An Unequal Pandemic: Insights and Evidence from Communities and Civil Society Organisations.
Impel Consultancy. Civil Society Collaborative on Inclusive COVID-19 Data.
Technical Report International Resource
Published: July 2021
This report begins by sharing the reflections of four community advocates on the impacts of the COVID-19 pandemic to illustrate how certain populations have been marginalized in data published and used by government agencies and public bodies. It notes that to understand the unequal effects of the COVID-19 pandemic and chart the pathway to an inclusive recovery, a group of Civil Society Collaboratives (CSOs) formed the Civil Society Collaborative on Inclusive COVID-19 Data. Working alongside communities, the Collaborative advocates for a more holistic approach that values using community and CSO data to help meet the diverse needs of people and groups who have been marginalized. This report uses insights from community and CSO data collected by Collaborative partners, often in close cooperation with communities, to provide a clearer picture of the impact of the COVID-19 pandemic on people who have been marginalized and their responses. For the study, an online survey was conducted with 41 Collaborative partners to identify 38 studies they had undertaken or supports, and a desk review was conducted of 60 resources containing relevant community and CSO data, including published reports, case studies, and blogs. Findings highlight five common issues and impacts for people who have been marginalized: access to health; income and livelihoods; food insecurity; education; and violence, abuse and discrimination. The report explains that official data provide an inadequate picture of communities experiencing marginalization in this pandemic and the enormous challenges that people who have been marginalized have had to respond to, often without adequate support from governments. The report closes with recommendations for preventing inequalities from deepening further through more inclusive data systems. 81 references.
COVID-19; Data collection; Data analysis; Data use; International resource; Diversity equity inclusion; Disaster response; Community based services; Implicit bias