Evaluating Human Excreta Management and Sanitation Services Using a Shitflow Diagram at Iten Municipality, Elgeyo Marakwet County, Kenya/ (Record no. 93752)

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fixed length control field 03357nam a22003137a 4500
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003 - CONTROL NUMBER IDENTIFIER
control field KE-MeUCS
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20260330154837.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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Transcribing agency KE-MeUCS
050 ## - LIBRARY OF CONGRESS CALL NUMBER
Classification number RA567.5.K5 2025
100 ## - MAIN ENTRY--PERSONAL NAME
Relator code Kiprop, Cynthia Jelagat
245 ## - TITLE STATEMENT
Title Evaluating Human Excreta Management and Sanitation Services Using a Shitflow Diagram at Iten Municipality, Elgeyo Marakwet County, Kenya/
Statement of responsibility, etc Cynthia Jelagat Kiprop
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Meru,
Name of publisher, distributor, etc Meru University,
Date of publication, distribution, etc 2025.
300 ## - PHYSICAL DESCRIPTION
Extent xvi,186p.
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General note Includes Appendix and Reference
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Summary, etc In low- and middle-income countries such as Kenya, access to safe sanitation is a significant challenge contributing to public health issues and economic burdens. Various sanitation interventions have been implemented to address these challenges. However, the effectiveness of these interventions in managing human excreta along the sanitation service chain remains unclear. Therefore, the primary objective of the research was to evaluate human excreta management and sanitation services in Iten Municipality, using the Shit Flow Diagram (SFD), to identify existing gaps and challenges. The study's specific objectives included determining the main onsite sanitation technologies used, evaluating their performance, generating SFD, and identifying potential health risks associated with the current sanitation service chain. A mixed-methods approach was employed, involving quantitative and qualitative data collection. A sample size of 388 household heads was determined using the Yamane formula and selected through a cluster random proportionate sampling technique. Qualitative data were obtained via purposely selected key informants and observations, using a checklist and a transect walk guide. Quantitative data were analyzed using the Statistical Package for the Social Sciences (SPSS) version 26 for descriptive statistics and chi-square tests of association. Findings were presented in tables and charts. Qualitative data were transcribed and manually analyzed into themes, and the results were presented in a narrative format. Results indicated that major onsite sanitation technologies include pit latrines (69.1%), septic tanks (22.9%), and Anaerobic digesters(2.9%). The study also established that 69% of the waste was adequately managed, while31% was not safely managed, and 3% still practice open defecation. Pests (42%), odour(41.8%), malfunctions, and blockages (64.6%) were common issues with these on-site technologies. The results revealed that 28% of the population had experienced sanitation-related health issues in the past year, with 12.9% reporting diseases such as amoebiasis, dysentery, and diarrhoea. Additionally, 19.1% of respondents acknowledge local water source contamination, exacerbating health risks, as indicated by laboratory findings of high levels of E. coli and Total coliforms in various water sources. These findings underscore the need for enhanced sanitation infrastructure, standardized maintenance protocols, and community education to improve waste management and public health outcomes in Iten Municipality.
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Source of classification or shelving scheme Library of Congress Classification
Koha item type Thesis
Cataloguer Selina Muthii
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Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Source of acquisition Cost, normal purchase price Cataloguer Total Checkouts Full call number Barcode Date last seen Price effective from Koha item type
    Library of Congress Classification     Meru University Meru University Periodical Section 30/03/2026 Meru University of science and Technology (MUST) 0.00 Selina Muthii   RA567.5.K5 2025 26-39366 30/03/2026 30/03/2026 Thesis

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