Epidemiological Analysis in Malaria Program Implementation - Case Study Example

Running Head: Epidemiological Analysis in Malaria program Implementation Student’s Name: Instructor’s Name: Course Code and Name: Institution: Date of Submission: Epidemiological Analysis in Malaria program Implementation Introduction Malaria kills over one million people globally each year, and other studies suggest the number to be 2.7 million people dying from the epidemic each year (WHO, 2008). From the WHO reports, approximately 90% of Malaria caused deaths globally in a year happen where malaria programs are inadequate. In this case, establishment of programs is necessary to develop better approaches and contain the epidemic salvaging the situation from extremes and implementing future controls. This paper looks into the use of epidemiological data on malaria to facilitate the evolution, definition and refinement of the malaria programs. Identifying geographic risk factors related to malaria, understanding the spatial distribution of the disease as well as the populace at risk is the necessary steps toward facilitating programs for annual and effective malaria control. The current epidemiological data presented from research worldwide is of use in highlighting the respective issues of concern (Bautista, 2006; Hung et al, 2005; Ronald et al, 2006; John et al, 2006). Evolution of a malaria management program requires informed decision-making. This can only happen by exploiting the available data on the disease from well-researched epidemiologic researches (Bautista, 2006; WHO, 2008). The 21st century experiences many health needs yet with remarkably few resources in handling Malaria epidemic. It is expedient that data on epidemiological research sources for malaria increase in number over the years, which are why in the past 10–15 years there have been considerable establishment of malaria programs globally (Hung et al, 2005; John et al, 2006; WHO, 2008). National policymakers globally always have a problem in knowing the right approaches to develop in facilitating the best program to enhance success and facilitate a better intervention of controlling the epidemic. With this in mind, it is apparent that the epidemiologic data from many researches done previously remains relevant for ministries of health and other partisan organizations in starting up malaria programs (Cohen et al, 2008). To understand which interventions are of essence and hold the greatest impact on public health regarding malaria epidemic, the involved parties need to go back to books and understand the problem at hand (Bautista, 2006; John et al, 2006). It is expedient to know the problem before incorporating approaches to handle it. The data establishes annual malaria risk rate ranges of malaria to help frame a starting point. Epidemiological data also provides information on previous burden of malaria as a disease, expected impact of the malaria vaccine, as well as the implementation, supply issues and financing of the program. From the data, these elements feature perfectly and are applicable with minimal challenges. Since 1995, organizations as the Malaria Vaccine Testing in Africa (AMVTN), renamed (AMANET), encourages and promotes the global documentation of research data on the epidemiology of malaria. The main aim has been supporting malaria vaccine trials globally especially in the areas most hit by the disease, that is, Africa. This has been a proven success on the approach with the data being of help in facilitating the programs as per the severity of malaria in each region. In fact, the evolution of the programs had received support from epidemiological researches in giving the programs the best shot for success (Hung et al, 2005; John et al, 2006). In using epidemiological data, in a program to search for a malaria vaccine, it is crucial for national policymakers because they will have a chance to weigh the decision of introducing the malaria vaccine. Epidemiological data provide statistical analysis for malaria as a prevalent disease. The malaria risk rate therefore, can be calculated well to determine the number of new infections in making verifications on the needed program interventions. From the data, there are possible household classifications and age distribution helping the program implementation categorization and specialty determinacy (Bautista, 2006). Epidemiological data incorporate information of earlier introduced and tested vaccines of malaria in respective communities and with varying and described levels of malaria therefore, this could be the best chance to verify the effectiveness of a new vaccine. Policymakers involved in the malaria-endemic program face such hard decisions to make calling in for a base to draw their strength of making decisions (Cohen et al, 2008; WHO, 2008). They therefore, require the data using it in making comparisons and evaluating the best vaccine with a potential impact on Malaria including its ability to cut down and treat malaria cases with its assessed impact of controlling or treating interventions of malaria as an epidemic (Bautista, 2006; Hung et al, 2005; Daniel, 2008). Demographic surveillance systems (DSS), is one of the astronomical bodies providing long-term information on health of large populations globally. Its epidemiological researches provide data, which is supremely relevant to malaria disease tracking. This has been of the essence to may organizations and governments in starting programs in specific areas. They are able to learn on the latest malaria levels and new threats of the virus therefore, introducing revised interventions that rarely fail. Epidemiological data are of relevance in starting up of cost effective programs. There have been many interventions introduced in the past. The epidemiological data provide an analysis of the cost involved in the previous approaches (Hung et al, 2005). It also gives an estimation of the number of patients expected and the progression of the disease. This way, it is fast and reliable for any program evolution because budgeting is easy for enhancing the continued running of the program (Rosen et al, 2008). The program facilitators will solely depend on the epidemiological data to determine which malaria intervention approaches applicable to the program will provide the greatest impact and still at the lowest cost (Bautista, 2006; Hung et al, 2005; Daniel, 2008; WHO, 2008). Cost-effectiveness analysis is the main use of the epidemiological data analysis. The latest analysis of epidemiological data from Demographic surveillance systems (DSS) revealed that EPI vaccines used in treating malaria are highly cost-effective, providing low costs per dose. This was of the essence for non-governmental organizations in Africa in resolving the program hitches on controlling malaria. The WHO reports indicated a reduction of deaths in the continent following the introduction of these vaccines. Bearing in mind that malaria vaccines are expensive, such epidemiological data would be of relevance in controlling the severity of the disease through initiation of such programs (Hung et al, 2005). In the definition of a malaria management program, considerable planning is of the essence to enhance the success of the program and promote its effectiveness. This requires already researched and published epidemiologic data to assist with raw data on the expectations of the program and develop a base in its operations. Epidemiological data in the definition of malaria program apply in varying perspectives (Rosen et al, 2008). Governments support malaria control programs as well as other treatment efforts. It facilitates the health systems by providing enough resources for administration budgets. On the other hand, the remaining part of the funding on Malaria comes from donors and private organizations in effort of controlling the disease (Bautista, 2006; Hung et al, 2005; Rosen et al, 2008). This means that defining the epidemic is the sole effort necessary to convince the respective donors in facilitating the program. This is the role of the epidemiological data in ensuring that the parties are convinced beyond doubt on the prevalence, risks and other issues pertaining to the epidemic for them to incorporate the same in decision making on funding the respective programs (Bautista, 2006). UNICEF reports estimate that yearly, African governments in respective budgets spend an estimated $300,000 annually in starting and implementing control programs on the disease. The application of such reports comes from the epidemiological data on the disease. For a country with a population of about five million people, the amounts mathematically sums as $0.06 for each person. The spending of these governments annually ranges at $2 to $130. With dosing schedules, the respective program facilitators need to make decisions as to whether national budgets accommodate the cost to evaluate on the urgency to seek for funding (Hung et al, 2005). This means that such a definition is of relevance so that when the governments cannot afford, policymakers can come in and search for other funders of the malaria projects (Keating et al, 2005). From a good deliberation by the policyholders and with the support of the epidemiological data, it is possible to come up with financing strategies for the respective malaria programs that are of importance in facilitating long-term sustainability of the malaria programs (Bautista, 2006; Hung et al, 2005; Daniel, 2008). Epidemiological data on malaria help marginally in establishing the Delivery System Infrastructure of a malaria program (Bautista, 2006). This is tremendously useful in the event of running the program and when refining it to make a better approach and maintaining its long-term success. Policymakers need to make considerations as to how the program delivers malaria vaccines as well as other interventions on malaria control including educational programs to the respective country’s citizens. The systems have to be stratified in appropriate approaches to develop strong programs and enhance their effectiveness in measuring up to their standards and delivering their roles effectively (Daniel, 2008). Health infrastructures establishment for the program is the key feature depending solely of the features in the epidemiological data (Bautista, 2006; Hung et al, 2005; Keating et al, 2005). The program facilitators can be able to establish some of the possible barriers and any challenges possible in the establishment of the program to control malaria. With the data, the program facilitators get ready to handle issues relating to the rates of malaria spread, the knowledge gap on the disease and any other interventions of the requirement to ensure that the program runs on in long-term (Hung et al, 2005). Refinement of any program demands a review of the program’s history to check out on the set goals and the achievements so far. In doing so, the epidemiologic data serve as indispensable in enhancing a better review and a new beginning in setting out approaches to reach the unreached goals of the program (Keating et al, 2005; Avellino et al, 2008). The epidemiological data especially done on a specific area for the first time on malaria as a fast spreading disease is useful in target setting for future goals of interventions programs. In the refinement of the program, the involved parties incorporate some of the featured elements in the epidemiological data including severity, risk per age groups, resistance and many other variables (Hung et al, 2005). The involved party can therefore, evaluate a given program and assess its success story. Revising the wrong approaches in the facilitation of the respective programs if the role that the data plays in this event (Bautista, 2006; Hung et al, 2005; Moffett et al, 2007). The World Health Organization uses the established data of respective regions in reviving terminated malaria programs (Deressa et al, 2006). It also helps develop the existing programs in respective countries by looking into established data and assisting with the inadequate resources to facilitate programs and promote the program’s effect on controlling Malaria (Bautista, 2006). From the epidemiological data, it is possible for WHO and other organizations to facilitate a reasonable distribution of resources in starting and running of malaria programs. Among the many resources include, human personnel (nurses, doctors) and other humanitarian requirements including medicines, mosquito nets among others (Hung et al, 2005; Avellino et al, 2008). The data present an approximation of statistical data on prevalence rates and the urgency of resources in each specific discipline therefore, making it easy to facilitate the running of organizations with minimal challenges. Disease burden data, which is part of the epidemiological data, would be of relevance for any party to establish the requirement in furnishing the already running program (Ronald et al, 2006). Conclusion With epidemiologic data easy access on malaria, before starting of the malaria programs, the program facilitators can make sound decisions on the facilitation of the programs therefore, promoting its success. The BRAC responsible in implementing the programs on controlling Malaria should always use the available surveillance data as well as use epidemiological data in detecting the malaria cluster regularly to enhance target intervention (Hung et al, 2005). That will be a marvelous opportunity where the facilitators use available but limited resources optimally for the establishment of control programs nationally to control malaria. Given the enormous mortality and morbidity rates associated with malaria, it is urgent that programs need fast implementations (Bautista, 2006; Hung et al, 2005; Negash et al, 2005; Avellino et al, 2008). Blind implementation of the programs is illogical especially in the modern era where data provision is easy (Negash et al, 2005). The call for all organizations and government sectors is to use epidemiological data in assessing the applicability of the programs and look into aspects that may tolerate the program to successful heights (Moffett et al, 2007). Preparing the answers to long sought questions is the role of the epidemiological data and of relevance to the program facilitators in ensuring success of respective programs (Hung et al, 2005). In conclusion, epidemiological data are the best tool for use for any involved party in the evolution, definition and refinement of malaria programs. Genuinely, the existing efforts of collecting epidemiological data on malaria including DHS, DSS, and HMIS, need strengthening and expansion to more countries if handling malaria will be a success (Bautista, 2006; Hung et al, 2005; Deressa, et al, 2006; John et al, 2006; WHO, 2008). References Avellino, P. et al. 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(2006). “Malaria hotspot areas in a highland Kenya site are consistent in epidemic and non-epidemic years and are associated with ecological factors” Malaria Journal 5:78 Keating, J. et al. (2005). “Self-reported malaria and mosquito avoidance in relation to household risk factors in a Kenyan coastal city” Journal of Bio-sociological Sciences 37:761–771 Moffett A. et al. (2007). “Malaria in Africa: Vector Species' Niche Models and Relative Risk Maps” PLoS ONE, 2(9):e824. Negash, K. et al. (2005). “Malaria epidemics in the highlands of Ethiopia” East African Medical Journal 82:186-192 Ronald, L. et al. (2006). “Malaria and anemia among children in two communities of Kumasi, Ghana: a cross-sectional survey” Malaria Journal 5:105 Rosen, D. et al. 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