Prevention, identification, and treatment options for the management of bed bug infestations
Bibliographic record
Abstract
In the past decade, bed bug infestations have been increasing worldwide. Historically, studies have failed to provide evidence for the transmission of human diseases through bed bugs, but recent evidence is lacking. Although physical reactions to bed bug bites continue to be documented, evidence regarding the mental health effects arising from bed bug infestations is limited to anecdotes and case reports. This report provides an update and summary of the bed bug management strategies discussed during a workshop at the 2010 Canadian Public Health Association Conference. “Best practices” regarding prevention, identification, and treatment options are presented, using evidence from existing evaluative studies. Awareness of bed bug behaviour and proper building maintenance can prevent transfer of bed bugs from belongings, including second-hand items, and reduce entry points and harbourage sites. In addition to inspection by trained professionals, early recognition of clinical symptoms and environmental signs of an infestation are important to avoid further spread of bed bugs and to allow implementation of safe and effective treatment options. Early findings may indicate a need for special support for vulnerable individuals with mental health issues potentially exacerbated by bed bug infestations. Preparing units for treatment, including the removal of clutter, is essential. However, physical and financial limitations are challenges for managing bed bug infestations, especially for vulnerable populations. Current treatment options such as application of heat or pesticides can be effective when properly implemented, but there are concerns with pesticide resistance. An Integrated Pest Management approach is recommended and should include ongoing monitoring and prevention that are essential for positive treatment outcomes. Regulatory officials, building management, and pest management professionals are encouraged to collaborate using a systematic approach to address bed bug infestations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".