Differentiate between bias and confounding.

Differentiate between bias and confounding.

Differentiate between bias and confounding. 150 150 Nyagu

PUB 540 Principles of epidemiology – Topic 3: Causal Inference, Confounding, and Bias
PUB 540 Principles of epidemiology – Topic 3: Causal Inference, Confounding, and Bias

Topic 3: Causal Inference, Confounding, and Bias
Objectives:
Determine sources of bias within a study design.
Describe confounding relationships.
Evaluate the types of causal relationships associated with causation.
Assess measures of morbidity.
Measuring Morbidity: Prevalence and Incidence

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Read the scenario below and complete the assignment as instructed.

Scenario

In Community X (population 20,000), an epidemiologist conducted a prevalence survey in January of 2012 and reported an HIV prevalence of 2.2%. Over the next 12 months, the department of health reported an additional 50 new HIV cases between February 2012 and January 2013. The total population stayed constant at 20,000. PUB 540 Principles of epidemiology – Topic 3: Causal Inference, Confounding, and Bias

Part 1

How many people had HIV in January 2012? Present or describe the formula you used to arrive at your answer.
Calculate the incidence rate assuming no HIV-related deaths over the 12-month period. Present or describe the formula you used to arrive at your answer. Be sure to clearly indicate the numerator and denominator used in your calculation and include an appropriate label for the rate. PUB 540 Principles of epidemiology – Topic 3: Causal Inference, Confounding, and Bias.
In a summary of 200-250 words, interpret the results and discuss the relationship between incidence and prevalence. Discuss whether or not the epidemiologist should be concerned about these new HIV infections, assuming a previous incidence rate of 0.5 per 1,000 person-years prior to this updated risk assessment.

Part 2

A rapid test used for diagnosing HIV has a sensitivity of 99.1% and a specificity of 90%. Based on the population prevalence of 2.2% in 2012, create a 2×2 table showing the number of true positives, false positives, false negatives, and true negatives. PUB 540 Principles of epidemiology – Topic 3: Causal Inference, Confounding, and Bias. Calculate the positive predicative value and negative predictive value for this test. Refer to the “Creating a 2×2 Contingency Table” resource for guidance.

In 200-250 words, discuss whether or not the epidemiologist should recommend this test as part of a universal HIV screening program. Provide rationale for your recommendation applying the positive and negative predictive values. Present or describe the formula you used to arrive at your answer.

General Requirements

APA style is not required, but solid academic writing is expected.

This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion. PUB 540 Principles of epidemiology – Topic 3: Causal Inference, Confounding, and Bias,

You are not required to submit this assignment to LopesWrite.

Topic 3 DQ 1

Differentiate between bias and confounding. Discuss the criteria necessary to establish a factor as a confounder and provide an example applying these criteria. What is one way to adjust for a confounding relationship in the study design or the analysis?

Topic 3 DQ 2

Explain the two major types of bias. Identify a peer-reviewed epidemiology article that discusses potential issues with bias as a limitation and discuss what could have been done to minimize the bias (exclude articles that combine multiple studies such as meta-analysis and systemic review articles). What are the implications of making inferences based on data with bias? Include a link to the article in your reference. PUB 540 Principles of epidemiology – Topic 3: Causal Inference, Confounding, and Bias