Development of a methodology for the quantification of reaerosolization of a biological contaminate surrogate particle from a military uniform fabric

Abstract

In a mass casualty medical evacuation after a bioaerosol (BA) dispersal event, a decontamination (DC) method is needed that can both decontaminate and prevent biological particle (BP) re-aerosolization (RA) of contaminated clothes. However, neither the efficacy of current DC methods nor the risk of BP RA is greatly explored in the existing literature. The goals of this study were to develop a repeatable method to quantify the RA of a biological contaminant off military uniform fabric swatches and to test the efficacy of one DC protocol (high-volume, low-pressure water) using 1 µm polystyrene latex (PSL) spheres as a surrogate. A four-step methodology was developed: contamination using a Collison Nebulizer; RA using a laboratory mixer and aerosol collection using an inhalable air sampler with a polyvinyl chloride filter; DC using a gravity-fed water shower; and quantification using ultraviolet microscopy via both visual and computer techniques. All results for uncontaminated control samples showed little to no presence of PSL sphere-like particles, while the contaminated experimental trials showed that RA was much lower after DC with water at the 99% confidence level (p-value = 0.0081). The water DC showed an average ∼73% reduction in particle RA, along with a change in air sampler filter deposition patterns from aerosol-like (before DC) to droplet-like (after DC). The fluorescent sphere contamination method for testing the DC residual risk of RA was repeatable and successful.

Keywords:

• Bioaerosol
• decontamination
• fluorescent
• image analysis
• PSL
• vibration

Disclosure statement

All authors declare they have no conflicts of interest.

Data availability statement

The data that support the findings of this study are openly available on the AFIT Scholar website at https://scholar.afit.edu/etd/5391/, reference number (AFIT Designator) AFIT-ENV-MS-22-M-187.

Additional information

Funding

The research described in this article has been funded wholly by the United States Air Force through the 711th Human Performance Wing, Grant Number 2020-055R, and was hosted by the Air Force Institute of Technology, Department of Systems Engineering and Management.