"Patient Zero"

(noun)

A term used to refer to the index case in the spread of HIV in North America.

Related Terms

Examples of "Patient Zero" in the following topics:

  • Finding Patient Zero and Tracking Diseases

    • "Patient Zero" was used to refer to the index case in the spread of HIV in North America.
    • For example, in the early years of the AIDS epidemic there was controversy about a so-called Patient Zero, who was the basis of a complex transmission scenario.
    • This epidemiological study showed how Patient Zero had infected multiple partners with HIV, and they in turn transmitted it to others and rapidly spread the virus to locations all over the world.
    • In the eboloa outbreak of 2014, the Patient Zero was identified as a two year-old boy in Guinea who died on Dec. 2, 2013 of Ebolavirus during the fruitbat migration.
    • Other prominent "Patient Zeroes" include Typhoid Mary.

  • Absorption of Alcohol

    • Post-operative gastric bypass patients develop a lowered tolerance for alcoholic beverages because their altered digestive tract absorbs alcohol at a faster rate than people who have not undergone the surgery.
    • It also takes a post-operative patient longer to reach sober levels after consuming alcohol.
    • In a study conducted on 36 post-operative patients and a control group of 36 subjects (who had not undergone surgery), each subject drank a 5 oz. glass of red wine and had the alcohol in their breath measured to evaluate alcohol metabolism.
    • It took on average 108 minutes for the gastric bypass patients group to return to an alcohol breath of zero, while it took the control group an average of 72 minutes.
    • In cases of severe liver disease, the only treatment option may be a liver transplant in alcohol-abstinent patients.

  • The t-Test

    • A test of a null hypothesis that the difference between two responses measured on the same statistical unit has a mean value of zero.
    • For example, suppose we measure the size of a cancer patient's tumor before and after a treatment.
    • If the treatment is effective, we expect the tumor size for many of the patients to be smaller following the treatment.

  • Simulating a difference under the null distribution

    • The expected difference between the two proportions under this simulation is zero.
    • We run this simulation by taking 40 treatment fake and 50 control fake labels and randomly assigning them to the patients.
    • We use a computer program to randomly assign these labels to the patients, and we organize the simulation results into Table 6.24.
    • Caution: Simulation in the two proportion case requires that the null difference is zero
    • The labels were randomly assigned and are independent of the outcome of the patient.

  • Zeroes of Linear Functions

    • A zero, or $x$-intercept, is the point at which a linear function's value will equal zero.
    • Zeros can be observed graphically.  
    • Because the $x$-intercept (zero) is a point at which the function crosses the $x$-axis, it will have the value $(x,0)$, where $x$ is the zero.
    • The zero is $(-4,0)$.  
    • The blue line, $y=\frac{1}{2}x+2$, has a zero at $(-4,0)$; the red line, $y=-x+5$, has a zero at $(5,0)$.  

  • Hypothesis testing for nearly normal point estimates

    • A drug called sulphinpyrazone was under consideration for use in reducing the death rate in heart attack patients.
    • In the control group, 60 of 742 patients died.
    • In the treatment group, 41 of 733 patients died.
    • The distribution is centered at zero since p control − p treatment = 0 under the null hypothesis.
    • That is, we reject the null hypothesis in favor of the alternative and conclude that the drug is effective at reducing deaths in heart attack patients.

  • Large sample framework for a difference in two proportions

    • There were 50 patients in the experiment who did not receive the blood thinner and 40 patients who did.
    • According to the point estimate, for patients who have undergone CPR outside of the hospital, an additional 13% of these patients survive when they are treated with blood thinners.
    • We will assume the patients are independent, which is probably reasonable.
    • The null distribution with mean zero and standard deviation 0.095 is shown in Figure 6.23.
    • Patients in the treatment group were given a blood thinner, and patients in the control group were not.

  • TQM’s seven basic elements

    • Continuous improvement: An organizational culture that promotes continuous learning and problem solving is essential in the pursuit of zero defects.
    • In the case of health care, the TPS approach enabled one hospital to analyze the causes of patient infections from catheters and pneumonia in patients on ventilators.
    • With simple changes in procedures that prevented patients from getting these secondary illnesses, the hospital was able to save USD 40,000 per patient in these cases.
    • For example, when a dental office designs the service process, it might have patients fill out a form that covers important information on general health issues, allergies, and medications.
    • Staff, hygienists, and dentists are highly trained to follow proper procedures, the facility is both functional and pleasant, and the equipment and tools are state of the art to ensure that the patient's desired outcome is achieved.

  • Review

    • What does it mean when a data set has a standard deviation equal to zero?
    • The next four questions refer to the following: Recently, a nurse commented that when a patient calls the medical advice line claiming to have the flu, the chance that he/she truly has the flu (and not just a nasty cold) is only about 4%.
    • Of the next 25 patients calling in claiming to have the flu, we are interested in how many actually have the flu.
    • Find the probability that at least 4 of the 25 patients actually have the flu.
    • On average, for every 25 patients calling in, how many do you expect to have the flu?

  • Finding Polynomials with Given Zeros

    • To construct a polynomial from given zeros, set $x$ equal to each zero, move everything to one side, then multiply each resulting equation.
    • One type of problem is to generate a polynomial from given zeros.
    • If it is not specified what the multiplicity of the zeros are, we want the zeros to have multiplicity one.
    • There are no other zeros, i.e. if a number is not mentioned in the problem statement, it cannot be a zero of the polynomial we find.
    • Two polynomials with the same zeros: Both $f(x)$ and $g(x)$ have zeros $0, 1$ and $2$.