02619nas a2200193 4500000000100000008004100001653000900042653001200051653002000063100002000083700001500103700002000118245009900138856020000237300001200437490001200449520195100461022001302412 2013 d10aWASH10aMapping10aData Collection1 aGiné Garriga R1 aJiménez A1 aPérez Foguet A00aWater–sanitation–hygiene mapping: An improved approach for data collection at local level. uhttps://www.researchgate.net/profile/Ricard_Gine2/publication/249319381_Water-sanitation-hygiene_mapping_An_improved_approach_for_data_collection_at_local_level/links/56b516d208ae3c1b79ab2105.pdf a700-7110 v463-4643 a

 

Strategic planning and appropriate development and management of water and sanitation services are strongly supported by accurate and accessible data. If adequately exploited, these data might assist water managers with performance monitoring, benchmarking comparisons, policy progress evaluation, resources allocation, and decision making. A variety of tools and techniques are in place to collect such information. However, some methodological weaknesses arise when developing an instrument for routine data collection, particularly at local level: i) comparability problems due to heterogeneity of indicators, ii) poor reliability of collected data, iii) inadequate combination of different information sources, and iv) statistical validity of produced estimates when disaggregated into small geographic subareas.

This study proposes an improved approach for water, sanitation and hygiene (WASH) data collection at decentralised level in low income settings, as an attempt to overcome previous shortcomings. The ultimate aim is to provide local policymakers with strong evidences to inform their planning decisions. The survey design takes the Water Point Mapping (WPM) as a starting point to record all available water sources at a particular location. This information is then linked to data produced by a household survey. Different survey instruments are implemented to collect reliable data by employing a variety of techniques, such as structured questionnaires, direct observation and water quality testing. The collected data is finally validated through simple statistical analysis, which in turn produces valuable outputs that might feed into the decision-making process. In order to demonstrate the applicability of the method, outcomes produced from three different case studies (Homa Bay District -Kenya-; Kibondo District -Tanzania-; and Municipality of Manhiça –Mozambique-) are presented.

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