The economic burden of Lyme disease and the cost-effectiveness of Lyme disease interventions: A scoping review
Bibliographic record
Abstract
INTRODUCTION: While Lyme disease (LD) is mostly treatable, misdiagnosed or untreated LD can result in debilitating sequelae and excessive healthcare usage. The objective of this review was to characterize the body of literature on the economic burden of Lyme disease (LD) and the cost-effectiveness of LD interventions, such as antibiotic treatment and vaccination. METHODS: We followed Joanna Briggs Institute scoping review methodologies. We systematically searched terms related to LD, economic evaluations, costs, and cost-effectiveness in Medline, Embase, PsycInfo, Cochrane Library, and the grey literature up to November 2017. We included primary economic evaluations conducted in North America and Europe, reporting LD-related costs or cost-effectiveness of human interventions. Two reviewers screened articles and charted data independently. Costs were standardized to 2017 United States dollars (USD). RESULTS: We screened 923 articles, and included 10 cost-effectiveness analyses (CEA) and 11 cost analyses (CA). Three CEAs concluded LD vaccination was likely cost-effective only in endemic areas (probability of infection ≥1%). However, LD vaccination is not currently available as an intervention in the US or Europe. Six studies assessed economic burden from a societal perspective and estimated significant annual national economic impact of: 735,550 USD for Scotland (0.14 USD per capita, population = 5.40M), 142,562 USD in Sweden (0.014 USD per capita, 9.96M), 40.88M USD in Germany (0.51 USD per capita, 80.59M), 23.12M USD in the Netherlands (1.36 USD per capita, 17.08M), and up to 786M USD in the US (2.41 USD per capita, 326.63M). CONCLUSIONS: Lyme disease imposes an economic burden that could be considered significant in the US and other developed countries to justify further research efforts in disease control and management. Societal costs for Lyme disease can be equally impactful as healthcare costs, but are not fully understood. Economic literature from countries with historically high incidence rates or increasing rates of Lyme disease are limited, and can be useful for future justification of resource allocation.
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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 | 0.015 | 0.093 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.017 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".