Teacher’s HIV Lesson Plan and Activity Packet

What you will find in this packet:

1. Explanation of packet (page 1)2. Instructions (page 1)3. Background and Lecture Information (page 2)4. Activity 5. Answer Keys 6. Discussion Questions

Part I: Explanation of packet

The purpose of this packet is to reinforce biological concepts while practicing statistical principles that will be tested on the AP Exam. In this packet teachers will find lecture material, an in-class exercise and a homework assignment. Students will learn about HIV and AIDS – specifically the life cycle and treatment options. Additionally, they will review important concepts in genetics and immunology. Finally, students will get to take on the role of doctors, which is sure to capture their attention.

Part III: Instructions

To set up: Print off copies of all worksheets. Place “Pathology Lab Results” at the front of the classroom. Give lecture on HIV. Ask students to work in groups of 4. Give one copy of both the “Patient Information Worksheet” and the “Medicine Data Table” to each group of 4. In this activity, students will be analyzing HIV+ patient histories, performing t-tests and chi square tests, and prescribing treatment options. After completing the assignment, you can pass out the homework assignment to each student. The next day, after going over the homework, you can ask the discussion questions if you wish.

Part II: Background and Lecture Information

Teacher’s Guide and Lecture Material

This lesson plan allows you to combine the Immune System and Genetics into one lesson that involves a real world problem (HIV). It also combines statistical analysis into biological problems. It serves as a great review for the AP Exam or any test students might be taking.

You can use the information on this sheet to create a lesson that is suited to your classroom.

Included:

1. Statistics Review Information2. Genetics Review Guide3. Immunology Review Guide4. What is HIV? – background and history5. Classroom Activity and flowchart6. Molecular Information about HIV7. Symptoms and Treatments and flowchart

Step 1: Statistics Review Information.

- Use the statistics page on this website to provide students with a background on statistical principles that they might be tested on.

-Step 2: Genetics Review

- Terms to know:o DNAo RNAo Transcriptiono Reverse Transcriptiono Translationo cDNAo mRNAo Vesicles/Virionso Nucleus, cytoplasm, cell membraneo Cell receptors

Step 3: Immunology Review

- Terms to know:o Immune systemo Viruso T-cellso Infection

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o Opportunistic InfectionStep 4: What is HIV? (background and history)

- HIV stands for human immunodeficiency virus.- It is transferred by bodily fluids (blood, semen, breast milk)- However, it is NOT transferred by sweat, saliva, and mucous. - HIV is a lentivirus, meaning you can become infected, but you may not show signs for years

or decades. Sometimes, people infected with HIV never have symptoms.- It is believed to have originated in primates in West Africa in the early 1900s. It was

probably first passed to humans who had close interactions with primates, perhaps hunters.- More than 30 million people throughout the world now live with HIV.- Over time, HIV can lead to AIDS – Acquired immune deficiency syndrome. AIDS is a more

severe condition.- HIV and AIDS both weaken your immune system. This makes it easier for you to get other

diseases/illnesses, including certain types of cancer – like Kaposi’s Sarcoma. - People with AIDS often lose weight and/or muscle mass, and are sick very frequently.- A person will not die from HIV or AIDS, rather the illnesses that they acquire due to their

weakened immune system.-

Step 5: Classroom Activity

- Before presenting the lifecycle of HIV, challenge your students to think. Give them the following sheet of paper and ask them to cut out the squares. Working in groups, ask them to arrange the squares into the appropriate order of the HIV lifecycle.

- NOTE: the worksheet is not in order- The correct order is as follows:

1. Infection of host body 2. Virus binds with receptors on T-cell3. Virus enters into cytoplasm of cell4. Reverse Transcription of viral RNA5. cDNA is produced and enters nucleus6. cDNA enters into host DNA7. Transcription and translation of DNA8. Virus is reproduced and cleaved into smaller viral proteins9. The virus leaves the cell in virions/vesicles

- After completion, continue on with the rest of the lecture material (listed below).

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Infection of host body

Integration into host DNA

Budding of viral protein chains

Virus enters into cytoplasm

Virions/Vesicles released from cell

DNA enters into nucleus

Transcription and translation

Binds with receptors on T-cells

Reverse transcription

Infect other cells/other host

bodies

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Step 6: On a molecular level

- HIV attacks T-cells in the body. - The virus combines with receptors on the surface of the cell. - Then viral material is unloaded into the cell, across the membrane- Once inside the cytoplasm, reverse transcription occurs. Viral RNA is used to form cDNA.- This cDNA enters into the cell nucleus, where it combines with the cell’s DNA.- Here, the virus can remain latent (or dormant) for long periods of time.- Once activated, transcription and translation occur. - New virus protein is produced- Protease is an enzyme that cleaves(cuts up) these virus proteins into smaller proteins- They are packaged up and sent off into vesicles called virions- The cycle continues and these virions are off to infect new t-cells!

*** review questions for the class:

1. What type of cells does the HIV virus attack?2. What is reverse transcription?3. What does latent mean?4. What is protease?5. What is a virion?

Take it a step further: Ask students to draw their own diagram/image/cartoon of the HIV cycle.

Check out the flow chart listed below and feel free to use it in the classroom.

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Step 7: Symptoms and Treatments

a. First and foremost, HiV and AIDS have no cure, meaning they cannot be completely treated or irradicated from the body. The main problem in treating HIV is that it can remain latent (dormant) in your cells and your body will not detect it the virus at this time, therefore it will not fight it off.

b. Additionally, there are also no vaccines against HIV/AIDS.c. Now that you know that HIV affects t-cells in the body, you must learn what this means

in the grand scheme of things.d. Everyone needs T-cells to stay alive. They are a crucial part of the immune system.

When HIV infects these cells, they die.e. A normal T-cell range is >500 cells/mm3. You can determine your t-cell count by a simple

blood test.f. A person infected with HIV generally has less than 500 cells/mm3. g. To be diagnosed with AIDS, a person must have a t-cell count that is less than 200

cells/mm3. h. Lowered t-cell counts make it harder for the immune system to fight off illnesses.i. Common symptoms of HIV include:j. Patients with AIDS, and sometimes HIV, often suffer from certain types of cancers and

pneumonia.k. Fortunately, t-cell counts can increase with medication! l. Medication can prevent the amount of cells that are being infected by the active HIV

virus.m. We will discuss 3 main treatment options:

1. NRTI: nucleoside reverse transcription inhibitor – prevents the viral RNA from being reverse transcribed into cDNA. Therefore- nothing enters the nucleus

2. PI: Protease inhibitor – prevents protease (an enzyme) from cleaving the larger viral protein chains into smaller protein chains. Therefore – nothing leaves the cell.

3. HAART Therapy “cocktail”: most commonly a combination of 2 NRTI’s and 1 PI. This is the most common treatment option because it works to inhibit the HIV virus in multiple ways.

**Check out the following diagram to help visualize what these medicines do, and when/where they work.

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Part IV: Activity

Worksheet list:

1. Pathology Lab Results (place a few copies at the front of the classroom)2. Patient Information Worksheet (one copy per group of 4)3. Medicine Data Table (one copy per group of four)4. HIV and Data Analysis Activity (one copy per student)5. Homework Assignment (one copy per student)

Answer Keys:

1. Data Analysis Activity2. Homework Assignment

Instructions:

To set up: Print off copies of all worksheets. Place “Pathology Lab Results” at the front of the classroom. Give lecture on HIV. Ask students to work in groups of 4. Give one copy of both the “Patient Information Worksheet” and the “Medicine Data Table” to each group of 4. In this activity, students will be analyzing HIV+ patient histories, performing t-tests and chi square tests, and prescribing treatment options. After completing the assignment, you can pass out the homework assignment to each student. The next day, after going over the homework, you can ask the discussion questions if you wish

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Pathology Lab Results: place a few copies at front of classroom, simulating lab at doctor’s office

Patient Information: #48392 CJ Blue

Tested for: Amount:Platelets 100,000/mLWhite Blood Cells (WBCs) 5700 cells/µLT-cell count 431 cells/mm3

Red Blood Cells (RBCs) 5.1 mil cells/µLGlucose 98 mg/dLHemoglobin 13 gm/dL

Patient Information: #277948 Naomi Green

Tested for: Amount:T-cell count 130 cells/mm3

Platelets 234,000/mLRed Blood Cells (WBCs) 5.7 mil cells/µLWhite Blood Cells (RBCs) 8,957 cells/µLHemoglobin 17 gm/dLGlucose 130 mg/dL

Patient Information: #920938 Cynthia Orange

Tested for: Amount:Red Blood Cells (RBCs) 6.1 mil cells/µLGlucose 77 mg/dLT-cell count 395 cells/mm3

White Blood Cells (RBCs) 7,723 cells/µLPlatelets 309,000/mLHemoglobin 9 gm/dL

Patient Information: #156309 John Red

Tested for: Amount:Platelets 276,835/mLT-cell count 175 cells/mm3

Hemoglobin 10 gm/dLWhite Blood Cells (RBCs) 4,714 cells/µLRed Blood Cells 6.1 mil cells/µLGlucose 99 mg/dL

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Patient Information Worksheet (one copy per group)

Patient #1 InformationThe patient’s name is John Red. He was born on July 8, 1960 in North Carolina. He is 6’2” and weighs 180 pounds. He had a tonsillectomy (tonsils removed) when he was 8 years old. His grandfather had lung cancer. His dad has heart disease and had a heart attack when he was 60, but survived. His twin brother had a stroke when he was 33. His blood pressure today was 120/80 mm Hg. His heart rate is 75 bpm. He is an accountant who liked to play sports and hike in his free time. He is currently suffering from Kaposi’s Sarcoma, which is an opportunistic infection that comes when someone’s immune system is lowered due to HIV/AIDS. Kaposi’s is a type of cancer that causes legions on the body. Today he has legions in his mouth.

Patient #2 InformationThe patient is CJ Blue. He is 5’7” and weighs 198 pounds. He was born on December 29, 1989 in New York. His dad suffers from anxiety. His mom has arthritis. His grandfather has heart disease. He previously had an appendectomy (appendix removed). He takes Flonase for asthma. His blood pressure today was 120/80 mm Hg. His heart rate is 100 bpm. He is a graduate student at a university, who enjoys video games and web design. Today he has a flu-like illness. He had been taking Nyquil for a few days because he thought he had the flu. However, his HIV test just came back positive, so he knows it is not the flu.

Patient #3 Information The patient’s name is Naomi Green. She was born on January 1, 1981 in California. She is 5’3” and weighs 90 pounds. Her grandmother had colon cancer. Her dad and sister have diabetes. Her mom has heart disease. Her blood pressure today was 140/90 mm Hg. Her heart rate is 100 bpm. She is a stay at home mom, who enjoys planning philanthropic events and school fundraising. She is suffering from wasting syndrome, which means she is losing weight and muscle mass. Wasting syndrome is common with HIV and AIDS.

Patient # 4 InformationThe patient is Cynthia Orange. She is 5’10” and weighs 180 pounds. She was born on September 13, 1981 in Texas. Her grandmother had breast cancer. Her dad has type II diabetes. Her younger sister had leukemia but survived. She previously had surgery for a torn ACL while playing basketball. Her blood pressure today was 140/100 mm Hg. Her heart rate is 68 bpm. She is a scientist, who enjoys bird watching in her free time. Today she is suffering from joint pain and swollen lymph nodes. She had been taking ibuprofen because she did not know she had HIV until her test came back positive today.

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Medicine Data Tables: (one copy per group)

Medicine A: NRTI (nucleoside reverse transcriptase inhibitor)

Gender D.O.B. T-cell count before treatment (cells/mm3)

Follow-up T-cell count after 3 months (cells/mm3)

Patient 1 M 1989 302 306Patient 2 F 1957 417 417Patient 3 F 1978 212 213

Medicine B: PI (protease inhibitor)

Gender D.O.B. T-Cell count before treatment (cells/mm3)

Follow-up T-cell count after 3 months (cells/mm3)

Patient 1 F 1963 436 440Patient 2 M 1993 315 315Patient 3 M 1984 281 282

Medicine C: HAART therapy (2 NRTIs and 1 PI)

Gender D.O.B. T-cell count before treatment (cells/mm3)

Follow-up T-cell count after 3 months (cells/mm3)

Patient 1 M 1999 404 409Patient 2 M 1977 213 219Patient 3 F 1950 340 347

Medicine D: Antibiotic

Gender D.O.B. Before treatment (cells/mm3)

Follow-up T-cell count after 3 months (cells/mm3)

Patient 1 M 1998 206 209Patient 2 F 1968 300 300Patient 3 F 1940 447 447

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Name: __________________________

Date: ___________________________

HIV and Data Analysis Activity

Part I: Patient Medical Record

1. Congratulations, you are now doctors! Working in groups of 4, you must analyze your patient’s histories and diagnose them with the appropriate conditions. Additionally, you must also determine their current symptoms. Use the following charts to gather all the necessary information.

2. Everyone in the group is responsible for filling in the medical record for 1 patient. Do not duplicate patients so that they all get the help they need.

3. Review: HIV infects _________a. Heart cellsb. T-cellsc. Red Blood Cells

4. What are potential consequences of having a weakened immune system?

Patient Medical Record

PATIENT INFORMATION

First M.I. LastName:

Date of Birth Month Day Year

GENERAL INFORMATION

Temperature Normal: 98.6 °FWeight Normal: Varies

Heart Rate Normal: 60-100 bpmBlood Pressure Normal : 120/80 mm Hg

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FAMILY HISTORY

PREVIOUS SURGERIES

CURRENT MEDICATIONS

CURRENT SYMPTOMS/OPPORTUNISTIC INFECTIONS

BLOOD TEST RESULTS (go to Pathology Lab to obtain results)

Date: / / Normal Range Normal? Y/NGlucose 70 - 110 mg/dLHemoglobin 12 - 18 gm/dLWhite Blood Cells (WBCs) 4,300 - 10,800 cells/µLRed Blood Cells (RBCs) 4.2 - 6.9 million cells/µLPlatelets 150,000 - 350,000/mLT-cell count 500-1000 cells/mm3

CURRENT CLASSIFICATION (T-cells/mm3)

Healthy >500 HIV+ 500-200 AIDS <200

Review: What are a few differences between HIV and AIDS?

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Part II: Prescribing Medication

As you can see, patients diagnosed with HIV and AIDS have a broad range of symptoms. Now it is time to prescribe a treatment option.

Dr. ___________________

Prescription Form

Medicine A: NRTI (nucleoside reverse transcriptase inhibitor) – this medicine inhibits reverse

transcription, so that viral RNA cannot create cDNA within the host cell.

Medicine B: PI (protease inhibitor) – This medicine prevents an enzyme (called protease) from

cleaving long HIV protein strands into smaller proteins, which are sent off in vesicles

to infect other cells.

Medicine C: HAART therapy “cocktail” (2 NRTIS and 1 PI) – a combination therapy.

Medicine D: Antibiotic – kills bacterial infections in the body.

1. Based on the descriptions of the medicines, which do you think will be most effective? Why?

2. Clinical trials were run for each of the 4 medicines listed above. The results are listed in the “Medicine Data Tables” which have been provided to your group.

3. Divide up the 4 medicines among each of the 4 group members.

4. In order to determine which medicine is most effective in treating HIV/AIDS, a data analysis test must be performed. In this case, we will use a t-test. Why is a t-test the appropriate test?

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5. Perform the t-test for your assigned medicine. Medicine: __________________________***Use a p-value of 0.05.***

H0 (null hypothesis):

(In this example, the Specified mean difference (µ) is 0. )

Ha (alternative hypothesis):

Total difference (add up differences for all patients between ‘ before’ and ‘after’ treatment): ________

Mean difference: ________ (total difference/number of patients)

Standard Deviation:

Standard Error:

T – value = (mean difference) – (specified mean difference) Standard Error

T –value =

D F= n-1 = ______

Now find the α-value. α = ______________

How does α compare to the p-value of 0.05? _________________________ (hint: greater or less than)

Share the results with your group.

Medicine A- t= ______ α=______ Medicine B - t= ______ α=______ Medicine C - t=______ α=______ Medicine D- t=_______ α=______

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6. Which medicine has statistically significant results (meaning it was an effective treatment)?

7. Did you predict correctly? If not, why do you think your medicine was not as effective?

Part III: HIV treatments throughout the world

Studies done in the United States show that HAART therapy is effective in the treatment of HIV. However, a group of researchers is trying to determine if HAART therapy will be effective in HIV+ patients in other countries. To test this, researchers collected the average t-cell counts after 3 months of HAART therapy for men and women in Scienceville, USA. These are the results they found:

Location Gender Avg T-cell count after 3 months of HAART Therapy (cells/mm3)

Scienceville, USA Male 440Scienceville, USA Female 451

Next, the researchers went to Medicineville, World. They tested the HAART therapy in 14 patients.

Results:

Location Gender Avg T-cell count after 3 months of HAART Therapy(cells/mm3)

Medicineville, World Female 490Medicineville, World Female 501Medicineville, World Female 477Medicineville, World Male 460Medicineville, World Female 470Medicineville, World Male 455Medicineville, World Male 478Medicineville, World Female 471Medicineville, World Male 457Medicineville, World Male 463Medicineville, World Male 460Medicineville, World Female 480Medicineville, World Male 468Medicineville, World Female 471

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1. A Chi Square Goodness of Fit test should be used to determine if the results observed in Medicineville, World are statistically similar to the results obtained in Scienceville, USA (expected results). Why would you use a Chi Square test and not a t-test?

2. Perform the Chi Square test. (use p = 0.05)

X2=∑ (observed−expected )2

expected=¿¿

H0 (null hypothesis)=

Ha (alternative hypothesis)=

Fill in the chart:

Gender Observed Expected (O-E) (O-E)2 ((O-E)2)/E)

X2 =

DF = n-1 = ________ α = __________

How does the α-value compare to the p-value?

3. Was there a statistically significant difference between the two populations?

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Name: ______________________

Homework Assignment: HIV Statistics

The goal of this homework assignment is to learn more about HIV prevalence in the US and the World.

Part I: HIV by Age in the US

Source: http://www.cdc.gov/hiv/risk/age/youth/index.html

Using this graph, answer the following questions.

1. What is the mean age of diagnosis?

2. What is the median age of diagnosis?

3. What is the mode age of diagnosis?

4. Describe the distribution of the graph (ex: skewed, bimodal, etc).

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Part II: HIV throughout the US

State/Dependent Area Number of Diagnoses of HIV Infection, 2011California 5,973Florida 5,403Texas 5,065New York 4,960Georgia 2,522Illinois 2,142Maryland 1,783North Carolina 1,672New Jersey 1,567Pennsylvania 1,545

Source: http://www.cdc.gov/hiv/statistics/basics/

5. Use the following information to construct an appropriate graph that accurately displays the data.

6. Explain why you chose this type of graph.

7. Do you notice any trends? (For ex: geographic regions with high rates of HIV infection?)

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Part III: HIV throughout the world

Geographical region

Number of children (0-14 years) receiving antiretroviral therapy

Estimated number of children needing antiretroviral therapy

Percentage of children receiving coverage?

Sub-Saharan Africa 495 700 1 830 000

Eastern and southern Africa 426 800 1 310 000

West and central Africa 68 900 520 000

Latin America and the Caribbean

17 000 39 000

Latin America 13 500 29 000

The Caribbean 3 500 10 200

East, South and South-East Asia 44 400 111 000

Europe and Central Asia 8 200 7 800

North Africa and the Middle East 900 6 500

Total 566 000 1 990 000

Source: http://www.who.int/hiv/topics/paediatric/data/en/index1.html

8. Determine the percentage of children receiving treatment in each area of the world and complete the chart.

9. What are reasons you can think of for why children in some world regions do not receive the treatment they need?

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Name: ANSWER KEY

HIV and Data Analysis Activity

Part I: Patient Medical Record

5. Congratulations, you are now doctors! Working in groups of 4, you must analyze your patient’s histories and diagnose them with the appropriate conditions. Additionally, you must also determine their current symptoms. Use the following charts to gather all the necessary information.

6. Everyone in the group is responsible for filling in the medical record for 1 patient. Do not duplicate patients so that they all get the help they need.

7. Review: HIV infects _________d. Heart cellse. T-cellsf. Red Blood Cells

8. What are potential consequences of having a weakened immune system?

Expect a variety of answers. Should be something along the lines of: easier to get other illnesses/disease/etc.

Patient Medical Record

PATIENT INFORMATION – this information will vary for each member of the group

First M.I. LastName:

Date of Birth Month Day Year

GENERAL INFORMATION - this information will vary for each member of the group

Temperature Normal: 98.6 °FWeight Normal: Varies

Heart Rate Normal: 60-100 bpmBlood Pressure Normal : 120/80 mm Hg

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FAMILY HISTORY

this information will vary for each member of the group

PREVIOUS SURGERIES-

this information will vary for each member of the group

CURRENT MEDICATIONS

this information will vary for each member of the group

CURRENT SYMPTOMS/OPPORTUNISTIC INFECTIONS

this information will vary for each member of the group

BLOOD TEST RESULTS (go to Pathology Lab to obtain results) - this information will vary

Date: / / Normal Range Normal? Y/NGlucose 70 - 110 mg/dLHemoglobin 12 - 18 gm/dLWhite Blood Cells (WBCs) 4,300 - 10,800 cells/µLRed Blood Cells (RBCs) 4.2 - 6.9 million cells/µLPlatelets 150,000 - 350,000/mLT-cell count 500-1000 cells/mm3

CURRENT CLASSIFICATION (T-cells/mm3) - this information will vary for each member of the group

Healthy >500 HIV+ 500-200 AIDS <200

*Naomi Green and John Red both have AIDS

Review: What are a few differences between HIV and AIDS?

A variety of answers are acceptable including:

- Difference in t-cell counts- Progression of the disease- More opportunistic infections with AIDS- Different acronyms

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Part II: Prescribing Medication

As you can see, patients diagnosed with HIV and AIDS have a broad range of symptoms. Now it is time to prescribe a treatment option.

Dr. ___________________

Prescription Form

Medicine A: NRTI (nucleoside reverse transcriptase inhibitor) – this medicine inhibits reverse

transcription, so that viral RNA cannot create cDNA within the host cell.

Medicine B: PI (protease inhibitor) – This medicine prevents an enzyme (called protease) from

cleaving long HIV protein strands into smaller proteins, which are sent off in vesicles

to infect other cells.

Medicine C: HAART therapy “cocktail” (2 NRTIS and 1 PI) – a combination therapy.

Medicine D: Antibiotic – kills bacterial infections in the body.

8. Based on the descriptions of the medicines, which do you think will be most effective? Why?

Expect different answers. Most likely answer is Medicine C - HAART

9. Clinical trials were run for each of the 4 medicines listed above. The results are listed in the “Medicine Data Tables” which have been provided to your group.

10. Divide up the 4 medicines among each of the 4 group members.

11. In order to determine which medicine is most effective in treating HIV/AIDS, a data analysis test must be performed. In this case, we will use a t-test. Why is a t-test the appropriate test?

Comparing paired data with before and after

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12. Perform the t-test for your assigned medicine. Medicine:__A and B______________

H0 (null hypothesis): There is no difference between the before and after OR µ is 0.

(In this example, the Specified mean difference (µ) is 0.

Ha (alternative hypothesis):

There is a difference between the before and after OR µ is not 0.

Total difference (add up differences for all patients between ‘ before’ and ‘after’ treatment): __5____

Mean difference: __1.67______ (total difference/number of patients)

Standard Deviation:

√( (4−1.67 )2+(0−1.67 )2+(1−1.67 )2 )(3−1)

=2.08

Standard Error:

2.08√3

=1.20

T – value = (mean difference) – (specified mean difference) Standard Error

T –value = (1.67-0)/1.20 = 1.39

D F= n-1 = __2____

Now find the α-value. α>0.1

How does α compare to the p-value of 0.05? α > 0.1 therefore greater than the p-value

13. Share the results with your group.Medicine A- t= __1.39_____ α>_0.1_____Medicine B - t= __1.39_____ α>_0.1_____Medicine C - t= __10.4____ α<__0.05___

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Medicine D- t= __1.0_____ α>__0.1____1. Perform the t-test for your assigned medicine. Medicine:__C ______________

H0 (null hypothesis): There is no difference between the before and after OR µ is 0.

(In this example, the Specified mean difference (µ) is 0.

Ha (alternative hypothesis):

There is a difference between the before and after OR µ is not 0.

Total difference (add up differences for all patients between ‘ before’ and ‘after’ treatment): __18____

Mean difference: __6______ (total difference/number of patients)

Standard Deviation:

√( (5−6 )2+ (6−6 )2+ (7−6 )2 )(3−1)

=1

Standard Error:

1√3

=.578

T – value = (mean difference) – (specified mean difference) Standard Error

T –value = (6-0)/.578 = 10.4

D F= n-1 = __2____

Now find the α-value. α<0.005

How does α compare to the p-value of 0.05? α < .05 therefore less than the p-value

2. Share the results with your group.Medicine A- t= __1.39_____ α>_0.1_____Medicine B - t= __1.39_____ α>_0.1_____

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Medicine C - t= __10.4____ α<__0.05___Medicine D- t= __1.0_____ α>__0.1____

1. Perform the t-test for your assigned medicine. Medicine:__D______________

H0 (null hypothesis): There is no difference between the before and after OR µ is 0.

(In this example, the Specified mean difference (µ) is 0.

Ha (alternative hypothesis):

There is a difference between the before and after OR µ is not 0.

Total difference (add up differences for all patients between ‘ before’ and ‘after’ treatment): __3____

Mean difference: __1______ (total difference/number of patients)

Standard Deviation:

√( (3−1 )2+ (0−1 )2+ (0−1 )2 )(3−1)

=1.73

Standard Error:

1.73√3

=1

T – value = (mean difference) – (specified mean difference) Standard Error

T –value = (1-0)/1 = 1

D F= n-1 = __2____

Now find the α-value. α>0.1

How does α compare to the p-value of 0.05? α > 0.1 therefore greater than the p-value

2. Share the results with your group.Medicine A- t= __1.39_____ α>_0.1_____

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Medicine B - t= __1.39_____ α>_0.1_____Medicine C - t= __10.4____ α<__0.05___Medicine D- t= __1.0_____ α>__0.1____

3. Which medicine has statistically significant results (meaning it was an effective treatment)?

Medicine C- HAART

4. Did you predict correctly? If not, why do you think your medicine was not as effective?

Answers will vary by student. Expect all kinds of hypotheses.

Part III: HIV treatments throughout the world

Studies done in the United States show that HAART therapy is effective in the treatment of HIV. However, a group of researchers is trying to determine if HAART therapy will be effective in HIV+ patients in other countries. To test this, researchers collected the average t-cell counts after 3 months of HAART therapy for men and women in Scienceville, USA. These are the results they found:

Location Gender Avg T-cell count after 3 months of HAART Therapy (cells/mm3)

Scienceville, USA Male 440Scienceville, USA Female 451

Next, the researchers went to Medicineville, World. They tested the HAART therapy in 15 patients.

Results:

Location Gender Avg T-cell count after 3 months of HAART Therapy(cells/mm3)

Medicineville, World Female 490Medicineville, World Female 501Medicineville, World Female 477Medicineville, World Male 460Medicineville, World Female 470Medicineville, World Male 455Medicineville, World Male 478Medicineville, World Female 471Medicineville, World Male 457Medicineville, World Male 463Medicineville, World Male 460

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Medicineville, World Female 480Medicineville, World Male 468Medicineville, World Female 471

4. A Chi Square Goodness of Fit test should be used to determine if the results observed in Medicineville, World are statistically similar to the results obtained in Scienceville, USA (expected results). Why would you use a Chi Square test and not a t-test?

Because you are comparing observed and expected.

5. Perform that test.

X2=∑ (observed−expected )2

expected=¿¿

H0 (null hypothesis)= there is no difference in male and female populations

Ha (alternative hypothesis)= at least one gender is different

Fill in the chart:

Gender Observed Expected (O-E) (O-E)2 ((O-E)2)/E)

Male 463 440 23 529 1.20

Female 480 451 29 841 1.86

X2 =

DF = n-1 = __2______ α = ___is between 0.1 and 0.15_______

How does the α-value compare to the p-value?

The α-value is greater than the p-value.

6. Was there a statistically significant difference between the two populations? If so, what reasons can you think of for why HAART therapy affected the patients in Medicineville, World differently than the patients in Scienceville, USA? If not, what does this mean?

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3.06

No, there is no significant difference. Therefore HAART is effective in all populations.

Name: ______________________

Homework Assignment: HIV Statistics

The goal of this homework assignment is to learn more about HIV prevalence in the US and the World.

Part I: HIV by Age in the US

Source: http://www.cdc.gov/hiv/risk/age/youth/index.html

Using this graph, answer the following questions.

10. What is the mean age range of diagnosis? Ages 30-34

11. What is the median age range of diagnosis? Ages 35-39

12. What is the mode age range of diagnosis? Ages 20-24

13. Describe the distribution of the graph (ex: skewed, bimodal, etc).

Could say it is bimodal, skewed left, expect different results

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Part II: HIV throughout the US

State/Dependent Area Number of Diagnoses of HIV Infection, 2011California 5,973Florida 5,403Texas 5,065New York 4,960Georgia 2,522Illinois 2,142Maryland 1,783North Carolina 1,672New Jersey 1,567Pennsylvania 1,545

Source: http://www.cdc.gov/hiv/statistics/basics/

14. Use the following information to construct an appropriate graph that accurately displays the data.

*could be a variety of graphs, most likely is bar graph

15. Explain why you chose this type of graph.

Answers will vary by student

16. Do you notice any trends? (For ex: geographic regions with high rates of HIV infection? What about the populations of these states?)

The north and south (depending on what student classifies as geographic region) do tend to see higher rates of HIV. Could mention states with higher populations have higher rates, etc.

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Part III: HIV throughout the world

Geographical region

Number of children (0-14 years) receiving antiretroviral therapy

Estimated number of children needing antiretroviral therapy

Percentage of children receiving coverage?

Sub-Saharan Africa 495 700 1 830 000 27%

Eastern and southern Africa 426 800 1 310 000 33%

West and central Africa 68 900 520 000 13%

Latin America and the Caribbean

17 000 39 000 43%

Latin America 13 500 29 000 46%

The Caribbean 3 500 10 200 34%

East, South and South-East Asia 44 400 111 000 40%

Europe and Central Asia 8 200 7 800 >95%

North Africa and the Middle East 900 6 500 14%

Total 566 000 1 990 000 28%

Source: http://www.who.int/hiv/topics/paediatric/data/en/index1.html

17. Determine the percentage of children receiving treatment in each area of the world and complete the chart.

18. What are reasons you can think of for why children in some world regions do not receive the treatment they need?

Expect a wide range of answers. Sample reasons include: cannot afford treatment, no access to doctors, live in remote areas with no access to treatment, do not know treatment exists, do not want treatment, are too young to seek treatment on their own, etc.

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Discussion Questions

1. Lots of treatment options have terrible side effects. Is it okay for doctors to prescribe medicines that will make patients suffer, if the end result is good?

2. Can HIV be transferred by hugs? Sharing utensils? Standing next to an infected person? Therefore, should we treat infected people differently?

3. Can you think of any celebrities with HIV or AIDS?

4. Think of common stereotypes of people with HIV/AIDS. Are they all true?

5. People who take medicines for a long period of time often develop drug resistance. What does this mean? What can be done to avoid this? What can patients/doctors do if this occurs?

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