title: Lot quality assurance sampling (LQAS) for monitoring a leprosy elimination program.
abstract: In a statistical sense, prevalences of leprosy in different geographical areas can be called very low or rare. Conventional survey methods to monitor leprosy control programs, therefore, need large sample sizes, are expensive, and are time-consuming. Further, with the lowering of prevalence to the near-desired target level, 1 case per 10,000 population at national or subnational levels, the program administrator's concern will be shifted to smaller areas, e.g., districts, for assessment and, if needed, for necessary interventions. In this paper, Lot Quality Assurance Sampling (LQAS), a quality control tool in industry, is proposed to identify districts/regions having a prevalence of leprosy at or above a certain target level, e.g., 1 in 10,000. This technique can also be considered for identifying districts/regions at or below the target level of 1 per 10,000, i.e., areas where the elimination level is attained. For simulating various situations and strategies, a hypothetical computerized population of 10 million persons was created. This population mimics the actual population in terms of the empirical information on rural/urban distributions and the distribution of households by size for the state of Tamil Nadu, India. Various levels with respect to leprosy prevalence are created using this population. The distribution of the number of cases in the population was expected to follow the Poisson process, and this was also confirmed by examination. Sample sizes and corresponding critical values were computed using Poisson approximation. Initially, villages/towns are selected from the population and from each selected village/town households are selected using systematic sampling. Households instead of individuals are used as sampling units. This sampling procedure was simulated 1000 times in the computer from the base population. The results in four different prevalence situations meet the required limits of Type I error of 5% and 90% Power. It is concluded that after validation under field conditions, this method can be considered for a rapid assessment of the leprosy situation.
authors.affiliation: Institute for Research in Medical Statistics, Tamil Nadu, India.
authors.forename: M D
authors.initials: MD
authors.lastname: Gupte
authors.forename: B
authors.initials: B
authors.lastname: Narasimhamurthy
mesh_terms: D003198:Computer Simulation; D006801:Humans; D007918:Leprosy / Q000453:epidemiology / Q000517:prevention & control*; D008962:Models, Theoretical; D016012:Poisson Distribution; D015995:Prevalence; D015397:Program Evaluation / Q000379:methods*; D011785:Quality Assurance, Health Care / Q000379:methods*; D011786:Quality Control; D012494:Sampling Studies