HCS 457 Week 2 Epidemiology Concepts: Measurement of Health Status Example

Counting Lyme Disease in One County: Incidence, Prevalence, Rates, Surveillance Gaps and What the Numbers Can and Cannot Tell a Health Department

[Student Name]

University of Phoenix

HCS/457: Public and Community Health

Week 2 Assignment

[Instructor Name]

[Date]

The county and its case counts are composites written for a model paper; national figures come from the sources listed.

At its spring meeting, the board of health in a composite county of 180,000 people asked a direct question: is Lyme disease getting worse here? Reported cases had risen from 72 to 104 over three years, and a local news story had called it an epidemic. Answering the question well requires more than looking at counts. This paper applies basic epidemiologic measures to the county's Lyme disease data, compares the county with larger areas, explains what surveillance data miss and describes how the health department should present the results.

Choosing the Right Measure

Epidemiologists describe the amount of disease in a population with two main measures. Incidence counts new cases occurring during a period among people at risk. Prevalence counts all people who have the condition at a point or during a period, whether their disease began recently or long ago (Centers for Disease Control and Prevention, 2012). Prevalence suits long-lasting conditions such as diabetes. Lyme disease is an acute infection, usually treated and resolved within weeks, so prevalence at any moment would be small and would say little about risk. Incidence, and specifically the incidence rate per 100,000 people per year, is the right measure.

Crude Incidence Over Three Years

The crude incidence rate divides new reported cases by the county's population and multiplies by 100,000. With a population of 180,000 in each year, the rates were:

Year 1: 72 cases / 180,000 x 100,000 = 40.0 per 100,000.

Year 2: 88 cases / 180,000 x 100,000 = 48.9 per 100,000.

Year 3: 104 cases / 180,000 x 100,000 = 57.8 per 100,000.

The rate rose by about 44% over three years. Because the population barely changed, the rise in rates mirrors the rise in counts; in a fast-growing county, the two could diverge, which is why rates are always the safer basis for comparison.

Age-Specific Rates

A crude rate treats the whole population alike. Age-specific rates divide cases in an age group by the population in that group. In Year 3, the county reported 21 cases among 22,000 children aged 5 to 14, a rate of 95.5 per 100,000, and 33 cases among 27,000 adults aged 55 to 69, a rate of 122.2 per 100,000, compared with 57.8 overall. The age-specific rates reveal two groups at markedly higher risk, schoolchildren and older adults who spend time outdoors, a pattern that the single crude rate completely hides. This matches the national pattern of a bimodal age distribution for Lyme disease.

Comparing Places

Comparisons must use rates. The county's Year 3 rate of 57.8 per 100,000 was higher than its state's rate of about 41 per 100,000 in the same year. Nationally, reported rates vary enormously: most cases come from a group of high-incidence states in the Northeast, mid-Atlantic and upper Midwest, while many Southern and Western states report very few. Comparing the county with a national average would mislead; comparison with its own state and neighbors is more meaningful.

What Surveillance Misses

Reported cases are not the same as all cases. Clinicians must recognize the disease, test or diagnose it and report it, and the health department must confirm that the case meets the surveillance definition. Kugeler et al. (2021) used a large national database of insurance claims and estimated that roughly 476,000 Americans a year received a Lyme diagnosis and treatment between 2010 and 2018, many times the number reported through surveillance. Some of those diagnoses may be wrong, but most experts agree that reported cases are a fraction of the true total. For the county, the rise from 72 to 104 reported cases could reflect a real increase, greater awareness among clinicians, a new laboratory reporting system or all three.

Other Measures of Health Status

Lyme disease rarely causes death, so mortality rates are not useful here. Other measures of burden include the share of cases with late manifestations, such as arthritis or facial palsy, which suggests delayed diagnosis, and emergency department visits for tick bites, which the county's syndromic surveillance system counts in near real time. The proportion of cases with late signs fell from 24% to 18% over the three years, suggesting earlier recognition.

Where the Cases Happen

Rates by place add a third dimension. The county geocoded Year 3 cases by residence: 61 of the 104 came from the four townships along the river corridor, home to about 48,000 residents, a rate of about 127 per 100,000, compared with roughly 33 per 100,000 in the rest of the county. The river townships have more wooded lots, more deer and more homes built at the edge of forest. The map does not prove where each person was bitten, since people are infected at parks, trails and workplaces as well as at home, but it points prevention toward the places where exposure is most likely and suggests where tick checks and yard management messages will matter most.

Presenting the Numbers to the Board

The health department's answer to the board should be careful. Reported incidence has risen, and two age groups carry most of the risk. Part of the increase may reflect better recognition and reporting rather than more infection, and reported cases undercount the true burden. The practical conclusion does not depend on resolving that uncertainty: prevention should focus on children and older adults, and clinicians should keep reporting. A one-page summary with a small table of crude and age-specific rates, a comparison with the state and a plain statement of the data's limits would serve the board better than a headline number, and it models the kind of data-based reporting health administrators are expected to provide to governing bodies (Shi & Singh, 2022).

Conclusion

Measuring health status is a matter of choosing the right measure, calculating it correctly and saying honestly what it can and cannot show. For Lyme disease in one county, incidence rates, age-specific rates and a clear view of surveillance gaps turn a frightening headline into information the board can use.

References

Centers for Disease Control and Prevention. (2012). Principles of epidemiology in public health practice: An introduction to applied epidemiology and biostatistics (3rd ed.). https://archive.cdc.gov/www_cdc_gov/csels/dsepd/ss1978/index.html

Kugeler, K. J., Schwartz, A. M., Delorey, M. J., Mead, P. S., & Hinckley, A. F. (2021). Estimating the frequency of Lyme disease diagnoses, United States, 2010-2018. Emerging Infectious Diseases, 27(2), 616-619. https://doi.org/10.3201/eid2702.202731

Shi, L., & Singh, D. A. (2022). Delivering health care in America: A systems approach (8th ed.). Jones & Bartlett Learning.