| Course | HLTH 6740 Disaster, Crisis, and Trauma |
|---|---|
| Week | Week 3 |
| Paper type | Prevalence summary brief |
| Length | About 510 words, 4 pages |
| Format | APA 7 student paper |
| School | Walden University |
| Program | MS in Emergency Management |
| Updated | October 2026 |
Free sample paper for HLTH 6740 Week 3
Prevalence Summary: How Common Is PTSD After Disasters, and What the Numbers Depend On
Student Name
Walden University
HLTH 6740: Disaster, Crisis, and Trauma
Instructor Name
Month Day, Year
Prevalence Summary: How Common Is PTSD After Disasters, and What the Numbers Depend On
The Question
This summary reports how common posttraumatic stress disorder is after disasters, then asks what those figures depend on. Estimates of post-event distress move sharply with the instrument used, the interval since the event and the population sampled, so the figures below are reported the way the literature reports them, with their qualifiers attached.
The Figures
Table 1 sets out figures from the sources reviewed.
Table 1
Reported PTSD Prevalence After Disasters, With Qualifiers
| Source | Population | Timing | Method | Reported figure |
|---|---|---|---|---|
| Galea et al. (2005), review | Direct victims | Varies by study | Varies | Roughly 30% to 40% |
| Galea et al. (2005), review | Rescue and recovery workers | Varies by study | Varies | Roughly 10% to 20% |
| Galea et al. (2005), review | General population of affected area | Varies by study | Varies | Roughly 5% to 10% |
| Kessler et al. (2008) | Pre-hurricane residents of Katrina-affected areas, n = 815 | 5 to 8 months, then 1 year later | Screening scale used to estimate diagnosis | 14.9%, then 20.9% |
| Bonanno et al. (2006) | New York area adults, n = 2,752 | Within 6 months | Symptom count | Resilience in 65.1%; PTSD higher with exposure |
What the Figures Depend On
Population. The largest source of variation is who was sampled, and it can change an estimate several times over. Direct victims, rescue workers and the general population of an affected area produce very different rates, which is why a review grouped them separately (Galea et al., 2005). Mixing them, or applying a general population rate to people who lost homes, misleads.
Instrument. Many studies use screening scales rather than diagnostic interviews, mainly because interviews are costly to run at scale after a disaster. Screening scales can estimate the share likely to meet criteria but tend to classify differently from clinical interviews. The Katrina panel, for example, used a screening scale to generate estimates of diagnostic prevalence (Kessler et al., 2008).
Interval. Timing matters in both directions. Distress is usually highest soon after an event and declines, but ongoing stressors can reverse that pattern; in the Katrina panel, the PTSD estimate climbed by about six percentage points between interviews, which the authors linked largely to unresolved hurricane-related stresses (Kessler et al., 2008).
Event type and setting. An earlier review found more impairment after mass violence than natural disasters and in developing than developed countries (Norris et al., 2002).
What a Figure Can Honestly Say
A responsible statement of prevalence names the population, the timing and the method: for example, among adult residents of hurricane-affected areas surveyed five to eight months after the storm with a screening scale, an estimated 15% met criteria for PTSD. Stripped of those qualifiers, the same number could be read as the rate for all survivors or all disasters, which it is not. Reviews of the field continue to stress these methodological limits (Goldmann & Galea, 2014). For planning, the practical rule is to use figures from studies whose population, timing and method most closely match the group being planned for, and to state the mismatch where one remains.
References
Bonanno, G. A., Galea, S., Bucciarelli, A., & Vlahov, D. (2006). Psychological resilience after disaster: New York City in the aftermath of the September 11th terrorist attack. Psychological Science, 17(3), 181-186. https://doi.org/10.1111/j.1467-9280.2006.01682.x
Galea, S., Nandi, A., & Vlahov, D. (2005). The epidemiology of post-traumatic stress disorder after disasters. Epidemiologic Reviews, 27(1), 78-91. https://doi.org/10.1093/epirev/mxi003
Goldmann, E., & Galea, S. (2014). Mental health consequences of disasters. Annual Review of Public Health, 35, 169-183. https://doi.org/10.1146/annurev-publhealth-032013-182435
Kessler, R. C., Galea, S., Gruber, M. J., Sampson, N. A., Ursano, R. J., & Wessely, S. (2008). Trends in mental illness and suicidality after Hurricane Katrina. Molecular Psychiatry, 13(4), 374-384. https://doi.org/10.1038/sj.mp.4002119
Norris, F. H., Friedman, M. J., Watson, P. J., Byrne, C. M., Diaz, E., & Kaniasty, K. (2002). 60,000 disaster victims speak: Part I. An empirical review of the empirical literature, 1981-2001. Psychiatry, 65(3), 207-239. https://doi.org/10.1521/psyc.65.3.207.20173
Reading the HLTH 6740 Week 3 instructions
Prevalence summaries in this course generally ask for figures and then for an account of what they depend on. Report prevalence figures from reviews and key studies with their population, timing and method attached, ideally in a table. Then explain the main sources of variation: who was sampled, what instrument was used, how long after the event and what kind of event and setting. Use examples from the studies to show each source of variation at work. Close by showing how a figure can be stated responsibly, naming population, timing and method, and why a figure stripped of those qualifiers misleads. Keep the brief concise and precise.
How this HLTH 6740 Week 3 example is built
The opening states the two questions. A table lists figures for direct victims, rescue workers and the general population from Galea and colleagues, the Katrina panel's two estimates from Kessler and colleagues and the September 11 resilience figure from Bonanno and colleagues, each with population, timing and method. The variation section explains population differences, the use of screening scales rather than interviews, the effect of timing, including the Katrina rise linked to unresolved stress, and event and setting differences from Norris and colleagues. The closing models a responsibly stated figure and cites Goldmann and Galea on persistent methodological limits. No figure appears in the text without its population beside it.
Reading the HLTH 6740 Week 3 rubric
The second question, whether a number means anything, carries much of the grade. Instructors look for figures reported with their qualifiers attached: population, timing and method. Explaining the main sources of variation, with examples from actual studies, shows understanding of how prevalence estimates are produced. Recognizing that screening scales and diagnostic interviews classify differently, and that timing can raise or lower estimates, earns credit. A closing example of a responsibly stated figure demonstrates the skill directly. A clear table and accurate citations complete what is assessed; figures reported without context lose most of the available credit. Summaries that show how one population's figure would mislead if applied to another demonstrate the point most clearly.
HLTH 6740 Week 3 help: mistakes that cost marks
Prevalence summaries often report a single headline figure, such as one in three survivors develops PTSD, without saying who was studied, when or how. Others list figures from different studies without explaining why they differ. Some treat screening estimates as diagnoses. Build a table with columns for source, population, timing, method and figure before writing. Then write one paragraph for each column that changes the figure. If your course asks for prevalence after a particular kind of event, we can prepare a summary that reports figures with their qualifiers and explains what they depend on. Keep the qualifiers beside each number in every sentence, not only in the table.
Get a HLTH 6740 Week 3 example written to your instructions
The Week 3 prompt, the rubric and any assigned surveillance or review sources are enough to start, and a prevalence summary written to that scope returns in 24 to 48 hours, free on a first custom request. Figures come from published work only; no number is invented to fill a gap, and operational data belonging to a service never reaches the page.
More HLTH 6740 papers and MS in Emergency Management samples
- HLTH 6740 Week 1: Trauma Research Literature Brief
- HLTH 6740 Week 2: Research Finding Discussion Post
- HLTH 6740 Week 4: Distress Trajectory Analysis
- HLTH 6740 Week 5: Disaster Study Evidence Critique
- HLTH 6740 Week 6: Evidence-Based Peer Reply
- HLTH 6740 Week 7: High-Burden Population Profile
- HLTH 6740 Week 8: Post-Disaster Support Plan
- HLTH 6740 Week 9: Crisis Program Evaluation
- HLTH 6740 Week 10: Responder Wellbeing Memo
- HLTH 6740 Week 11: Disaster Support Synthesis Paper
- HLTH 6510 Week 3: Medicaid Payer Profile
- HLTH 6300 Week 3: Function Coordination Analysis
- HLTH 6200 Week 3: Flood Exposure Summary
- HLTH 6100 Week 3: Source Fitness Appraisal
HLTH 6740 Week 3 questions, answered
Where can I find a free HLTH 6740 Week 3 sample paper?
The prevalence summary and its table can be read here at no cost.
How does PTSD prevalence differ by population in the HLTH 6740 Week 3 summary?
Roughly 30% to 40% among direct victims, 10% to 20% among rescue workers and 5% to 10% in the general population of affected areas, according to a review.
Why did PTSD rise in the Katrina panel?
The authors tied most of the increase between interviews to storm-related problems that had not been resolved.
What makes estimates vary?
The population sampled, the instrument used, the time since the event and the type of event and setting.
How should a prevalence figure be stated?
With its population, timing and method, so readers do not apply it to groups or events it does not describe.