Initial Analysis for Program Planning
Initial Analysis for Program Planning
Tuberculosis or collectively known as TB is among the most common public health problems that has already reached a global scale of concern. It is caused by Mycobacterium tuberculosis (Stein, 2011). At the rise of the global pandemic, tuberculosis has infected almost one-third of the world population with more than eight million diagnosed of the disease every year and an average of two million deaths every year (Stein and Baker, 2011).
Identification of the Problem
Relocation from third world to first world countries more and more determines the severity of tuberculosis (TB) cases in the adopted country. Socially marginalized groups, whom little is known about, may explain for a large number of TB among the immigrant populations. Classifying the age group and where the immigrants originated from the moment of their arrival, calculated the danger of active tuberculosis in immigrants to Victoria, Australia.
Earlier studies have presented data on the dangers of TB but not have utilized the group data needed to provide the exact changing risk estimates for TB reactivation. Previous research concerning the incidence of TB in Australia has used a more explanatory approach in showing the information. Further researches has used group data on Australian immigrants but has studied only a certain group making the information somewhat limiting.
Recent facts imply that the division of dormant TB infection and TB among the settlers is uneven. In countries with a low statistics of TB, exposed populations, such as people inside prisons and shelters and places that the health department has a hard time reaching are at a high risk of getting and spreading TB. Settlers who are living below the poverty line has a combined risk of coming from a country with a high statistic on TB and being exposed to the infection because of their economic situation in the countries that they are settling in.
Appropriate Logic Model
Given the topic of concern for the study, the most appropriate logic model to use would be the Research Performance Logic Model. It is apparent that logic models such as RPLM are constantly linear in construction and its elements are designed to lead directly to the next, which encompasses a relationship that among the various elements in the study. RPLM constitutes inputs leading to research activity, output, and outcome (researchutilization.org, N.D.). In studying tuberculosis among immigrants, the appropriateness of the model is entailed in determining inputs, which came from statistics and other health related researches. The research activity on the other hand will embody the entire process needed to scrutinize the obtained inputs to create an output (findings) and eventually the outcome, which represents the conclusion of the study on TB among immigrants.
Method
The numbers relating to the immigrants were attained from the Australian Bureau of Statistics to delineate the annual group data, which comprised all immigrants of Victoria with the statistics collected on age, area of origin, and the year they arrived in Australia. All studied numbers were de-identified before removal and used with the approval from the data keepers.
The recruitment of the refugee population was done through a selection method designed to balance the Health Services routine diagnostics to detect the dormant TB infection and TB in the general population. The selection process was created to point and examine the local people and immigrant’s altogether in spite of their status in the country.
Results
An estimate of 8.9 million is at risk per year during the period of the research (1995 -2010). The Victorian Department of Health recorded 5347 reports of active TB which was 3712 were included in the group data of immigrants who were recorded to have arrived between 1975 and 2007 (Stein, 2011). Moreover, the variety of risks since the time of arrival differs with the highest occurrence in the first two years, but more reports came in after that period. The people who have developed active TB on the 35 years of the study, half presented it in within seven years while the 20% showed itself within 2 years (McBryde and Denholm, 2012).
Discussion
The rate of the risk of TB is averagely high among the immigrants in Australia and that is also dependent on their age and the occurrence from the country they came from.
The measurement of the changing occurrence rate of TB by age, country of origin, and time of arrival allowed the study to establish the fact that immigration group data can be used as a denominator for measuring the risk per person-year of active TB infection. The only drawback of the study is its backward recording method, but a nationwide data gathering system was used to reduce duplicate records and biases (Baussano et al., 20113).
Assumptions notwithstanding, the results were still the same. The danger of getting infected with TB is dependent on age, with the elderly getting a second peek, and the occurrence rate of TB is highest after the arrival of the immigrants in Australia and it remains high after several years (Baussano et al., 2012). This partly due to the fact that people infected with TB stays in the area, infecting others and also the fact that TB stays with the person for a long time unless the person dies of complications.
The result of the study shows that it can be used into a flexible model that will predict the occurrence of TB in Australia. By following the patterns of immigration, policies could be made to avoid the troublesome examination in low-risk population. The effectiveness of the treatments for TB will depend of the dangers of getting infected again, and the study can be used to pinpoint the measures needed to create public health plans in preventing the spread of TB.
References
Buscano, I., Mercadante, S., Pareek, M., Lavlani, A., & Bulgani, M. (2013). High Rates of Mycobacterium tuberculosis among Socially Marginalized Immigrants in Low-Incidence Area, 1991–2010, Italy. EID Journal, 19(9), 1437 - 1445. Retrieved from http://dx.doi.org/10.3201/eid1909.120200
McBryde, E. S., & Denholm, J. T. (2012). Risk of active tuberculosis in immigrants: effects of age, region of origin and time since arrival in a low-exposure setting. Med J, 197(music), 458-461. doi:10.5694/mja12.10035
Researchutilization.org (n.d.). Types of Logic Models. Retrieved December 28, 2013, from http://www.researchutilization.org/logicmodel/types.html#outcomes
Stein, C. M. (2011). Genetic epidemiology of Tuberculosis susceptibility: Impact of study design. PLoS Pathog, 7(1), e1001189. doi:10.1371/journal.ppat.1001189
Stein, C. M., & Baker, A. R. (2011). Tuberculosis as a complex trait: impact of genetic epidemiological study design. Mamm Genome, 1(2), 91-99. Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3043369/
