Statistical Reasoning Lecture 7

Public Health Surveillance

Pablo Martinez Amezcua, MD, PhD, MHS

Johns Hopkins University

Produced by the Center for Teaching and Learning at the Johns Hopkins Bloomberg School of Public Health.

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Introduction to Public Health Surveillance

• Overview of the field of public health surveillance.

  • Produced by the Center for Teaching and Learning at Johns Hopkins Bloomberg School of Public Health.

  • Educational material subject to copyright.

Defining Surveillance in Public Health

Definition

• According to the Centers for Disease Control and Prevention (CDC):

  • Surveillance is the “ongoing systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice closely integrated with the timely dissemination of these data to those who need to know.”

Epidemiological Toolbox

• Tools to utilize in public health surveillance:

  • Measure disease burden

  • Assess risk factors for disease

  • Evaluate interventions

  • Assist policy decisions

  • Communicate public health evidence

Historical Background

• Includes references to significant historical events, such as the Anglo-Egyptian War (1882).

The Need for Health Surveillance

• Health surveillance is critical for understanding and responding to public health needs globally.

• Source image: World Airline Route Map (2009).

Purposes of Surveillance

• Provides a quantitative and scientific basis for public health practice.

  • Key Purposes include:

  • Assess current population health status and trends

  • Provide early warnings to guide immediate control measures

  • Define public health objectives and priorities

  • Design and plan effective public health programs

  • Evaluate the effectiveness of public health interventions and programs

  • Source: Gregg, M. & Gregg, M. B. (Eds.). (2008). Field epidemiology. Oxford University Press, USA.

The Surveillance Cycle

• Stages of surveillance process:

  • Collection: Pertinent, regular, frequent, timely

  • Analysis: Descriptive, standardized, timely

  • Dissemination: Timely, appropriate, complete

  • Action: Control and prevent outbreaks

  • Evaluation: Continuous review and adjustment of surveillance systems

  • Source: Scutchfield, F. D. & Keek, C. W. (1997). Principles of public health practice. Delmar, USA.

Surveillance and Epidemiology

• Field epidemiologists use surveillance to identify public health threats and guide preventive measures.

• Conducted at multiple levels: global, national, state, and local.

• In the U.S., county health departments are significant players in local public health surveillance efforts.

Types of Surveillance

Classification

1. Passive Surveillance:

   • Data is supplied by health providers or laboratories according to established policies.

   • Most globally utilized surveillance systems are passive.

   • Advantages: cheaper and more sustainable.

   • Source: Gregg, M. & Gregg, M. B. (Eds.). (2008). Field epidemiology. Oxford University Press, USA.

2. Active Surveillance:

   • Health agency proactively collects data by contacting various health sources and providers.

   • Commonly used during health emergencies or outbreaks.

   • Source: Gregg, M. & Gregg, M. B. (Eds.). (2008). Field epidemiology. Oxford University Press, USA.

3. Enhanced Passive Surveillance:

   • A modification involving follow-up of each reported case (e.g., contact tracing) to identify new cases.

4. Sentinel Surveillance:

   • Involves selected providers likely to report certain conditions, acting as representatives for that health issue.

   • Source: Gregg, M. & Gregg, M. B. (Eds.). (2008). Field epidemiology. Oxford University Press, USA; Scutchfield, F. D. & Keek, C. W. (1997). Principles of public health practice. Delmar, USA.

5. Limitations:

   • There is no perfect surveillance system; effectiveness varies by disease urgency and need for complete data.

   • Source: Gregg, M. & Gregg, M. B. (Eds.). (2008). Field epidemiology. Oxford University Press, USA.

Implementing Surveillance Systems and Data Sources

Health Event Criteria for Surveillance

• Identifying high-priority health events based on:

  • Frequency of occurrence

  • Severity of impact

  • Cost considerations

  • Preventability of events

  • Transmission routes

  • Level of public interest in the health issue

  • Source: Lee, L. M. (2010). Principles and practice of public health surveillance. Oxford University Press, USA.

Surveillance Goals

• Clearly defined goals are essential before establishing surveillance systems.

  • Goals may include:

  • Monitoring health event occurrences

  • Detecting outbreaks

  • Assessing public health interventions' effects

  • Different systems may be needed based on intended actions from generated data.

  • Source: Gregg, M. & Gregg, M. B. (Eds.). (2008). Field epidemiology. Oxford University Press, USA.

Features of a Surveillance System

• Important characteristics include:

  • Simplicity

  • Sensitivity to detect true cases

  • Flexibility to adapt to changes

  • Acceptability among stakeholders

  • Timeliness in reporting and response

  • Representativeness of the population served

  • Source: Scutchfield, F. D. & Keek, C. W. (1997). Principles of public health practice. Delmar, USA.

Data Sources

• Variety of sources used for health surveillance data include:

  • Vital statistics records

  • Notifiable diseases surveillance system

  • Laboratory results

  • Surveys (e.g., National Health and Nutrition Examination Survey, NHANES)

  • Administrative data

  • Customized surveillance systems

  • Community-based surveillance initiatives

  • When new data is required, prioritize rapid, standardized, and simple methods.

  • Source: Scutchfield, F. D. & Keek, C. W. (1997). Principles of public health practice. Delmar, USA.

Challenges in Data Collection

• Unlike academic research, surveillance data often has immediate requirements which can lead to compromised accuracy but remain necessary to identify health issues.

• Early surveillance results often trigger searches for additional data sources for holistic health assessment.

• Confidentiality concerns may arise in data handling and reporting.

  • Source: Scutchfield, F. D. & Keek, C. W. (1997). Principles of public health practice. Delmar, USA.

Surveillance Case Definitions

• A standardized set of criteria used to characterize events monitored by surveillance.

  • Should be clear, simple, and quantifiable, incorporating essential clinical, epidemiological, and laboratory information.

  • Classes of case definitions include:

  • Suspected

  • Probable

  • Confirmed

  • Definitions evolve during outbreaks, beginning broad with high sensitivity and becoming more precise as more information becomes available.

Examples of Surveillance Systems

National Notifiable Diseases Surveillance System (NNDSS)

• Overview and procedures of NNDSS are crucial for monitoring designated notifiable diseases in the U.S.

• Source material includes recent CDC infographics on the NNDSS.

The National Electronic Injury Surveillance System (NEISS)

• Operated by the U.S. Consumer Product Safety Commission.

• Collects nonfatal injury and poisoning data from emergency department visits.

• Utilizes sentinel surveillance, covering 66 hospitals, which report approximately half a million cases annually to inform national estimates.

NEISS 2020 Statistics on Nonfatal Injuries

• Breakdown of injury types:

  • Fall: 8.9%

  • Poisoning: 7.5%

  • Motor Vehicle: 6.6%

  • Overexertion: Specified cases and others included.

• Example of data visualization presented for statistical analysis of injuries.

Surveillance During Outbreaks

• Notable examples include COVID-19, monkeypox, and polio outbreaks.

Detailed Look at COVID-19 Data Under Surveillance

• Monitored data includes:

  • Cases

  • Deaths

  • Testing data

  • Hospitalizations

  • Vaccination records

Dissemination of COVID-19 Data

• Various sources provide dashboards tracking current COVID-19 statistics, such as total cases, deaths, and vaccinations across demographics and geographical regions.

Monkeypox Outbreak Surveillance

• Initial reports and data collection during the spring and summer of 2022 identified multiple regions affected.

  • A single case can be classified as an outbreak.

  • Surveillance goals include the prevention of human-to-human transmission, with health providers reporting claims to authorities for case investigations.

Criteria for Suspected and Probable Monkeypox Cases

• Suspected case definition within surveillance:

  • Any individual of any age presenting symptoms since January 1, 2022, including an unexplained rash along with symptoms like headache, fever, lymphadenopathy, myalgia, back pain, or asthenia.

Probable and Confirmed Cases of Monkeypox

• Probable case:

  • Meets suspected criteria and has an epidemiological link or detectable orthopoxvirus antibodies.

• Confirmed case:

  • Laboratory-confirmed detection of the virus (via Polymerase Chain Reaction - PCR test).

Polio Surveillance

• Currently, polio is a viral infection close to eradication but still endemic in certain countries.

• Sewage surveillance is valuable for detecting the presence of the virus despite falls in incidence due to vaccination efforts.

Equations, Explanations, and Applications in Public Health Surveillance

• Incidence Rate

  • Explanation: Measures the rate at which new cases of a disease occur in a population at risk over a specified period.

  • Equation: ${Incidence ext{ }Rate} = \frac{Number ext{ }of ext{ }new ext{ }cases ext{ }in ext{ }a ext{ }period}{Population ext{ }at ext{ }risk ext{ }over ext{ }the ext{ }same ext{ }period} \times k$ (where $k$ is a multiplier, e.g., 1,000 or 100,000)

  • When to Use: To assess the risk of developing a disease, identify emerging health problems, and evaluate the effectiveness of prevention programs.

• Prevalence Rate

  • Explanation: Measures the proportion of individuals in a population who have a disease at a specific point in time (point prevalence) or over a specified period (period prevalence).

  • Equation: ${Prevalence ext{ }Rate} = \frac{Total ext{ }number ext{ }of ext{ }existing ext{ }cases ext{ }at ext{ }a ext{ }point ext{ }or ext{ }period}{Total ext{ }population ext{ }at ext{ }that ext{ }same ext{ }point ext{ }or ext{ }period} \times k$

  • When to Use: To determine the overall burden of a disease in a population, estimate healthcare needs, and plan public health interventions for chronic conditions.

• Attack Rate

  • Explanation: A type of incidence rate used typically in outbreak investigations, measuring the proportion of an exposed population that becomes ill during a defined outbreak.

  • Equation: ${Attack ext{ }Rate} = \frac{Number ext{ }of ext{ }people ext{ }who ext{ }became ext{ }ill ext{ }(cases) ext{ }in ext{ }an ext{ }exposed ext{ }group}{Total ext{ }number ext{ }of ext{ }people ext{ }in ext{ }that ext{ }exposed ext{ }group} \times 100\%$

  • When to Use: During acute disease outbreaks to identify potential sources of infection and assess the risk of illness among specific exposure groups.

• Crude Mortality Rate

  • Explanation: The rate at which deaths occur from all causes in a population over a specified period.

  • Equation: ${Crude ext{ }Mortality ext{ }Rate} = \frac{Total ext{ }number ext{ }of ext{ }deaths ext{ }in ext{ }a ext{ }period}{Mid-period ext{ }population} \times k$

  • When to Use: To assess the overall health status of a population and compare death risks between different populations or over time.

• Case Fatality Rate (CFR)

  • Explanation: The proportion of individuals diagnosed with a particular disease who die from that disease within a specified period. It's a measure of disease severity.

  • Equation: ${Case ext{ }Fatality ext{ }Rate} = \frac{Number ext{ }of ext{ }deaths ext{ }from ext{ }a ext{ }specific ext{ }disease}{Number ext{ }of ext{ }confirmed ext{ }cases ext{ }of ext{ }the ext{ }same ext{ }disease} \times 100\%$

  • When to Use: To gauge the virulence of a disease, evaluate the effectiveness of treatments, and understand the prognosis for affected individuals.

• Basic Reproduction Number ($R_0$)

  • Explanation: The average number of secondary infections produced by one infected individual in a completely susceptible population during the infectious period.

  • Equation: ${R_0} = (Average ext{ }number ext{ }of ext{ }contacts ext{ }per ext{ }unit ext{ }time) \times (Probability ext{ }of ext{ }transmission ext{ }per ext{ }contact) \times (Duration ext{ }of ext{ }infectiousness)$

  • When to Use: To evaluate the transmissibility of an infectious disease, predict the potential for an epidemic, and estimate the level of vaccination needed for herd immunity.

All information should remain accurate and up to date based on recent findings and guidelines in the field of Public Health.