Systematic mapping of gender equality and social inclusion in WASH interventions: knowledge clusters and gaps

INTRODUCTION: Poor access to water, sanitation and hygiene (WASH) services threatens population health and contributes to gender and social inequalities, especially in low-resource settings. Despite awareness in the WASH sector of the importance of promoting gender equality and social inclusion (GESI) to address these inequalities, evaluations of interventions focus largely on health outcomes, while gender equality and other social outcomes are rarely included. This review aimed to collate and describe available research evidence of GESI outcomes evaluated in WASH intervention studies. METHODS: We applied a systematic mapping methodology and searched for both academic and grey literature published between 2010 and 2020 in 16 bibliographic databases and 53 specialist websites. Eligibility screening (with consistency checking) was conducted according to predetermined criteria, followed by metadata coding and narrative synthesis. RESULTS: Our evidence base comprises 463 intervention studies. Only 42% of studies measured transformative GESI outcomes of WASH interventions, referring to those that seek to transform gender relations and power imbalances to promote equality. A majority of studies disaggregated outcome data by sex, but other forms of data disaggregation were limited. Most included studies (78%) lacked a specific GESI mainstreaming component in their intervention design. Of the interventions with GESI mainstreaming, the majority targeted women and girls, with very few focused on other social groups or intersectional considerations. CONCLUSION: The review points to various areas for future primary and secondary research. Given the potential contribution of WASH to GESI, GESI considerations should be incorporated into the evaluation of WASH interventions. Regular collection of data and monitoring of GESI outcomes is needed as well as developing new and testing existing methods for monitoring and evaluation of such data.