Understanding Disease Distribution

By examining patterns of non-infectious diseases, researchers gain insights into risk factors, resource allocation, and prevention strategies. Reliable data collection and analytical techniques underpin effective public health decision-making.

Incidence of Nutritional Diseases

Incidence of Environmental Diseases

Key Epidemiological Measures

Incidence measures new cases, prevalence indicates the overall burden, and mortality rates reflect disease severity. Analysing temporal patterns helps identify environmental and behavioural influences.

Measure	Definition	Formula	Application
Incidence	New cases in a time period	(New cases / Population at risk) × 1000	Disease onset patterns
Prevalence	Existing cases at a point	(Total cases / Total population) × 100	Disease burden
Mortality Rate	Deaths from disease	(Deaths / Population) × 100,000	Disease severity

Data Collection Methods

Surveillance systems (active or passive) and quality control measures ensure accurate, standardised, and validated data. Hospital records, laboratory reports, and death certificates are common data sources.

Pattern Analysis

Geographic distribution studies reveal differences based on location, while demographic analyses consider age, gender, ethnicity, and socioeconomic status. Time series analyses identify seasonal and long-term trends, and risk factor analysis uncovers behavioural and environmental contributors.

Statistical Methods

Descriptive and inferential statistics, regression models, and multivariate techniques support robust data analysis. These methods inform policy development, resource allocation, and targeted interventions.

Future Directions

Integration of big data, machine learning, and predictive analytics promises improved surveillance, forecasting, and intervention planning. As data analysis tools advance, so does our capacity to understand and respond effectively to non-infectious disease challenges.