Infectious Keratitis Epidemiology and Management

Infectious keratitis remains a leading cause of corneal opacity and visual impairment worldwide, with incidence ranging from 2.5 to 799 new cases per 100 000 population-year. Aetiological agents include bacteria, fungi, viruses and Acanthamoeba species, whose relative prevalence varies by geography, climate and behavioural risk factors such as contact-lens wear, ocular trauma and surface disease. Rapid identification and tailored antimicrobial therapy are pivotal to prevent progression to perforation or scarring; however, traditional culture and microscopy can be slow or insensitive, and the rising tide of antimicrobial resistance undermines the efficacy of broad-spectrum agents. Recent advances in digital imaging, confocal microscopy and artificial intelligence promise to shorten diagnostic delays, while evolving risk-stratification frameworks and regional surveillance programmes guide empirical management and public-health interventions. Continued integration of molecular diagnostics, epidemiological monitoring and optimised treatment protocols is essential to reduce the global burden of corneal blindness.

Research from Nature Portfolio

A deep learning system has been developed for automated classification of keratitis subtypes and other corneal abnormalities from slit-lamp photographs captured by both clinical microscopes and smartphone devices. The algorithm achieved areas under the curve exceeding 0.96 for distinguishing keratitis, producing sensitivity and specificity comparable to experienced specialists. Its compatibility with common imaging platforms offers a scalable approach to early detection in low-resource and remote settings, potentially reducing delays in treatment and improving visual outcomes.

Infectious Keratitis Epidemiology and Management publication trend

The graph below shows the total number of articles in infectious keratitis epidemiology and management across all publications each year (not limited to Nature Index journals).

Technical terms

Keratitis: Inflammation of the corneal stroma often caused by infectious agents.

Antimicrobial resistance: Ability of microorganisms to survive exposure to drugs meant to kill or inhibit them.

Deep learning: Artificial intelligence technique using layered neural networks to recognise patterns in complex data.

Slit-lamp biomicroscopy: High-magnification illumination and imaging method for detailed examination of the eye’s anterior segment.

Incidence: Rate at which new cases of a disease occur in a specified population over a defined time period.

References

1. Deep learning for multi-type infectious keratitis diagnosis: A nationwide, cross-sectional, multicenter study. npj Digital Medicine (2024).
2. Infectious keratitis: an update on epidemiology, causative microorganisms, risk factors, and antimicrobial resistance. Eye (2021).
3. 12-year analysis of incidence, microbiological profiles and in vitro antimicrobial susceptibility of infectious keratitis: the Nottingham Infectious Keratitis Study. British Journal of Ophthalmology (2020).
4. Preventing corneal blindness caused by keratitis using artificial intelligence. Nature Communications (2021).