HLT 362 Describe how epidemiological data influences changes in health practices

HLT 362 Describe how epidemiological data influences changes in health practices

HLT 362 Describe how epidemiological data influences changes in health practices

Epidemiological Data Influences on Health Practices

Epidemiology is the study of the distribution and determinants of health-related states or events within a specified population, its purpose being to inform decisions about the control of health problems (Hannaford & Owen-Smith, 1998). Epidemiological data can be useful in health practices to help promote health and well-being and save lives by collecting data. This data should include: what? How much? When? Where? and among whom? (CDC, 2018). Epidemiological data influences changes in health practices because it gathers and analyzes all aspects of a disease process, allowing for the development of best practices and evidence-based approaches that directly impact people’s lives. Collecting epidemiological data will affect healthcare policy by revealing how things are connected and whether making improvements results in different outcomes. For example, to stop germs from infecting more people, we must break the chain of infection. The infectious agent, reservoir, portal of exit, mode of transmission, portal of entry, and susceptible host are all part of the chain. Hand hygiene has been described as essential in breaking the chain of infection based on epidemiological evidence.

Example of Epidemiology Data

The COVID-19 pandemic we are currently facing is an example of how epidemiological evidence affects improvements in health practices. Epidemiologists collaborate with other scientists to determine who has been infected, why they have been infected, and what the CDC may do to help (CDC, 2020). Epidemiologists could pinpoint the outbreak’s source, track and control the disease, and determine risk factors, transmission mode, and the most appropriate treatment. They devise strategies for slowing the disease’s spread and reducing its effects. The guidelines include masking, social distancing, personal protective equipment (PPE), and adequate hand washing.


Centers for Disease Control and Prevention (CDC). (2018). Describing Epidemiologic Data. Retrieved from: https://www.cdc.gov/eis/field-epi-manual/chapters/Describing-Epi-Data.html

Centers for Disease Control and Prevention (CDC). (2020). About COVID-19 Epidemiology, Investigating Covid-19: The Science Behind CDC’s Response. https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/about-epidemiology/index.html

Hannaford, P. C., & Owen-Smith, V. (1998). Using epidemiological data to guide clinical practice: review of studies on cardiovascular disease and use of combined oral contraceptives. BMJ (Clinical research ed.), 316(7136), 984–987. https://doi.org/10.1136/bmj.316.7136.984

Torres, Elissa. (2018). Application of Analysis https://lc.gcumedia.com/hlt362v/applied- statistics-for-health-care/v1.1/#/chapter/5

Click here to ORDER an A++ paper from our Verified MASTERS and DOCTORATE WRITERS HLT 362 Describe how epidemiological data influences changes in health practices:

Epidemiology is the study of disease appearance, course, spread, and eradication. Data is raw unorganized information from which conclusions can be made. The purpose of epidemiological data is to influence changes in health practices. If as healthcare providers, we did not collect and look at data that concerns disease we would not be able to diagnosis and treat the disease. The epidemiological data influences the change in the health practices as it is the study of distribution and determinants of health-related events in specific populations (Fairchild et al. 2018). The epidemiological data inform the health authorities and public of the issues in the health department. The data are then used to estimate the frequency of diseases and the improvements needed to resolve the issues. The health status due to certain diseases, the risk factors of disease, and the relationship between the disease agents and health.

HLT 362 Describe how epidemiological data influences changes in health practices
HLT 362 Describe how epidemiological data influences changes in health practices

Cancer Epidemiology data has significantly contributed to determining the distribution, determinants, and frequency of malignant disease in specific populations (Aren & Loftfield, 2017). New diagnoses of breast cancer are presented by demographic and clinical/histological variables that include cancer grade, behavior, stage, and histological type at diagnosis. Data on the increased incidence rates of breast cancer would and has caused the medical practice to make changes in diagnosis and treatment. According to the American Cancer Society, several studies are looking most closely at the effect of exercise, weight gain or loss, and diet on risk. Studies on the best use of genetic testing for breast cancer mutations continue at a rapid pace. Scientists are exploring how common gene variations (small changes in genes that are not as significant as mutations) may affect breast cancer risk. Gene variants typically have only a modest effect on risk, but when taken together they could possibly have a large impact. Possible environmental causes of breast cancer have also received more attention in recent years.


Arem, H., & Loftfield, E. (2017). Cancer Epidemiology: A Survey of Modifiable Risk Factors for Prevention and Survivorship. American journal of lifestyle medicine, 12(3), 200–210. doi:10.1177/1559827617700600.

Fairchild, G., Tasseff, B., Khalsa, H., Generous, N., Daughton, A. R., Velappan, N., Priedhorsky, R., & Deshpande, A. (2018). Epidemiological Data Challenges: Planning for a More Robust Future Through Data Standards. Frontiers in public health6, 336. https://doi.org/10.3389/fpubh.2018.00336

Epidemiology is a branch of study that predicts the occurrences and patterns of diseases in different groups of the population (Project Guru, 2018). It is significant in health care, because it helps them to understand disease process, in that it helps in assessing the reason and factors behind the occurrence of a disease. Epidemiological data helps to plan and strategies to prevent and manage epidemic diseases or illness (Project Guru, 2018). Epidemiological data has greatly influenced health practice because the information and knowledge derived from the data can be translated into health interventions that are effective in improving health state that epidemiological data has focused on creating a wealth of accumulated experiences desirable in assessing the macro-environments as well as specific agents that may influence health. Epidemiological data is also desirable in influencing the changes in the health practices by making it possible for policymakers to access public health concerns and devise policies that can be implemented to improve a community’s general health. It also desirable in influencing the changes in the health practices by making it possible for policymakers to access public health concerns and devise policies that can be implemented to improve a community’s general health. For instance, due to epidemiology, it was discovered that people that do not use protective such as condom during sex is at risk of sexual transmitted disease, due to tis patents are been educated on using Condom during sexual especially if they have multiple sexual partners. Another example is vaccination, it was discovered that people that are vaccinated are at lesser risk of some disease condition such as TB, Polio, flu and much more.

There are different type of data that can be used to make changes in health care practice such as mortality, disease cases, treatment based data, financial, and research-based data, which are data used to analyze infectious disease prevalence by healthcare agencies and the policymakers

(Project Guru, 2018),this will help the health care team to know what to do, what can be done and ways to improved care and promote health. Also, healthcare and pharmaceuticals use drug-based data and clinical data which aimed to control and manage infectious diseases.

Project Guru, (2018). Epidemiological data play an important role in healthcare policy making. Retrieved from https://www.projectguru.in/epidemiological-data-play-important-role-healthcare-policy-making/#:

Epidemiology does play an important role in not only anticipating occurence of disease but it also seeks to improve the health of a particular community to prevent contracting said illness. For instance with regard to cardiovascular disease, it is only because of epidemiological evidence that we have come to learn that dietary changes associated with the nutritional transition, specifically the increasing consumption of energy-dense diets high in unhealthy fats, oils, sodium, and sugars, have contributed to an increase in cardiovascular disease incidence in low and middle income countries (Hu as cited in Institute of Medicine Committee on Preventing the Global Epidemic of Cardiovascular Disease, 2010). This prevalence also not only draws attention to the socio-economic factors impacting incidence of cardiovascular disease among certain sections of the more general population but also allows community health centers to develop tailored initiatives to assist in the adoption of healthier diets, thereby significantly reducing risk of developing cardiovascular disease and improving the health of a particular community within the population. 


Institute of Medicine Committee on Preventing the Global Epidemic of Cardiovascular Disease. (2010). Epidemiology of cardiovascular disease. Promoting Cardiovascular Health in the Developing World: A Critical Challenge to Achieve Global Health, (ch.2).   https://www.ncbi.nlm.nih.gov/books/NBK45688/

Epidemiology is the study of the distribution and determinants of health-related States or events in specified populations and the application of this study to the control of health problems (CDC, 2012). Epidemiology is a quantitative discipline that relies on a working knowledge of probability, statistics, and sound research methods. Epidemiology is a method of causal reasoning based on developing and testing hypothesis grounded in such scientific fields as biology, behavioral sciences, physics, and ergonomics to explain the health-related behaviors, states, and events. Epidemiology is not just a research activity but an integral component of public health, providing the foundation for directing practical and appropriate public health action based on this science and causal reasoning.

It is concerned with the frequency and pattern of health events in a population.

The Epidemiology data are first analyzed and then based on the inferences the healthcare need is determined. And then changes are made in health practices.

Furthermore planning is made for the policymaking.

For example public health epidemiological data are collected through various surveys and then they are analyzed and used for the required change in health practices.

Categorical data would be necessary to make a change in practice. It is a data that does not have number assigned to it. For instance, when doing a medical research and patient characteristics are recorded. Risk is one of the data that influences change in practice. The increased likelihood of an adverse event conferred by risk may be attributable to structural or environmental exposures; inherited or congenital conditions; chronic or acquired health problems, such as diabetes or high blood pressure; infections; complications from a previous pregnancy; risk behaviors or other issues that may unexpectedly arise during the course of pregnancy (Alliman & Phillip, 2016)

Another example is appearance which can be sick or healthy. It is a subjective categorical situation, you cannot measure it.

Another one that is important in medical studies is race because there is difference in incidence of certain diseases according to race, white, or black or hispanics.


CDC, (2012). Principles of Epidemiology in Public Practice, Third Edition: An Introduction to Applied Epidemiology and Biostatistics. http://www.cdc.gov/ophss/xsels/dsepd/ss1978/lessons/sextion8.html

Alliman, J., & Phillippi, J., (2016). Maternal outcomes in birth centers: An integrative review of the literature. Journal of Midwifery and Woman’s Health. https://www.ncbi.nlm.nih.gov/books/NBK55489/

Health Care needs the availability of epidemiology data for use in varieties of disciplines and from the public health perspective, epidemiology data is used to gain an understanding of diseases that affect the population and their progression (Fairchild et al., 2018). When epidemiology data are accessed, they create values for emergency preparedness and response to health-related problems, understand diseases and its prevention (Fairchild et al., 2018). As a result, the internet serves as the predominant way to publish, share, and collect epidemiological data. As mentioned, the health of the population is dependent on many different factors. Epidemiology as a discipline has a crucial and critical role to play in describing health status, identifying the risks factors, and analyzing relationships between health and different harmful agents that are causing the diseases (Gulis & Fijino, 2015). There is the classified epidemiology triangle of host-agent-environment which describes how individuals become ill (Gulis & Fijino, 2019). To illustrate this more clearly, disease occurs when an outside agent (vector) capable of causing disease or injury meets with a host that is vulnerable to the agent and this happens in the environment that allows the agent and the host to interact (Gulis & Fijino, 2015). Here comes epidemiology, which measures the relationships between hosts and agents in a certain environment and analyses the health status of the population living in the environment (Gulis & Fijino, 2015).

There are different types of interventions that tackle all three elements of the triangle-One works with the hosts and improve their immune system, increase their knowledge, and motivate behavioral change to make the hosts more resistant to agents (Fairchild et al., 20180. Public health can also help as an example of the presence and distribution of agents and this is often done via traditional hygiene measure, such as providing safe drinking water, clean air, and good waste management. It is done also via anti-smoking regulations, diet advice, and physical activity guidelines (Fairchild et al., 2018). Epidemiology provides evidence-based knowledge on the distribution of health effects and their risk factors across different population groups, if not looked into seriously, epidemiology may overlook the fact that decision-making may be based on not only scientific evidence, but also on political, economic, and social considerations (Fairchild et al., 2018).


Fairchild, G., Tasseff, B., Khalsa, H., Generous, N., Daughton, A. R., Velappan, N., Priedhorsky, R., & Deshpande, A. 92018). Epidemiology data challenges: Planning for a more robust future through data standards. Front Public Health,6. doi: 10.3389/fpubh.2018.00336

Gulis, G. & Fijino, Y. (2015). Epidemiology, population health, and health impact assessment. Journal of Epidemiology, 25(3), 179-180. doi: 10.2188/jea/JE20140212

Epidemiology is a branch of medicine which deals with the incidence, distribution, possible control of diseases and other factors relating to health. It is a part of public health.

The word epidemiology comes from the Greek words’ epi, meaning on or upon, demos, meaning people, and logos, meaning the study of. In other words, the word epidemiology has its roots in the study of what befalls a population. Many definitions have been proposed, but the following definition captures the underlying principles and public health spirit of epidemiology.

Epidemiology is a scientific discipline with sound methods of scientific inquiry at its foundation. Epidemiology is data-driven and relies on a systematic and unbiased approach to the collection, analysis, and interpretation of data. Basic epidemiologic methods tend to rely on careful observation and use of valid comparison groups to assess whether what was observed, such as the number of cases of disease in a particular area during a particular period of time or the frequency of an exposure among persons with disease, differs from what might be expected. However, epidemiology also draws on methods from other scientific fields, including biostatistics and informatics, with biologic, economic, social, and behavioral sciences.

Accessible epidemiological data are of great value for emergency preparedness and response, understanding disease progression through a population, and building statistical and mechanistic disease models that enable forecasting. The status quo, however, renders acquiring and using such data difficult in practice. In many cases, a primary way of obtaining epidemiological data is through the internet, but the methods by which the data are presented to the public often differ drastically among institutions. As a result, there is a strong need for better data sharing practices. This paper identifies, in detail and with examples, the three key challenges one encounters when attempting to acquire and use epidemiological data: (1) interfaces, (2) data formatting, and (3) reporting. These challenges are used to provide suggestions and guidance for improvement as these systems evolve in the future. If these suggested data and interface recommendations were adhered to, epidemiological and public health analysis, modeling, and informatics work would be significantly streamlined, which can in turn yield better public health decision-making capabilities.

At the heart of disease surveillance and modeling are epidemiological data. These data are generally presented as a time series of cases, T, for a geographic region, G, and for a demographic, D. The type of cases presented may vary depending on the context. For example, T may be a time series of confirmed or suspected cases, or it might be hospitalizations or deaths; in some circumstances, it may be a summation of some combination of these (e.g., confirmed + suspected cases). G is most commonly a political boundary; it might be a country, state/province, county/district, city, or sub-city region, such as a postal code or United States (U.S.) Census Bureau census tract. Depending on the context, D may simply be the the entire population of G, or it might be stratified by age, sex, race, education, or other relevant factors.

Epidemiological data have a variety of uses. From a public health perspective, they can be used to gain an understanding of population-level disease progression. This understanding can in turn be used to aid in decision-making and allocation of resources. Recent outbreaks like Ebola and Zika have demonstrated the value of accessible epidemiological data for emergency preparedness and the need for better data sharing. These data may influence vaccine distribution, and hospitals can anticipate surge capacity during an outbreak, allowing them to obtain extra temporary help if necessary. Local, state, and national levels can also be engaged in formulating appropriate policies that will favor the health of the identified population. Epidemiological data will influence education, practice, and research in the medical field. Traditional care methods will also be questioned, and more effective ways of care will be devised and implemented.

The internet has become the predominant way to publish, share, and collect epidemiological data. While data standards exist for observational studies and clinical research, for example, no such standards exist for the publication of the kind of public health-related epidemiological data described above. Despite the strong need to share and consume data, there are many legal, technical, political, and cultural challenges in implementing a standardized epidemiological data framework (22, 23). As a result, the methods by which data are presented to the public often differ significantly among data-sharing institutions (e.g., public health departments, ministries of health, data collection or aggregation services). Moreover, these problems are not unique to epidemiological data; the issues described in this paper are common across many different disciplines.

First, epidemiological data on the internet are presented to the user through a variety of interfaces. These interfaces vary widely not only in their appearance but also in their functionality. Some data are openly available through clear modern web interfaces, complete with well-documented programmer-friendly application programming interfaces (APIs), while others are displayed as static web pages that require error-prone and brittle web scraping. Still others are offered as machine-readable documents [e.g., comma-separate values (CSV), Microsoft Excel, Extensible Markup Language (XML), Adobe PDF]. Finally, some necessitate contacting a human, who then prepares and sends the requested data manually.

Second, there are many data formats. Data containers [e.g., CSV, JavaScript Object Notation (JSON)] and element formats (e.g., timestamp format, location name format) may differ. Character encodings (e.g., ASCII, UTF-8) and line endings (e.g., \r\n, \n) may also differ. Compounding these issues, formats can change over time (e.g., renaming, or reordering spreadsheet columns). More broadly, these challenges are closely tied to schema, data model, and vocabulary standardization.

Finally, there are differences among institutions in their reporting habits; even within a single institution, there are often reporting nuances among diseases. For example, one context may be reported monthly (e.g., Q fever in Australia), while another context is reported weekly (e.g., influenza in the U.S.) or even more finely (e.g., 2014 West African Ebola outbreak). Furthermore, what is meant by “weekly” in one context may be different than another context (e.g., CDC epi weeks vs. irregular reporting intervals in Poland, as described later).

We do epidemiology on all kinds of problems such as the flu, HIV spread in segregated neighborhoods, and identifying risk factors for all sorts of cancer. Epidemiology is the hard backbone that makes up the science of Public Health.

One of the first effective uses of epidemiology was by John Snow in London about 150 years ago. Snow did mapping of cases of cholera. It showed a pattern that indicated that the problem may have been the supply of water to a certain pump. When the pump was made inoperable there was a clear recovery. This showed that smell was not the cause of the infection which was a commonly believed cause of illness. Rather than a symptom.

This discovery showed how vital it was for public health to maintain a clean supply of drinking water. And this also saved many millions of lives. Water management is now a vital part of community health care. And in developed nations diseases like cholera are rare.

Another doctor using observation in a maternity hospital leads to the thought that infections may have been spread by dirty hands. At the time having children was very dangerous. Deaths during pregnancy were expected. Doctors went to and from the wards to the mortuary. At one time where the deaths were more frequent, the doctor considered the practice of cleaning hands. A mild antiseptic hand wash was used. The handwashing was hugely successful and greatly improved the safety of pregnant women. Probably saving millions of lives. While microscopes had been available for hundreds of years doctors and scientists could not show the link with disease. Smell was a common thing to blame rather than microorganisms. After these discoveries and some other and successes, it was realized that we could find the cause of many infectious diseases. Individual organisms could be related to different infections.

Epidemiology remains vital. In this pandemic, it is being used to track the chains of infection so that infected people could be isolated if needed. And microbiology with the use of genetics can show who infected who. This can be done by finding genetic mutations that are common in viruses. These are mostly harmless mutations but allows people to see who may have infected other people. They can then trace other people that may have been exposed. When done effectively many lives can be saved. And has been very effective in many cases.


1. Chretien JP, Rivers CM, Johansson MA. Make data sharing routine to prepare for public health emergencies. PLoS Med. (2016) 13:e1002109. doi: 10.1371/journal.pmed.1002109

2. Hota S, Fried E, Burry L, Stewart TE, Christian MD. Preparing your intensive care unit for the second wave of H1N1 and future surges. Crit Care Med. (2010) 38:e110–9. doi: 10.1097/CCM.0b013e3181c66940

3. Nap RE, Andriessen MPHM, Meessen NEL, van der Werf TS. Pandemic influenza and hospital resources. Emerg Infect Dis. (2007) 13:1714–9. doi: 10.3201/eid1311.070103

4. US Department of Health and Human Services US Department of Homeland Security. Guidance on Allocating and Targeting Pandemic Influenza Vaccine (2008). Available online at: https://asprtracie.hhs.gov/technical-resources/resource/2846/guidance-on-allocating-and-targeting-pandemic-influenza-vaccine