Describe the methods to measure disease occurrence.

Understanding Key Terms

Before discussing measurement methods, it’s crucial to define core epidemiological terms:

• Incidence: The rate at which new cases of a disease occur in a population over a specific time period.
• Prevalence: The proportion of a population that has a disease at a specific point in time.
• Mortality: The rate of deaths due to a specific disease.
• Attack Rate: The proportion of susceptible individuals who develop a disease during a specific period, often used for outbreak investigations.

Methods to Measure Disease Occurrence

1. Measuring Incidence

Incidence is typically measured as incidence density, which considers the person-time or animal-time at risk. It is calculated as:

Incidence Density = (Number of new cases) / (Total person-time/animal-time at risk)

For example, if 10 new cases of foot-and-mouth disease (FMD) occur in a cattle herd of 1000 animals over a period of 6 months, the incidence density would be 10 / (1000 x 0.5) = 20 cases per animal-year.

2. Measuring Prevalence

Prevalence is calculated as:

Prevalence = (Number of existing cases) / (Total population)

A high prevalence indicates a large proportion of the population is affected, while a low prevalence suggests the disease is rare. Prevalence can be point prevalence (at a single point in time) or period prevalence (over a specific period).

3. Measuring Mortality

Mortality can be expressed in several ways:

• Crude Mortality Rate: Total number of deaths due to a disease in a population over a specific period.
• Case Fatality Rate: Proportion of diagnosed cases that result in death. (Number of deaths / Number of cases)
• Specific Mortality Rate: Mortality rate within a specific age group or population subgroup.

4. Data Collection Methods & Sampling

Accurate disease occurrence measurement requires robust data collection and appropriate sampling strategies:

• Active Surveillance: Regular and systematic data collection through veterinary inspections, farm visits, and laboratory testing. This is resource-intensive but provides timely information.
• Passive Surveillance: Relies on voluntary reporting by veterinarians and farmers. Less expensive but potentially biased due to underreporting.
• Serological Surveys: Testing blood samples for antibodies to detect past or current infections. Useful for estimating prevalence of diseases with subclinical or asymptomatic infections.
• Necropsies: Examination of deceased animals to determine cause of death.
• Sampling Methods: Simple random sampling, stratified sampling (e.g., by farm size, region), cluster sampling (e.g., selecting entire villages).

5. Challenges and Limitations

Measuring disease occurrence is often challenging:

• Underreporting: Farmers may not report disease due to fear of culling or economic losses.
• Diagnostic Difficulties: Some diseases have vague clinical signs, making diagnosis difficult.
• Changing Diagnostic Criteria: Changes in diagnostic tests can affect reported incidence and prevalence.
• Population Dynamics: Births and deaths can affect prevalence calculations.
• Bias in Sampling: Non-random sampling can lead to inaccurate estimates.

Comparison of Measures

Measure	Calculation	Interpretation	Limitations
Incidence Density	(New cases) / (Person-time at risk)	Rate of new infections	Requires accurate person-time data
Prevalence	(Existing cases) / (Total population)	Proportion of population affected	Affected by population dynamics, diagnostic changes
Case Fatality Rate	(Deaths) / (Cases)	Severity of disease	Dependent on accurate case definitions

The National Animal Disease Reporting System (NADRS) in India, launched in 2020, aims to improve disease surveillance and reporting through a centralized platform. It exemplifies active surveillance, leveraging veterinary officers and diagnostic laboratories for timely data collection. However, its success hinges on overcoming challenges like farmer participation and data quality.