Measures of frequency and mortality

Measures of Frequency and Mortality

Serious Diseases Poll

  • Disease A: Kills 60,000 annually, preventable by vaccine but 100% mortality if untreated within 7 days of symptoms.

  • Disease B: Affects 1 in 4 adults globally, not fatal but leads to disability and costs over $300 billion in the U.S. yearly.

  • Disease C: Unpredictable epidemiology, 50-90% mortality, highly contagious with no licensed treatment, 55 global deaths in 2023.

  • Disease D: Affects 530 million globally, contributes to 6.7 million deaths annually, requires lifelong treatment.

Evaluating Disease Seriousness

  • Consider factors: survival, quality of life, socioeconomic effects.

  • Public health metrics: contagiousness, burden of disease, prevalence, incidence, mortality.

Top 10 Causes of Death in the U.S. (2023)

  1. Heart Disease

  2. Cancer

  3. Accidents/Unintentional Injuries

  4. Stroke

  5. Chronic Lower Respiratory Diseases

  6. Alzheimer’s Disease

  7. Diabetes

  8. Kidney Diseases

  9. Chronic Liver Disease & Cirrhosis

  10. COVID-19

  • Data retrieved from CDC Wonder.

Leading Causes of Death Analysis (2015-2020)

  • Heart Disease: 2,712,630 deaths in 2015; increased annually.

  • COVID-19: 345,323 deaths in 2020.

  • Diabetes: 79,535 deaths in 2015, increasing over years.

Fundamentals of Epidemiology

  • Definition: Study of distribution and determinants of health-related states.

  • Key Components: Who, when, where, what.

Epidemiologic Metrics

  1. Prevalence: Proportion affected at a given time.

    • Point Prevalence: Specific time point measurement.

    • Period Prevalence: Measurement over a specified time period.

  2. Incidence: New cases during a time period.

    • Requires a definition of at-risk population.

  3. Mortality Rates: Rates of death from all causes, specific causes, and case fatality rates.

Definitions of Prevalence

  • Prevalence = Number of existing cases / total population.

  • Important to note:

    • Prevalence is a proportion, not risk.

    • Point prevalence is typically the default unspecific reference.

Calculating Prevalence

  • Example: Diabetes Prevalence in Michigan (2021-2023)

    • State Overall: 9.8%

    • Iron County: 21.9%

    • Washtenaw County: 6.9%

    • Population figures:

      • State: 10,054,112

      • Iron: 11,668

      • Washtenaw: 370,231

    • Useful for directing resources.

Point Prevalence Calculation Example

  • Event measurement in a specified population:

    • Total N = 100

    • Point prevalence = 3 cases / 100 = 3%.

Factors Influencing Point Prevalence

  • Influenced by new incidences and duration of disease outcomes.

Period Prevalence Calculations

  • Definition: Proportion at any time during a specified period.

  • Uses both past incidences and those newly developed during the measure period.

  • Example: 7 out of 100 over specified period = 7% period prevalence.

Incidence

  • Measure of new disease cases in a specified at-risk population.

  • Cumulative incidence example: Number of new cases / population at risk.

Limitations of Cumulative Incidence

  • May lead to misinterpretations in unstable populations (loss of participants, migrations, etc.).

  • Best in stable populations without competing risks or loss to follow-up.

Using Person-Time for Cumulative Incidence

  • Person-time allows accurate follow-up measure adjustment in unstable populations.

  • Example: 5 individuals followed over varying times yielding person-time metrics.

Incidence Rate

  • Defined as new cases / total person-time.

  • Important for recurrent outcomes measurement.

  • Example: 13 events over 249 person-years = 0.052 events per person-year.

Relationships Between Metrics

  • Risk and Rate Relationship: CI (Cumulative Incidence) can be approximated using IR (Incidence Rate) with certain assumptions about stability and timing of events.

  • Prevalence relates to IR and duration understanding how new and existing cases interact over time.

Trends and Current Data

  • Monitor shifts in incidence and mortality trends including public health implications (e.g., cancer diagnoses post-pandemic).

  • Current data from various sources such as NIH indicates recovery trends or falls in mortality rates (e.g., drug overdose deaths declining).

Conclusions

  • Interpreting morbidity and mortality requires detailed analysis considering temporal, geographical, and demographic contexts.

  • Accurate representation fosters effective public health policymaking.

Mortality Rates

  • Mortality Rates: General term for rates of death.

  • All-Cause Mortality Rate: The total number of deaths in a population from all causes over a specified period. This indicates the overall health status of a population.

  • Cause-Specific Mortality Rate: The number of deaths due to a particular disease or cause (e.g., heart disease, cancer) in a population over a specified period. This helps identify the impact of individual diseases.

  • Case Fatality Rate (CFR): The proportion of individuals who die from a particular disease among all individuals who have been diagnosed with that disease. It measures the severity of a disease among those infected.

  • Proportionate Mortality: The proportion of all deaths in a population that are due to a specific cause over a specified period. It indicates the relative importance of a specific cause of death compared to all other causes, but does not measure the risk of dying from that cause.