MPH 530 Week 6 Applied Epidemiologic Case Study Example

Eight Days Over 100 Degrees: An Applied Epidemiologic Case Study of Heat Illness, From Syndromic Surveillance to Evaluating a Heat Action Plan

[Student Name]

University of Phoenix

MPH/530: Epidemiology Concepts and Public Health Diseases

Week 6 Assignment

[Instructor Name]

[Date]

The county, the heat wave, emergency visit counts and plans are composites written for a model paper; national findings come from the sources cited.

In late July, the composite southern Colorado county recorded eight consecutive days with high temperatures above 100 degrees. On the fourth day, the health department's syndromic surveillance system, which receives emergency department visit data daily, flagged a sharp rise in visits with heat-related illness. This final case study follows the department's epidemiologic work from that alert to an evaluation plan, drawing on each skill from the course.

The National Picture

Heat is a leading weather-related cause of death. An analysis of national mortality data found an average of 702 heat-related deaths a year in the United States from 2004 through 2018, and death rates ran higher for men, for people 65 and over, for Native American residents and for people living in either the most rural or the most urban counties (Vaidyanathan et al., 2020).

Heat Illness Beyond Deaths

Deaths are the tip of the burden. A nationally representative analysis estimated 326,497 emergency department visits for heat illness in the summers of 2006 through 2010; 88.2% were treated and released, 11.8% were admitted and visit rates tracked annual temperature anomalies closely, with the highest rates in rural areas (Hess et al., 2014). For every heat death, hundreds of people reach the emergency department.

Skill One: Measures

The syndromic system recorded 86 emergency visits for heat-related illness during the eight days, compared with a baseline of about 12 for the same period in mild summers. With a county population of about 169,000, the heat-wave visit rate was 86 divided by 169,000, or about 51 per 100,000 over eight days. Two deaths were attributed to heat by the coroner during the same period.

Skill Two: Time

The epidemic curve plotted daily visits against daily high temperature. Visits rose on day two, peaked on day five at 17 and fell after temperatures dropped. Visits lagged temperature by about a day, consistent with cumulative heat stress.

Skill Two: Place

Visits were highest among residents of two older neighborhoods with little tree cover and many homes without central air conditioning, and among people with no fixed address.

Skill Two: Person

Adults 65 and older had a visit rate of about 96 per 100,000 during the heat wave, nearly twice the overall rate. Men made up 64% of visits. Outdoor workers, including construction and agricultural workers, accounted for 23 visits; 14 visits were by people experiencing homelessness.

Skill Three: A Hypothesis

Staff hypothesized that people who did not reach cooling centers were at higher risk. Cooling centers had opened on day two, but attendance was low.

Skill Three: A Design

A full cohort study was not feasible quickly, so the epidemiologist designed a small case-control comparison: 40 older adults treated for heat illness, the cases, were compared with 80 older adults of similar age from the same neighborhoods, identified through the senior center and aging services, who were not treated for heat illness. Both groups were asked about air conditioning, cooling center use, living alone and medications.

Results

Cases were more likely than controls to live alone and to lack working air conditioning, and less likely to have visited a cooling center. Living without air conditioning had an odds ratio of about 3.4.

Skill Four: Bias and Confounding

The comparison has limits. Controls recruited through the senior center may be more socially connected than typical older adults, which could exaggerate the protective effect of social contact. Cases may recall their heat exposure differently after being ill. Income could confound the link between air conditioning and illness, since poorer residents are both less likely to have air conditioning and more likely to have chronic diseases. The team adjusted for self-reported chronic conditions but could not fully control for income.

What the Deaths Showed

The two heat deaths were reviewed in detail. Both were older adults who lived alone in upstairs apartments without air conditioning, found by relatives after a day or more. Neither had been reached by outreach. Their circumstances matched the case-control findings and the national pattern, giving the numbers a human face for the commission.

Outdoor Workers

The 23 visits by outdoor workers came mostly from construction sites and farms. Interviews found that few workplaces had scheduled breaks in shade or increased water access during the heat wave. Unlike older adults, workers often had no choice about their exposure, which pointed to employer practices rather than individual behavior.

Skill Five: Surveillance

Syndromic surveillance detected the rise within a day, allowing the department to extend cooling center hours and send outreach teams. After the event, the team reviewed the system's performance and added a daily heat illness dashboard for summer months.

Why a Case-Control Design Here

The case-control design fit the situation: heat illness was relatively uncommon, the question was about past exposures and results were needed within weeks, before the next heat wave. A cohort following thousands of older adults through future summers would give stronger evidence but too late for this summer's decisions.

Recommendations

The analysis pointed to specific actions: door-to-door checks on older adults living alone in the two neighborhoods during heat alerts, transportation to cooling centers, a program to repair or provide air conditioning units for low-income older adults, water and cooling stations for outdoor workers and shade and water at encampments.

A Heat Action Plan

The department combined these actions into a heat action plan triggered when forecast temperatures exceed a threshold, with partners including aging services, the city, employers and homeless services.

Skill Six: Evaluation

Evaluating the plan requires a comparison. A Montreal study used a difference-in-differences approach, comparing mortality on hot days and non-hot days before and after a heat action plan, and found evidence that the plan reduced mortality on hot days, with larger reductions for older people and people in low-education neighborhoods (Benmarhnia et al., 2016). The county will use the same design with emergency visits and deaths, comparing hot and non-hot days before and after the plan.

Communicating Risk

During future heat alerts, the department will issue warnings through text alerts, radio in English and Spanish, senior centers and employers, and will ask neighbors and family members to check on older adults living alone, the group at highest risk of dying unseen.

Limits

Because the county sees only dozens of heat visits in a summer, results will swing noticeably between summers. Changes in air conditioning ownership and population could affect results. The evaluation will run for at least five summers.

Conclusion

An eight-day heat wave tested every skill in the course: rates sized the problem, descriptive analysis found the older adults, outdoor workers and neighborhoods at risk, a case-control comparison tested the cooling center hypothesis, bias analysis tempered the result and surveillance enabled rapid response. National evidence framed the risks, and a difference-in-differences design borrowed from Montreal will tell whether the county's heat action plan saves lives.

References

Benmarhnia, T., Bailey, Z., Kaiser, D., Auger, N., King, N., & Kaufman, J. S. (2016). A difference-in-differences approach to assess the effect of a heat action plan on heat-related mortality, and differences in effectiveness according to sex, age, and socioeconomic status (Montreal, Quebec). Environmental Health Perspectives, 124(11), 1694-1699. https://doi.org/10.1289/EHP203

Hess, J. J., Saha, S., & Luber, G. (2014). Summertime acute heat illness in U.S. emergency departments from 2006 through 2010: Analysis of a nationally representative sample. Environmental Health Perspectives, 122(11), 1209-1215. https://doi.org/10.1289/ehp.1306796

Vaidyanathan, A., Malilay, J., Schramm, P., & Saha, S. (2020). Heat-related deaths: United States, 2004-2018. MMWR. Morbidity and Mortality Weekly Report, 69(24), 729-734. https://doi.org/10.15585/mmwr.mm6924a1