Healthcare-associated infections (HAIs) remain among the most frequent and costly adverse events worldwide, contributing substantially to preventable morbidity, mortality and health-system strain. Although tens of millions of patients are estimated to acquire infections annually through healthcare exposure, the true magnitude remains uncertain owing to heterogeneous surveillance systems, variable diagnostic capacity and inconsistent reporting standards (1). These limitations disproportionately affect pathogens that rely on specialized laboratory identification and antifungal susceptibility testing, allowing critical threats to remain under-recognized until outbreaks occur.

Within this under-characterized landscape, fungal infections are persistently under-recognized despite their disproportionate contribution to global mortality. Invasive fungal diseases are estimated to affect 6 million individuals annually, resulting in ~3-4 million deaths, either directly or in the context of severe underlying illness. These figures, although constrained by methodological uncertainty, underscore an escalating public health challenge exacerbated by delayed diagnosis, limited resistance surveillance and the insufficient integration of fungal pathogens into routine HAI monitoring frameworks (2).

In 2022, the World Health Organization (WHO) included Candidozyma auris (formerly known as Candida auris, henceforth referred to C. auris) in its first Global Priority List of Fungal Pathogens of critical concern. This designation reflects a convergence of high-risk characteristics: Multidrug resistance, environmental persistence, healthcare-associated transmission and a marked capacity to cause sustained outbreaks across diverse clinical settings (3-5). Notably, C. auris has emerged at the interface of clinical microbiology, antifungal stewardship, and infection prevention and control (IPC), exposing gaps created by fragmented, discipline-specific responses.

The clinical challenge posed by C. auris is rooted in its complex and evolving resistome. Resistance to azoles is commonly associated with mutations in ERG11 and the overexpression of efflux pumps, while echinocandin resistance is primarily mediated by hotspot mutations in FKS1 (6,7). Although resistance to polyenes appears less frequent, reduced susceptibility has been documented and remains incompletely understood. These mechanisms significantly constrain therapeutic options, particularly in critically ill patients. They also underscore the need for timely species identification, antifungal susceptibility testing, and resistance surveillance to inform clinical management and stewardship strategies (4,8).

Beyond genetic resistance, C. auris exhibits marked environmental resilience. It tolerates heat, osmotic stress and several commonly used disinfectants, and readily forms biofilms on medical devices and hospital surfaces. These properties facilitate prolonged environmental persistence and recurrent transmission, particularly in intensive care units and long-term care facilities. Genomic analyses have identified at least five major clades with distinct geographic distributions and resistance profiles, supporting the hypothesis of multiple, near-simultaneous emergences rather than dissemination from a single source (7-10). From an operational perspective, these findings highlight the importance of linking genomic epidemiology with local laboratory surveillance and IPC interventions. Despite growing recognition, the management of C. auris infections remains largely reactive. Current approaches emphasize case detection, patient isolation, cohorting and intensified environmental cleaning after colonization or infection has occurred. While essential, these measures are often implemented at a late stage, are resource-intensive, and may fail to prevent recurrent transmission when laboratory detection, resistance data and IPC decision-making are insufficiently integrated (11,12).

More fundamentally, the emergence of C. auris exposes structural limitations in healthcare systems that prioritize individual-level treatment over anticipatory, system-wide prevention (13).

Surveillance programs frequently focus on bacterial pathogens, with fungal organisms underrepresented in routine reporting (14). Data sharing between institutions may be inconsistent, and laboratory capacity for advanced diagnostics or genomic sequencing remains uneven across regions. These gaps undermine early detection, delay coordinated responses, and allow outbreaks to expand before comprehensive containment measures are deployed.

Addressing these limitations requires more than incremental improvements in diagnostics or environmental cleaning. It demands a framework capable of linking molecular insight, clinical decision-making, behavioral engagement and public-health coordination. The predictive, preventive, personalized, participatory, psycho-cognitive and public (P6) model of medicine provides such an integrative approach. Extending beyond traditional precision medicine, which often centers primarily on individualized therapy, P6 explicitly incorporates population health, behavioral science and governance into a unified model. In doing so, it positions clinical microbiology, not merely as a diagnostic service, but as a sentinel discipline within healthcare systems (15).

Applied to C. auris, the P6 model enables predictive and personalized care using clinical, microbiological and genomic data to identify high-risk patients and wards before transmission escalates. The preventive component emphasizes proactive laboratory screening policies, environmental monitoring and early IPC engagement, rather than reliance on post hoc containment. Personalized care integrates antifungal susceptibility data and patient-specific risk factors to optimize therapy, while limiting unnecessary antifungal exposure (Fig. 1).

The participatory dimension recognizes that effective containment depends on the engagement of healthcare workers, patients and caregivers. Education on transmission dynamics, adherence to IPC protocols, and transparent communication during outbreaks are critical for sustaining compliance. The psycho-cognitive element addresses often-overlooked factors, such as stigma associated with isolation, alert fatigue among staff and psychological stress during prolonged outbreaks, factors that can erode adherence and compromise IPC effectiveness. Finally, the public dimension situates C. auris within broader surveillance and governance systems, promoting harmonized reporting standards, cross-institutional data sharing, and alignment between antifungal resistance surveillance and IPC programs at regional and national levels (Fig. 1). The core conceptual shifts required to move from these traditional, reactive approaches to a P6-integrated paradigm are summarized in Table I.

Artificial intelligence and advanced analytics can strengthen the P6 framework by integrating electronic health records, laboratory information systems and genomic databases to identify high-risk patients and anticipate outbreak hotspots, transmission clusters or resistance trends. However, implementation remains uneven and requires careful governance-accompanied by robust governance, interoperability standards and safeguards to ensure responsible data use and equitable access to advanced diagnostics (16). Notably, adopting an integrative framework does not diminish the importance of established IPC measures. Rather, it strengthens them by embedding these measures within a predictive and system-oriented structure. Clinical microbiology laboratories, with their access to diagnostic, susceptibility and genomic data, are uniquely positioned to generate the microbiological intelligence that triggers integrated responses. By rapidly communicating laboratory findings to clinicians, epidemiologists, infection prevention and control teams, antifungal stewardship programs, public health inspectors and public health authorities, laboratories transform diagnostic data into actionable intelligence that supports coordinated surveillance, investigation and control.

Finally, the public dimension situates C. auris within broader surveillance and governance systems, promoting harmonized reporting standards, cross-institutional data sharing, and alignment between antifungal resistance surveillance and IPC programs at regional and national levels (3,11). This dimension also recognizes the complementary responsibilities of clinical microbiologists, epidemiologists, public health inspectors, IPC professionals and public health authorities (12). Clinical microbiology provides the microbiological intelligence that initiates surveillance and response activities, epidemiologists investigate transmission dynamics and analyze surveillance data, public health inspectors evaluate environmental and regulatory compliance within healthcare facilities (17), while public health authorities coordinate surveillance systems, policy implementation, and population-level responses (3,11,12).

Although the P6 framework is conceptual in nature, its principles can be translated into practical health-system actions. An integrated response can be organized across three complementary phases: Pre-emptive prevention, targeted clinical management and coordinated systems-level governance.

Phase 1: Predictive and preventive response. The predictive and preventive dimensions aim to shift the management of C. auris from outbreak response to early risk identification. Hospitals may implement targeted screening strategies for high-risk populations, including patients transferred from healthcare facilities with known transmission, individuals requiring intensive care, and those with prolonged healthcare exposure. During outbreaks or in high-risk settings, targeted environmental assessment may complement patient screening, particularly given the ability of C. auris to persist on surfaces and medical equipment (18).

Where infrastructure permits, the integration of electronic health records, laboratory information systems, and genomic surveillance platforms may support identification of transmission patterns and emerging outbreak clusters. However, these approaches should complement, rather than replace, foundational requirements such as diagnostic capacity, surveillance infrastructure, and effective IPC programs.