Epidemiology HPRO 7712 Fall 2018 Final Examination Pa 629178

Epidemiology Hpro 7712fall 2018final Examinationpart B

Identify the sample questions and calculations related to epidemiological data, including outbreak investigation, attack rates, secondary attack rates, age-adjusted death rates, and interpretation of statistical data within public health contexts.

Paper For Above instruction

Introduction

Understanding epidemiology involves analyzing data related to disease outbreaks, incidence, prevalence, and mortality rates, which ultimately informs public health interventions. The provided questions cover a broad spectrum of fundamental epidemiological concepts and calculations, including outbreak investigation, attack rates, secondary attack rates, and age-adjusted death rates. This essay aims to explore these themes in detail, illustrating their significance and application in real-world public health scenarios.

Investigating Disease Outbreaks and Incubation Periods

The first scenario describes an outbreak of 108 cases of staphylococcal food poisoning in a rural community. The first case was recorded at 8:00 p.m., August 6, with the last at 4:00 a.m., August 7, 1989, and the peak occurred at 10:00 p.m. The incubation period for foodborne illnesses generally ranges from 2 to 6 hours, depending on the pathogen. Given that the earliest case occurred at 8:00 p.m., and the peak was at 10:00 p.m., the most probable exposure time would be approximately 2 hours before the onset of symptoms, namely around 6:00 p.m., on August 6. By analyzing the incubation period's typical range and symptom onset, epidemiologists can identify the likely time window of exposure, which is crucial for source tracing and controlling the outbreak. This process exemplifies the use of incubation periods in epidemiological investigations, emphasizing their value in establishing etiological relationships in outbreaks.

Calculating Median Incubation Periods

The second scenario involves an outbreak of 110 cases of gastroenteritis at a college, with 101 cases’ incubation periods calculated using time of onset data. The data are compiled into a frequency distribution based on one-hour interval incubation periods, which enables the calculation of the median. To compute the median incubation period, we first find the cumulative frequency and identify the interval where the 50th percentile falls. For example, suppose the cumulative frequency reaches 51 at the 3-hour interval. In that case, the median is located within that interval, and interpolation may be used to determine its precise value. The median provides a central tendency measure of the incubation period, offering insights into the typical disease progression and aiding in refining source identification and intervention timing.

Attack Rates and Secondary Attack Rates

The third scenario addresses measles transmission within a school setting. The attack rate is calculated as the number of new cases divided by the population at risk during a specific period. In this case, 71 pupils were absent from a total enrollment of 271. The attack rate for measles is therefore 71/271 = 26.2%, representing the proportion of the school population affected during this outbreak. The secondary attack rate focuses on the transmission among close contacts, in this case, the siblings at home. With 21 out of 93 siblings developing measles, the secondary attack rate is 22.6%. This indicates significant transmission within households, emphasizing the importance of targeted interventions such as quarantine and vaccination to control spread.

Attack Rates in Group Settings

The subsequent question examines an outbreak of staphylococcal intoxication among picnic attendees. All 42 persons who attended and were evaluated, including 39 additional cases identified through interviews, are considered. The attack rate among those who attended the picnic can be calculated as the total number of ill persons (17 initially treated plus the additional cases) divided by the total attendees, which is 42. This yields an attack rate of approximately 59.5%, reflecting a high attack rate typical of foodborne outbreaks where exposure is common.

Gender-specific Attack Rates and Food Source Attribution

Further analysis includes sex-specific attack rates among cases and controls from the picnic incident. For females, with 14 cases among the group of females, and considering the total number of females attending, the sex-specific attack rate is calculated accordingly. The ratio of attack rates in males versus females provides insight into gender-related vulnerability or exposure differences. If males had a higher attack rate, it could suggest behavioral or biological factors influencing susceptibility.

Food Exposure and Attack Rate Calculations

Likewise, the investigation of potato salad consumption provides a method to evaluate risk factors. With 53 cases among those who consumed the potato salad at home and only 3 cases among those who did not, the attack rate among non-consumers of potato salad can be calculated. Given no one else consumed it, the attack rate among "not potato salad eaters" provides evidence of the association between potato salad and illness, supporting causality in epidemiological studies.

Comparative Mortality and Age Adjustment

The final scenario discusses mortality data comparing Malays in West Malaysia and residents of Washington State, USA. Raw mortality rates often do not account for differences in population age structures, making age adjustment essential. The calculation of age-adjusted death rates involves standardization, applying age-specific mortality rates in the study population to a standard population distribution, such as that of Washington State. This process involves multiplying the age-specific death rates by the proportion of each age group in the standard population and summing these to obtain a single standardized rate. The comparison of crude and adjusted death rates reveals the true burden of diseases within populations, highlighting the importance of age standardization in public health statistics.

Conclusion

Collectively, these epidemiological measures and calculations are vital tools for public health professionals. They facilitate understanding disease dynamics, identifying risk factors, evaluating interventions, and making informed policy decisions. Whether investigating outbreaks, calculating attack rates, or performing demographic standardizations, a thorough grasp of these concepts enhances the capacity to improve population health outcomes.

References

  • Gordis, L. (2014). Epidemiology. Elsevier Saunders.
  • Last, J. M. (2001). A Dictionary of Epidemiology (4th ed.). Oxford University Press.
  • Thacker, S. B., & Berkelman, R. L. (1988). Public health surveillance in the United States. Epidemiologic Reviews, 10, 164-190.
  • Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology. Lippincott Williams & Wilkins.
  • Friis, R. H., & Sellers, T. A. (2014). Epidemiology for Public Health Practice. Jones & Bartlett Learning.
  • Wagner, E. L., et al. (2014). Foodborne Disease Outbreaks: Background and Lessons Learned. Food Microbiology.
  • World Health Organization. (2014). Global Classification of Cancers. WHO Press.
  • Simonsen, L., et al. (2005). The Impact of Influenza Vaccination on Mortality in the United States. Bulletin of the WHO.
  • Centers for Disease Control and Prevention. (2017). Principles of Epidemiology in Public Health Practice. CDC.
  • Dean, A. G., et al. (2013). Basic Epidemiology. CDC.

Related Assignments