The effectiveness of genomic surveillance in controlling antimicrobial resistance (AMR) does not depend solely on technological advances or laboratory capacity, but also on a range of social and behavioral factors that directly influence how genomic data is collected, interpreted, and applied in public health decision-making. One of the key elements is the behavior of healthcare professionals. Genomic surveillance requires physicians, microbiologists, epidemiologists, and policymakers to be trained and willing to incorporate this information into their workflows. When there is a lack of understanding, resistance to change, or insufficient interdisciplinary collaboration, the data generated can be underutilized or overlooked, thereby reducing its impact.

In addition, public behavior related to antibiotic use plays a crucial role. In settings where antibiotics are used indiscriminately, accessed without prescription, or misused due to cultural habits or lack of awareness, resistant bacterial strains spread more rapidly. Even with advanced surveillance systems in place, AMR cannot be effectively controlled if the population continues to practice behaviors that favor the emergence and dissemination of resistance.

Another critical factor is the flow of data between institutions and countries. Genomic surveillance relies on the timely and transparent exchange of information to detect outbreaks and emerging resistance variants early. However, social and political barriers, such as institutional mistrust, national interests, or concerns about blame and data ownership, can hinder effective collaboration.

Furthermore, social inequality plays a significant role in surveillance gaps. Populations in rural or marginalized areas often have limited access to diagnostic tools, sequencing technologies, and trained personnel, resulting in underrepresentation and gaps in surveillance coverage. Behavioral patterns associated with socioeconomic status, such as delayed care-seeking or reliance on informal healthcare systems, can also distort surveillance outcomes.

Ultimately, while genomic surveillance provides powerful tools for monitoring AMR, its success is heavily dependent on human factors, ranging from health system capacity and professional practices to public trust, policy commitment, and cross-sector cooperation. Addressing these social and behavioral dimensions is essential to ensure that genomic data translates into effective action and helps mitigate one of the most pressing public health threats of our time.