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Table 7 Case example: leveraging existing or routinely collected quantitative data to identify trends and potential risks

From: Promising practices for the monitoring and evaluation of gender-based violence risk mitigation interventions in humanitarian response: a multi-methods study

Country: Myanmar

Sector: Health

In camps in Rakhine state, Myanmar, health sector professionals collected routine monitoring data on the number of community members who were accessing each of the health centers in the camps. These data were disaggregated by sex and also by which camp the community members were coming from. Analysis of this data over time showed a decrease in the number of women accessing the health centers from certain camps and even from specific neighborhoods. This trend raised a red flag among humanitarian staff, as it was indicative of a potential change in GBV risk. For example, women in those particular locations may have stopped using the health centers because of increased in GBV-related safety concerns on the way to the health centers. In order to better understand the situation, consultations with women and girls were carried out to further investigate why women were not accessing health services. Women reported that they had to pass through new checkpoints to reach the health facilities, and that they were experiencing harassment at these checkpoints. The team used this information to improve their programming, adding accompanied transport services for women, children, and people with disabilities so that they did not have to walk through the checkpoint on their own. This intervention quickly increased access to health center services

Key take away: Leverage existing data or routinely collected monitoring data to identify changes in trends (such as decreases in access to services) that may signal potential red flags for GBV risk, and follow up with further qualitative assessments to better understand what factors have contributed to the change