Community Perception Tracker


Launched by Oxfam in 2018, the Community Perception Tracker (CPT) is an approach that uses a mobile tool to enable staff to capture, analyse and understand the perceptions of communities during disease outbreaks.

The CPT process is rooted in our wider Community Engagement approach and contributes to various aspects of the latter’s framework, including context analysis, programme activities, capacity building, coordination and advocacy.

Ideally, the CPT should be set up from the outset of a programme to capitalise on the process’ ability to shape/adapt activities based on the analysis of captured data. The CPT has been specifically designed for use during disease outbreaks (including Covid-19) but will be adapted in due course to suit other types of emergency response.

How does the CPT add value to an existing response programme?

1. A Systematic Approach

During a disease outbreak, qualitative information is often informal and subjective, and can be considered anecdotal – rather than integral to the response. By capturing such information in a more systematic manner, we can translate informal data into more purposeful evidence that can inform current and future response activities.

2. Enables Rapid Analysis

We know from previous experience with data collection that the use of digital tools to capture information can support faster, more accurate, data collection in a way that avoids placing burden on programme staff. In so doing, it also provides reports that are rapidly analysed to produce findings that can – in real time – directly impact a humanitarian response.

3. Captures Trends

The rapid analysis of systematically collected data enables us to generate concrete evidence. This enables us to identify relevant trends, anticipate their reoccurrence and thereby inform future responses and preparedness plans.


The following resources have been produced to provide straightforward guidance around use of the CPT and how best to implement the approach into existing response programmes: