| Course | NR 442 Community Health Nursing |
|---|---|
| Week | 5 |
| Paper type | Epidemiology write-up |
| Length | About 1,110 words, 6 pages |
| Format | APA 7 student paper |
| School | Chamberlain University |
| Program | RN-to-BSN |
| Updated | October 2026 |
Free sample paper for NR 442 Week 5
Hepatitis A Among People Experiencing Homelessness in a Composite County: An Epidemiology Write-Up of a Sixteen-Week Cluster
Student Name
College of Nursing, Chamberlain University
NR 442: Community Health Nursing
Instructor Name
Month Day, Year
Hepatitis A Among People Experiencing Homelessness in a Composite County: An Epidemiology Write-Up of a Sixteen-Week Cluster
The Case Definition, Written Out
This write-up uses the national surveillance case definition for acute hepatitis A adopted by the Council of State and Territorial Epidemiologists and published by the Centers for Disease Control and Prevention (Centers for Disease Control and Prevention, 2019). A case must first meet the clinical criteria: an acute illness with a discrete onset of symptoms consistent with acute viral hepatitis, such as fever, malaise, loss of appetite, nausea, abdominal pain or dark urine, together with jaundice, or an elevated total bilirubin, or an alanine aminotransferase level above 200 international units per liter. A case is confirmed when it meets the clinical criteria and has a positive test for immunoglobulin M antibody to hepatitis A virus or a positive nucleic acid test, or when it meets the clinical criteria and occurred in a person who had contact with a laboratory-confirmed case 15 to 50 days before symptom onset.
For its own outbreak investigation, the county health department also tracked suspected cases, people with compatible symptoms reported by shelters or street outreach teams who had not yet been tested. Suspected cases are not counted in any rate below. Every count in this paper is of confirmed cases only, because that is the category reported to the state and nationally.
How a Case Becomes a Number
Hepatitis A is a reportable condition in every state. In the composite state used here, laboratories and clinicians must report a positive hepatitis A test or a suspected case to the local health department within one business day under the state's reportable disease rule. The local health department investigates each report, confirms whether the person meets the case definition, interviews the person about symptoms, contacts and living situation, and enters the case into the state's surveillance system, which transmits it to the national notifiable disease system. Each number in this paper therefore depends on four steps: a sick person seeking care, a clinician ordering the test, a laboratory reporting it and an investigator confirming it. A person who never reaches care never becomes a case.
The reporting window matters for more than counting. Hepatitis A vaccine or immune globulin given within two weeks of exposure can prevent illness in contacts, according to national recommendations (Nelson et al., 2020), so each day between a positive test and a completed investigation shortens the time left to protect the people who shared a tent, a meal or drug equipment with the case. During this cluster, investigators found that the median time from positive test to interview was three days for housed cases and nine days for people experiencing homelessness, because the latter were harder to locate. That delay affects both the completeness of contact information behind the numbers and the opportunity for prevention.
Numerator and Denominator
Numerator: 38 confirmed cases of acute hepatitis A with symptom onset during a 16-week period, reported to the county health department (composite county surveillance data). Of these, 21 were in people experiencing homelessness at the time of illness, 11 in people who reported drug use but had housing, and 6 in neither group.
Denominator, whole county: about 520,000 residents (U.S. Census Bureau population estimate for the same year).
Denominator, people experiencing homelessness: 1,450 people counted in the county's most recent point-in-time count, conducted in January by the local continuum of care under federal housing program requirements.
Baseline for comparison: an average of 3 confirmed cases per year over the previous five years in the same county, from the same surveillance system.
Arithmetic, Shown
The attack rate in the whole county over the 16 weeks was 38 divided by 520,000, multiplied by 100,000, which is 7.3 cases per 100,000 residents. Among people experiencing homelessness it was 21 divided by 1,450, multiplied by 100,000, which is about 1,448 per 100,000, or roughly 1.4 of every 100 people counted. The rate among people experiencing homelessness was therefore about 200 times the rate for the whole county. Compared with the county's usual burden, 38 cases in 16 weeks is more than twelve times the five-year average of 3 cases per year, which meets any reasonable definition of an outbreak.
These are cumulative incidence figures for a defined period, not prevalence. Prevalence would count everyone currently infected at a point in time, which for an acute infection lasting weeks is a different and much smaller figure. The distinction matters when describing the trend: a falling weekly count of new cases would mean the outbreak is slowing even if many people are still sick.
Comparison and Context
The cluster fits a national pattern. Beginning in 2016, hepatitis A infections in the United States rose sharply after years of decline, driven by person-to-person outbreaks among people who use drugs and people experiencing homelessness, groups that had not been routinely vaccinated as children (Foster et al., 2019). In response, the Advisory Committee on Immunization Practices recommended hepatitis A vaccination for all people experiencing homelessness aged one year and older and for people who use drugs (Nelson et al., 2020). The county's cluster, with more than half of cases among people experiencing homelessness and most of the rest among people who use drugs, matches that pattern closely.
Limits
Four limits shape how far these figures can be trusted. First, under-ascertainment: hepatitis A is often mild or without symptoms in younger adults, and people experiencing homelessness may not seek care, so confirmed cases are a floor, not a full count. Second, testing access changed during the cluster, because once the outbreak was recognized, outreach teams began referring people for testing, which found cases that would otherwise have been missed and makes the later weeks look worse than the earlier ones. Third, the homelessness denominator comes from a one-night January count that is known to undercount people living unsheltered, which would make the true rate in that group lower than 1,448 per 100,000, though still far higher than the county rate. Fourth, housing status was self-reported at interview and may have changed during the 16 weeks.
None of these limits changes the conclusion that the county experienced an outbreak concentrated among people experiencing homelessness. They do limit any claim about the exact size of the rate difference, and they mean that a decline in reported cases after vaccination clinics began should be read against changes in testing, not taken at face value.
References
Centers for Disease Control and Prevention. (2019). Hepatitis A, acute: 2019 case definition. National Notifiable Diseases Surveillance System. https://ndc.services.cdc.gov/case-definitions/hepatitis-a-acute-2019/
Foster, M. A., Hofmeister, M. G., Kupronis, B. A., Lin, Y., Xia, G.-L., Yin, S., & Teshale, E. (2019). Increase in hepatitis A virus infections: United States, 2013-2018. Morbidity and Mortality Weekly Report, 68(18), 413-415. https://doi.org/10.15585/mmwr.mm6818a2
Nelson, N. P., Weng, M. K., Hofmeister, M. G., Moore, K. L., Doshani, M., Kamili, S., Koneru, A., Haber, P., Hagan, L., Romero, J. R., Schillie, S., & Harris, A. M. (2020). Prevention of hepatitis A virus infection in the United States: Recommendations of the Advisory Committee on Immunization Practices, 2020. MMWR Recommendations and Reports, 69(5), 1-38. https://doi.org/10.15585/mmwr.rr6905a1
What the NR 442 Week 5 assignment asks for
The Week 5 write-up has you analyze a communicable disease or health condition in a population using epidemiologic data. Instructors generally want the case definition, how cases are reported, numerators and denominators, calculated rates, comparison with a baseline or other places, limitations and APA. Write out the case definition in the surveillance system's own terms, and say which category your counts use. Explain how a case reaches the health department. Give your numerator and denominator with their sources and dates, and note when they come from different systems. Show the arithmetic. Separate incidence from prevalence. Compare with a baseline. Name the limits and which way each would push the rate.
Inside the NR 442 Week 5 example
The case definition section quotes the clinical and laboratory criteria for confirmed acute hepatitis A and explains how the county also tracked suspected cases. The reporting section describes mandatory reporting by laboratories and clinicians and explains why vaccine or immune globulin within two weeks of exposure makes speed matter, citing Nelson and colleagues. The numerator and denominator section lists 38 confirmed cases, 21 among people experiencing homelessness, a county population of about 520,000 and a point-in-time count of 1,450. The arithmetic section shows both attack rates and their ratio of about 200, and separates cumulative incidence from prevalence. The context section links the cluster to the national rise since 2016. Four limits close the paper.
Reading the NR 442 Week 5 grading rubric
Epidemiology write-up rubrics in this course typically score the case definition, understanding of surveillance and reporting, correct numerators and denominators, accurate calculations, interpretation against a baseline, limitations and APA. Correct calculation counts most, and this paper earns it by showing every division and multiplication where the reader can check it. The case definition row is credited because it is written out before any number and its category is stated. Numerators and denominators score for their sources, dates and the admitted mismatch between systems. Interpretation earns points through the five-year baseline. Limitations are credited because each names the direction it would push the figures. The CDC definition, Foster and colleagues and Nelson and colleagues support the paper.
NR 442 Week 5 help: mistakes that cost points
The most expensive error on this paper is a count presented as if it were a rate, comparing cases in areas of different size with no population underneath. Another loss is a missing case definition, so no reader knows what was counted. Students also confuse incidence with prevalence, use a denominator from a different year without saying so or list limitations without saying how they affect the figures. Choose a condition with public surveillance data for your county or state. National data are acceptable when local counts are suppressed, if labeled. If your assigned condition is different, send the counts you have and an NR 442 epidemiology write-up can show the arithmetic step by step.
Get a NR 442 Week 5 example written to your instructions
Send the condition your section assigned, the rubric and any data set you were pointed at, and we will write a fresh NR 442 Week 5 epidemiology write-up on your numbers rather than these. It comes back inside 24-48h with the arithmetic shown and sources current, and the first one is free.
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NR 442 Week 5 questions, answered
Which condition makes for a workable paper?
One that is notifiable, so a reporting pathway exists to describe, and common enough locally that counts are not suppressed for small numbers. Foodborne illness, pertussis, hepatitis and sexually transmitted infections all satisfy both in most areas. A rare condition forces the writer up to state or national data and removes the local layer the rubric is usually reading for.
Is national data acceptable when local counts are suppressed?
Yes, and the suppression itself is worth a sentence, since small-number rules are part of how surveillance works rather than a gap in the writer's research. The usual arrangement is a national or state rate carrying the analysis with whatever local figure exists reported alongside it, clearly labeled, and no comparison drawn between two different bases.
How much does the paper need on limitations?
A real paragraph. Sections grading this genre closely tend to place several points there, and it is the part writers cut when they run out of room. Naming under-ascertainment, a reporting lag and one source of bias specific to the chosen condition is enough. Generic statements about needing further study earn almost nothing.
Where can I find a free NR 442 Week 5 sample paper?
The complete Week 5 write-up on a hepatitis A cluster among people experiencing homelessness, with the case definition, reporting, numerators, denominators, shown arithmetic, context, limits and three references, is here.
What attack rates does the NR 442 Week 5 write-up calculate?
About 7.3 per 100,000 for the whole county over 16 weeks and about 1,448 per 100,000 among people experiencing homelessness, roughly 200 times higher.