Epidemiologic Methods
1. Introduction
Epidemiology refers to the study of diseases in a population. The various public health professionals, and veterinarians involved in the multiple types of research for preventive medicines use the epidemiological methods for disease outbreak investigations, and surveillance to identify the various risk factors, which influence both the animal and human populations. Further research and inquiries can thus be carried because of the knowledge from the risk factors assessed. The principal purpose of epidemiology is to understand what risk factors are specific to which type of a disease, and the possible preventive measures for the disease in groups of individuals. Epidemiology is observational. Regarding this aspect, this study can tell what caused a condition to a specific individual.
Epidemiological studies can be categorized into four types. These include the cohort study, occupational epidemiological study, case-control study, and cross-sectional study. The epidemiologists use statistical approaches to determine whether the differences in the research results are real or instigated by chance fluctuations. Epidemiological studies can be used in various ways to estimate the disease frequency, and find the correlations in the potential cause of the disease. Epidemiological methods have contributed to the broad scope of medical research in various fields using feasible, and interpretable statistical approaches. Various epidemiological methods have contributed in arriving at the quality of medical research using appropriate methodological approaches, and study designs.
2.0 The Contribution and Assessment of Epidemiological Studies
2.1 Cluster Studies
A cancer cluster is an average of a high number of cases. If the disease under study has a high incidence rate, then clustering can be spatial. Clustering can also be temporal if the incidence rate is higher at some specific time concerning the other times. At times, a disease cluster can encompass the two cases in what is called “spatiotemporal.” In this case, testing only involves correlating only the observable number of cases to the expected number based on certain population factors such as age, and size (Pearce, 2012). Examining a disease cluster allows for extensive learning about the cluster causes. The health care professionals, and the epidemiologists recognize the importance of the historical examples of the cluster examination for cancer. This approach yielded the knowledge about the human carcinogens in those situations, due to a well-defined, prolonged, and high exposure.
2.2 Ecologic studies
Epidemiology has also contributed to the development of research in the areas of ecologic studies. The ecologic study uses the average measure of the disease exposure frequency. The analysis in this section focuses on determining if aggregates with high exposure also display high disease rates. In this particular area of research, the epidemiological study eliminates ecological bias by limiting the measurement errors (Azevedo et al, 2012). The limitation is achieved by minimizing mistakes, which come because of the confounding variables across the geographic units. The justification for this contribution is as follows.
In a study that uses a state as the unit of analysis in a cancer research outcome, the data of concern may the aggregate values of exposure to the disease as well as the aggregate count of the disease by state. In reality, individuals who may develop cancer in these states may be more or less than the aggregate count. In this case, the association across the population of the states may not be an accurate reflection of those people who develop cancer (Carr et al, 2010). Therefore, epidemiology in research has always called for the correct interpretation of the results with a clear but careful statement of the results.
2.3 Case-Control Studies
The primary objective of the case-control study is to determine the relative frequency of exposure of the possible risk factors among people with the disease of interest, and the group without the disease. This category can otherwise be referred to as the cases, and the control respectively (Hedström et al, 2010). This section of the research in the broader perspective of the epidemiological study, consist of the proportion of cases with, and without the exposure, and suspected to be correlated to the disease, is the proportion used for the control experiment. If a particular exposure causes a disease, then a past high exposure proportion is anticipated compared to the previous control proportions.
A situation may demand inference of the character if a stochastic process cannot explain the difference. The case-control of the epidemiological studies allow the cases to be selected from areas like the hospitals, data registers, or any other relevant source (Herrett et al, 2015). The hospitals’ cases may be biased because cases at the referrals may be unusual or more serious. The epidemiological methods in the case-control thus require the population-based ascertainment as the preferred study design. The cancer registry may of use if only it can provide complete diagnosed cases. The control selection requires equal considerations since the controls must come from the same population as the cases.
2.4 Cohort Studies
In this study, an investigator selects a group of exposed, and unexposed persons, and follows them over time to identify any disease occurrence considering the exposure. The cohort study will typically examine the gradients of exposure in the field of radiation epidemiology when the doses or the individual exposures are available. Periodic examinations of individuals can obtain the data used in the cohort studies for the disease assessment. The data can also be obtained from the clinic records, disease registers, and death certificates.
A cohort study has rigorously contributed to scientific research study designs compared to any other form of an epidemiological method. The cohort study attempts to measure the potential exposures even before the disease occurs, and thus reveal the possible causative agents for the disease. Cohort studies are often concerned about the future of research.
3.0 Epidemiological Methods and Principles
The epidemiological methods are essential for public health workers, who use the principle as a foundation for disease surveillance. Every healthcare professional, and public health workers must be conversant with the existing policies, and how each is important in the disease surveillance.
3.1 Distribution
Epidemiology considers most, the pattern and the frequency of a disease occurrence or health events in a population. The Spectrum includes both the risk of disease in the population, and the number of events in the population. In these principles, epidemiology focuses on getting the rate of the disease occurrence by obtaining the ratio between the number of events, and the size of the population. This step is critical in making comparisons across different population structures (Maulik et al, 2011). Distribution assists the healthcare workers to obtain the ratio of the disease prevalence or occurrence, and thus, amicable preventive measures can be designed appropriately.
3.2 Determinants
Epidemiology is also concerned about the causes of the diseases, and other factors that affect the occurrence of a disease in a population. Such incidents of the health-related events relate to several determinants, which the researchers should bring on board (Wu et al, 2016). Disease determinants may include the susceptibility of the host to a disease, the opportunity for exposure to the disease-causing microorganism, the aspect of environmental toxin, and the insect vector. Without knowing the disease determinants, it is improper to design both the preventive, and control measures.
3.3 Specified Populations
From the definition of epidemiology, it is clear that the population is of great concern when it comes to assessing health impacts. Epidemiologists are majorly concerned with the overall health of people, or the area of the impact of health event on the population. The population specified may act as the section for the descriptive epidemiology, which focuses on the “who,” and “where” questions of the health-related events (Maulik et al, 2011).
3.4 Application
The epidemiological methods provide data for public health actions. Scientific methods, and procedures are extensively applied in the fields of analytical, and descriptive epidemiology in the diagnosis phases of the health of the community (Hedström et al, 2010). The principle of application also calls for the experience, and creativity when planning on the control, and preventive methods of a disease in the community.
4.0 Skills for Evaluating Public Health Literature
Public health professionals must bear the necessary skills required to evaluate the relevant literature on public health critically. There are various sources of literature available for the public health sector. The conventional sources for epidemiological research include the reviewed articles and journals textbooks, and data compilations. The available pieces of literature from these sources require various skills for analysis so that the health care professionals can arrive at accurate conclusions during epidemiological research.
4.1 Analytical Skills
Most literature for epidemiological research originates from robust scientific databases. Some of the data are usually raw, while the possible materials for particular research may require statistics. This aspect means that the health care professionals have to convert the available data into statistics for correct interpretation (Wu et al, 2016). Producing statistics from raw data require excellent analytical skills. The skills may encompass the background knowledge about the various statistical tools such as STATA, SPSS, and MATLAB. Good analytical skills produce good statistics from the various research data. Analytical skills are not only specific to data processing, but also article, and journal selection for epidemiological studies (Hedström et al, 2010). The ability to hose the correct articles, and peer-reviewed journals for research back-up requires good analysis of the materials.
4.2 Interpretive Skills
Good interpretive skills give accurate conclusions in research work. Health care industry is a field with rampant research works. Indeed, an effective health care provider should focus more on health care research, to come up with various solutions to the endangered populations (Pearce, 2012). Interpretive skill is part of the research. Wrong interpretation of the available data from multiple research works has led health care professionals into a long search for preventive measures, and cure for certain diseases.
4.3 Critical Appraisal skills
Critical appraisal skills play pivotal roles in the evidence-based approaches in health care practice. The clinicians, and caregivers need to turn the problems they experience in the clinical practice into focused questions (Hedström et al, 2010). While doing this, they need to comprehensively search for relevant pieces of literature, which will address the questions paused, critically appraise the literature, and apply the results to their daily practice. This approach is the overall framework laid by the critical appraisal skills.
5.0 Sources of Data for Epidemiological Research
There are various sources for data collection for epidemiological research. Such sources include the existing medical databases in clinics, and hospitals, data from insurance firms, and other vital records (Petersen et al, 2016). The practice of epidemiology would be inconceivable without the accessing vital, and health records in the routinely assembled tabulations. The vital, and health records are a source of data for the measurement of the incidences, and prevalence of a disease. Such data also identify the groups of people who are at risk of a particular disease. Such data sources originate from vital events such as birth, deaths, marriages, and divorces (Bilinski et al, 2012). Nevertheless, there is a broad category of data sources for epidemiological reassert. They include data from the government and private sources.
5.1 Government Sources
Epidemiological data from the government sources emanate from the agencies such as the Agency for Healthcare Research and Quality: Nationwide Inpatient Sample (NIS), the National Vital Statistics System (NVSS), Behavioral Risk Factor Surveillance System (BRFSS), National modifiable Diseases Surveillance System (NMDSS), and National Health and Nutrition Examination Survey (NHANES). NIS provides one of the most useful, and cost-effective data sources. Their data are provided via electronic methods in CD, and ROM, and are subject to annual updates (Maulik et al, 2011). The data from NIS is stratified in a probability sample of approximately 1000 US community hospitals in 22 states. NVSS provides datasets on births and deaths for public use. The management of NVSS is under the Public Health Service since 1946 (Chen et al, 2010). BRFSS provides data from the telephone surveys from the residents of the US on their health-related risk behaviors, and other chronic conditions. BFSS now collects data from 50 states across the US (Wu et al, 2016). NHANES is a study program designed to assess the health conditions for both adults and children in the US. The combines both interviews and physical examinations to provide data for epidemiological studies.
5.2 Private Data Sources
The private data sources for epidemiological research are from the registries, IMS America Hospital Supply Index (IMS-AHSI), Managed Care Organizations (MCOs), and Harvard Pilgrim Health Care.
6.0 Lessons Learned
Epidemiological methods have contributed directly to the risk assessment processes. Regarding this, the clustering approach for an epidemiological method when the disease under study has high incident rate calls for spatial clustering of the individuals. Additionally, epidemiological methods take into account, the ecological aspects of the disease prevalence. In this regard, the methods provide a framework for ensuring environmental aspects are also take into consideration if the disease cycle has to be terminated in some cases. Nevertheless, ecological studies are exposed to errors from the measurements of the confounding variables. Epidemiology takes into account the measure of a disease burden, and it integrates the concepts of mortality indices for the disease like in the case of cancer. The two statistical concepts are thus glued together to reflect the incidences and the survival probability.
7.0 Summary and Conclusion
Epidemiological methods have contributed to the wide scope of medical research in various fields using possible methods, skills, and statistical approaches. The contribution of the epidemiological studies in areas of research can be illustrated from the different epidemiological methods. The methods include cluster studies, ecological studies, cohort studies, and case-control studies. Each method is unique in addressing the practice areas, policy simulations while tackling the concept of epidemiology. The epidemiological principles and methods factor in the ideas of distribution, determinants, specific populations, and the applications of the principles. For the health care professionals to adhere to these principles, they require specific skills, which will enable them to traverse the complex nature of epidemiology. The skills include analytical, interpretative, and critical appraisal skills. Several sources avail the required data for epidemiological studies. They include government sources such as the NHANES, NIS, NVSS, NMDSS, and BFSS. Other sources are private data sources such as the MCOs, and the IMS-AHSI.
8.0 References
Azevedo, L. F., Costa-Pereira, A., Mendonça, L., Dias, C. C., & Castro-Lopes, J. M. (2012). Epidemiology of chronic pain: a population-based nationwide study on its prevalence, characteristics and associated disability in Portugal. The journal of pain, 13(8), 773-783.
Bilinski, P., Kapka-Skrzypczak, L., & Jablonski, P. (2012). Determining the scale of designer drugs (DD) abuse and risk to public health in Poland through an epidemiological study in adolescents. Annals of Agricultural and Environmental Medicine, 19(3).
Carr, A. S., Cardwell, C. R., McCarron, P. O., & McConville, J. (2010). A systematic review of population based epidemiological studies in Myasthenia Gravis. BMC neurology, 10(1), 46.
Chen, H., Cohen, P., & Chen, S. (2010). How big is a big odds ratio? Interpreting the magnitudes of odds ratios in epidemiological studies. Communications in Statistics—Simulation and Computation®, 39(4), 860-864.
Hedström, E. M., Svensson, O., Bergström, U., & Michno, P. (2010). Epidemiology of fractures in children and adolescents: Increased incidence over the past decade: a population-based study from northern Sweden. Acta orthopaedica, 81(1), 148-153.
Herrett, E., Gallagher, A. M., Bhaskaran, K., Forbes, H., Mathur, R., van Staa, T., & Smeeth, L. (2015). Data resource profile: clinical practice research datalink (CPRD). International journal of epidemiology, 44(3), 827-836.
Manogaran, G., Thota, C., Lopez, D., Vijayakumar, V., Abbas, K. M., & Sundarsekar, R. (2017). Big data knowledge system in healthcare. In Internet of things and big data technologies for next generation healthcare (pp. 133-157). Springer, Cham.
Maulik, P. K., Mascarenhas, M. N., Mathers, C. D., Dua, T., & Saxena, S. (2011). Prevalence of intellectual disability: a meta-analysis of population-based studies. Research in developmental disabilities, 32(2), 419-436.
Pearce, N. (2012). Classification of epidemiological study designs. International journal of epidemiology, 41(2), 393-397.
Petersen, I., Douglas, I., & Whitaker, H. (2016). Self controlled case series methods: an alternative to standard epidemiological study designs. bmj, 354, i4515.
Wu, Y. T., Fratiglioni, L., Matthews, F. E., Lobo, A., Breteler, M. M., Skoog, I., & Brayne, C. (2016). Dementia in western Europe: epidemiological evidence and implications for policy making. The Lancet Neurology, 15(1), 116-124.