An Epidemiological Study of Feline and Canine Dermatophytoses in Japan

Shigeo Yamada1, Kazushi Anzawa2, Takashi Mochizuki2

  • 1Yamada Animal Hospital.

Insights

Microsporum canis is a common cause of fungal infections in cats and dogs in Japan. Microsatellite genotyping helps identify infection sources, crucial for controlling the spread of dermatophytoses.

Area of Science:

  • Veterinary Dermatology
  • Mycology
  • Epidemiology

Background:

  • Feline and canine dermatophytoses are significant zoonotic diseases.
  • Understanding the prevalence and sources of fungal infections is vital for public health.
  • Microsporum canis is a primary etiological agent of dermatophytosis in companion animals.

Purpose of the Study:

  • To investigate the prevalence of dermatophytoses in cats and dogs in Japan.
  • To identify the etiological agents, particularly Microsporum canis.
  • To determine the infection routes of Microsporum canis in companion animals.

Main Methods:

  • Epidemiological surveys conducted between 2012-2014 and 2012-2017.
  • Fungal isolation and identification from affected animals.
  • Microsatellite genotyping for molecular epidemiological analysis.

Main Results:

  • Microsporum canis was identified as the predominant cause of dermatophytosis in cats and dogs.
  • A high prevalence of dermatophytosis was observed in animals from breeding facilities and pet shops.
  • Human infections (tinea) were found in 18.7% of animal owners.
  • Microsatellite genotyping proved effective in tracing infection routes.

Conclusions:

  • Microsporum canis poses a significant risk for dermatophytosis in Japanese companion animals.
  • Stray animals, breeding facilities, and pet shops are key reservoirs and transmission sources.
  • Molecular tools like microsatellite genotyping are essential for effective epidemiological control strategies.

Related Concept Videos

Study Designs in Epidemiology01:20

Study Designs in Epidemiology

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...
929
Confounding in Epidemiological Studies01:27

Confounding in Epidemiological Studies

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...
612
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

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:  
1.3K
Introduction to Epidemiology01:26

Introduction to Epidemiology

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,...
1.7K
Causality in Epidemiology01:21

Causality in Epidemiology

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...
1.5K
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

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:
921