Keywords
Goals and objectives
Step | Instruction and Access |
---|---|
One | Visit UC Davis-LLNL POCT. |
Web site: http://www.ucdmc.ucdavis.edu/pathology/poctcenter | |
Two | The Clinical Needs Assessment survey link appears in the top right corner of the navigation bar. It is the first item under POC Technologies Center. Please click on “Needs Assessment Survey” |
Three | Please contact Keith Brock, Research Specialist, at 530 752 8471, email: tkbrock@ucdavis.edu, to receive an accession number |
Four | Follow the instructions on the screen to complete the survey. Note: Your progress will be saved after pressing the “next” button at the end of each page. Please note, your progress online is managed through your web browser cookies. Please complete the survey on the same computer and do not delete the cookies on your web browser before completion of the online survey |
Five | Thank you for your time and input on the survey! |
Needs assessment survey: preliminary results
Participants
Development
Procedures
Statistics
Preliminary results
Demography
Device Design








Pathogen Test Cluster Design
Weighted Score | Pathogen | |
---|---|---|
A. General disaster test cluster (n = 18) | 117 | Vibrio cholerae |
108 | Escherichia coli | |
100 | Staphylococcus aureus | |
77 | Yellow fever | |
73 | Salmonella enterica | |
66 | Pseudomonas aeruginosa | |
62 | Plasmodium falciparum | |
54 | Enterobacter species | |
49 | Dengue fever virus | |
38 | Klebsiella species | |
B. Blood donor screening test cluster (n = 23) | 224 | HIV 1 and 2 |
190 | Hepatitis B | |
190 | Hepatitis C | |
125.5 | Human T cell lymphotropic virus 1 and 2 (HTLV 1 and 2) | |
109.5 | West Nile virus | |
109 | Cytomegalovirus | |
93 | Dengue fever | |
77 | Parvovirus B19 | |
74 | Epstein-Barr virus | |
46 | Chikungunya | |
C. Bloodstream pathogen test cluster (n = 20) | 147 | Methicillin-resistant Staphylococcus aureus |
118 | Escherichia coli | |
91 | Pseudomonas aeruginosa | |
90.5 | Streptococcus pneumoniae | |
90 | Enterobacter species | |
87.5 | Methicillin-sensitive Staphylococcus aureus | |
79 | Klebsiella species | |
61 | Enterococcus faecalis | |
50 | Streptococcus pyogenes | |
48 | Coagulase-negative Staphylococcus | |
D. Pandemic test cluster (n = 22) | 189 | Influenza A/B |
121.5 | Parainfluenza 1, 2, 3 | |
115.5 | Streptococcus pneumoniae | |
112.5 | Respiratory syncytial virus | |
112.5 | Methicillin-resistant Staphylococcus aureus | |
100 | Haemophilus influenza | |
90.5 | Mycobacterium tuberculosis | |
87 | Adenovirus | |
57 | Mycoplasm pneumoniae | |
51.5 | Metapneumovirus |
Preliminary results versus current disaster pathogens
Scenario | Location, Year | Pathogens Detected (Isolation Site) | Path of Infection |
---|---|---|---|
Drought | Florida, 5 epidemics since 1952 7 , 8 | Saint Louis encephalitis (blood) | Vector borne |
West Nile (blood) | Vector borne | ||
Indonesia, 1997 9 | Malaria (blood) | Vector borne | |
Earthquake | California, 1994 10 | Coccidioides immitis (skin) | Dust cloud |
China, 2008 11 | Staphylococcus aureus (pus and wound) | Wound | |
Escherichia coli (pus and wound) | Wound | ||
Acinetobacter baumannii (pus and wound) | Wound | ||
Enterobacter cloacae (pus and wound) | Wound | ||
Pseudomonas aeruginosa (pus and wound) | Wound | ||
Turkey, 1999 12 | Pseudomonas aeruginosa (wound) | Wound | |
Acinetobacter baumannii (wound) | Wound | ||
Methicillin-resistant | |||
Staphylococcus aureus (wound) | Wound | ||
Candida species (wound) | Wound | ||
Turkey, 1999 13 | Acinetobacter species (wound) | Wound | |
Pseudomonas aeruginosa (wound, blood, urine) | Wound | ||
Methicillin-resistant | |||
Staphylococcus aureus (wound, blood, urine) | Wound | ||
Serratia marcescens (wound) | Wound | ||
Klebsiella pneumoniae (wound) | Wound | ||
Enterobacter species (wound) | Wound | ||
Candida albicans (wound) | Wound | ||
Flooding | Bangladesh, 2004 14 | Escherichia coli (blood) | Water, food borne |
Vibrio cholerae (stool) | |||
Global, 1980–2008 15 | Malaria (blood) | Vector borne | |
Yellow fever (blood) | Vector borne | ||
West Nile (blood) | Vector borne | ||
Dengue (blood) | Vector borne | ||
Indonesia, 2004 16 | Salmonella paratyphi (blood) | Water, food borne | |
Nonspecific 17 , 18 | Streptococcus pneumoniae (blood) | Inhalation | |
Hurricanes/tornadoes | Katrina, 2005 19 , 20 , 21 , 22 , 23 | Nontoxigenic Vibrio cholerae O1 (blood) | Food borne |
Vibrio cholerae non-O1 (blood) | Water borne | ||
Vibrio vulnificus (blood) | Wound, food borne | ||
Vibrio parahaemolyticus (blood) | Wound, food borne | ||
Methicillin-resistant | Wound | ||
Staphylococcus aureus (wound) | |||
Norovirus (stool) | Water borne | ||
Vibrio species (lake surface water) | Water borne | ||
Legionella species (lake surface water) | Water borne | ||
Cryptosporidium (interior canal water) | Water borne | ||
Giardia (interior canal water) | Water borne | ||
Escherichia coli (shoreline canal water) | Water borne | ||
Bifidobacterium (shoreline canal water) | Water borne | ||
Georgia, 2000 24 | Serratia marcescens (wound) | Wound | |
Pseudomonas aeruginosa (wound) | Wound | ||
Enterococcus (wound) | Wound | ||
Low-resource settings/rural areas | Indonesia, 2001–2003 16 | Salmonella enterica (blood) | Food, water borne |
Salmonella paratyphi (blood) | Food, water borne | ||
Salmonella typhi (blood) | Food, water borne | ||
Philippines, 1994–1996 25 | Streptococcus pneumoniae (blood) | Inhalation | |
Haemophilus influenzae (blood) | Inhalation | ||
Tsunamis | Thailand, 2004 26 , 27 , 28 , 29 | Aeromonas (pus and wound) | Wound |
Escherichia coli (stool) | Water, food borne | ||
Klebsiella pneumoniae (pus and wound) | Wound | ||
Pseudomonas aeruginosa (pus and wound) | Wound | ||
Burkolderia pseudomallei (blood) | Soil, water borne | ||
Acinetobacter baumannii (blood) | Soil, water borne | ||
Stenotrophomonas (blood) | Soil, water borne | ||
Methicillin-resistant | |||
Staphylococcus aureus (wound) | Wound | ||
Staphylococcus aureus (wound) | Wound | ||
Candida species (blood) | Inhalation, wound | ||
Aspergillus species (blood) | Inhalation, wound | ||
Scedosporium species (blood) | Inhalation, wound | ||
Salmonella species (well water) | Water borne | ||
Clostridium species (wound) | Soil | ||
Aeromonas species (wound) | Water borne | ||
World Trade Center disaster | New York, 2001 30 , 31 , 32 | Asthma and WTC cough (pathogens not named) |
Current use of POCT in disasters in the United States


Instrument/Manufacturer | Performance Characteristics (%) | ||||||
---|---|---|---|---|---|---|---|
Immunoassay Tests | Type | Target | Time | Sensitivity | Specificity | PPV | NPV |
3M Rapid Detection Flu A+B 34 http://www.3M.com, St. Paul, MN | Chromatographic immunoassay | Influenza A | 15 min | 70 | 100 | 99 | 93 |
Influenza B (nucleoprotein) | 87 | 99 | 88 | 98 | |||
BD Directigen EZ Flu A+B, http://www.bd.com, Franklin Lakes, NJ | Chromatographic immunoassay | Influenza A | 15 min | 77–91 | 86–99 | 60–98 | 93–95 |
Influenza B | 69–100 | 99–100 | 93–98 | 93–100 | |||
BD Directigen Flu A Kit http://www.bd.com, Franklin Lakes, NJ | Immunoassay | Influenza A (nucleoprotein) | 15 min | 67–96 | 88–97 | NA | NA |
BD Directigen Flu A + BKit 35 http://www.bd.com, Franklin Lakes, NJ | Immunoassay | Influenza A | 15 min | 77–96 | 90–91 | 63–71 | 94–99 |
Influenza B (nucleoprotein) | 71–88 | 98–100 | 82–100 | 98–100 | |||
BinaxNOW Influenza A&B 36 , http://www.binax.com, Scarborough, ME | Chromatographic immunoassay | Influenza A | 15 min | 77–83 | 96–99 | 88–97 | 95–96 |
Influenza B (nucleoprotein) | 50–69 | 100 | 82–100 | 99 | |||
ESPLINE Influenza A&B, 36 http://www.fujirebio.co.jp, Tokyo, Japan | Chromatographic immunoassay | Influenza A | 15 min | 67 | 100 | 100 | 89 |
Influenza B (nucleoprotein) | 30 | 100 | 100 | 96 | |||
fluID Rapid Influenza Test, http://www.hxdiagnostics.com, Emeryville, CA | Lateral flow immunoassay | Influenza A | NA | NA | NA | NA | NA |
Influenza B | NA | NA | NA | NA | NA | ||
Subtype A/H1 | NA | NA | NA | NA | NA | ||
Subtype A/H3 | NA | NA | NA | NA | NA | ||
Influ-A&B Respi-Strip, http://www.corisbio.com, Gembloux, Belgium | Chromatographic immunoassay | Influenza A | 15 min | 97 | 100 | 100 | 98 |
Influenza B (nucleoprotein) | 97 | 100 | 100 | 98 | |||
OSOM Influenza A & B Test, http://www.genzymediagnostics.com, Framingham, MA | Chromatographic immunoassay | Influenza A | 10 min | 74 | 96 | 90 | 90 |
Influenza B (nucleoprotein) | 60 | 96 | 73 | 94 | |||
panfluID Rapid Influenza Test, http://www.hxdiagnostics.com, Emeryville, CA | Lateral flow immunoassay | Avian Influenza | NA | NA | NA | NA | NA |
QuickVue Influenza A+B Test, http://www.quidel.com, San Diego, CA | Lateral flow immunoassay | Influenza A | 10 min | 77–94 | 89–99 | 62–91 | 95–99 |
Influenza B (nucleoprotein) | 62–82 | 97–99 | 80–90 | 94–97 | |||
QuickVue Influenza Test, http://www.quidel.com, San Diego, CA | Lateral flow immunoassay | Influenza A+B | 10 min | 73–81 | 96–99 | 92–96 | 85–93 |
No differentiation (nucleoprotein) | |||||||
Rockeby Influenza A Test, 36 , http://www.rockeby.com, Singapore | Immunoassay | Influenza A (nucleoprotein) | 10 min | 10 | 100 | 100 | 74 |
SAS FluAlert, http://www.sascientific.com, San Antonio, TX | Chromatographic immunoassay | Influenza A | 15 min | 76 | 98 | 93 | 91 |
Influenza B (nucleoprotein) | 15 min | 91 | 99–100 | 100 | 99 | ||
Xpect Flu A&B Test Kit, 37 http://www.remelinc.com, Lenexa, KS | Chromatographic immunoassay | Influenza A | 15 min | 90–100 | 100 | 100 | 97–100 |
Influenza B (nucleoprotein) | 83–100 | 100 | 100 | 99–100 | |||
Nucleic Acid Tests | |||||||
Primer design, http://www.primerdesign.co.uk, Southampton, UK | Real time qPCR | H1N1 (swine flu) | <2 h | NA | NA | NA | NA |
proFLU plus, http://www.prodesse.com, Waukesha, WI | Real time RT-PCR | Influenza A (matrix) | 3 h | 100 | 93 | 71 | 100 |
Influenza B (nonstructural NS1 & NS2) | 98 | 99 | 80 | 100 | |||
Instrument/Manufacturer | Performance Characteristics (%) | ||||||
Nucleic Acid Tests | Type | Target | Time | Sensitivity | Specificity | PPV | NPV |
xTAG Respiratory viral panel, 38 Luminex, http://www.luminexcorp.com, Austin, TX | Flow through microsphere array | Influenza A | <4 h | 98 | 100 | 99 | 100 |
H1 | |||||||
H3 | |||||||
H5 | |||||||
Influenza B | 94 | 100 | 100 | 100 | |||
SARS | |||||||
Corona virus NL63 | |||||||
Corona virus 229E | |||||||
Corona virus OC43 | |||||||
Corona virus HKU1 | |||||||
RSV, subtype A | |||||||
RSV, subtype B | |||||||
Parainfluenza 1 | |||||||
Parainfluenza 2 | |||||||
Parainfluenza 3 | |||||||
Parainfluenza 4 | |||||||
Metapneumovirus | |||||||
Rhinovirus/ | |||||||
Enterovirus | |||||||
Adenovirus |
Preparedness: gap analysis
- Novel new POC technologies for complex POCT in different global settings
Discovery
- Native sample testing from complex matrices with minimal prenalytical processing
- Cassette-contained sample processing to avoid (pathogen) contamination
- Back-end biohazard disposal in the same cassette, which can be disposed of intact
- Internal, automated, and electronic quality control; external proficiency testing
- Battery operation with flexible multiple power supplies
Operational characteristics
- Durable handheld and portable formats for different emergency settings
- Simple, fast, smart, and easy use codified to achieve CLIA-waived status
- Competency demonstrated beforehand as part of preparedness in disaster plan
- Standardized test results verified with “new math” (eg, LS MAD curves)
Format, licensing, and standardization
- Sensors on board to document location and environmental conditions
- Durable reagents and equipment not susceptible to environmental stresses
- Environmental certification based on dynamic stress testing
- Suitability for meteorologic profiles of disaster sites worldwide
Environmental robustness
- Quantitative POC tests capable of satisfactory accuracy, sensitivity, and specificity
- Multiplex or multiple patient testing with needs-based test clusters
- Index case (eg, H1N1) and risk (eg, HIV 1/2 in emergency blood donors) identification
- Broad-spectrum pathogen surveillance for hazards (eg, World Trade Center [WTC] cough)
- Mutations and detection of multiresistant strains (eg, tuberculosis) in challenging environments
Diagnostic performance
- Full user awareness of performance characteristics based on field evaluations
- Informatics compatibility, connectivity, and archival in small-world networks
- Risk indexing of diagnostic targets, wireless results reporting, and outcomes monitoring
- Cost-effectiveness for implementation in low-resource settings
Knowledge optimization
Integration strategy: POCT and small-world networks
Summary
Acknowledgments
References
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Article info
Footnotes
This study was supported by the Point-of-Care Testing Center for Teaching and Research (POCT•CTRSM), School of Medicine, University of California, Davis, and by a NIBIB Point-of-Care Technologies Center grant (Dr Kost, PI, NIH U54 EB007959). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Biomedical Imaging and Bioengineering or the National Institutes of Health.