Evidence map›Paper›PMID 42902293›Full record

ArticleBMC public health2026

WASH policy landscape: exploring context, process, content, and actors in childcare centres in Nairobi's informal settlements.

Ivy Chumo, Caroline Kabaria, Helen Elsey, Penelope A Phillips-Howard, Blessing Mberu

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Article in BMC public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Ivy ChumoAfrican Population and Health Research Center (APHRC), Nairobi, Kenya. ivychumo@gmail.com.ORCID https://orcid.org/0000-0003-1235-719X
Caroline KabariaAfrican Population and Health Research Center (APHRC), Nairobi, Kenya.
Helen ElseyUniversity of York, Hull York Medical School, York, UK.
Penelope A Phillips-HowardDepartment of Clinical Sciences, Liverpool, 3 Liverpool School of Tropical Medicine, Liverpool, UK.
Blessing MberuAfrican Population and Health Research Center (APHRC), Nairobi, Kenya.

Funding

UKRI Collective Fund award ES/S00811X/1
6 · The paper itself

Abstract

introductionAdequate water, sanitation, and hygiene (WASH) services are fundamental to health and development. However, many underserved areas such as informal settlements lack these services, creating significant infrastructural and public health challenges. Inadequate WASH infrastructure in Nairobi's informal settlements reveal significant gaps in childcare centre guidelines. Integrating robust guidelines and quality WASH services into childcare centres optimize operations and directly improves children's wellbeing. This study explores the policy environment governing WASH service delivery in these settings. We analysed the policy landscape's content, context, actors, and processes.

methodsThis study employed a dual-methodological approach within Nairobi's informal settlements. First, we systematically reviewed 25 policy documents to analyse the content, context, actors, and processes governing WASH guidelines, utilizing Walt and Gilson's Policy Triangle Framework. Second, we conducted 32 in-depth interviews (IDIs) and 8 key informant interviews (KIIs) with policymakers, parents, and childcare providers. These interviews used the same framework to identify policy gaps and practical implementation barriers.

resultsResults revealed a systemic fragmentation within the WASH policy landscape. While water (88%) and sanitation (80%) guidelines appeared frequently, hygiene guidelines were significantly less represented (68%). Overlapping mandates among the Ministries of Health, Education, and Water and Sanitation hindered effective implementation of policy guidelines. Gaps in the policy process and fragmented inter-sectoral coordination weakened the overall governance of WASH services and practices. This lack of institutional synergy ultimately resulted in suboptimal and precarious WASH outcomes within informal settlements.

conclusionsCurrent WASH policy frameworks are misaligned with the realities of informal urban settlements. Existing documents have inadequate strategies for these environments and for children under five. This contextual disconnect, coupled with the barriers of persistent poverty, means that service delivery often remains stalled or unsustainable. Bridging the gap between policy and practice requires moving beyond the policy content to the "how" of the policy process. Relevant actors in the sector should move towards a governance model that prioritizes a cohesive, politically supported, and monitored architecture for tangible community impact.

Indexed as

Child Day Care CentersHealth PolicyHygieneSanitationWater SupplyChild, PreschoolHumansInterviews as TopicKenyaQualitative ResearchChildcare centresInformal settlementsKenyaPolicy reviewWASH

Identifiers

PMID42902293
PMCPMC13685175

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.