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Epidemiology is a branch of medical science that studies the distribution of diseases in the human population and the different factors that determine that distribution using statistics. It is an interdisciplinary topic that covers mathematics, statistics, biology, and geography. Being such a technical topic of study, students have to spend long hours learning this challenging topic. However, we have provided an alternative by providing epidemiology homework help to students. Any student seeking help in epidemiology homework will get experienced experts here. Students seek help in epidemiology because;
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Descriptive Statistics in Epidemiology
Descriptive statistics are used in epidemiology to identify and describe how diseases and determinants are distributed. It provides useful tools that organize and analyze data that defines the frequency of disease variation among populations. As a result, we can say that descriptive statistics in epidemiology can generate hypotheses from etiologic research. For example, standard survey instruments (which are tools of descriptive statistics) are often used to measure health conditions such as cancer, diabetes, and heart failure.
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1. Natural disasters – Natural disasters occur without the triggers of a human being.
2. Human-made disasters – Man-made disasters are caused by human loopholes such as chemical spills, nuclear accidents, and many more.
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Epidemiology models
Epidemiology models are techniques applied in the mathematical modeling of infectious diseases. The models include;
| The SIS model | This is a model in which the infection does not lead to immunity. In the model, people return to the susceptible class after recovering from the infection. Naturally occurring births and deaths are included in the SIS model. |
| The SIR model without vital dynamics | In this model, the dynamics of an epidemic are faster than those of birth and death. Here the considered diseases are diseases that confer permanent immunity. In this case, a disease goes through a population within a short period. A good example is flu. |
| The SIR models with vital dynamics | The SIR model with vital dynamics occurs where a disease behavior in a population stays for a long time. In this case, the disease is endemic if it stays in a population for more than ten years. |
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Epidemiology modeling approaches
1. Interaction-based approach
Mathematical epidemiology stresses differential equation models that are rate-based. The interaction-based approach uses various criteria to divide the population into sub-groups. These criteria can be the state of diseases or demographic characteristics. Differential equation models are then used to define the dynamics of the disease across the created groups. However, this method is limited and fraught with several technical difficulties. It is near impossible to get a detailed and accurate human social contact network using simple measurements.
2. Synthetic information environments approach
This approach comprises four components, the statistical model of the synthetic population, social contact network activity-based model, disease progression models, and models that will be used to represent and evaluate individual adaptation, public policies, and interventions. A synthetic population is the group of interest. To generate this population, we have to create a group of individual agents by integrating the census data with other geographic or demographic data. Next, we will generate a comprehensive schedule for each agent in the population being studied. This is usually done using machine learning methods and time-use surveys. The third step uses a probabilistic transition system to represent the within-host model and endow each individual. Lastly, we analyze how effective the intervention strategies used are.
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In epidemiology, scientists work with a mammoth of data from medical records from patients registered with various conditions and cohorts compiled with a definitive objective. As you already know, epidemiology is constrained to a sample of individuals from a study population. Since it is impractical to study the entire population, samples are often used to make statistical inferences. Statistical methods such as statistical significance tests and confidence intervals can be used to assess the observations and estimates made.
