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Record W2889184218 · doi:10.14745/ccdr.v40i05a04

Lyme disease prevention and control – the way forward

2014· article· en· W2889184218 on OpenAlexvenueaboutno aff
CB Beard

Bibliographic record

VenueCanada Communicable Disease Report · 2014
Typearticle
Languageen
FieldImmunology and Microbiology
TopicVector-borne infectious diseases
Canadian institutionsnot available
FundersCenters for Disease Control and Prevention
KeywordsLyme diseaseDisease controlMedicineVirology

Abstract

fetched live from OpenAlex

Lyme borreliosis is a tick-borne illness caused by the spirochete Borrelia burgdorferi, harbored primarily by small rodents, and transmitted by ticks in the genus Ixodes. It was first recognized clinically in the 1970s, in a cluster of juvenile arthritis cases in Connecticut (1). Over the last twenty five years, Lyme disease has been increasing steadily in the United States, both in case numbers and in geographic distribution. As noted in the other articles in this issue, Lyme disease has started to show a similar pattern in Canada. In the United States, there were over 30,000 cases reported to the Centers for Disease Control and Prevention (CDC) in 2012, making it the 7th most common reportable condition. The increasing numbers of cases is thought to have resulted from expanding deer populations and suburban growth that have led to abundant reservoir hosts, more ticks, and greater opportunities for exposure in humans (2). It is important to note that the observed trends for Lyme disease emergence are similar for several other tick-borne diseases that share similar ecologies, including anaplasmosis, babesiosis, ehrlichiciosis, and Powassan disease. Symptoms of Lyme disease range from an erythema migrans rash, early in the course of infection, to neuritis (e.g., facial palsy), carditis, and arthritis in later, disseminated stages of illness. Prompt treatment with 2-4 weeks of oral doxycycline results in symptomatic cure of the great majority of patients. Nevertheless, a subset of patients, especially those diagnosed and treated in later stages of illness, may have persistent fatigue, muscle aches, short-term memory problems, and other nonspecific symptoms. Consequently, one of the highest priority research needs in the field of Lyme disease is to elucidate the specific cause or causes of symptoms in these patients and to determine the safest and most effective treatment options. This question is the focus of several current or recently published research studies in humans and non-human primates that are evaluating treatment response, clinical outcome, and the possibility of spirochete persistence following treatment (3-5). Another very high priority research need is for improved diagnostics. The currently validated diagnostic tests in common use for Lyme disease are all serologic tests that rely on a detectable antibody response. Consequently, these tests have limited value early in infection or in patients who have had prior infection, depending on how long ago the infection occurred. Some of the more promising research that is ongoing in this area focuses on the identification of direct diagnostic targets. These may either be nucleic acids or low molecular weight cellular metabolites that are indicators of active infection or a specific host-mediated response to infection. One last highly critical research need worth noting is for the development and evaluation of safe and effective prevention and control tools and methods. This topic will be discussed further below. In addition to these research needs, other critical needs must be addressed in order to establish and maintain an effective public health response. These include 1.) an accurate understanding of disease distribution and risk; 2.) an awareness of the disease among the public at risk and knowledge about how to protect themselves; 3.) informed healthcare providers who can recognize the disease and provide early and accurate diagnosis and treatment; 4.) validated prevention and control practices; and 5.) effective multi-level collaboration toward the goal of prevention. The remaining sections of this paper briefly discuss each of these topics.

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 imitation

Not 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.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.993
Threshold uncertainty score0.129

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.018
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.001
Science and technology studies0.0020.003
Scholarly communication0.0080.011
Open science0.0050.005
Research integrity0.0160.023
Insufficient payload (model declined to judge)0.0390.011

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.

Opus teacher head0.008
GPT teacher head0.225
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations10
Published2014
Admission routes2
Has abstractyes

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