Introduction
In quantification of disease frequency, epidemiologists investigate the occurrence and dominance of an ailment. Disease occurrence is the figure of the recent illness in a population within an instance (Ibrahim, Alexander, Shy & Farr, 1999). It is significant in deciding if a given population is at risk of contracting a disease.
Appropriate Measure of Disease Frequency in Different Scenarios
The candidate population best determines the percentage of elderly men diagnosed with prostate cancer by the age of 80. The candidate population defines the people at risk of getting a particular disease (Aschengrau & Searge, 2003). In this case, men aged eighty are the candidate population for prostate cancer.
Cause-specific mortality rate appropriately measures the number of women who die within the first year of parturition due to birth-related complications. The cause-specific mortality rate is the number of deaths resulting from an exact cause per 100,000 populations per year (Aschengrau & Searge, 2003). The death cause is birth complications.
Attack rate quantifies the number of freshman college students, who by the end of the year gained 15 more pounds. The attack rate is the number of new cases of disease that develop during a defined short period per the number in a healthy populace at the beginning of the observation period (Aschengrau & Searge, 2003). Here, the defined duration is one year; varied diseases may develop from weight gain.
Calculating the Appropriate Disease Frequency Rate
The cumulative incidence rate in a population of 100,000 people is reporting 9 cases within 1 year.
Incidence rate= # disease cases /Person-time-at-risk. (Ibrahim et al., 2000). Person- time at the year start = # of people*time, which is 100,000*1year = 100000 p-y. Actual p-y at year-end = Initial p-y – p-y of sick.
= 100000 – (9*1) which is 99991.
Incident Rate = New disease cases/person-time at risk. Incident Rate = 9/99991which is 0.00009. When multiplied by 100%, we get 0.009% incident rate, meaning that there are 9 new infections per 1000 people in a year.
Find the prevalence of chronic disease on November 1st, with 9 original instances establishing in September, and a further 45 cases reported in October of a tiny city with a population of 75000 people.
Prevalence= # affected individuals/Total # individuals in the population (Ibrahim et al., 2001). Total Affected is 9+45=54 and Total Population = 75000.
Prevalence is 54/75000 = 0.00072, when multiplied by 100% = 0.072%. Meaning for every 1000 people 72 is infected.
The relative risk of death from a disease on exposure, if the mortality rate in exposed groups is 60 deaths per 1000 person-years and the mortality rate in the unexposed group is 20 per 1000 person-years.
Relative Risk = Risk (incidence) exposed/Risk (incidence) unexposed (Ibrahim et al., 2001). Risk exposed is 60/1000 = 0.06% whereas Risk unexposed is 20/1000 = 0.02%. Relative Risk = 0.06/0.02 and is equivalent to 3. The risk is greater than 1.0 meaning that an exposed individual is more likely to die from the disease.
Factors Affecting the Prevalence of a Health Condition
Improvements in diagnostic criteria would increase the prevalence of disease as previously undiagnosed cases would be identified, thus increasing the prevalence.
A shorter duration of a health condition would decrease the prevalence of disease because prevalence measures all existing cases of a disease, and if a condition lasts shortly, this suggests that data taking would find previous patients already cured of the disease.
A decrease in the incidence of the health condition would reduce the prevalence. Incidence measures the transition of status from non-disease to disease. Therefore, if the number of people acquiring the disease decreases, then the overall surviving people with the disease would decrease.
Loss of healthy people caused by other factors would not affect the prevalence, since these people do not have the disease whose prevalence we are evaluating.
Conclusion
Understanding incidence and prevalence is extremely important. Knowledge of risk information could go a long way in averting demise due to early intervention in illnesses (Hitchens, 2008).
References
Aschengrau, A & Searge G.R. (2003). Essentials of epidemiology for public health. Web.
Hitchens, L. (2008). Population approach is needed for heart disease prevention to reach more people. Web.
Ibrahim, M., Alexander, l., Shy, C. & Farr, S. (1999). Incidence vs. prevalence. Web.
Ibrahim, M., Alexander, I., Shy, C. & Farr, S. (2000). Calculating person-time. Web.
Ibrahim, M., Alexander, l., Shy, C. & Farr, S. (2001). Common measures and statistics in epidemiological literature. Web.