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Reconstructing Heroin Use Incidence: Statistical Method of RDA in Public Health Research

Explore the reconstruction of heroin use incidence curves using statistical method RDA. Learn about the principles and techniques in analyzing treatment data, including left and right truncation, and implications on estimating latency period. This study, funded by the Federal Public Service of Public Health, aims to provide valuable insights into the epidemic of drug addiction using Belgian data.

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Reconstructing Heroin Use Incidence: Statistical Method of RDA in Public Health Research

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  1. Reconstructing incidence of heroin use from treatment data Francis SARTOR Scientific Institute of Public Health Epidemiology Unit Brussels, Belgium

  2. Background • Collaborative study IPH-Biostatistical Unit at the University of Liège (Prof. A. Albert) aiming to investigate : • A compartment model for epidemic of drug addiction • Incidence curve of heroin use applied to Belgian data • Funded by Federal Public Service of Public Health • Local continuation of one of the TSER projects • Final report expected by end Augustus

  3. Reconstructing incidence curves using RDA : contents • Statistical method • Principle • Characteristics of treatment data used to calculate latency time (survival techniques) • Random sample (representative) • Effect of incomplete observation • Left & right truncation • Left censoring • Use of treatment data collected in a sample of 15 centres in the French Community(1993-98)

  4. Statistical method

  5. Principle of the RDA • Ex : adjusted (expected) incidence at time X • Ox : observed incidence at time X • F(x*-X) : cumulated frequency distribution of latency period (i.e the probability that an individual starting heroin use at time X demands a treatment for the first time not later than x*) can be estimated via survival analyses techniques

  6. Truncation & censoring

  7. Right & left truncation

  8. Cumulated frequency distribution of latency period • Ignore truncation problems : random sample assumption  empirical cumulated distribution • Only right truncated data : adapted life table techniques* can be used to estimate the conditional cumulated distribution *Lagakos et al, 1988; Kalfleish & Lawless, 1989.

  9. Cumulated frequency distribution of latency period • More difficult when data are both left & right truncated • Left censoring could be taken into account if unknown date at first use is known to have occurred before the start of the observation

  10. Sample of heroin users (n=2265) * used as a random sample of heroin users ** used in survival analyses with right truncated data

  11. Results

  12. Results

  13. Results

  14. Conclusions • Need of individual data on treatment demands • Random sample vs right/left truncation  sample size may  considerably • but, comparable adjustement by the 2 methods • need for comparisons in other countries/regions • Extended period of observation if epidemic peak closed to end of observation period • Effect on estimate of left censored & missing data should be studied

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