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Quantifying the effects of pfizer-biontech vaccine

    Assignment Instructions

    Assignment ID: FG133049178

    Please thoroughly answer the following questions:

    Question 1. Quantifying the Effects of Pfizer/BioNTech Vaccine

    Question 1A. Find the number of people living in nursing homes in the USA. 

    Question 1B. Find the number of Sars-Cov-2 related deaths among nursing home residents in the USA since the start of the Covid-19 pandemic.

    Question 1C. What is the effect of the Pfizer/BioNTech vaccine on the likelihood of catching a Covid-19 infection?

    • To answer this question, use the Phase III randomized controlled trial results for the Pfizer/BioNTech vaccine.
    • Discuss the percentage-point effect.
    • Discuss the percent effect.
    • Articulate the effect size. For example, if 1,000,000 people are given the vaccine: (1) How many fever infections would happen?

    Question 1D. If 100% of nursing home residents are given the Pfizer/BioNTech vaccine: 

    • How many lives would be saved?
    • How many life years would be saved?
      • Find out how many years the average nursing home resident is expected to live.
    • What is the dollar value of life-years saved?
    • How many hospitalizations due to covid could be avoided?
    • Estimate the cost-savings due to prevented covid-19 hospitalizations.

    Question 2. Quantifying the Effects of Primary Care Availability 

    Table I: The Impact of “Primary Care Availability” on Logarithm of Mortality Rates

     

    (1)

    (2)

    (3)

    (4)

     

    Log All-Age Mortality Rate

    Log Infant 

    Mortality Rate

    Log Child Mortality Rate

    Log Elderly 

    Mortality Rate

    Primary Care Clinic

    -0.058

    -0.153

    -0.062

    -0.053

     

    (0.028)

    (0.066)

    (0.077)

    (0.025)

    Standard errors are in parenthesis. (N=800)

    The independent variable, Primary Care Clinic, is a dummy variable. Using county-level annual data, the analysis tests what happens to mortality rates for the associated age group. 

    Dependent variables are the following: 

    • All-Age Mortality = (Total deaths)/(Population)*1000
    • Infant Mortality = (Deaths in the first 12 months of age)/(Total Births) *1000
    • Child Mortality = (Deaths between the ages 1 and 4)/(Population between ages and 1 4) *1000
    • Elderly Mortality = (Deaths among people older than 65)/(Population older than 65)*1000

    In the analysis, all dependent variables are converted to the natural logarithm.  Each column heading corresponds to the associated dependent variable.

    Use information from Table 1 to answer the questions. 

    Question 2A. Interpret each coefficient considering its statistical significance.

    Question 2B. Provide the 95% confidence interval in each case.

    Question 2C. Is the effect size in column 4 economically significant?

    Question 2D. Using actual infant mortality statistics in Connecticut, simulate how many infants/babies (ages 0 to 12 months old) would be saved because of a potential primary clinic expansion? (Hint: you need to refer to the mean value of infant mortality rate and the number of infants dies each year).

    Question 2E. Using actual infant mortality statistics in Connecticut, simulate the 95% confidence interval for how many infants/babies (ages 0 to 12 months old) would be saved because of a potential primary clinic expansion?

    Question 2F. Find an estimate of the value of life per year. 

    Question 2G. Estimate the dollar value of saved infant lives. 

    Question 2H. Estimate the 95% confidence for the dollar value of saved infant lives. 

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