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“Lyme borreliosis”- is simply known for the combination with many outdoor professions but the beekeepers have not investigated Lyme borreliosis at first. In this research, the survey has been conducted by the researcher by distributing a questionary among the beekeepers to collect data about Lyme borreliosis.
Research rationale
The research rationale is the reason for conducting the whole study about the risk factors of beekeepers contracting Lyme borreliosis which has been conducted by the researcher to collect essential data about Lyme borreliosis to know its impact (Woodward, 2019). In this research, the researcher wants to identify all the gaps and will emphasize why the gaps addressing is important. The researcher has found some objectives of the research which will be used to analyze all the data of this study.
Research aim
The research aims to analyze the data about the high risk of beekeepers in central Europe contracting Lyme borreliosis. The disease has effect the beekeepers majorly (Glasgow et al. 2019). So the research has conducted a survey on the beekeepers and the main motive is to analyze the data to gather the proper information about the disease and the risk factors of beekeepers of central Europe.
Research objectives
There are many objectives regarding the research which has to identify by the researcher after analyzing the data of the research (Dumpler et al. 2020). The objectives of the research are:
Design of research
This particular research would be conducted on a few levels. The researcher has c created a questionnaire to conduct the whole research and go to a survey to collect the essential data regarding the case study (Sovacool et al. 2018). The research design has indicated the main strategy of collection of data and analysis method of the study which will conduct by the researcher. In this research, the researcher will collect the primary data from the case study by applying the qualitative method of data collection. The qualitative data collection method is very beneficial and has shortcomings. The researcher has considered the data analysis, data collection method, and the hypothesis of the research which are relevant to the finding data.
The approach to research
In this research, the researcher will implement the research approach so the data can understand the data consequences by the readers easily. In the research, the “Deductive” approach will be implemented to collect the required and essential data for the case study. The deductive approach will help the researcher to collect the primary data on Lyme borreliosis and its impact on the beekeepers in central Europe. This research approach will help the researcher to collect the appropriate and right data about the case study of “Beekeepers in central Europe who are at high risk for contracting Lyme borreliosis” (Roy, and Uekusa, 2020). The two factors of the approach will help the researcher to collect the proper data regarding the case study of “Beekeepers in central Europe who are at high risk for contracting Lyme borreliosis”. The two factors are “predictability” and “consistency”. These will help the researcher to understand the collected data properly so the researcher can conduct the analysis to get the appropriate information on the case study of “Lyme borreliosis” and its major impact. In the research approach, experts identified the major issue of Lyme disease is related to the bacterial infection which can initiate with which cause by the bite of “infected tick. This could spread infection to the joints, nervous system and heart. These liable tests will help the researcher to explore the important views of the impact and the high-risk factors of beekeepers. The researcher will positively collect the data after applying the deductive approach in this case study which will help the researcher to easily understand all the data to gather important knowledge about it. A minor issue reflects the symptoms whicjh cause mild fever and flus and can later transformed into the development of high risk diseases.
Method of collecting the data
The researcher will implement some strategic data collection methods to gather all the data about the case study of “Beekeepers in central Europe who are at high risk for contracting Lyme borreliosis”. At first, the researcher will conduct a survey while using their questionnaire to gather information about the beekeepers. The researcher will distribute the questionnaire which is based on different types of investigations among all the beekeepers of central Europe to know the impact of Lyme borreliosis (Al-Qurabat, and Idrees, 2018). The human Lyme disease and the companion the bee tick surveillance data will obtain from the state health departments to organize the data in an excel spreadsheet and have to sort the data regarding the year and country. The survey report will conduct the original data of the research from the experienced beekeepers to know the original data of the research (Radolf et al. 2021). This particular research would support the experts to analyze the appropriate data regarding the research and help the researcher to access the important data of the case study of “Beekeepers in central Europe who are facing a critical risk of contracting Lyme borreliosis”. The data will be collected by using the qualitative method which will help the researcher to conduct the survey to collect the correct data of the beekeepers. It will help by providing the survey or taking the interview with beekeepers face-to-face or by a Phone call in the process of data collection.
In the data collection process, there will be many issues that have to be faced by the researcher. To conduct a survey on the beekeepers many of them will not answer the questions on it and the practical survey will be disrupted by and natural disaster (Mahmood et al. 2019). Many of the beekeepers will be infected by the viral disease Lyme borreliosis. All these issues will disrupt the research by conducting it properly by the researcher. These issues will affect the beekeeper's economical status and the company’s contribution to the state by giving the tax.
Bias confounding
The human Lyme disease and the companion bee tick surveillance data will obtain from the state health departments to organize the data in an excel spreadsheet and have to sort the data regarding the year and country (Mathur, and VanderWeele, 2022). There are two confounders of the bias which have discussed below:
Data analysis process
In the research on Beekeepers in central Europe who are at high risk for contracting Lyme borreliosis the primary data will be analyzed by the researcher to reflect on the case study of “Lyme” disease and its effects on the human association. For the research purpose, all the data will be collected from the survey report of the beekeepers to analyze the impact of the disease “Lyme” on their association. After analyzing all the data their outcomes can be utilized within the experiment due to the reason. That will further support the researchers for the implementation of the data’s depth. That particular portion can be looked out to verify the content throughout in explained manner as per the outcome (Lee et al. 2020). The particular knowledge would be improved through the researchers or the expert’s result and the detailing of the picture as per a few situations of beekeepers in “central Europe ''. The methods of analysis are done by implementing the qualitative data collection method and the essential information about Beekeepers in central Europe who actually under the critical risk factors for completing the contract with “Lyme borreliosis”.
Presentation
The primary data will be analyzed by using statistical graphs and the excel spreadsheet presentation which will help the researchers easily understand all the data of “Beekeepers in central Europe who are at high risk for contracting Lyme borreliosis” and the methods of analysis by implementing the qualitative data collection method (Nakra et al. 2020). All the analyzed data and the results will be processed in a descriptive format so the researcher can easily understand all the data.
Interpretation
The primary data will be analyzed by the researcher to reflect on the case study of Lyme disease and its effects on human association. For the experiment purpose, all the data will collect from the survey result of the beekeepers to analyze the impact of the disease “Lyme” in their association (Cardenas-de la Garza et al. 2019). The researcher will conduct a survey to gather the proper information about the Beekeepers in central Europe who are at critical risk for contracting Lyme borreliosis. The researcher will conduct a survey while using their questionnaire to gather information about the beekeepers. The researcher will distribute the questionnaire which is based on different types of investigations among all the beekeepers of central Europe to know the impact of Lyme borreliosis.
This research is based on “Beekeepers in central Europe who are at high risk for contracting Lyme borreliosis” to know the impact of “Lyme borreliosis”. The researcher will mainly focus on the impact of the disease Lyme borreliosis on the body of humans and its effect on the entire association. In this case study, the researcher will face many issues to collect the primary data such as many of the beekeepers will not answer the questions on it and the practical survey will be disrupted by and natural disaster. Many of the beekeepers will be infected by the viral disease Lyme borreliosis so the researcher cannot conduct the survey properly in the scarcity of spreading the infection. The impact on “Beekeepers in central Europe who are at high risk for contracting Lyme borreliosis” and the recovery process of the disease will be analyzed by the researcher to get the proper information about it and conduct the survey report to inform all the researchers about the report of the research survey. An overview of the collected data and the survey report can fill the knowledge gap of the researcher which will help the researcher to take quick action about the disease if it breakdowns towards the researcher.
To conduct a survey on the beekeepers many of them will not answer the questions on it and the practical survey will be disrupted by and natural disaster. After the research, there are many faults that will be shown. So the researcher has to focus on some points to make it effective research.
Journals
Al-Qurabat, A.K.M. and Idrees, A.K., 2018. Energy-efficient adaptive distributed data collection method for periodic sensor networks. International journal of internet technology and secured transactions, 8(3), pp.297-335.
Cardenas-de la Garza, J.A., la Cruz-Valadez, D., Ocampo-Candiani, J. and Welsh, O., 2019. Clinical spectrum of Lyme disease. European Journal of Clinical Microbiology & Infectious Diseases, 38(2), pp.201-208.
Choi, K.H. and Martinson, M.L., 2018. The relationship between low birthweight and childhood health: disparities by race, ethnicity, and national origin. Annals of Epidemiology, 28(10), pp.704-709.
Dumpler, J., Huppertz, T. and Kulozik, U., 2020. Invited review: Heat stability of milk and concentrated milk: Past, present, and future research objectives. Journal of Dairy Science, 103(12), pp.10986-11007.
Glasgow, R.E., Harden, S.M., Gaglio, B., Rabin, B., Smith, M.L., Porter, G.C., Ory, M.G. and Estabrooks, P.A., 2019. RE-AIM planning and evaluation framework: adapting to new science and practice with a 20-year review. Frontiers in public health, 7, p.64.
Hackman, D.A., Suthar, H., Molina, A.P., Dawson, W.C. and Putnam-Hornstein, E., 2022. Neighborhood poverty, intergenerational mobility, and early developmental health in a population birth cohort. Health & Place, 74, p.102754.
Lee, J., Hyeon, D.Y. and Hwang, D., 2020. Single-cell multiomics: technologies and data analysis methods. Experimental & Molecular Medicine, 52(9), pp.1428-1442.
Mahmood, F., Khan, A.Z. and Bokhari, R.H., 2019. ERP issues and challenges: a research synthesis. Kybernetes.
Mathur, M.B. and VanderWeele, T.J., 2022. Methods to address confounding and other biases in meta-analyses: review and recommendations. Annual review of public health, 43, p.19.
Nakra, N.A., Blumberg, D.A., Herrera-Guerra, A. and Lakshminrusimha, S., 2020. Multi-system inflammatory syndrome in children (MIS-C) following SARS-CoV-2 infection: review of clinical presentation, hypothetical pathogenesis, and proposed management. Children, 7(7), p.69.
Radolf, J.D., Strle, K., Lemieux, J.E. and Strle, F., 2021. Lyme disease in humans. Current issues in molecular biology, 42(1), pp.333-384.
Roy, R. and Uekusa, S., 2020. Collaborative autoethnography:“Self-reflection” as a timely alternative research approach during the global pandemic. Qualitative Research Journal.
Sovacool, B.K., Axsen, J. and Sorrell, S., 2018. Promoting novelty, rigor, and style in energy social science: Towards codes of practice for appropriate methods and research design. Energy Research & Social Science, 45, pp.12-42.
Testa, A. and Jackson, D.B., 2021. Race, ethnicity, WIC participation, and infant health disparities in the United States. Annals of epidemiology, 58, pp.22-28.
Woodward, M., 2019. Rationale and tutorial for analysing and reporting sex differences in cardiovascular associations. Heart, 105(22), pp.1701-1708.
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