Related Experiment Video
Updated: Feb 8, 2026

04:41
Plaquing of Herpes Simplex Viruses
Published on: November 5, 2021
7.1K
Herpes simplex epithelial and stromal keratitis: an epidemiologic update
1Department of Ophthalmology and Visual Sciences, College of Medicine, University of Illinois at Chicago, Chicago, Illinois 60612, USA.
Survey of Ophthalmology
|May 1, 2012
Summary
Herpes simplex virus (HSV) keratitis affects 1.5 million globally each year. This includes 40,000 new cases of blindness or severe vision loss from HSV eye disease annually.
Area of Science:
- Ophthalmology
- Virology
- Epidemiology
Background:
- Herpes simplex virus (HSV) causes ocular diseases like epithelial and stromal keratitis.
- HSV keratitis is a leading cause of infectious blindness globally.
- Understanding the burden of HSV keratitis is crucial for prevention and treatment.
Purpose of the Study:
- To estimate the global incidence of HSV keratitis.
- To determine the annual number of new cases of severe vision loss due to HSV keratitis.
- To discuss epidemiological factors of HSV epithelial and stromal disease.
Main Methods:
- Epidemiological analysis of global HSV keratitis incidence.
- Estimation of severe visual impairment and blindness cases.
- Review of relevant literature on HSV ocular disease.
Main Results:
- The global incidence of HSV keratitis is approximately 1.5 million cases annually.
- Around 40,000 new cases of severe monocular visual impairment or blindness occur each year.
- Significant epidemiological data regarding HSV epithelial and stromal keratitis were analyzed.
Conclusions:
- HSV keratitis represents a substantial global health burden.
- The findings highlight the urgent need for effective prevention and treatment strategies.
- Further research into HSV ocular disease epidemiology is warranted.
Related Concept Videos
Introduction to Epidemiology
1.9K
Epidemiology, known as the cornerstone of public health, involves studying the distribution and determinants of health-related events in defined populations and applying these insights to control health issues. This is essential for understanding how diseases spread, identifying populations at greater risk, and implementing measures to control or prevent outbreaks. Epidemiology addresses not only infectious diseases but also non-communicable conditions like cancer and cardiovascular disease,...
1.9K
Causality in Epidemiology
1.7K
Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
1.7K
Study Designs in Epidemiology
1.0K
Epidemiological study designs are fundamental tools for investigating the distribution, determinants, and control of health conditions in populations. They help researchers understand the relationships between exposures and outcomes, and they broadly fall into two categories: "observational" and "experimental" studies.
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...
1.0K
Confounding in Epidemiological Studies
846
Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This...
846
Bias in Epidemiological Studies
1.4K
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
1.4K
Statistical Methods for Analyzing Epidemiological Data
984
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
984

