide, we introduce a scalable, hybrid training framework designed to rapidly accelerate regional bioinformatics capacity. We exemplify this approach through the Eastern European Bioinformatics and Genomics (EEBG) workshop series -- a cross-disciplinary initiative that pairs international faculty with local institutions to deliver modular, hands-on curricula. Functioning as a structured knowledge-transfer pipeline, the series has catalyzed a sustainable educational ecosystem, evidenced by the establishment of multiple independent summer schools across the region. The assessment of the 2025 EEBG workshop in Krakow, Poland, validates the models viability; participant metrics confirm high efficacy in skill acquisition (mean satisfaction: 4.4/5.0) and community building. Crucially, the hybrid delivery mode dismantled geographic barriers, serving as a vital mechanism for maintaining scientific continuity for researchers facing displacement and crisis. Synthesizing these outcomes, we define the core features of a replicable blueprint for scientific readiness in resource-constrained environments. We conclude by presenting a strategic roadmap -- organized around infrastructure standardization, governance sustainability, and geographical expansion -- for adapting this regional proof-of-concept into a global export-ready model, offering a critical path toward ensuring universal access to genomic innovation.

scientific communication and education↗

Cloud-Connected Pluripotent Stem Cell Platform Enhances Scientific Identity in Underrepresented Students

Stem cell research offers unique opportunities for authentic scientific engagement, yet infrastructure requirements have confined participation to elite institutions, perpetuating workforce disparities. We developed an integrated framework combining engineered biology, cloud-connected microscopy, and validated psychometric assessment to make pluripotent stem cell (PSC) experimentation widely accessible. The framework comprises three components: a doxycycline-inducible NGN2 mouse embryonic stem cell line for rapid neuronal specification, low-cost cloud microscopy for remote observation, and the validated Stem Cell Research Identity Scale (SCRIS) for quantifying educational outcomes. Implementation across a Title I high school and urban community college demonstrated significant increases in scientific identity. Students using differentiating PSCs showed broader science identity development than those using neuroblastoma cells, particularly in competence, research readiness, and recognition. High school students showed enhanced research competence gains compared to community college students despite equivalent intervention duration. Demographic analyses revealed enhanced effectiveness for Hispanic and first-generation college students. This framework provides a scalable model for broadening participation in advanced biomedical research.

scientific communication and education↗