Descriptive Epidemiology: Data Sources and Data Collection
Descriptive epidemiology deals with describing disease patterns using three major categories: person, place, or time (Friis & Sellers, 2021). Consider the following example:
Over the last weekend, six people went to the Alcan City Hospital emergency room with similar symptoms. The laboratory results for the six patients were indicative of an infection due to Escherichia coli (E. coli). Patient interviews revealed they had all eaten a meal at Sam’s Sandwich Food Truck during the Alcan City Fair within 48 hours of going to
the hospital. Further inquiries by the Alcan City public health officials identified that the source of the E. coli contamination was the lettuce that Sam’s had purchased from M&L Produce (a produce supplier located in Tempe, Arizona). Epidemiologists from the Arizona State Health Department determined that the lettuce that M&L supplied Sam’s was from a farm located in Xion, California (the key supplier for M&L Produce).
Aside from the six patients who sought treatment, epidemiologists tracked down and conducted interviews with 400 of the fair attendees to identify any potential cases who did not seek treatment and compare data with those who attended but did not become ill. Interview questions pertained to descriptive aspects of the outbreak (person, place, and time). Analysis of data collected on foods eaten allowed the epidemiologists to narrow it down and identify sandwiches served by Sam’s
Sandwich Food Truck at the fair on Saturday as the source of infection. Alcan City public health officials were quick to visit the food truck to inquire into their food management and handling. The food truck owner was cooperative and helpful in providing licensing, permits, operations, and sales information.
Descriptive epidemiologic studies are often conducted as precursors to analytic studies. Epidemiologic concepts are used to gather data to better understand and evaluate health trends in populations. Data, such as characteristics of the persons affected, place where an incident occurred, and time of occurrence, are collected and analyzed to look for patterns in an effort to identify emerging health problems. It was in just this way that the HIV/AIDS epidemic was first identified.
In this Discussion, you will apply the epidemiologic concepts of time, place, and person to a specific population health problem. You will also consider methods for obtaining data to study an issue.
Resources
Be sure to review the Learning Resources before completing this activity.
Click the weekly resources link to access the resources.
· Curley, A. L. C. (Ed.). (2024).
Population-based nursing: Concepts and competencies for advanced practice (4th ed.). Springer.
· Chapter 7, “Using Information Technology to Improve Population Outcomes” (pp. 158-182)
· Friis, R. H., & Sellers, T. A. (2021).
Epidemiology for public health practice (6th ed.). Jones & Bartlett.
· Chapter 4, “Descriptive Epidemiology: Person, Place, Time”
· Chapter 5, “Sources of Data for Use in Epidemiology”
· National Institutes of Health National Library of Medicine. (2019).
Finding and using health statistics.Links to an external site.
SECONDARY DATA SOURCES
Use the following resources to locate secondary data sources for this week’s Assignment:
· Centers for Disease Control and Prevention. (n.d.).
Data.CDC.gov: Home.Links to an external site.
· National Center for Health Statistics. (2015).
Resources for researchers.Links to an external site.
· Walden University Office of Research and Doctoral Services. (n.d.).
Explore existing datasets.Links to an external site.
· World Health Organization. (2021).
WHO Data collectionsLinks to an external site.
[Data sets].
· Secondary Data Sources for Population Health
Time Estimate: 2 minutes
· Walden University, LLC. (2021).
Descriptive epidemiology—person, place, and timeLinks to an external site.
[Interactive media]. Walden University Blackboard.
· Walden University, LLC. (2021).
Theoretical models—One Health and socioecological modelLinks to an external site.[Interactive media]. Walden University Blackboard.
To prepare:
· Examine Table 3.2 in your Curley textbook. Select a topic from the table to use for this Discussion.
· Locate two scholarly articles that provide background information about the problem.
· Identify a specific population affected by your selected health problem.
· Research the patterns of the disease in your selected population using the epidemiologic characteristics of person, place, and time.
· Consider methods for obtaining data to examine the association you selected.
· Ask yourself: How would the methods I select influence the accuracy of case identification, definition, and diagnosis
By Day 3 of Week 2
Post a cohesive response that addresses the following:
· Describe your selected health problem using the epidemiologic model (person, place, and time), with a focus on the population affected by this problem.
· Discuss sampling methods you could use to collect primary data to describe and study your health problem.
· Identify two secondary data sources that you could use to collect the data needed to address this topic.
· Explain how these methods and sources would influence the completeness of case identification as well as the case definition/diagnostic criteria used.
By Day 6 of Week 2
Respond to
at least two colleagues on
two different days in one or more of the following ways:
· Ask a probing question, substantiated with additional background information, evidence, or research.
· Share an insight from having read your colleagues’ postings, synthesizing the information to provide new perspectives.
· Offer and support an alternative perspective using readings from the classroom or from your own research in the Walden Library.
· Validate an idea with your own experience and additional research.
· Make a suggestion based on additional evidence drawn from readings or after synthesizing multiple postings.
· Expand on your colleagues’ postings by providing additional insights or contrasting perspectives based on readings and evidence.
RESPOND TO THIS DISCUSSION POST
Denise
HIV in Prison Populations
Person
HIV disproportionately affects Black men in prison, especially those who have sex with men (MSM). This population faces significant healthcare barriers and shows higher HIV rates than the general population (Hoff et al., 2022; Ndeffo-Mbah et al., 2018).
Place
Prison environments facilitate disease transmission due to confined conditions.
Institutional barriers limit access to HIV testing, treatment, and prevention services (Ndeffo-Mbah et al., 2018; Kuester & Freestone, 2021). Transitions between prison and communities disrupt care continuity (Friis & Sellers, 2021).
Time
Incarceration duration affects healthcare continuity, while repetition complicates sustained HIV treatment. Some individuals report seeking reimprisonment to access healthcare unavailable in their communities (Kuester & Freestone, 2021).
Addressing this health disparity requires population-based approaches that consider individual, community, and structural factors (Curley, 2024).
Primary Collection Strategies
Stratified random sampling organizes the incarcerated population into demographic subgroups before random selection, enabling representative sampling while facilitating comparison between groups (Friis & Sellers, 2021). Respondent-driven sampling leverages peer networks through chain-referral techniques with statistical adjustments, proving especially valuable for accessing populations typically underrepresented in traditional sampling frameworks (Friis & Sellers, 2021).
Secondary Data Resources
Institutional health records document clinical encounters, treatment regimens, and medication compliance (Curley, 2024), though diagnostic protocols may lack standardization across facilities. The CDC HIV surveillance infrastructure maintains consistent reporting standards and demographic documentation
nationwide (Friis & Sellers, 2021), but relies on testing participation, potentially missing undiagnosed cases.
Implications for Case Assessment
Data collection methodologies substantially impact case identification carefulness. While primary collection may detect cases overlooked by standard surveillance, institutional records capture only those formally diagnosed. Case definitions similarly vary, with national surveillance employing uniform criteria while facility-based records may reflect resource constraints and local protocols (Curley, 2024). A multi-method approach yields the most comprehensive epidemiological understanding, capturing both diagnosed and undiagnosed infections while acknowledging the unique contextual factors shaping disease patterns in correctional environments.
Conclusion
HIV in prison populations, showing how incarcerated individuals especially Black men who have sex with men face higher infection risks in confined settings (Hoff et al., 2022). Two primary data collection methods (stratified random sampling and respondent-driven sampling) complement secondary sources like prison health records and CDC surveillance data (Friis & Sellers, 2021). The choice of data collection method affects both case identification and definition consistency. A combined approach offers the most complete picture of HIV patterns in correctional settings, providing a foundation for targeted interventions (Curley, 2024).
References
Curley, A. L. C. (Ed.). (2024).
Population-based nursing: Concepts and competencies for advanced practice (4th ed.). Springer.
Friis, R. H., & Sellers, T. A. (2021).
Epidemiology for public health practice (6th ed.). Jones & Bartlett.
Hoff, L., Scheidell, J. D., Mazumdar, M., Feelemyer, J., Dyer, T. V., Turpin, R. E., Cleland, C. M., Caniglia, E. C., Remch, M., Brewer, R., Hucks-Ortiz, C., Irvine, N. M., Mayer, K. H., & Khan, M. R. (2022). The associations of incarceration and depression with healthcare experiences and utilization among Black men who have sex with men in HPTN 061.
AIDS Care,
34(9), 1169–1178.
Ndeffo-Mbah, M. L., Vigliotti, V. S., Skrip, L. A., Dolan, K., & Galvani, A. P. (2018). Dynamic Models of Infectious Disease Transmission in Prisons and the General Population.
Epidemiologic Reviews,
40(1), 40–57.
to an external site.
Kuester, L. B., & Freestone, M. C. (2021). Time away is time out: Narratives of intentional reimprisonment amongst inmates living with HIV in a US setting.
Critical Public Health,
31(5), 561–572.
Tan, S. T., Rodríguez-Barraquer, I., Kwan, A. T., Blumberg, S., Park, H. J., Hutchinson, J., Leidner, D., Lewnard, J. A., Sears, D., & Lo, N. C. (2025). Strength and durability of indirect protection against SARS-CoV-2 infection through vaccine and infection-acquired immunity.
Nature Communications,
16(1), 1090.
