Comparing HIV and AIDS Prevalence within Countries By: Dan Evans Ida Nordestgaard Lacey McLean By: Dan Evans Ida Nordestgaard Lacey McLean 30 April 2009Economic

Comparing HIV and AIDS

Prevalence within Countries

Comparing HIV and AIDS

Prevalence within Countries

By: Dan Evans

Ida NordestgaardLacey McLean

By: Dan Evans

Ida NordestgaardLacey McLean

30 April 2009Economic Statistics 120

Research Question:

What is the social impact of HIV/AIDS?

What can we do to lower the AIDS prevalence rate in countries?

Research Question:

What is the social impact of HIV/AIDS?

What can we do to lower the AIDS prevalence rate in countries?

Over 1/5th of deaths in Africa are due to AIDS

Estimated number of people living with HIV, by region(1990-2006)

Estimated number of people living with HIV, by region(1990-2006)

Countries We Included In Our Study:Countries We Included In Our Study:Wealthiest Countries • USA• China• Japan• India• Germany• UK• Russia• France• Brazil• Italy

Wealthiest Countries • USA• China• Japan• India• Germany• UK• Russia• France• Brazil• Italy

•Liberia•Madagascar•Malawui•Mali•Mauritania•Mauritius•Mozambique•Nambia•Niger•Nigeria•Rwanda•Senegal•Sierra Leone•Somalia•South Africa•Swaziland•Tanzania•Togo•Uganda•Zambia•ZimbabweSub-Saharan African countries are home to 70% of total world HIV positive population

Sub-Saharan African Countries •Angola•Benin•Botswana•Burkina Faso•Burundi•Cameroon•Central African Republic•Chad•Comoros•Congo•Cote D’Ivoire•Democratic Republic of the Congo•Djibouti•Equilateral Guinea•Eritrea•Ethiopia•Gabon•Gambia•Ghana•Guinea•Guinea-Bissau•Kenya•Lesotho

Measuring Social Cost of HIV/AIDS:

“It is no exaggeration to say that today AIDS is the greatest threat to Africa’s development.”

-K.Y. Amoako, Executive SecretaryUN Economic Commission for Africa

Measuring Social Cost of HIV/AIDS:

“It is no exaggeration to say that today AIDS is the greatest threat to Africa’s development.”

-K.Y. Amoako, Executive SecretaryUN Economic Commission for Africa

Factors we considered:

• GDP per Capita• Life Expectancy• Literacy Rate• GDP Real Growth Rate• Unemployment Rate

Factors we considered:

• GDP per Capita• Life Expectancy• Literacy Rate• GDP Real Growth Rate• Unemployment Rate

Hypotheses:Hypotheses:

• The higher the AIDS prevalence rate, the lower the GDP per Capita

• The higher the AIDS prevalence rate, the lower the Life Expectancy

• The higher the AIDS prevalence rate, the lower the Literacy Rate

• The higher the AIDS prevalence rate, the lower the GDP Real Growth Rate

• The higher the AIDS prevalence rate, the higher the Unemployment Rate

• The higher the AIDS prevalence rate, the lower the GDP per Capita

• The higher the AIDS prevalence rate, the lower the Life Expectancy

• The higher the AIDS prevalence rate, the lower the Literacy Rate

• The higher the AIDS prevalence rate, the lower the GDP Real Growth Rate

• The higher the AIDS prevalence rate, the higher the Unemployment Rate

Top U.S. Humanitarian Aid Recipients: 2000-2003

Top U.S. Humanitarian Aid Recipients: 2000-2003

Country

FY 2000 FY 2001 FY 2002 FY 2003 Total

(millions) (millions) (millions) (millions) 4-Year Total

Uganda $9.30 $13.40 $20.00 $27.90 $70.60

Zambia $9.10 $12.90 $18.50 $25.50 $66.00

Kenya $9.20 $10.40 $17.20 $26.50 $63.30

Nigeria $6.70 $12.80 $14.50 $23.90 $57.90

Ethiopia $7.60 $18.82 $11.30 $19 $56.72

South Africa $6.50 $10.90 $15.00 $22.90 $55.30

GDPP Per CapitaGDPP Per Capita

GDPP

Mean 6835.926

Standard Error 1528.543

Median 1600

Mode 700

Standard Deviation 11232.45

Sample Variance 1.26E+08

Kurtosis 3.988933

Skewness 2.210648

Range 46800

Minimum 200

Maximum 47000

Sum 369140

Count 54


Coefficients Standard Error t Stat P-value Lower 95% Upper 95%Intercept 8318.213 2011.232574 4.135878 0.000129423 4282.379183 12354.05X Variable 1 -19585.28 24924.12492 -0.785796 0.435553089 -69599.1928 30428.64

ˆ y 8313.213 19585.28x

Our results indicate a negative relationship between HIV/AIDSPrevalence rate and GDPP


Regression Statistics

Multiple R 0.351007

R Square 0.123206

Adjusted R Square 0.10233


Observations 44

ANOVA

df SS MS F Significance F

Regression 1 66296348 66296348 5.901785 0.019483

Residual 42 4.72E+08 11233270

Total 43 5.38E+08

Life ExpectancyLife ExpectancyLife Expectancy

Mean 56.43426


Median 54.255

Mode 59

Standard Deviation 12.26679

Sample Variance 150.4742

Kurtosis -0.31711

Skewness 0.485418

Range 50.24

Minimum 31.88

Maximum 82.12

Sum 3047.45

Count 54

Life ExpectancyLife Expectancy

Coefficients Standard Error t Stat P-value Lower 95% Upper 95%Intercept 60.80634425 1.869942029 32.51776971 3.13055E-36 57.05403114 64.55865737X Variable 1 -89.29371774 23.17318708 -3.85332054 0.000321816 -135.7941185 -42.79331695

ˆ y 60.8063 89.294x

Our results indicate a negative relationship between HIV/AIDSPrevalence rate and Life Expectancy

Life ExpectancyLife Expectancy


Multiple R 0.434662

R Square 0.188931



Observations 44

ANOVA


Regression 1 559.7514 559.7514 9.783514 0.003195

Residual 42 2402.977 57.21374

Total 43 2962.729

Literacy RateLiteracy Rate

Literacy Rate

Mean 0.589134

Standard Error 0.031552Median 0.61Mode 0.679Standard Deviation 0.209295Sample Variance 0.043805Kurtosis -0.53233Skewness -0.38326Range 0.8461Minimum 0.0609Maximum 0.907Sum 25.9219Count 44


Coefficients Standard Error t Stat P-value Lower 95% Upper 95%Intercept 0.6056498 0.039526061 15.322798 6.35E-21 0.526335 0.6849647X Variable 1 0.9643753 0.489825237 1.9688151 0.054315 -0.0185309 1.9472815

ˆ y .6056 .9644x

Our results indicate a positive relationship between HIV/AIDSprevalence rate and literacy rate



Multiple R 0.560812

R Square 0.31451



Observations 44

ANOVA


Regression 1 0.59241 0.59241 19.27004 7.51E-05

Residual 42 1.291187 0.030743

Total 43 1.883597

GDP Real Growth RateGDP Real Growth Rate

GDP Real Growth

Mean 0.047Standard Error 0.005588Median 0.0475Mode 0.032Standard Deviation 0.037066Sample Variance 0.001374Kurtosis 10.67931Skewness -2.05298Range 0.258Minimum -0.126Maximum 0.132Sum 2.068Count 44


Coefficients Standard Error t Stat P-value Lower 95% Upper 95%Intercept 0.047204329 0.006547228 7.2098192 2.2904E-09 0.034066355 0.060342303X Variable 1 -0.080194316 0.081136278 -0.9883904 0.32753844 -0.243006165 0.082617534

ˆ y .0472 .0801x

Our results indicate a negative relationship between HIV/AIDSPrevalence rate and GDP Real Growth Rate



Multiple R 0.228344

R Square 0.052141



Observations 44

ANOVA


Regression 1 0.00308 0.00308 2.31038 0.136006

Residual 42 0.055996 0.001333

Total 43 0.059076

Unemployment RateUnemployment Rate

Unemployment Rate

Mean 0.31575

Standard Error 0.035746Median 0.29Mode 0.5Standard Deviation 0.237112Sample Variance 0.056222Kurtosis -0.37837Skewness 0.700858Range 0.822Minimum 0.028Maximum 0.85Sum 13.893 Count 44


Coefficients Standard Error t Stat P-value Lower 95% Upper 95%Intercept 0.24213826 0.040151469 6.03062 1.72E-07 0.16156844 0.32270807X Variable 1 0.55693426 0.497575583 1.119296 0.268158 -0.4415242 1.55539269

Our results indicate a positive relationship between HIV/AIDSPrevalence rate and the unemployment rate

xy 5569.2421.ˆ



Multiple R 0.03775

R Square 0.001425

Adjusted R Square -0.02235


Observations 44

ANOVA


Regression 1 0.003445 0.003445 0.059938 0.807786

Residual 42 2.414099 0.057479

Total 43 2.417544

ResultsResultsWe can conclude statistically that the AIDS prevalence rate affects Life

Expectancy. We were surprised to find that these factors were affected by the AIDS rate, and will not dismiss the possibility that

GDP per Capita, GDP Growth, Literacy Rate and Unemployment may be affected.

If relief funding from organizations increases, lowering the AIDS prevalence rate, it can be inferred from our data that Life

Expectancy will rise.

Possible Limitations:• Data collected within the Sub-Saharan African region is questionable

because of instability within the country due to the AIDS epidemic• We collected the most recent data available, however the AIDS

epidemic continues to growth and expand• Selection of countries

We can conclude statistically that the AIDS prevalence rate affects Life Expectancy. We were surprised to find that these factors were

affected by the AIDS rate, and will not dismiss the possibility that GDP per Capita, GDP Growth, Literacy Rate and Unemployment may

be affected.

If relief funding from organizations increases, lowering the AIDS prevalence rate, it can be inferred from our data that Life

Expectancy will rise.

Possible Limitations:• Data collected within the Sub-Saharan African region is questionable

because of instability within the country due to the AIDS epidemic• We collected the most recent data available, however the AIDS

epidemic continues to growth and expand• Selection of countries

Funding Toward AIDSFunding Toward AIDS• Global Spending on AIDS has increased from $3 million in

1996 to $6.1 in 2004. • It was projected in 2008 the world would need to spend $22

billion to effectively respond to the epidemic.• Sources of funding include:

– National Governments– Multilateral Funding Organizations– Private Sector Funding– Domestic Resources

• Projected distribution of resources:– 38% HIV care and treatment– 35% for prevention– 22% for orphan support– 5% for policy, advocacy and administration costs

• Global Spending on AIDS has increased from $3 million in 1996 to $6.1 in 2004.

• It was projected in 2008 the world would need to spend $22 billion to effectively respond to the epidemic.

• Sources of funding include:– National Governments– Multilateral Funding Organizations– Private Sector Funding– Domestic Resources

• Projected distribution of resources:– 38% HIV care and treatment– 35% for prevention– 22% for orphan support– 5% for policy, advocacy and administration costs

Nation ProfilesNation Profiles

HIV/AIDS pervalance

Rate GDP Per Capita Literacy

RateUnemploymen

t RateGDP Real

Growth RateLife

Expectancy

Uganda 5.40% $

1,100.00 66.80% 3.20% 6.90% 52.72

Zambia 15.20% $

1,500.00 80.60% 50.00% 5.80% 38.63

Ethiopia 2.10% $

800.00 42.70% 50.00% 8.50% 55.41

Kenya 6.70% $

1,600.00 85.10% 40.00% 2.20% 57.86

Nigeria 3.10% $

2,300.00 68.00% 4.90% 6.10% 46.94

South Africa 18.10%

$ 10,000.00 86.40% 21.70% 2.80% 49.98

Nation ProfilesNation Profiles

Decreased RateHIV/AIDS pervalance Rate

Uganda 4.86% 5.40%

Zambia 13.68% 15.20%

Ethiopia 1.89% 2.10%

Kenya 6.03% 6.70%

Nigeria 2.79% 3.10%

South Africa 16.29% 18.10%

Nation ProfilesNation ProfilesHIV/AIDS

pervalance Rate GDP Per Capita

Literacy Rate

Unemployment Rate

GDP Real Growth Rate

Life Expectancy

Uganda 4.86% $

1,133.00 66.93% 2.88% 6.90% 54.8288

Zambia 13.68% $

1,545.00 80.76% 45.00% 5.80% 40.1752

Ethiopia 1.89% $

824.00 42.79% 45.00% 8.50% 57.6264

Kenya 6.03% $

1,648.00 85.27% 36.00% 2.20% 60.1744

Nigeria 2.79% $

2,369.00 68.14% 4.41% 6.10% 48.8176

South Africa 16.29% $

10,300.00 86.57% 19.53% 2.80% 51.9792

The Social Costs of AIDS

“AIDS is negatively affecting every aspect of the social, economic and political development of Africa. It strikes people down in their prime, when they are raising their children, farming their lands, earning their wages, teaching future generations and leading their countries. By the same token, every development challenge that

Africa is facing, whether poverty, poor health, gender inequality, or war and instability, is contributing and driving the spread of AIDS.”

- Mr. Kevin Perkins, Executive Director,Canada Africa Partnership on AIDS

The Social Costs of AIDS

“AIDS is negatively affecting every aspect of the social, economic and political development of Africa. It strikes people down in their prime, when they are raising their children, farming their lands, earning their wages, teaching future generations and leading their countries. By the same token, every development challenge that

Africa is facing, whether poverty, poor health, gender inequality, or war and instability, is contributing and driving the spread of AIDS.”

- Mr. Kevin Perkins, Executive Director,Canada Africa Partnership on AIDS

For Additional Information:For Additional Information:

• CIA World Fact Book• AIDS.ORG• UNICEF.ORG• JournAIDS.ORG• World Health Organization

• CIA World Fact Book• AIDS.ORG• UNICEF.ORG• JournAIDS.ORG• World Health Organization

Documents

Comparing HIV and AIDS Prevalence within Countries By: Dan Evans Ida Nordestgaard Lacey McLean By: Dan Evans Ida Nordestgaard Lacey McLean 30 April 2009Economic