Counting Before Planning: A Descriptive Epidemiology of Opioid Overdose Deaths in a Composite County and a MAP-IT Plan Built on It
[Student Name]
University of Phoenix
NSG/486: Public Health: Health Promotion and Disease Prevention
Week 3 Assignment
[Instructor Name]
[Date]
The county and all county figures are a composite written for a model paper; the national figure is cited.
Public health planning that begins with a solution often picks the wrong one. Epidemiology offers a better starting point: count the cases, calculate rates, describe who, where and when, and only then decide what to do. This paper applies that approach to opioid overdose deaths in a composite county of 150,000 people and then uses the results to build a community health plan. The numbers do not tell a county what to do, but they tell it where to stand, and in overdose prevention the place a program stands decides whom it reaches.
Measures and Calculations
Epidemiology describes disease with rates rather than counts, because counts cannot be compared across populations of different sizes (Celentano & Szklo, 2019). A rate needs three parts: the number of events, the population at risk and the time period. In this paper every rate is expressed per 100,000 people per year.
In the composite county, 63 residents died of opioid-involved overdoses last year. The crude death rate is therefore 63 divided by 150,000, multiplied by 100,000, or 42.0 per 100,000. Four years earlier, the county recorded 29 such deaths, a crude rate of 19.3 per 100,000. With a stable population, deaths rose by 117% over four years, calculated as 63 minus 29, divided by 29.
Group-specific rates show where the burden falls. Of the 63 deaths, 46 were men and 17 were women. With about 74,000 men and 76,000 women in the county, the rate was 62.2 per 100,000 for men and 22.4 per 100,000 for women, so men died at almost three times the rate of women. Thirty-eight deaths occurred among adults aged 25 to 44, a group of about 39,000 people, giving an age-specific rate of 97.4 per 100,000, more than twice the county's overall crude rate.
For comparison, the national age-adjusted drug overdose death rate for all drugs was 32.6 per 100,000 in 2022 (Spencer et al., 2023). The county's figure is a crude rate for opioid-involved deaths only, so the two are not directly comparable; an age-adjusted county rate would be needed for a fair comparison, and the county's large share of young adults could make its crude rate look higher than an adjusted rate would.
Person, Place and Time
Descriptive epidemiology organizes cases by person, place and time. By person, deaths were concentrated among men and among adults aged 25 to 44, and toxicology showed fentanyl in 54 of the 63 deaths, often combined with stimulants. About a third of the people who died had been released from jail or a residential treatment program within the previous year, a group known to be at high risk because tolerance falls during abstinence.
By place, 41 of the 63 deaths occurred in two zip codes near the county seat, which together hold about a third of the population. Most deaths occurred at home, and in about half of them another person was present nearby, which means a bystander could have given naloxone if one had been available.
By time, deaths rose steadily over four years and clustered on weekends and in the first week of the month, a pattern often linked to the timing of income payments.
Limits of the Data
These figures carry limits that the coalition must understand before acting on them. Death certificate data depend on toxicology testing and on how medical examiners record the drugs involved, and practices vary between counties and change over time; part of an apparent rise can reflect more complete testing. Counts of 63 and 29 are small enough that one unusual year can shift a rate noticeably, so a three-year rolling average would give a steadier picture of the trend. Deaths also capture only the most severe outcome. Nonfatal overdoses, which emergency medical services and emergency departments record, are far more numerous and would show where overdoses happen before they become deaths. The plan therefore adds nonfatal overdose data from emergency medical services as a second surveillance source. None of these limits undermines the main findings, which are consistent across sources, but they shape how confidently the coalition can read small changes from one year to the next.
The Epidemiologic Triangle
The epidemiologic triangle explains disease as the interaction of an agent, a host and an environment (Celentano & Szklo, 2019). Here the agent is illicitly manufactured fentanyl, whose potency and unpredictable concentration in the drug supply make overdose more likely. The host factors include opioid use disorder, loss of tolerance after incarceration or treatment, and use of multiple substances. The environment includes using alone, limited naloxone availability, limited access to medication treatment for opioid use disorder in the two high-burden zip codes and stigma that discourages people from calling for help. The triangle points to interventions on each side: reducing exposure to the agent, supporting the host through treatment and changing the environment so that overdoses are witnessed and reversed.
A MAP-IT Plan
MAP-IT, the planning framework used with Healthy People, moves through five steps: mobilize partners, assess the community's needs and resources, plan an approach, implement the plan and track progress (Office of Disease Prevention and Health Promotion [ODPHP], n.d.).
Mobilize. The health department convenes the county's overdose prevention coalition: the sheriff's office and jail, emergency medical services, the two hospitals, treatment providers, pharmacies, a harm reduction program and people with lived experience of opioid use and recovery.
Assess. The coalition uses the descriptive epidemiology above and adds a resource inventory, which finds that naloxone is sold in pharmacies but is rarely stocked at the jail's release desk, and that the two high-burden zip codes have one buprenorphine prescriber between them.
Plan. The coalition sets a goal to reduce opioid overdose deaths by 25% within three years and chooses three strategies matched to the data. First, provide naloxone and overdose education to every person leaving the jail and residential treatment, the group at highest risk after release. Second, place naloxone boxes and conduct community training in the two high-burden zip codes, since most deaths happened at home with someone nearby. In an interrupted time series across Massachusetts towns, Walley et al. (2013) reported lower opioid overdose death rates where naloxone programs had been put in place, and the reductions were larger where more residents had enrolled. Third, add a buprenorphine clinic day in the high-burden area in partnership with a federally qualified health center.
Implement. Public health nurses lead the naloxone training, work with jail health staff on release kits and coordinate with the health center on the clinic schedule.
Track. The coalition tracks the number of naloxone kits distributed, the number of people trained, reported naloxone reversals from emergency medical services and, as the outcome, the opioid overdose death rate, calculated each year the same way as the baseline.
Conclusion
Counting before planning changed what the county would do. The crude rate showed a doubling in four years; group-specific rates showed that young adult men carried the heaviest burden; place and circumstance showed that most deaths occurred at home in two zip codes, often with someone nearby; and the triangle showed where intervention could break the chain. A MAP-IT plan built on those findings puts naloxone, training and treatment in the places and at the moments where the data say deaths occur.
References
Celentano, D. D., & Szklo, M. (2019). Gordis epidemiology (6th ed.). Elsevier.
Office of Disease Prevention and Health Promotion. (n.d.). Program planning: MAP-IT. Healthy People 2030. U.S. Department of Health and Human Services. https://odphp.health.gov/healthypeople/tools-action
Spencer, M. R., Garnett, M. F., & Minino, A. M. (2023). Drug overdose deaths in the United States, 2002-2022 (NCHS Data Brief No. 491). National Center for Health Statistics. https://doi.org/10.15620/cdc:135849
Walley, A. Y., Xuan, Z., Hackman, H. H., Quinn, E., Doe-Simkins, M., Sorensen-Alawad, A., Ruiz, S., & Ozonoff, A. (2013). Opioid overdose rates and implementation of overdose education and nasal naloxone distribution in Massachusetts: Interrupted time series analysis. BMJ, 346, Article f174. https://doi.org/10.1136/bmj.f174
How this NSG 486 Week 3 example is structured
The University of Phoenix library guide for NSG/486 lists Week 3 as Epidemiology and Public/Community Health Planning. The paper computes every rate it uses and shows the arithmetic, because epidemiology papers are graded on whether the numbers are right and correctly interpreted. Descriptive epidemiology comes before any explanation, the triangle comes before the plan, and the plan follows the MAP-IT steps in order so the reader can see how each step uses the data. Students search this week as NSG 486 Week 3, NSG486 Wk 3 or NSG/486 Wk 3; all three are the same assignment.
NSG/486 Week 3 questions, answered
What does NSG/486 Week 3 usually ask for?
The library guide for NSG/486 lists Week 3 as epidemiology and public or community health planning. Many sections ask for a paper that uses epidemiologic data, such as rates and trends, to describe a health problem in a community and to plan an intervention, often with a named planning model. Check your instructions for the data source and model.
What is the difference between a crude rate and an age-adjusted rate?
A crude rate divides all cases by the whole population. An age-adjusted rate weights the rates for each age group to a standard population, so communities with different age structures can be compared fairly. When you compare your county with the nation, say which kind of rate you are using.
What does MAP-IT stand for?
Mobilize, Assess, Plan, Implement and Track. It is the planning framework associated with Healthy People, and it moves a community from gathering partners to measuring results.
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