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Jefferson County Community Health Epidemiology - Essay Example

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The essay "Jefferson County Community Health Epidemiology" focuses on the critical, and thorough analysis of the major issues and peculiarities of the state of the community health epidemiology at Jefferson County, a region located in the State of Texas…
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Jefferson County Community Health Epidemiology
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? Community Health Epidemiology Jefferson County is a region located at the of Texas. As per the census, the county hosted 252, 273 people, at a population density of 280 per square mile. The population is multi-ethnic and racial, but the larger population is comprised of whites, at 57.24%. An approximated 17.40% of the populations live below the poverty line, while unemployment levels stand at 9.4% - which amounts to about 27,918 people. Health sector indicators show that 10.8% of the people are not insured, thus greatly, at the risk of the health risk factors there, including behavioral risks, substance abuse, nutrition imbalances and unfavorable exercising patterns. Health statistics from year 2007 show that disease threats include diarrhea, campylobacteriosis and Hepatitis, which have been checked by health programs like the immunization of all age groups – newborns to adults. Other health threats include T.B, Sexually transmitted diseases and HIV, which are the focus of public programs, created to explore and offer their surveillance. From the community genogram, focus is placed on group-centered health education and integrating team networks among the different vulnerable groups. Focus is also placed on the family and other small groups, towards fostering the current healthcare system – so that it can address the health issues discussed. These intervention steps will be affected through the exploratory, analytical and the health action phases, towards realizing the desired changes and solutions to the health threats. Community Health Epidemiology Introduction Jefferson County is a county in the United States, located in the State of Texas. As per the 2010 census statistics, the county had a total population of 252,273. The population density registered in the county stood at an average of 280 per square mile. The racial makeup of the county reflects 57.24 % of whites, 33.74 % of African-Americans and a minority of other groups, including Asians, Hispanic or Latino, French, German, and Irish among other minority racial groups (Mecke, 1984). The median income of a household in the county stands at $34,706, while the median income level for a family is $42,290 – the men reflecting a median earning level of $ 36,719 as opposed to $23,924 for females. An approximate level of 17.40% of the total population and 14.6% of families live below the poverty line. 24.6 % of those living below the poverty line are composed of those under the age of 18, while 11.8% are composed of those above the age of 65 years. As of January 2011, the unemployment ratio of the county stood at 9.4 percent registering 27,918 members of the total population as unemployed. The underemployment rate for that year stood at 10.7 percent, implying that the county is a home to 26, 993 unemployed citizens and a considerable number of underemployed workers who may not afford substantial healthcare services (Mecke, 1984). Discussion From a careful assessment of the economic, community safety inventory, cultural evaluation, disaster assessment, as well as planning, the results of the county’s health status indicators reflected the following. 10.8 % of the population as uninsured. Behavioral risk factors included alcohol use and abuse, substance abuse, nutrition imbalances and vulnerability based on unfavorable physical activity patterns. An example here is the recent anti-tobacco campaign, offered to urge people reduce the consumption of tobacco, as well as protect the others from secondhand smoke. Other areas with shortage causing imbalances and deficits in healthcare services administration include socio-economic factors, like economic and social imbalances, as well as inadequate education and limited access to education. Other community health indicators influencing the health patterns depicted within the framework of Jefferson County include vulnerability indicators like crime rate, especially that involving abuse of the elderly and domestic violence. Other causes of health imbalances include the inability to access clean water, due to wide well water usage and clean quality air, as concerns have been raised, over the health effects of wildfire smoke. Despite its location at an area of multiple racial and ethnical strata, Jefferson County’s population is mainly composed of white people (Nutter, 1999). Description One of the Data Collected From the county, statistics showed that in 2007, a total of 306 cases of diarrhea were reported, though no deaths were registered from the cases. Of this number, 25.8%, which amounts to 79, resulted from day-care associated centers. The common infectious causes were salmonella, which constituted 35.3% of infections and shigella making about 43.8%. The cases of Giardiasis from the statistics collected showed that they remained comparatively stable over the past six years, at an average rate of 8 infections per 100,000 people (Mecke, 1984). The number of cases of campylobacteriosis remained comparatively stable, at an average rate of 4 infections per 100,000 people – though it registered slight increments in the years after 2005. Food-related complaints, which are attributed to a common cause and source of infection, for example a grocery center, restaurant or a community event were also registered – based on which 19 investigations were conducted in 2007 (Schmidt, N.D). From the investigations, at least 84 cases were reported, registering an average of 4 per investigation. The causes of the infections included food, contact and water. Cases of Hepatitis were registered, and the cases identified as viral hepatitis A, B, and C. Among the different types, A had the most incidence rate at the county for decades, although B registered the highest rate in 2004. Since 1997, the B type has remained highest ranking at the county (Mecke, 1984). Discussion of Data Collected in Description One The data shows that a number of diseases have remained a threat to the health wellbeing of the people of Jefferson County, including diarrhea – often traceable to child-care centers, which shows that the hygiene standards maintained at such centers should be checked, if only community health nurses and other personnel are to succeed in maintaining health wellbeing. For instance, the program offering vaccination to newborns, children, youngsters and adults was initiated, which requires highly knowledgeable health teams, towards reducing the cases of immunize-able diseases. Another threat is Giardiasis, and campylobacteriosis – which have been on the decrease in the years preceding 2006. Food-related attacks do not pose a major threat, but hepatitis – especially B-type has remained a threat in the way of realizing successful healthcare administration at the county, therefore, should be checked by healthcare official (Lieberson & Santi, 1985). Description Two of the Data Collected In 2007 alone, 13,293 cases of tuberculosis were reported, at an average rate of 4.2% of the population. In 2007, 34 cases of tuberculosis were diagnosed in the county, registering higher rates among blacks than the whites. Sexually transmitted diseases pose a major threat at Jefferson County; Chlamydia remained the most common, of the reported STIs. In 2007, its rate stood at 347.8 for every 100,000 – which was 1.9 times that of the U.S. in general. Of the infection cases, 74.2% were female – registering 2.6 times that of their male counterparts. Of the infections registered among women in 2007, the highest incidences were registered among those between 15 and 19 years (Schmidt, N.D). Gonorrhea was the second most common STI, the cases of the county maintaining a high of 2.6 times that of the U.S. 95.3% of the gonorrhea cases registered among black residents at 836.1 cases out of every 100,000 people as opposed to 27.0 cases per 100,000 people. In 2007, 429 cases of syphilis were registered at the county, showing a reduction of 21.9 % from the figures registered in 2006. The rate of HIV infection at Jefferson County stood at 26.3 per 100,000 people, which is 1.5 times higher than the rate registered for the entire U.S. statistics. Males accounted for 70% of the new infections registered, while the rate was higher among the black, as compared to the rates registered among the whites. Other diseases reported at the county include influenza, Meningococcal disease, which reduced in 2005 and after then; vaccine-preventable diseases like pertussis has been on the increase at the county since 2002 to 2006, registering a reduction in 2007 and after then (Clayton & Hills, 1993). Discussion of Data Collected in Description Two A major treat to the healthcare wellbeing of the residents of the county is posed by tuberculosis, which affects 4.2% of the total population – and higher among black people. This shows that, in addressing the threat – medical personnel should offer more attention to the black groups – as these are noted as showing higher vulnerability to the disease. In the area of STIs, medical personnel should have the resources required and the know-how to be used in addressing the STI threat facing the county – placing more attention on the major one, which is Chlamydia. In response to these threats, the department of health offers exploration and surveillance of these infectious diseases, especially T.B, STDs and Vaccine preventable cases (Lieberson & Santi, 1985; Schmidt, N.D). From the statistics of health of Jefferson County as compared to those of the larger Texas region and the entire U.S, the county is more under threat of diseases like STIs like Chlamydia, Gonorrhea and HIV. From the data, medical personnel should also offer more attention to black groups, as they are further, affected by the threat of STIs, as compared to the whites. For instance, the rate of infection to HIV was higher among blacks than whites. From the information, 70% of the new infections of HIV were registered among blacks, especially those associated to homosexuality. From this indicator, medical personnel should offer more attention to these highly vulnerable groups – as some amount to 70% of the health threat posed (Lieberson & Santi, 1985). Community Genogram INPUTS CARE CONTEXT OUTPUT From a detailed analysis of the data collected from the assessment of the data showing the economic disposition, community care inventory and cultural disposition, it is clear that certain groups are more vulnerable to the healthcare threats facing the county. These groups, which are particularly vulnerable, include the poor and the middle class, who are exposed to unhygienic conditions at the heath threat centers they frequent – including child-care centers, restaurants and groceries. These groups, especially the low-earning groups are more vulnerable to diseases like diarrhea, as they are often marginalized to unhygienic living surroundings, which are characteristic with the lack of clean water and poor food supply chains. The threat of hygiene related diseases is further, heightened by the exposure to highly populated areas, which is a primary characteristic of the county (Beck, 1987). Among the highly vulnerable groups were the blacks – who were at higher risk of contracting T.B, and STDs and STIs like Gonorrhea and HIV. Females were also vulnerable to diseases like Chlamydia, where they registered 74.2% of all the cases (Nutter, 1999). The other threat, which may be fully addressed, is that of vaccine-preventable diseases like pertussis, which maintained an average rate of 0.4 in 200; 0.4, in 2008 and 0.8 out of every 100,000 people in 2009 – which shows that it is comparatively, increasing (Margolis, 2000). In addressing the healthcare deficiencies – through policy and implementation – health education should be administered to focus groups, for instance the youths, who may be trained to offer further education (Schmidt, N.D). The integration of education and awareness teams and groups in the intervention, especially among the vulnerable groups should also be implemented. Lastly is administering family and small group healthcare centered administration. These three approaches should be directed into the current healthcare service within the community, so as to realize family and focus group centered healthcare – as it is the only approach, sufficient to identify vulnerabilities and care implementation deficiencies (Beck, 1987). The community diagnosis model is based on the current trends in policies and implementation at Jefferson County, from a holistic view of healthcare service, which will mean more responsibility for the personnel at the county. The model has three phases, namely the explanatory, analytic and the health action programs phase. The explanatory phase will involve exchange of ideas between the different parties to community healthcare at Jefferson County, including nurses, doctors, community representatives, group representatives, and patients. This phase will also touch on the policy requirements of implementing the healthcare changes to be realized (Beck, 1987). The knowledge-base developed from the different groups will be of great significance to the daily practice of practitioners – especially, with regard to the vulnerability of different groups, and the more prevalent diseases. The analytic phase will offer a platform, through which treatment of these diseases, especially, among highly vulnerable groups – to ascertain the practical nature of the model. The second phase will offer know-how on health risks – personal or environmental, as well as cultivate participation and dialogue between the members of Jefferson County towards the formulation of preventive models. The third phase will involve the implementation of health programs with reference to the needs and differences of various focus groups (Margolis, 2000; Schmidt, N.D). References Beck, R. (1987). The genogram as process. American Journal of Family Therapy, 23-25. Clayton, D. & Hills, M. (1993). Statistical Models in Epidemiology. Oxford: University Press. Lieberson, S. & Santi, L. (1985). The use of nativity data to estimate ethnic characteristics and patterns. Social Science Research, 14 (1), 44–46. Margolis, C. (2000). Community-based medical education. Medical Teacher, 22 (5), 482-484. Mecke, M. (1984). Community health diagnosis in nursing. Public Health Nursing, 1 (1), 23- 35. Nutter, F. (1999). Understanding the interrelationships between botanical, human, and veterinary epidemiology: the Ys and Rs of it all. Ecosys Health, 5 (3), 131–40. Schmidt, C. (N.D). Public Health Nursing Competencies. Jefferson County Department of Health and Environment. Accessed June 05, 2012 From http://jeffco.us/jeffco/health_uploads/Presentations/PHNCompAPHA11_07final.pdf Read More
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