Technical Note

Evaluation of errors and limits of the 63-μm house-dust-fraction method, a surrogate to predict hidden moisture damage

Christoph Baudisch¹ , Ojan Assadian² and Axel Kramer³

¹  State Health and Social Office of Mecklenburg-Pomerania, Branch Office Schwerin, Germany

²  Clinical Institute for Hygiene and Medical Microbiology of the Medical University of Vienna, Department of Hospital Hygiene, Vienna General Hospital, Waehringer Guertel 18-20, 1090 Vienna, Austria

³  Institute for Hygiene and Environmental Medicine, Ernst Moritz Arndt University, Greifswald, Germany

author email corresponding author email

BMC Research Notes 2009, 2:218doi:10.1186/1756-0500-2-218

Published:	24 October 2009

Abstract

Background

The aim of this study is to analyze possible random and systematic measurement errors and to detect methodological limits of the previously established method.

Findings

To examine the distribution of random errors (repeatability standard deviation) of the detection procedure, collective samples were taken from two uncontaminated rooms using a sampling vacuum cleaner, and 10 sub-samples each were examined with 3 parallel cultivation plates (DG18). In this two collective samples of new dust, the total counts of Aspergillus spp. varied moderately by 25 and 29% (both 9 cfu per plate). At an average of 28 cfu/plate, the total number varied only by 13%.

For the evaluation of the influence of old dust, old and fresh dust samples were examined. In both cases with old dust, the old dust influenced the results indicating false positive results, where hidden moist was indicated but was not present. To quantify the influence of sand and sieving, 13 sites were sampled in parallel using the 63-μm- and total dust collection approaches. Sieving to 63-μm resulted in a more then 10-fold enrichment, due to the different quantity of inert sand in each total dust sample.

Conclusion

The major errors during the quantitative evaluation from house dust samples for mould fungi as reference values for assessment resulted from missing filtration, contamination with old dust and the massive influence of soil. If the assessment is guided by indicator genera, the percentage standard deviation lies in a moderate range.