8.2 Limits to surveillance data

Equitable AMR surveillance depends on comprehensive data, but persistent limits in surveillance systems often exclude the marginalised communities most affected by AMR. It is also important to consider the limitations of surveillance data and what it currently cannot tell us, including biases in the data that need to be understood.

AMR surveillance also relies primarily on data collected at health facilities. This means that community-level infections are rarely detected, particularly among those who use informal health providers. Additionally, individuals and groups who face specific barriers to accessing formal health services and diagnostics will not be represented in surveillance data.

This highlights the fact that trends in surveillance data cannot be understood without the contextual understandings of the upstream drivers of exposure, health-seeking, use of antimicrobials and animal health, which can be unpacked with qualitative and social science research.

Together, surveillance data and contextual social research can support decision-making and intervention design. Surveillance data needs to be complemented with:

• research to map the burden of resistance among communities and key populations that may be excluded from current surveillance efforts
• qualitative or co-produced research with communities that unpacks structural drivers of AMR and prioritises community knowledge to support context-appropriate intervention design and prevention.

To mitigate these barriers, it’s important to address the equity gaps in AMR.