Fieldwork-based determination of design priorities for point-of-use drinking water quality sensors for use in resource-limited environments
Autoři:
Michael S. Bono, Jr. aff001; Sydney Beasley aff002; Emily Hanhauser aff001; A. John Hart aff001; Rohit Karnik aff001; Chintan Vaishnav aff002
Působiště autorů:
Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States of America
aff001; Tata Center for Technology and Design, Massachusetts Institute of Technology, Cambridge, MA, United States of America
aff002; Technology and Policy Program, Massachusetts Institute of Technology, Cambridge, MA, United States of America
aff003; Department of Urban Studies and Planning, Massachusetts Institute of Technology, Cambridge, MA, United States of America
aff004; Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, United States of America
aff005
Vyšlo v časopise:
PLoS ONE 15(1)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0228140
Souhrn
Improved capabilities in microfluidics, electrochemistry, and portable assays have resulted in the development of a wide range of point-of-use sensors intended for environmental, medical, and agricultural applications in resource-limited environments of developing countries. However, these devices are frequently developed without direct interaction with their often-remote intended user base, creating the potential for a disconnect between users’ actual needs and those perceived by sensor developers. As different analytical techniques have inherent strengths and limitations, effective measurement solution development requires determination of desired sensor attributes early in the development process. In this work, we present our findings on design priorities for point-of-use microbial water sensors based on fieldwork in rural India, as well as a guide to fieldwork methodologies for determining desired sensor attributes. We utilized group design workshops for initial identification of design priorities, and then conducted choice-based conjoint analysis interviews for quantification of user preferences among these priorities. We found the highest user preference for integrated reporting of contaminant concentration and recommended actions, as well as significant preferences for mostly reusable sensor architectures, same-day results, and combined ingredients. These findings serve as a framework for future microbial sensor development and a guide for fieldwork-based understanding of user needs.
Klíčová slova:
Contaminants – Ecological remediation – Electrochemistry – Sanitation – Water pollution – Water quality – Water resources – Workshops
Zdroje
1. Jaworska E, Schmidt M, Scarpa G, Maksymiuk K, Michalska A. Spray-coated all-solid-state potentiometric sensors. Analyst. 2014;139:6010–6015. doi: 10.1039/c4an01277a 25270688
2. Khan AA, Shaheen S. Determination of arsenate in water by anion selective membrane electrode using polyurethane–silica gel fibrous anion exchanger composite. Journal of Hazardous Materials. 2014;264:84–90. doi: 10.1016/j.jhazmat.2013.10.061 24275475
3. Rosenberg R, Bono MS Jr, Braganza S, Vaishnav C, Karnik R, Hart AJ. In-field determination of soil ion content using a handheld device and screen-printed solid-state ion-selective electrodes. PLOS ONE. 2018;13(9):e0203862. doi: 10.1371/journal.pone.0203862 30252859
4. Jokerst JC, Adkins JA, Bisha B, Mentele MM, Goodridge LD, Henry CS. Development of a Paper-Based Analytical Device for Colorimetric Detection of Select Foodborne Pathogens. Analytical Chemistry. 2012;84(6):2900–2907. doi: 10.1021/ac203466y 22320200
5. Derda R, Lockett MR, Tang SKY, Fuller RC, Maxwell EJ, Breiten B, et al. Filter-Based Assay for Escherichia coli in Aqueous Samples Using Bacteriophage-Based Amplification. Analytical Chemistry. 2013;85(15):7213–7220. doi: 10.1021/ac400961b 23848541
6. Gunda NSK, Naicker S, Shinde S, Kimbahune S, Shrivastavac S, Mitra S. Mobile Water Kit (MWK): a smartphone compatible low-cost water monitoring system for rapid detection of total coliform and E. coli. Analytical Methods. 2014;6(16):6139–6590.
7. Park TS, Yoon JY. Smartphone Detection of Escherichia coli From Field Water Samples on Paper Microfluidics. IEEE Sensors Journal. 2015;15(3):1902–1907. doi: 10.1109/JSEN.2014.2367039
8. Gunda NSK, Chavali R, Mitra SK. A hydrogel based rapid test method for detection of Escherichia coli (E. coli) in contaminated water samples. Analyst. 2016;141:2920–2929. doi: 10.1039/c6an00400h 27137782
9. Hinkley TC, Garing S, Singh, L Ny ALM, Nichols KP, Peters JE, et al. Reporter bacteriophage T7NLC utilizes a novel NanoLuc::CBM fusion for the ultrasensitive detection of Escherichia coli in water. Analyst. 2018;143:4074–4082. doi: 10.1039/c8an00781k 30069563
10. Gunda NSK, Gautam SH, Mitra SK. Artificial Intelligence Based Mobile Application for Water Quality Monitoring. Journal of The Electrochemical Society. 2019;166(9):B3031–B3035. doi: 10.1149/2.0081909jes
11. Shafiee H, Kanakasabapathy MK, Juillard F, Keser M, Sadasivam M, Yuksekkaya M, et al. Printed Flexible Plastic Microchip for Viral Load Measurement through Quantitative Detection of Viruses in Plasma and Saliva. Scientific Reports. 2015;5:9919. doi: 10.1038/srep09919 26046668
12. Jiang L, Mancuso M, Lu Z, Akar G, Cesarman E, Erickson D. Solar thermal polymerase chain reaction for smartphone-assisted molecular diagnostics. Scientific Reports. 2014;4:4137. doi: 10.1038/srep04137 24553130
13. Song Y, Gyarmati P, Araújo AC, Lundeberg J, Brumer H, Ståhl PL. Visual Detection of DNA on Paper Chips. Analytical Chemistry. 2014;86(3):1575–1582. doi: 10.1021/ac403196b 24383957
14. Rodriguez NM, Linnes JC, Fan A, Ellenson CK, Pollock NR, Klapperick CM. Paper-Based RNA Extraction, in Situ Isothermal Amplification, and Lateral Flow Detection for Low-Cost, Rapid Diagnosis of Influenza A (H1N1) from Clinical Specimens. Analytical Chemistry. 2015;87(15):7872–7879. doi: 10.1021/acs.analchem.5b01594 26125635
15. Bain R, Bartram J, Elliot M, Matthews R, McMahan L, Tung R, et al. A Summary Catalogue of Microbial Drinking Water Tests for Low and Medium Resource Settings. International Journal of Environmental Research and Public Healthy. 2012;9:1609–1625. doi: 10.3390/ijerph9051609
16. UNICEF and World Health Organization. Progress on Sanitation and Drinking Water—2015 Update and MDG Assessment. Geneva, Switzerland: World Health Organization; 2015.
17. World Health Organization. Quantifying selected major risks to health. In: The World Health Report 2002; 2002.
18. Liu L, Johnson HL, Cousens S, Perin J, Scott S, Lawn JE, et al. Global, regional, and national causes of child mortality: an updated systematic analysis for 2010 with time trends since 2000. The Lancet. 2012;379:2151–2161. doi: 10.1016/S0140-6736(12)60560-1
19. World Health Organization. Guidelines for Drinking-water Quality. Geneva, Switzerland: World Health Organization; 2011.
20. Peal A, Evans B, van der Voorden C. Hygiene and Sanitation Software: An Overview of Approaches. Water Supply & Sanitation Collaborative Council; 2010.
21. Mosler HJ. A systematic approach to behavior change interventions for the water and sanitation sector in developing countries: a conceptual model, a review, and a guideline. International Journal of Environmental Health Research. 2012;22(5):431–449. doi: 10.1080/09603123.2011.650156 22292899
22. Mbuya MNN, Tavengwa NV, Stoltzfus RJ, Curtis V, Pelto GH, Ntozini R, et al. Design of an Intervention to Minimize Ingestion of Fecal Microbes by Young Children in Rural Zimbabwe. Clinical Infectious Diseases. 2015;61(Suppl 7):S703–S709. doi: 10.1093/cid/civ845 26602297
23. Gautam A. Understanding Behavior Change for Ending Open Defecation in Rural India: A Review of India’s Sanitation Policy Efforts. In: Yoshino N, Araral E, Ram KS, editors. Water Security and Sanitation in Asia. Tokyo, Japan: Asian Development Bank Institute; 2019.
24. Jalan J, Somanathan E. The importance of being informed: Experimental evidence on demand for environmental quality. Journal of Development Economics. 2008;87:14–28. doi: 10.1016/j.jdeveco.2007.10.002
25. Hamoudi A, Jeuland M, Lombardo S, Patil S, Pattanayak SK, Rai S. The Effect of Water Quality Testing on Household Behavior: Evidence from an Experiment in Rural India. American Journal of Tropical Medicine and Hygiene. 2012;87(1):18–22. doi: 10.4269/ajtmh.2012.12-0051 22764286
26. Brown J, Hamoudi A, Jeuland M, Turrini G. Seeing, Believing, and Behaving: Heterogenous Effects of an Information Intervention on Household Water Treatment. Journal of Environmental Economics and Management. 2017;86:141–159. doi: 10.1016/j.jeem.2016.08.005
27. Trent M, Dreibelbis R, Bir A, Tripathi SN, Labhasetwar P, Nagarnaik P, et al. Access to Household Water Quality Information Leads to Safer Water: A Cluster Randomized Controlled Trial in india. Environmental Science & Technology. 2018;52:5319–5329. doi: 10.1021/acs.est.8b00035
28. Manja KS, Maurya MS, Rao KM. A simple field test for the detection of faecal pollution in drinking water. Bulletin of the World Health Organization. 1982;60(5):797–801. 6983930
29. Wright JA, Yang H, Walker K, Pedley S, Elliott J, Gundry SW. The H2S test versus standard indicator bacteria tests for faecal contamination of water: systematic review and meta-analysis. Tropical Medicine and International Health. 2012;17(1):94–105. doi: 10.1111/j.1365-3156.2011.02887.x 21951335
30. Murcott S, Keegan M, Hanson A, Jain A, Knutson J, Liu S, et al. Evaluation of microbial water quality tests for humanitarian emergency and development settings. Procedia Engineering. 2015;107:237–246. doi: 10.1016/j.proeng.2015.06.078
31. Tryland I, Fiksdal L. Enzyme Characteristics of β-D-Galactosidase- and β-D-Glucuronidase-Positive Bacteria and Their Interference in Rapid Methods for Detection of Waterborne Coliforms and Escherichia coli. Applied and Environmental Microbiology. 1998;64(3):1018–1023. doi: 10.1128/AEM.64.3.1018-1023.1998 9501441
32. Burnet JB, Dinh QT, Imbeault S, Servais P, Dorner S, Prévost M. Autonomous online measurement of β-D-glucuronidase activity in surface water: is it suitable for rapid E. coli monitoring? Water Research. 2019;152:241–250. doi: 10.1016/j.watres.2018.12.060 30677635
33. Mabey D, Peeling RW, Ustianowski A, Perkins MD. Diagnostics for the Developing World. Nature Reviews Microbiology. 2004;2:231–240. doi: 10.1038/nrmicro841 15083158
34. Peeling RW, Holmes KK, Mabey D, Ronald A. Rapid tests for sexually transmitted infections (STIs): the way forward. Sexually Transmitted Infections. 2006;82(suppl 5):v1–v6. doi: 10.1136/sti.2006.024265 17151023
35. Kumar AA, Hennek JW, Smith BS, Kumar S, Beattie P, Jain S, et al. Diagnostics for the Developing World. Angewandte Chemie International Edition. 2015;54:5836–5853.
36. Kosack CS, Page AL, Klatser PR. A guide to aid the selection of diagnostic tests. Bulletin of the World Health Organization. 2017;95:639–645. doi: 10.2471/BLT.16.187468 28867844
37. Yamada K, Shibata H, Suzuki K, Citterio D. Toward practical application of paper-based microfluidics for medical diagnostics: state-of-the-art and challenges. Lab on a Chip. 2017;17:1206–1249. doi: 10.1039/c6lc01577h 28251200
38. Laczka O, García-Aljaro C, del Campo FJ, Pascual FXM, Mas-Gordi J, Baldrich E. Amperometric detection of Enterobacteriaceae in river water by measuring β-galactosidase activity at interdigitated microelectrode arrays. Analytica Chimica Acta. 2010;677:156–161. doi: 10.1016/j.aca.2010.08.001 20837182
39. Bono MS, Beasley SB, Hanhauser EB, Vaishnav C, Hart AJ, Karnik RN. Systems, Devices, and Methods for Point-of-Use Testing for Fluid Contamination; Filed Oct. 18, 2017. U.S. PCT Patent Application No. PCT/US2017/057265.
40. Ryzinska-Paier G, Lendenfeld T, Correa K, Stadler P, Blaschke AP, Mach RL, et al. A sensitive and robust method for automated on-line monitoring of enzymatic activities in water and water resources. Water Science & Technology. 2014;69(6):1349–1358. doi: 10.2166/wst.2014.032
41. Nie Z, Deiss F, Liu X, Akbulut O, Whitesides GM. Integration of paper-based microfluidic devices with commercial electrochemical readers. Lab on a Chip. 2010;10:3163–3169. doi: 10.1039/c0lc00237b 20927458
42. Derda R, Gitaka J, Klapperich CM, Mace CR, Kumar AA, Lieberman M, et al. Enabling the Development and Deployment of Next Generation Point-of-Care Diagnostics. PLOS Neglected Tropical Diseases. 2015;9(5):e0003676. doi: 10.1371/journal.pntd.0003676 25973602
43. Peeling RW, Smith PG, Bossuyt PMM. A guide for diagnostic evaluations. Nature Reviews Microbiology. 2006;4:S2–S6. doi: 10.1038/nrmicro1522
44. Zysk AM, Nguyen FT, Oldenburg AL, Marks DL, Boppart SA. Optical coherence tomography: a review of clinical development from bench to bedside. Journal of Biomedical Optics. 2007;12(5):051403. doi: 10.1117/1.2793736 17994864
45. Poulos C, Yang JC, Patil SR, Pattanayak S, Wood S, Goodyear L, et al. Consumer preferences for household water treatment products in Andhra Pradesh, India. Social Science & Medicine. 2012;75:738–746. doi: 10.1016/j.socscimed.2012.02.059
46. de Bekker-Grob EW, Donkers B, Jonker MF, Stolk EA. Sample Size Requirements for Discrete-Choice Experiments in Healthcare: a Practical Guide. Patient. 2015;8:373–384. doi: 10.1007/s40271-015-0118-z 25726010
47. Whitmore GA, Cavadias GS. Experimental determination of community preferences for water quality-cost alternatives. Decision Sciences. 1974;5:614–631. doi: 10.1111/j.1540-5915.1974.tb00641.x
48. Farber S, Griner B. Using Conjoint Analysis To Value Ecosystem Change. Environmental Science & Technology. 2000;34:1407–1412. doi: 10.1021/es990727r
49. National Ethical Guidelines For Biomedical And Health Research Involving Human Participants. New Delhi, India: Indian Council of Medical Research; 2017.
50. Lovecraft AL, Meek C, Eicken H. Connecting scientific observations to stakeholder needs in sea ice social–environmental systems: the institutional geography of northern Alaska. Polar Geography. 2013;36(1–2):105–125. doi: 10.1080/1088937X.2012.733893
51. Beasley SB. Implementing water and sanitation systems in rural India: the role of NGOs. Massachusetts Institute of Technology. Cambridge, Massachusetts, USA; 2018.
52. World Health Organization & Stop TB Partnership. Advocacy, communication and social mobilization for TB control: a guide to developing knowledge, attitude and practice surveys. Geneva, Switzerland: World Health Organization; 2008.
53. Médecins du Monde. Data Collection >> Quantitative Methods. In: The KAP Survey Model (Knowledge, Attitude & Practices). Paris, France: Médecins du Monde; 2011.
54. Louviere JJ. Quantitative Applications in the Social Sciences. In: Analyzing Decision Making: Metric Conjoint Analysis. vol. 67. 1st ed. Thousand Oaks, California, USA: SAGE Publications; 1988.
55. Green PE, Srinivasan V. Conjoint Analysis in Marketing: New Developments With Implications for Research and Practice. Journal of Marketing. 1990;54(4):3–19. doi: 10.2307/1251756
56. Kessels R, Jones B, Goos P. Bayesian Optimal Designs for Discrete Choice Experiments with Partial Profiles. Journal of Choice Modelling. 2011;4(3):52–74. doi: 10.1016/S1755-5345(13)70042-3
57. Vaishnav C, Beasley S, Bono M, Kothari V, Sharma S, Mallik A. The Evolutionary Dynamics of Indias Rural Water Systems: Part I. In: 35th International Conference of the System Dynamics Society; 2017.
58. Benjamin DJ, Berger JO, Johannesson M, Nosek BA, Wagenmakers EJ, Berk R, et al. Redefine statistical significance. Nature Human Behaviour. 2018;2:6–10. doi: 10.1038/s41562-017-0189-z 30980045
59. Ashbolt NJ. Microbial contamination of drinking water and disease outcomes in developing regions. Toxicology. 2004;198(1-3):229–238. doi: 10.1016/j.tox.2004.01.030 15138046
60. Department of Drinking Water and Sanitation. Strategic Plan—2011–2022: Ensuring Drinking Water Security In Rural India. New Delhi, India: Government of India; 2011.
61. Smedley PL, Kinniburgh DG. A review of the source, behaviour and distribution of arsenic in natural waters. Applied Geochemistry. 2002;17:517–568. doi: 10.1016/S0883-2927(02)00018-5
62. Davis C. Arsenic mitigation in Bangladesh: Progress of the UNICEF-DPHE Arsenic Mitigation Project 2002. In: Chappel WR, Abernathy CO, Calderon RI, Thomas DJ, editors. Arsenic exposure and health effects V: Proceedings of the fifth International Conference on Arsenic Exposure and Health Effects; 2003.
63. Brooks D, Cech I. Nitrates and bacterial distribution in rural domestic water supplies. Water Research. 1979;13(1):33–41. doi: 10.1016/0043-1354(79)90251-3
64. Kronimus A, Schwarzbauer J, Dsikowitzky L, Heim S, Littke R. Anthropogenic organic contaminants in sediments of the Lippe river, Germany. Water research. 2004;38(16):3473–3484. doi: 10.1016/j.watres.2004.04.054 15325173
65. IS 10500: Drinking water—Specification. New Delhi, India: Bureau of Indian Standards; 2012.
66. IS 1622 (1981, Reaffirmed 1996): Methods of Sampling and Microbiological Examination of Water (First Revision). New Delhi, India: Bureau of Indian Standards; 1981.
67. Crocker J, Bartram J. Comparison and Cost Analysis of Drinking Water Quality Monitoring Requirements versus Practice in Seven Developing Countries. International Journal of Environmental Research and Public Healthy. 2014;11:7333–7346. doi: 10.3390/ijerph110707333
68. Delaire C, Peletz R, Kumpel E, Kisiangani J, Bain R, Khush R. How Much Will It Cost To Monitor Microbial Drinking Water Quality in Sub-Saharan Africa? Environmental Science & Technology. 2017;51(11):5869–5878. doi: 10.1021/acs.est.6b06442
69. Guthmann JP, Klovstad H, Boccia D, Hamid N, Pinoges L, Nizou JY, et al. A Large Outbreak of Hepatitis E among a Displaced Population in Darfur, Sudan, 2004: The Role of Water Treatment Methods. Clinical Infectious Diseases. 2006;42(12):1685–1691. doi: 10.1086/504321 16705572
70. Schriewer A, Odagiri M, Wuertz S, Misra PR, Panigrahi P, Clasen T, et al. Human and animal fecal contamination of community water sources, stored drinking water and hands in rural India measured with validated microbial source tracking assays. The American journal of tropical medicine and hygiene. 2015;93(3):509–516. doi: 10.4269/ajtmh.14-0824 26149868
71. Wescoat JL, Fletcher S, Novellino M. National rural drinking water monitoring: progress and challenges with India’s IMIS database. Water Policy. 2016;18(4):1015–1032. doi: 10.2166/wp.2016.158
72. O’Toole M, Diamond D. Absorbance Based Light Emitting Diode Optical Sensors and Sensing Devices. Sensors. 2008;8:2453–2479. doi: 10.3390/s8042453 27879829
73. Albert DR, Todt MA, Davis HF. A Low-Cost Quantitative Absorption Spectrophotometer. Journal of Chemical Education. 2012;89:1432–1435. doi: 10.1021/ed200829d
74. Stephenson D. A Portable Diode Array Spectrophotometer. Applied Spectroscopy. 2016;70(5):874–878. doi: 10.1177/0003702816638292 27036399
75. Smith ZJ, Chu K, Espenson AR, Rahimzadeh M, Gryshuk A, Molinaro M, et al. Cell-Phone-Based Platform for Biomedical Device Development and Education Applications. PLOS ONE. 2011;6(3):e17150. doi: 10.1371/journal.pone.0017150 21399693
76. Barbosa AI, Gehlot P, Sidapra K, Edwards AD, Reis NM. Portable smartphone quantitation of prostate specific antigen (PSA) in a fluoropolymer microfluidic device. Biosensors and Bioelectronics. 2015;70:5–14. doi: 10.1016/j.bios.2015.03.006 25775968
77. Annala L, Beasley S, Green J, Murcott S, Parikh V, Pesek SL, et al. Streamlining a Methodology for Product Evaluation—Water Test Kits in Ahmedabad, India. Cambridge, Massachusetts, USA: Massachusetts Institute of Technology Comprehensive Initiative on Technology Evaluation; 2016.
78. Rosenberg R. Screen-printed Ion Selective Electrodes for Soil Ion Detection. Massachusetts Institute of Technology. Cambridge, Massachusetts, USA; 2016.
79. Midstokke PK. Adapting a Hazards-Risk Model to Water Scarcity in Rural India—Aurangabad Case Study. Massachusetts Institute of Technology. Cambridge, Massachusetts, USA; 2018.
80. Hui R, Wescoat JL Jr. Visualizing peri-urban and rurban water conditions in Pune district, Maharashtra, India. Geoforum. 2019;102:255–266. doi: 10.1016/j.geoforum.2018.01.008
81. Simon KP. Applications of Design For Value to Distributed Solar Generation in Indian Food Processing and Irrigation. Massachusetts Institute of Technology. Cambridge, Massachusetts, USA; 2015.
82. Braganza S. Point-of-use Soil Diagnostics: An Actionable Information System for Resource Constrained Farmers. Massachusetts Institute of Technology. Cambridge, Massachusetts, USA; 2016.
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