Environmental sampling for disease surveillance: Recent advances and recommendations for best practice

Figures & data

Figure 1. A graphical representation of the framework for developing and evaluating environmental sampling activities. The 3 key questions, as well as the general answers are provided in the rings. Graphical depictions of technologies that may be employed are shown in the center, including (from top left):surface sampling, air sampling, water sampling, culture, protein detection, nucleic acid characterization, and real time aerosol monitoring (top center).

Table 1. Real-time bioaerosol measurement technologies, their operating principals, advantage and limitations.

Category	Technique	Excitation source	Target	Particle Size Range	Advantages	Limitations	References
Optical Spectroscopy	UV-LIF	Laser 266 nm 365 nm 355 nm UV-LED 275 nm – TacBio 405 nm – IBAC Xenon flash lamp (280 and 370 nn)	260 nm-280 nm aromatic amino acids, primarily tryptophan, tyrosine and phenylalanine 350–370 nm NADH, NAD+ 405 nm flavins e.g.riboflavin	Varies based on instrument. Widest range: 0.5 to 30 µm (WIBS-5, Droplet Measurement Technologies, Boulder, CO)	Single particleanalysis Widely studied and available. Can be made relatively inexpensively with small size, weight and power.	Fluorescence signaturecan change or degrade when exposed to natural conditions. Causes false negatives Does not identify species. Non-biological moleculesalso fluorescence in all the wavelength ranges. Causes false positives.	Sources and Targets Pinnick et al. (1998); Eversole et al. (1999); Pan et al. (1999); Sivaprakasam et al. (2011); Pan, Hill et al. (2014); Ho (2002); Ho, Spence, and Hairston (1999); Kaye et al. (2005) Limitations Pan et al. (2021); Kinahan et al. (2019); Ratnesar-Shumate et al. (2015); Pan, Santarpia et al. (2014); Santarpia, Collins et al. (2022); Savage et al. (2017)
	Raman	Laser 514–532 nm640 nm (	Bond structures that can indicate various biological molecules	Single particle, real-time analysis not available Only one integrated system (Resource Effective Bio-Identification System, Battelle, Columbus OH) does not indicate the size range of collected aerosol	Detailed information about molecular structure.	No single particleanalysis in a real-time system. Signature-based analysiswith signatures developed in the laboratory. Laboratory developed signatures do not translate well to field environments where background aerosol material can complicate signatures. Does not identify species.	Tripathi et al. (2009); Sengupta et al. (2005); Doughty and Hill (2017); Kalume et al. (2018); Wang et al. (2015);
	Elastic Light Scattering	Laser 465 nm (surfaceproperties 266 nm (shape;Visible diode laser (e.g. Model 3330, TSI Inc., USA; Model 11-D, Grimm GmbH, Germany)	Particle size, shape and surface roughness	Sizing>0.25 µm Shape and surface properties>1 µm	Accurate size information. Simple, inexpensive	Does not identify species. Nonspecific for biological aerosol. Primarily supporting information. Does not measure properties uniquely associated to biological aerosols.	Fu et al. (2017); Kaye et al. (2000)
	Polarized Light Scattering	Laser 532 nm	Circular Intensity Differential Scattering – DNA, RNA and other chiral molecules	>1 µm (only3 µm demonstrated)	Direct detection of DNA and RNA containing particles.	Does not identify species. Extremely new technique for bioaerosol	Pan, Kalume et al. (2022)
Mass Spectrometry	MALDI-MS	Laser − 308 nm	Proteins and peptides, lipids	0.2–10 µm	Direct analysis of proteins and lipids from single particles. Commonplace in biological laboratory analysis.	Signature-based analysiswith signatures developed in the laboratory. Laboratory developed signatures do not translate well to field environments where background aerosol material can complicate signatures. Complex and expensive	van Wuijckhuijse et al. (2005), Kleefsman et al. (2007), Kleefsman et al. (2008);Marvin, Roberts, and Fay (2003)
	Laser Ablation MS/SPAMS	Laser − 266 nm	Amino acids and smaller fragments	>2 µm	Detailed molecular information on single particles	Signature-based analysiswith signatures developed in the laboratory. Laboratory developed signatures do not translate well to field environments where background aerosol material can complicate signatures. Complex and expensive	Tobias et al. (2005); Fergenson et al. (2004); Gard et al. (1997); Russell et al. (2004)
Atomic Spectroscopy		Laser − 266 nm Spark	Elemental composition	Laser - >1 µm Spark – not single particle	Detailed molecular information from single	Does not identify species. Signature-based analysis with signatures developed in the laboratory. Laboratory developed signatures do not translate well to field environments where background aerosol material can complicate signatures.	Hybl, Lithgow, and Buckley (2003); Bauer and Sonnenfroh (2009)

Table 2. Overview of high-level analysis techniques for biological sampling identification. Sample recovery refers to the need to extract the sample from the collection substrate. *In some cases, bacteria and fungi can be collected onto growth media and cultivated from the collection surface. Analyte extraction refers to extracting the molecular analyte (typically nucleic acid or protein) from the recovered sample. **In some cases, proteins and nucleic acids can be detected from the collected sample without extraction or purification, particularly if surface proteins are the target or if extracellular DNA/RNA is present. Analyte conversion refers, in this case to the conversion of RNA to DNA for use in DNA amplification technologies. Analyte amplification refers to the amplification of the analyte to improve sensitivity. This applies most directly to sequencing application where a segment of DNA must be read multiple times (termed coverage) to ensure the sequence is accurate and the detection is confident. ***PCR and LAMP both implicitly amplify the analyte as a part of the detection process and can be used to amplify target DNA for downstream sequencing. Sensitivity refers to the fundamental sensitivity of the technique. Most nucleic acid detection techniques advertise single copy sensitivity, meaning that the technique can identify a single copy of the target sequence, but that does not account for instrument signal to noise, chemical inhibition or other factors that may decrease sensitivity.

Category	Molecular Analysis					Culture
General Technique	Immunoassay	PCR	Sequencing	CRISPR	LAMP	Viral	Bacterial/Fungal
Analyte	Protein	DNA/RNA	DNA/RNA	DNA/RNA	DNA/RNA	Intact Virus	Intact bacteria or fungal cell
Sample Recovery?	Yes	Yes	Yes	Yes	Yes	Yes	Yes*
Analyte Extraction?	Yes**	Yes**	Yes	Yes**	Yes**	No	No
Analyte Conversion?	No	RNA only	RNA only	No	RNA only	No	No
Analyte Amplification?	No	No***	Optional	No	No***	No	No
Sensitivity	Depends on antibody affinity and optical background Typical ELISA: 0.1 to 1 ng/mL Typical lateral flow assay: 10s of organisms per sample	100–200 copies/mL (assuming sample volume of 5–10 µL in reaction)	Depends on coverage needs	Can be comparable to qPCR (100–200 copies/mL)	100–200 copies/mL (assuming sample volume of 5–10 µL in reaction)	1 organism in assay volume, typically 1–10 virions/mL	1 organism in assay volume, typically 1–2 organisms/mL
Examples and overviews	Andreotti et al. (2003)	Santarpia et al. (2020); Liu et al. (2020); Blachere et al. (2009); Lindsley et al. (2010)	Lednicky et al. (2020)	Yin et al. (2021)	Notomi et al. (2000)	Santarpia, Herrera et al. (2022); Lednicky et al. (2020)	Sharma et al. (2005)

Pinnick, R.G., S.C. Hill, P. Nachman, G. Videen, G. Chen, and R.K. Chang. 1998. Aerosol fluorescence spectrum analyzer for rapid measurement of single micrometer-sized airborne biological particles. Aerosol Sci. Technol. 28 (2):95–104. doi:10.1080/02786829808965514.

 Web of Science ®Google Scholar

Eversole, J.D., J.J. Hardgrove, W.K. Cary, D.P. Choulas, and M. Seaver. 1999. Continuous, rapid biological aerosol detection with the use of UV fluorescence: Outdoor test results. Field. Anal Chem Technol 3 (4–5):249–59. https://doi.org/10.1002/(SICI)1520-6521(1999)3:4/5<249::AID-FACT4>3.0.CO;2-O

 Web of Science ®Google Scholar

Pan, Y.L., S. Holler, R.K. Chang, S.C. Hill, R.G. Pinnick, S. Niles, and J.R. Bottiger. 1999. Single-shot fluorescence spectra of individual micrometer-sized bioaerosols illuminated by a 351- or a 266-Nm ultraviolet laser. Opt. Lett. 24 (2):116. doi:10.1364/OL.24.000116.

 PubMed Web of Science ®Google Scholar

Sivaprakasam, V., H.B. Lin, A.L. Huston, and J.D. Eversole. 2011. Spectral characterization of biological aerosol particles using two-wavelength excited laser-induced fluorescence and elastic scattering measurements. Opt. Express 19 (7):6191. doi:10.1364/OE.19.006191.

 PubMed Web of Science ®Google Scholar

Pan, Y.-L., S.C. Hill, J.L. Santarpia, K. Brinkley, T. Sickler, M. Coleman, C. Williamson, K. Gurton, M. Felton, R.G. Pinnick, et al. 2014. Spectrally-resolved fluorescence cross sections of aerosolized biological live agents and simulants using five excitation wavelengths in a BSL-3 Laboratory. Opt. Express. 22 (7):8165–89. doi:10.1364/OE.22.008165.

 PubMed Web of Science ®Google Scholar

Ho, J. 2002. Future of biological aerosol detection. Anal. Chim. Acta 457 (1):125–48. doi:10.1016/S0003-2670(01)01592-6.

 Web of Science ®Google Scholar

Ho, J., M. Spence, and P. Hairston. 1999. Measurement of biological aerosol with a Fluorescent Aerodynamic Particle Sizer (Flaps): Correlation of optical data with biological data. Aerobiologia 15 (4):281–91. doi:10.1023/A:1007647522397.

 Google Scholar

Kaye, P.H., W.R. Stanley, E. Hirst, E.V. Foot, K.L. Baxter, and S.J. Barrington. 2005. Single particle multichannel bio-aerosol fluorescence sensor. Opt Express 13 (10):3583. doi:10.1364/OPEX.13.003583.

 PubMed Web of Science ®Google Scholar

Pan, Y.L., A. Kalume, C. Wang, and J.L. Santarpia. 2021. Atmospheric aging processes of bioaerosols under laboratory-controlled conditions: A review. J. Aerosol. Sci. 155 (June):105767. doi:10.1016/j.jaerosci.2021.105767.

 Google Scholar

Kinahan, S.M., M.S. Tezak, C.M. Siegrist, G. Lucero, B.L. Servantes, J.L. Santarpia, A. Kalume, J. Zhang, M. Felton, C.C. Williamson, et al. 2019. Changes of fluorescence spectra and viability from aging aerosolized E. Coli cells under various laboratory-controlled conditions in an advanced rotating drum. Aerosol. Sci. Technol. 53 (11):1261–76. doi:10.1080/02786826.2019.1653446.

 Web of Science ®Google Scholar

Ratnesar-Shumate, S., Y.-L. Pan, S.C. Hill, S. Kinahan, E. Corson, J. Eshbaugh, and L.S. Joshua. 2015. Fluorescence spectra and biological activity of aerosolized bacillus spores and MS2 bacteriophage exposed to ozone at different relative humidities in a rotating drum. J. Quant. Spectrosc. Radiat. Transf. 153:13–28. doi:10.1016/j.jqsrt.2014.10.003.

 Web of Science ®Google Scholar

Santarpia, J.L., D.R. Collins, S.A. Ratnesar-Shumate, C.C. Glen, A.L. Sanchez, C.G. Antonietti, J. Taylor, N.F. Taylor, C.A. Bare, S.M. Kinahan, et al. 2022. Changes in the fluorescence of biological particles exposed to environmental conditions in the national capitol region. Atmosphere. 13 (9):1358. doi:10.3390/atmos13091358.

 Web of Science ®Google Scholar

Savage, N.J., C.E. Krentz, T. Könemann, T.T. Han, G. Mainelis, C. Pöhlker, and J. Alex Huffman. 2017. Systematic characterization and fluorescence threshold strategies for the Wideband Integrated Bioaerosol Sensor (WIBS) using size-resolved biological and interfering particles. Atmos. Meas. Tech. 10 (11):4279–302. doi:10.5194/amt-10-4279-2017.

 Web of Science ®Google Scholar

Tripathi, A., R.E. Jabbour, J.A. Guicheteau, S.D. Christesen, D.K. Emge, A.W. Fountain, J.R. Bottiger, E.D. Emmons, and A. Peter Snyder. 2009. Bioaerosol analysis with raman chemical imaging microspectroscopy. Anal. Chem. 81 (16):6981–90. doi:10.1021/ac901074c.

 PubMed Web of Science ®Google Scholar

Sengupta, A., M.L. Laucks, N. Dildine, E. Drapala, and E.J. Davis. 2005. Bioaerosol characterization by Surface-Enhanced Raman Spectroscopy (SERS). J. Aerosol. Sci. 36 (5–6):651–64. doi:10.1016/j.jaerosci.2004.11.001.

 Web of Science ®Google Scholar

Doughty, D.C., and S.C. Hill. 2017. Automated aerosol raman spectrometer for semi-continuous sampling of atmospheric aerosol. J. Quant. Spectrosc. Radiat. Transf. 188 (February):103–17. doi:10.1016/J.JQSRT.2016.06.042.

 Google Scholar

Kalume, A., Z. Gong, C. Wang, J.L. Santarpia, and Y.-L. Pan. 2018. Detection and characterization of chemical and biological aerosols using laser-trapping single-particle raman spectroscopy. WIT Trans. Ecol. Environ. 230:323–29. doi:10.2495/AIR180301.

 Google Scholar

Wang, C., Y.L. Pan, S.C. Hill, and B. Redding. 2015. Photophoretic trapping-raman spectroscopy for single pollens and fungal spores trapped in air. J. Quant. Spectrosc. Radiat. Transf. 153 (March):4–12. doi:10.1016/j.jqsrt.2014.11.004.

 Google Scholar

Fu, R., C. Wang, O. Muñoz, G. Videen, J.L. Santarpia, and Y.L. Pan. 2017. Elastic back-scattering patterns via particle surface roughness and orientation from single trapped airborne aerosol particles. J. Quant. Spectrosc. Radiat. Transf. 187 (January):224–31. doi:10.1016/j.jqsrt.2016.09.018.

 Google Scholar

Kaye, P.H., J.E. Barton, E. Hirst, and J.M. Clark. 2000. Simultaneous light scattering and intrinsic fluorescence measurement for the classification of airborne particles. Appl. Opt. 39 (21):3738. doi:10.1364/AO.39.003738.

 PubMed Web of Science ®Google Scholar

Pan, Y.L., A. Kalume, J. Arnold, L. Beresnev, C. Wang, D.N. Rivera, K.K. Crown, and J.L. Santarpia. 2022. Measurement of Circular Intensity Differential Scattering (CIDS) from single airborne aerosol particles for bioaerosol detection and identification. Opt Express 30 (2):1442. doi:10.1364/OE.448288.

 PubMed Web of Science ®Google Scholar

van Wuijckhuijse, A.L., M.A. Stowers, W.A. Kleefsman, B.L.M. van Baar, C.E. Kientz, and J.C.M. Marijnissen. 2005. Matrix-assisted laser desorption/ionisation aerosol time-of-flight mass spectrometry for the analysis of bioaerosols: Development of a fast detector for airborne biological pathogens. J. Aerosol. Sci. 36 (5–6):677–87. doi:10.1016/j.jaerosci.2004.11.003.

 Web of Science ®Google Scholar

Kleefsman, I., M.A. Stowers, P.J.T. Verheijen, A.L. van Wuijckhuijse, C.E. Kientz, and J.C.M. Marijnissen. 2007. Bioaerosol analysis by single particle mass spectrometry. Part. Part. Syst. Charact. 24 (2):85–90. doi:10.1002/ppsc.200601049.

 Web of Science ®Google Scholar

Kleefsman, W.A., M.A. Stowers, P.J.T. Verheijen, and J.C.M. Marijnissen. 2008. Single particle mass spectrometry–bioaerosol analysis by MALDI MS. KONA Powder Part. J. 26: 205–14. doi:10.14356/kona.2008018.

 Web of Science ®Google Scholar

Marvin, L.F., M.A. Roberts, and L.B. Fay. 2003. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry in clinical chemistry. Clin. Chim. Acta 337 (1–2):11–21. doi:10.1016/j.cccn.2003.08.008.

 PubMed Web of Science ®Google Scholar

Tobias, H.J., M.P. Schafer, M. Pitesky, D.P. Fergenson, J. Horn, M. Frank, and E.E. Gard. 2005. Bioaerosol mass spectrometry for rapid detection of individual airborne Mycobacterium Tuberculosis H37Ra particles. Appl. Environ. Microbiol. 71 (10):6086–95. doi:10.1128/AEM.71.10.6086-6095.2005.

 PubMed Web of Science ®Google Scholar

Fergenson, D.P., M.E. Pitesky, H.J. Tobias, P.T. Steele, G.A. Czerwieniec, S.C. Russell, C.B. Lebrilla, J.M. Horn, K.R. Coffee, A. Srivastava, et al. 2004. Reagentless detection and classification of individual bioaerosol particles in seconds. Anal. Chem. 76 (2):373–78. doi:10.1021/ac034467e.

 PubMed Web of Science ®Google Scholar

Gard, E., J.E. Mayer, B.D. Morrical, T. Dienes, D.P. Fergenson, and K.A. Prather. 1997. Real-time analysis of individual atmospheric aerosol particles: Design and performance of a portable ATOFMS. Anal. Chem. 69 (20):4083–91. doi:10.1021/ac970540n.

 Web of Science ®Google Scholar

Russell, S.C., G. Czerwieniec, C. Lebrilla, H. Tobias, D.P. Fergenson, P. Steele, M. Pitesky, J. Horn, A. Srivastava, M. Frank, et al. 2004. Toward understanding the ionization of biomarkers from micrometer particles by bio-aerosol mass spectrometry. J. Am. Soc. Mass Spectrom. 15 (6):900–09. doi:10.1016/j.jasms.2004.02.013.

 PubMed Web of Science ®Google Scholar

Hybl, J.D., G.A. Lithgow, and S.G. Buckley. 2003. Laser-induced breakdown spectroscopy detection and classification of biological aerosols. Appl. Spectrosc. 57 (10):1207–15. doi:10.1366/000370203769699054.

 PubMed Web of Science ®Google Scholar

Bauer, A.J.R., and D.M. Sonnenfroh. 2009. Spark-induced breakdown spectroscopy-based classification of bioaerosols. In 2009 IEEE international workshop on Safety, Security & Rescue Robotics (SSRR 2009), 1–4. IEEE. doi:10.1109/SSRR.2009.5424145.

 Google Scholar

Andreotti, P. E., G. V. Ludwig, A. Harwood Peruski, J.J. Tuite, S. S. Morse, and L. F. Peruski. 2003. Immunoassay of infectious agents. Bio.Techniques 35 (4):850–59. doi:10.2144/03354ss02.

 PubMed Web of Science ®Google Scholar

Santarpia, J.L., D.N. Rivera, V.L. Herrera, M. Jane Morwitzer, H.M. Creager, G.W. Santarpia, K.K. Crown, D.M. Brett-Major, E.R. Schnaubelt, M.J. Broadhurst, et al. 2020. Aerosol and surface contamination of SARS-CoV-2 observed in quarantine and isolation care. Sci Rep. 10 (1):12732. doi:10.1038/s41598-020-69286-3.

 PubMed Web of Science ®Google Scholar

Liu, Y., Z. Ning, Y. Chen, M. Guo, Y. Liu, N. Kumar Gali, L. Sun, Y. Duan, J. Cai, D. Westerdahl, et al. 2020. Aerodynamic analysis of SARS-CoV-2 in two Wuhan hospitals. Nature. 582 (7813):557–60. doi:https://doi.org/10.1038/s41586-020-2271-3.

 PubMed Web of Science ®Google Scholar

Blachere, F.M., W.G. Lindsley, T.A. Pearce, S.E. Anderson, M. Fisher, R. Khakoo, B.J. Meade, O. Lander, S. Davis, R. Thewlis, et al. 2009. Measurement of airborne influenza virus in a hospital emergency department. Clin. Infect. Dis. 48 (4):438–40. doi:https://doi.org/10.1086/596478.

 PubMed Web of Science ®Google Scholar

Lindsley, W.G., F.M. Blachere, R.E. Thewlis, A. Vishnu, K.A. Davis, G. Cao, J.E. Palmer, K.E. Clark, M.A. Fisher, R. Khakoo, et al. 2010. Measurements of airborne influenza virus in aerosol particles from human coughs. PLoS ONE. 5 (11):e15100. doi:10.1371/journal.pone.0015100.

 PubMed Web of Science ®Google Scholar

Lednicky, J.A., Z.H.F. Michael Lauzard, A. Jutla, T.B. Tilly, M. Gangwar, M. Usmani, M. Usmani, S.N. Shankar, K. Mohamed, A. Eiguren-Fernandez, et al. 2020. Viable SARS-CoV-2 in the air of a hospital room with COVID-19 patients. Int. J. Infect. Dis. 100 (November):476–82. doi:10.1016/J.IJID.2020.09.025.

 PubMedGoogle Scholar

Yin, L., S. Man, Y. Shengying, G. Liu, and M. Long. 2021. CRISPR-Cas based virus detection: Recent advances and perspectives. Biosens. Bioelectron. 193 (December):113541. doi:10.1016/j.bios.2021.113541.

 PubMedGoogle Scholar

Notomi, T., H. Okayama, H. Masubuchi, T. Yonekawa, K. Watanabe, N. Amino, and T. Hase. 2000. Loop-mediated isothermal amplification of DNA. Nucleic Acids Res. 28 (12):63e–663. doi:10.1093/nar/28.12.e63.

 PubMed Web of Science ®Google Scholar

Santarpia, J.L., V.L. Herrera, D.N. Rivera, S. Ratnesar-Shumate, S. Patrick Reid, D.N. Ackerman, P.W. Denton, J.W.S. Martens, Y. Fang, N. Conoan, et al. 2022. The size and culturability of patient-generated SARS-CoV-2 aerosol. J. Expo. Sci. Environ. Epidemiol. 32 (5):706–11. doi:10.1038/s41370-021-00376-8.

 PubMed Web of Science ®Google Scholar

Sharma, R., R. Ranjan, R. Kishor Kapardar, and A. Grover. 2005. ‘Unculturable’ bacterial diversity: An untapped resource. Curr. Sci. 89 (1): 72–77.

 Web of Science ®Google Scholar