Economic Burden of Herpes Zoster (“culebrilla”) in Latin America
Bibliographic record
Abstract
BACKGROUND: Herpes zoster (HZ) is characterized by debilitating pain and blistering dermatomal rash. The most common complication of HZ is postherpetic neuralgia (PHN), a persistent pain that can substantially affect patients' quality of life. HZ has significant impact on patients' lives with considerable implications for healthcare systems and society. The purpose of this study was to evaluate the healthcare resource utilization (HCRU) and medical costs associated with HZ in Latin America. METHOD: We conducted a pooled-analysis of three prospective cohort studies of HZ patients ≥50 years of age in Argentina (n=96); Brazil (n=145) and Mexico (n=142). Patients were recruited at different time-points during their HZ episode and were followed for six months. The incidence of PHN was defined as a worst ZBPI pain score of ≥3, persisting or appearing more than 90 days after the onset of rash. Work effectiveness was measured on a 100-point Likert scale where 100 was described as completely effective (able to work like before HZ began) and 0 as not effective at all. Direct costs included costs due to use of antiviral medications and all medical services used to treat HZ. Indirect cost was based on foregone earnings from patients due to work loss and presenteeism, and work loss by family caretakers. One-way sensitivity analysis was performed to assess the impact on total costs. All costs are reported in 2015 USD currency. RESULTS: 383 HZ patients were included and PHN incidence was 38.6%. The most commonly used resources were visits to the doctor's office (79.1% of patients), the emergency room (48.8%) and a specialist (37.9%); hospitalization was reported for 5.7% of patients. The overall direct cost per case was $763.19 USD, indirect cost was $701.40, for a total of $1,464.59 per HZ episode in Latin America. Total cost associated with HZ in patients with PHN was markedly higher compared to patients without PHN ($2,001.13 vs. $867.72, respectively) with indirect costs accounting for the most part of this difference. The sensitivity analysis was generally robust to changes in the assumptions made. CONCLUSION: HZ and its sequelae impose a substantial economic burden in Latin America which is expected to rise as the population ages and the number of HZ cases increases. The results support the need for early intervention, preventative strategies and improved disease management to reduce the HZ-associated disease burden in Latin America.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".