Analytical predictive bayesian assessment of occupational injury risk: Municipal solid waste collectors

James Douglas Englehardt, Huren An, Lora E. Fleming, Judy A. Bean

Research output: Contribution to journalArticle

20 Citations (Scopus)

Abstract

Unlike other waste streams, municipal solid waste (MSW) is collected manually, and MSW collection has recently been found to be among the highest-risk occupations in the United States. However, as for other occupational groups, actual total injury rates, including the great majority of injuries not compensated and those compensated by other insurance, are not known. In this article a predictive Bayesian method of assessing total injury rates from available information without computation is presented, and used to assess the actual numbers of musculoskeletal and dermal injuries requiring clinical care of MSW workers in Florida. Closed-form predictive Bayesian distributions that narrow progressively in response to information, representing both uncertainty and variability, are presented. Available information included workers' compensation (WC) data, worker population data, and safety records for one private and one public collection agency. Subjective input comprised epidemiological and medical judgment based on a review of 165 articles. The number of injuries was assessed at 3,146 annually in Florida, or 54 ± 18 injuries per 100 workers per year with 95% confidence. Further, WC data indicate that the injury rate is 50% higher for garbage collectors specifically, indicating a rate of approximately 80 per 100 workers. Results, though subject to uncertainty in worker numbers and classification and reporting bias, agreed closely with a survey of 251 MSW collectors, of whom 75% reported being injured (and 70% reported illness) within the past 12 months. The approach is recommended for assessment of total injury rates and, where sufficient information exists, for the more difficult assessment of occupational disease rates.

Original languageEnglish
Pages (from-to)917-927
Number of pages11
JournalRisk Analysis
Volume23
Issue number5
DOIs
StatePublished - Oct 1 2003

Fingerprint

Occupational risks
Occupational Injuries
Solid Waste
occupational injury
Municipal solid waste
worker
Wounds and Injuries
Occupational diseases
Workers' Compensation
available information
Insurance
Uncertainty
uncertainty
occupational disease
Garbage
occupational group
Occupational Groups
Bayes Theorem
Occupational Diseases
insurance

Keywords

  • Collector
  • Injury
  • Occupational safety
  • Predictive Bayesian
  • Solid waste worker

ASJC Scopus subject areas

  • Social Sciences (miscellaneous)
  • Safety, Risk, Reliability and Quality

Cite this

Analytical predictive bayesian assessment of occupational injury risk : Municipal solid waste collectors. / Englehardt, James Douglas; An, Huren; Fleming, Lora E.; Bean, Judy A.

In: Risk Analysis, Vol. 23, No. 5, 01.10.2003, p. 917-927.

Research output: Contribution to journalArticle

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