While informal limited exchanges among pediatricians frequently provide the first indications of emerging (para-)infectious diseases, these observations often remain anecdotal and unstructured, according to the results from a prospective study by van Kempen et al. To strengthen pediatric infectious disease surveillance, a clinical-based surveillance network that integrates real-time observations from frontline hospital-based health-care providers is needed to complement existing surveillance systems, according to the study authors.

Drawing on recent pediatric outbreaks, including COVID-19–related multisystem inflammatory syndrome in children (MIS-C), acute hepatitis of unknown origin, invasive group A streptococcal (iGAS) disease, and surges in Mycoplasma pneumoniae infections, the study highlights four major limitations of current systems, including:

• Difficulty identifying new or emerging diseases;

• Underreporting of severe but non-notifiable infections;

• Inconsistent diagnostic testing, and;

• Limited availability of granular clinical information.

These shortcomings can delay outbreak recognition, obscure shifts in disease presentation, and hinder timely treatment, argue the study authors. In several cases, clinicians noticed unusual patterns through informal communication—such as professional messaging groups—well before these conditions were formally recognized by public health surveillance systems. For instance, MIS-C emerged as a distinct post-infectious syndrome based on frontline observations rather than laboratory surveillance, while increases in iGAS and atypical pneumonia were initially recognized by hospital clinicians rather than national reporting systems. These examples demonstrate how valuable clinical insight can remain anecdotal and unstructured, limiting its broader public health impact.

Addressing the Gaps in Current Health-Care Systems

To address these issues, the researchers advocated for an active, case-based, hospital-centered surveillance network that captures real-time aggregated clinical data. In their paper, they described existing models in Australia and Switzerland that successfully monitor predefined pediatric diseases, but noted that these systems lack flexibility and real-time data sharing. In response, the authors launched a pilot surveillance network in 2025 designed to capture all serious pediatric infectious and para-infectious conditions, including those not predefined.

In this model, clinicians submit brief biweekly reports using ICD-11 codes, indicating whether they observed unusually severe or frequent infections. Data are aggregated at the hospital level to protect patient privacy and comply with data protection regulations. Results are displayed on a real-time dashboard and reviewed during short, regular meetings to identify emerging patterns. When a potential surge is detected, more detailed data collection can be initiated and validated through traditional laboratory or population-based surveillance.

The authors also outlined future developments, including automated extraction of clinical data from electronic health records using artificial intelligence and natural language processing models. These tools could improve data granularity while reducing the reporting burden on clinicians. However, the authors acknowledged challenges, such as reporting bias, false-positive signals, uneven hospital participation, and the risk of misinterpretation, and emphasized that close integration with existing public health infrastructure is essential.

To strengthen pediatric infectious disease surveillance, the authors called for formalizing frontline clinical intuition through structured, real-time hospital-based surveillance. By complementing traditional systems with clinician-driven data, this approach could enhance early detection, improve outbreak response, and ultimately lead to better outcomes in pediatric infectious diseases, according to the authors.

Key Points

• Recent outbreaks highlighted surveillance gaps in surveillance systems.

• Frontline clinical observations can precede formal outbreak recognition.

• Hospital-based clinical surveillance can bridge these surveillance gaps.

Integrating clinical data enables earlier detection and improved disease outbreak response.

The authors declared having no competing interests.
Source: International Journal of Infectious Diseases