| Course | IHP 515 Population-Based Epidemiology |
|---|---|
| Module | Module 3 |
| Paper type | graduate milestone descriptive epidemiology |
| Length | About 1,030 words, 6 pages |
| Format | APA 7 student paper |
| School | Southern New Hampshire University |
| Program | MPH |
| Updated | September 2026 |
Free sample paper for IHP 515 Module 3
Milestone One: Opioid Overdose Deaths in Harlan County, 2019-2023
[Student Name]
Southern New Hampshire University
IHP 515: Population-Based Epidemiology
Module Three Milestone One
[Instructor Name]
[Date]
Milestone One: Opioid Overdose Deaths in Harlan County, 2019-2023
Descriptive epidemiology asks three questions about a health problem: when is it happening, who is affected and where? Answering them carefully comes before any attempt to explain causes, because good description reveals patterns that suggest hypotheses and guides where to act. This milestone describes opioid overdose deaths across Harlan, a composite county of some 212,000 residents, from 2019 through 2023, using death certificates, medical examiner reports and census estimates.
National Context
Rudd et al. (2016) documented rapid increases in overdose deaths in the United States, with opioid-involved deaths rising steeply and the largest recent growth involving heroin and synthetic opioids such as fentanyl. Their report showed that the epidemic had moved from prescription opioids toward illicit drugs, a transition that shaped how many communities experienced the crisis in the years that followed.
Time
Harlan County's overdose death rate was fairly stable at 17 to 19 per 100,000 from 2016 through 2019, then rose each year: 22.4 in 2020, 26.9 in 2021, 30.1 in 2022 and 33.5 in 2023. The share of deaths with fentanyl detected in toxicology rose from 31% in 2019 to 78% in 2023. Deaths clustered modestly in late spring and summer and in the weeks after holiday periods. A sharp jump in the second quarter of 2020 coincided with pandemic restrictions and the temporary closure of the county's only opioid treatment program.
Table 1. Overdose Death Rates in Harlan County
| Year | Deaths | Rate per 100,000 | Fentanyl detected |
|---|---|---|---|
| 2019 | 38 | 18.1 | 31% |
| 2020 | 47 | 22.4 | 49% |
| 2021 | 57 | 26.9 | 63% |
| 2022 | 64 | 30.1 | 71% |
| 2023 | 71 | 33.5 | 78% |
Note. Figures are illustrative for the composite county.
Person
Over the five years, 72% of those who died were men. The highest rates were among adults aged 25 to 44, at 75 per 100,000 in 2023, followed by those aged 45 to 64. Rates among Black residents rose fastest, from 14.2 per 100,000 in 2019 to 41.8 in 2023, overtaking rates among white residents, which rose from 19.5 to 32.6. Nearly a quarter of decedents had left jail or prison within the prior twelve months, and 31% had a documented nonfatal overdose in the preceding twelve months. Fewer than one in five had any record of treatment with methadone or buprenorphine in the year before death.
Place
Deaths were mapped by residence across the county's six planning areas. The highest rate, 58 per 100,000, occurred in the Eastside area, which has the county's highest poverty rate and the plant closure that cost about 900 jobs in 2020. Two rural areas in the north had rates above the county average despite small numbers, and a third of deaths in those areas occurred with no one present to call for help. The lowest rate was in the affluent Westfield area, at 12 per 100,000.
Interpreting Differences Across Groups and Places
Krieger (2001) offers terms for interpreting such patterns without reducing them to individual behavior. Socioeconomic position, discrimination and the social production of disease direct attention to the conditions that shape exposure and access, such as job loss, incarceration, neighborhood poverty and unequal access to treatment. The faster rise among Black residents and the concentration in Eastside suggest that differences in drug supply exposure, treatment access and the aftermath of incarceration may be at work, rather than differences in individual choices.
A Population Perspective
Rose (1985) distinguished the causes of individual cases from the causes of a population's overall rate. Harlan's rise across nearly every group and area suggests a shift in a population-level exposure, fentanyl's spread through the county's street drugs, layered on top of existing vulnerabilities. That perspective implies that prevention must include population-wide measures, such as broad naloxone distribution, as well as efforts focused on the highest-risk groups identified here.
Circumstances of Death
Medical examiner reports add detail that rates alone cannot. In 2023, 61% of deaths occurred in a private residence, and in 44% of cases the person was alone, meaning no one was present to call for help or give naloxone. Naloxone was administered by a bystander or emergency responder in only 18% of deaths. Most people who died had used alone at home, and many of those in the northern rural areas lived more than twenty minutes from the nearest emergency medical services station. Among those with prior nonfatal overdoses, the median time from the last emergency visit to death was about four months, a window in which treatment or naloxone might have been offered. These circumstances point to specific opportunities: getting naloxone into homes, reducing solitary use and connecting people to treatment after an emergency visit.
Hypotheses
The description suggests four hypotheses for further study. First, fentanyl contamination of the local drug supply is the main driver of the county-wide increase. Second, the closure of the treatment program in 2020 contributed to the rise in 2020 and 2021. Third, release from incarceration without treatment is a major risk factor for death. Fourth, the faster rise among Black residents reflects later arrival of fentanyl in some drug markets combined with lower access to medication treatment.
Data Limitations
Death certificates vary in how thoroughly drugs are listed, especially in earlier years when toxicology testing was less complete. Race is recorded by funeral directors and may be misclassified. Place is based on residence rather than where the overdose occurred. Rates for small areas and groups are unstable from year to year.
Comparing with the State
Harlan's 2023 rate of 33.5 per 100,000 compares with a statewide age-adjusted rate of about 29 per 100,000 in the same year, suggesting the county's burden is somewhat higher than average, though age adjustment for the county would refine the comparison.
Next Steps
The next milestone will review evidence on interventions that address these patterns, including naloxone distribution and medication treatment after overdose. Later work will plan surveillance improvements and analyses to test the hypotheses.
Conclusion
Harlan County's overdose deaths nearly doubled over five years, rising fastest among Black residents and concentrating among adults aged 25 to 44, men, people recently released from incarceration and residents of the poorest area, as fentanyl came to dominate toxicology results. Careful description by time, person and place points to where action is most urgent and what questions to ask next.
References
Krieger, N. (2001). A glossary for social epidemiology. Journal of Epidemiology and Community Health, 55(10), 693-700. https://doi.org/10.1136/jech.55.10.693
Rose, G. (1985). Sick individuals and sick populations. International Journal of Epidemiology, 14(1), 32-38. https://doi.org/10.1093/ije/14.1.32
Rudd, R. A., Aleshire, N., Zibbell, J. E., & Gladden, R. M. (2016). Increases in drug and opioid overdose deaths: United States, 2000-2014. MMWR. Morbidity and Mortality Weekly Report, 64(50-51), 1378-1382. https://doi.org/10.15585/mmwr.mm6450a3
What the IHP 515 Module 3 instructions ask for
Milestone One in IHP 515 usually asks you to describe a population health problem using descriptive epidemiology, organized by time, person and place, and to generate hypotheses. Graduate milestones commonly run four to six APA 7 pages. Present rates rather than counts, show trends in a table, describe who is affected by relevant characteristics and map where cases occur. Interpret differences thoughtfully, avoiding explanations that blame groups, and end with specific hypotheses that the patterns suggest. Name the limits of your data sources, because instructors expect descriptive work to acknowledge what the numbers can and cannot show before moving on to analysis. IHP 515 graders notice clean headings in IHP 515 papers. IHP 515 names and dates need checking before IHP 515 submission.
How this IHP 515 Module 3 milestone one example is built
This milestone describes opioid overdose deaths in a composite county from 2019 to 2023. Rates rose from 18.1 to 33.5 per 100,000 as fentanyl detection climbed from 31% to 78%, shown in a table. By person, deaths were concentrated among men and adults aged 25 to 44, rose fastest among Black residents and often followed recent incarceration or a prior overdose. By place, the poorest area reached 58 per 100,000. Rudd and colleagues supply national context, Krieger's social epidemiology terms guide interpretation and Rose's population perspective frames four hypotheses, followed by data limitations and next steps. IHP 515 students can reuse this structure for IHP 515 work. IHP 515 claims here trace to cited IHP 515 sources.
Where the IHP 515 Module 3 rubric puts the points
Descriptive epidemiology milestones in IHP 515 are commonly judged on complete coverage of time, person and place, use of rates, clear tables, thoughtful interpretation of group differences, specific hypotheses, recognition of data limitations, scholarly support and APA 7. Strong milestones reveal patterns that point to action and questions, such as risk after release from incarceration. Milestones lose points when they report only counts, skip one of the three dimensions, interpret group differences in stigmatizing ways or end without hypotheses. Hypotheses that follow directly from the patterns are often credited as the milestone's key contribution. IHP 515 marks favor careful formatting across IHP 515 sections. IHP 515 citations keep every IHP 515 argument credible.
IHP 515 Module 3 help: the mistakes that cost points
In IHP 515, Milestone One often loses points for counts without rates, for missing place or person descriptions, for interpretations that blame groups and for hypotheses that do not follow from the data. Another frequent weakness is ignoring how data sources were produced. Describe by time, person and place with rates, use tables, interpret with care, generate specific hypotheses and state limitations. If you are working with a different health problem or data set, add it to your IHP 515 notes so the milestone describes those data. IHP 515 drafts start well from a IHP 515 outline. IHP 515 feedback already received guides IHP 515 revisions.
Get IHP 515 Module 3 written to your instructions
Send the IHP 515 Milestone One prompt and the data or problem you are describing. The milestone will organize rates by time, person and place, present tables, interpret differences carefully, generate specific hypotheses and name data limits, within 24 to 48 hours, free the first time. The paper above is an original model document written by our desk, not a submitted student paper and not an official Southern New Hampshire University document.
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IHP 515 Module 3 questions, answered
Where can I find a free IHP 515 Module 3 Milestone One sample?
The whole milestone is here: descriptive epidemiology of overdose deaths by time, person and place, with hypotheses and data limits.
What is descriptive epidemiology?
The study of how a health problem is distributed by time, person and place, used to reveal patterns and generate hypotheses.
Why describe by time, person and place?
Each dimension reveals different patterns, such as trends, high-risk groups and hot spots, that guide action and further study.
Who is at highest risk of opioid overdose death?
Patterns often include young and middle-aged adults, men, people recently released from incarceration and people with prior overdoses.
How should differences between groups be interpreted?
By considering the social conditions that shape exposure and access, rather than attributing differences to individual choices.