Executive Summary
In July 2020, iMMAP launched the Global COVID-19 Situation Analysis Project, funded by the Bureau of Humanitarian Assistance (BHA) of USAID. Implemented in Cox’s Bazar, Bangladesh, Burkina Faso, Colombia, DRC, Nigeria, and Syria, this project has produced monthly situation analysis reports that provide humanitarian stakeholders with comprehensive information on the spread of COVID-19 and related humanitarian consequences. In July 2021, iMMAP commissioned a series of sector-specific lessons learned reports to assess data availability and quality, adaptations, challenges, opportunities that emerged in six humanitarian sectors: education, food security, livelihoods, nutrition, protection, and water, sanitation and hygiene (WASH). This report focuses on the protection sector. Three data sources informed the analysis presented in this report: a review of secondary data on the DEEP platform from 01 March to 18 August 2021; a document review of iMMAP’s monthly situation analysis reports; and key informant interviews with humanitarian stakeholders from the protection sector.
A total of 2,492 leads and 365 assessments were tagged for the protection sector on the DEEP platform. The highest number of leads (700) were reported for Colombia while Burkina Faso accounted for the highest number of protection assessments (130). International nongovernmental organizations (INGOs) and United Nations (UN) agencies were the two types of organizations authoring the highest proportion of protection assessments – 38.5 per cent and 25.5 per cent of protection assessments respectively. This global trend held true for all countries except for Nigeria, where INGOs and donors were the two main developers of assessments. Overall, 54.2 per cent of protection assessments were uncoordinated and 43.6 per cent coordinated (joint). Only 2.2. per cent of assessments were coordinated (harmonized). In terms of assessments’ type of approach, 38.9 per cent were categorized as rapid assessments, 29 per cent as monitoring assessments, and 15.9 per cent as in-depth assessments.
On average, key informant interviews were the most employed type of data collection technique, followed by household interviews and individual interviews. Satellite imagery was the least employed type of data collection technique. Protection assessments employed both faceto-face and/or remote methods to varying degrees in each country. The use of remote methods for data collection surpassed face-to-face in the Democratic Republic of the Congo (DRC) and Nigeria, where 42 per cent and 61.9 per cent of protection assessments respectively employed this method. The community/site was, by far, the most common unit of analysis with 42.7 per cent of protection assessments employing it. When breaking down the data by country however, some variations emerged. Humanitarian conditions was the most covered theme of protection assessments, followed by displacement and context. Except for Nigeria and to a lesser extent Syria, the focus on COVID-19 containment measures was relatively minimal in the other countries.
While most assessments looked at more than one population group, internally displaced persons (IDPs) were the group with most coverage in all countries except for Bangladesh, where refugees were the population with the most coverage in the assessments. In Burkina Faso, DRC, Nigeria, and Syria, a large proportion of assessments were tagged at the department level. In Bangladesh, most assessments were tagged at the municipal level whereas in Colombia, most assessments were tagged at the country level.
Despite the myriad of challenges that emerged during COVID-19, protection-specific information continued to be collected, analyzed, and shared during the pandemic. As highlighted by key informants, COVID-19 exacerbated some of the pre-existing challenges on data availability and quality. It also created additional barriers such as lack of access to affected populations. Among the sub-sectors, it was reported that child protection has particularly suffered from data gaps.
Limited or lack of access due to lockdowns and movement restrictions affected the capacity of humanitarian stakeholders to engage in data collection efforts as well as provide essential protection services. In addition, some countries like Nigeria and Burkina Faso have witnessed a deterioration of security concerns which, compounded with COVID-19, have rendered any form of operation and information management activity extremely difficult. In places like Syria, longstanding barriers of access to certain areas have generated severe information gaps. It is only estimated that the pandemic has had detrimental consequences on protection risks in these areas. Challenges have been faced not only in the ability to access data, but also in the capacity to ensure that high-quality data is processed, reported, and disseminated. To curb some of the access barriers during COVID-19, protection actors turned to various adaptations. The use of remote methodologies and data collection methods was an important break from the traditional face-to-face methods typically employed by the sector. This is a promising area, but one which must take into consideration the primacy of safe and do no harm approaches in the ways that data is collected, stored, and shared. As noted by some key informants, remote methodologies can create digital inequities when those who are not connected are not reached. This can create skewed representations of the needs of the most vulnerable populations. In some contexts, remote methodologies must be cautiously introduced as communities may experience mistrust.
With regards to data quality, a common challenge across all countries has been limited capacity to collect, manage, and analyze high-quality data. Lastly, key informants noted that the pandemic has highlighted the need for recognizing the essential role of communities and affected populations in information management processes. More community-based approaches are needed to build capacity and empower populations to identify, collect, and manage information about protection issues at the local level. This can not only support wider availability of data, but it can also contribute to generating more quality data.
