The document analyzes current trends in HIV and AIDS infections in the United States based on data from the Centers for Disease Control and Prevention. It finds that while new diagnoses of both HIV and AIDS are declining overall, certain groups such as African Americans and Hispanics still have significantly higher rates of infection. By organizing the raw data into spreadsheets and graphs, it identifies trends like most HIV diagnoses occurring in individuals ages 20-24 and most AIDS diagnoses in those ages 35-44.

1. What are current trends in HIV & AIDS infections in the U.S.? Melanie Smith EDCI 5377 Spring 2010

2. This is an important issue not only in the world, but also in our own country. I think, because there so many commercials and celebrities pushing for more research for cures, many people (especially the youth) can become desensitized to the epidemic. What are the current trends in HIV and AIDS infections in the United States? Visit Bulgaria. http://visitbulgaria.info/california-cover-cost-hiv-screening-0 Viewed on February 27, 2011.

3. Having students (high school and perhaps middle school) mine the web for raw data about HIV and AIDS infections can make the plight of so many more real to them. What are the current trends in HIV and AIDS infections in the United States? Graphics Hunt. http://www.graphicshunt.com/tags/1/hiv+prevention.htm Viewed on February 27, 2011.

5. The Centers for Disease Control and Prevention (CDC) provides an enormous amount of information on their website. Specifically for the HIV and AIDS portion of their website, there is a host of specific topics: basic information, specifics for different gender and ethnic groups, etc. Centers for Disease Control and Prevention. http://www.cdc.gov/hiv/default.htm. Viewed February 27, 2011.

6. Data The CDC has all of their accumulated information nicely organized. Data regarding the diagnoses and infection of HIV and AIDS in the United States population can be found under “Reports.” All of the information I used can be found in the many pages of an all encompassing report from 2009 (the most current published). Centers for Disease Control and Prevention. http://www.cdc.gov/hiv/surveillance/resources/reports/2009report/index.htm. Viewed on February 27, 2011.

7. I took the data from the CDC’s report and organized it in an Excel spread sheet. This collection of data represents the ages at which HIV was diagnosed from 2006 to 2009. I then created various graphs that presented the information in smaller, easier to manage sections. Centers for Disease Control and Prevention. http://www.cdc.gov/hiv/surveillance/resources/reports/2009report/pdf/table1a.pdf. Viewed on February 27, 2011.

8. Age of HIV Diagnosis On the previous slide I provided the data for the age of diagnosis with HIV. I organized this data by creating graphs for each year in the study.

9. Age of HIV Diagnosis For each year’s data, I created a subtotal line that utilized one of Excel’s many mathematics features: Sum. Instead of adding each column outside of the application (with a calculator), set up the Sum feature (indicating which cells to add together) and the program automatically does it for you.

10. Age of HIV Diagnosis As one can see in the pie charts, the proportions of each age group stayed the same even though the actual numbers were different. This isn’t obvious (at least not as obvious) when looking at the raw data.

11. Age of HIV Diagnosis Presenting the raw data in a bar graph format allows one to see how each year’s data relates to the other years’ data. As one can see on the graph, with the exception of the 20-24 year old age group, the number of people being diagnosed with HIV in each age group has dropped over the span from 2006 to 2009.

12. Age of HIV Diagnosis With each step – raw data, spread sheet, graphs – the data appears much more understandable, easier to analyze, and just “prettier.” Centers for Disease Control and Prevention. http://www.cdc.gov/hiv/surveillance/resources/reports/2009report/pdf/table1a.pdf. Viewed on February 27, 2011.

13. Race/Ethnicity of HIV Diagnosis Using the raw data, the next logical break-down was to organize the data by ethnic background. After analyzing the numbers, it is obvious there is an alarming difference between three racial groups (African American, Hispanic, and white) and the rest of the population.

14. Race/Ethnicity of HIV Diagnosis Seeing the differences in the racial groups, I asked why there was such a difference. I’m sure students would do the same when presented with the same data. What is causing the numbers to be so much higher for blacks, Hispanics, and whites? What are these groups doing that the others are not?

15. Race/Ethnicity of HIV Diagnosis Once again, I broke down the data into smaller pieces. Analyzing these charts, the numbers reported stayed fairly proportionate as they changed.

16. I think it is important to note that while pie charts are an important tool, they need to be used appropriately. Pie charts are great for visually comparing amounts for one specified unit (a year in this case). When looking at the pie charts for each year, it is impossible to see that the total numbers are dropping.

17. Transmission of HIV - Males After looking at the Racial/Ethnicity breakdown, I organized the data based on who was infected and how the HIV infection was transmitted. Similar to my processing of the other data, I created a subtotal for each year using the Sum function within Excel.

18. Transmission of HIV - Males Using the pie chart to visually represent the data, it is extremely obvious to see how the majority of men transmit HIV. This can lead to increasing awareness movements within particular communities to ensure that this number continues to decrease.

19. Transmission of HIV - Males With the exception of “Other,” the trend within male transmission is a decrease in the occurrence an diagnosis of HIV. I think the next step in acquiring raw data would be to break down the “Other” group. How can the medical community increase the ways in which we can protect those males who seem to acquire HIV in more of a “medical” situation (hemophiliacs, blood transfusions, and perinatal [in utero])?

20. Transmission of HIV - Females As with the other data sets, I entered the raw data into Excel in order to organize it. I created a subtotal line, as I did with the other pieces of data, in order to see the overall change from year to year. The general decreasing trend holds true with this group of society.

21. Transmission of HIV - Females Similar to previous data sets, placing the raw data into an Excel spreadsheet allows the user and audience to understand and analyze the data in an easier manner and in a smaller amount of time.

22. Transmission of HIV - Child Taking away the natural emotional response, I think this set of data is interesting. I think that unless a student (child/teenager) has a personal experience with HIV, he or she generally thinks of the infection as an adult disease. AIDS & HIV. http://aids.immunodefence.com/2006/11/. Viewed on February 27, 2011.

23. The previous slides presented data involving the diagnosis of HIV – ages of those when initially diagnosed with the infection, their gender, race or ethnicity, and the transmission of the disease. The following slides will be about the next stage in the disease: AIDS. What are the current trends in HIV and AIDS infections in the United States? Science Roll. http://scienceroll.com/2010/06/28/aidshiv-in-social-media-2/. Viewed on February 27, 2011.

24. Age of AIDS Diagnosis As was done with the data about an HIV diagnosis, I started with raw data from the CDC and started “playing” with it. I then entered the data into a spreadsheet on Excel. Once this was done, I was able to create graphs in order to more easily analyze the data. Centers for Disease Control and Prevention. http://www.cdc.gov/hiv/surveillance/resources/reports/2009report/pdf/table2a.pdf. Viewed on February 27, 2011.

25. Age of AIDS Diagnosis Using a bar graph, it is much more obvious to see where the majority of the initial AIDS diagnosis are (age brackets 35-39, 40-44, and 45-49). As with the previous slides, it is also obvious that the decreasing trend holds true.

26. With the previous slide’s data, I think it is an appropriate time to compare two sets of data: initial diagnosis of HIV and that of AIDS. AIDS Diagnosis HIV Diagnosis In analyzing the graphs together, I came up with a few questions: Shouldn’t the curve of the overall graph be similar on both? Why is there a difference in the curves? Why is the AIDS graph a “true” bell curve while the HIV graph is not?

27. Age of AIDS Diagnosis After entering the data into a spreadsheet, generating a bar graph, and observing some apparent trends, I created pie charts in order to analyze any trends in the data from year to year. As was seen in previous pie chart visuals of the data, while the numbers change from year to year, the proportions between the age groups remains consistent from year to year.

28. Race/Ethnicity of AIDS Diagnosis Similar to the breakdown of Ethnicity with a diagnosis of HIV, the breakdown with AIDS is disproportionately weighted. As every analysis brings answers, it raises many more questions. Why is AIDS more prevalent in people of African American ethnicity? Why are there still only a few races that seem to be “hit hard”? Why are some of the races not “hit” as hard?

29. Race/Ethnicity of AIDS Diagnosis I think it is appropriate to compare the ethnicity data of an HIV Diagnosis to that of an AIDS Diagnosis. HIV Diagnosis When looking at the actual numbers, why is the diagnosis of HIV more prevalent than that of AIDS? What is preventing certain HIV cases from progressing to AIDS? Proportionately, the data is consistent between an HIV Diagnosis and an AIDS Diagnosis. AIDS Diagnosis

30. Race/Ethnicity of AIDS Diagnosis As with all of the previous data, I started with the raw material from the CDC, organized it into a spreadsheet, and “beautified” it into the easily palatable form of a graph. Centers for Disease Control and Prevention. http://www.cdc.gov/hiv/surveillance/resources/reports/2009report/pdf/table2a.pdf. Viewed on February 27, 2011.

31. Transmission of AIDS - Males As was done with previous data, to create the subtotal line (in order to analyze an overall change from year to year in AIDS transmission in males) I utilized Excel’s Sum function. The Sum function allows you to enter data and have the sum of designated boxes added together without needing an external calculator.

32. Transmission of AIDS - Females Between the two visual sets of the same data – a spreadsheet and a bar graph – the graph is easier to get a quick feel for the data, while the spreadsheet gives specific numbers more easily (quicker). Analyzing a data set is much “easier” to accomplish when given different ways of viewing the data. Seeing just one of these visuals is fine, but fully digesting the data won’t happen until both the numbers version and the picture version of the data are seen.

33. Transmission of AIDS - Child Transmission of HIV After analyzing these two sets of data, some natural questions arise. While both sets of data (transmission of HIV versus AIDS in children) are much lower than the other data in the study, why is the transmission of AIDS so much lower? How can the difference be used to decrease the HIV transmission numbers? Dr. Talented. http://www.drtalented.com/children-aids-and-hiv/. Viewed on February 27, 2011.

34. Diagnosis of AIDS in the U.S. – By Region I think this set of data benefits from having an actual picture along with the spreadsheet and graph forms. The map helps one visualize the breakdown by region better than mere words can do. Power of Peace. http://www.powerofpeace.com/node/4181. Viewed on February 27, 2011.

35. Concluding Thoughts What are the current trends in HIV and AIDS infections in the United States? After looking at and analyzing the data (using both the spreadsheets and graphs), the general trend is that the diagnoses (new occurrence) of both HIV and AIDS is on a slow decline. While that question is now answered, many more now arise. Why are certain groups still so high? Why is there such a difference between certain groups? Tapestry Health. http://teens.tapestryhealth.org/index.php/resources/i%E2%80%99m-a-teenager-what-do-i-need-to-know-about-hivaids-law-in-ma/. Viewed on February 27, 2011.

36. References AIDS & HIV. http://aids.immunodefence.com/2006/11/. Viewed on February 27, 2011. Centers for Disease Control and Prevention. http://www.cdc.gov/hiv/default.htm. Viewed February 27, 2011. Dr. Talented. http://www.drtalented.com/children-aids-and-hiv/. Viewed on February 27, 2011. Graphics Hunt. http://www.graphicshunt.com/tags/1/hiv+prevention.htm Viewed on February 27, 2011.

37. References Power of Peace. http://www.powerofpeace.com/node/4181. Viewed on February 27, 2011. Science Roll. http://scienceroll.com/2010/06/28/aidshiv-in-social-media-2/. Viewed on February 27, 2011. Tapestry Health. http://teens.tapestryhealth.org/index.php/resources/i%E2%80%99m-a-teenager-what-do-i-need-to-know-about-hivaids-law-in-ma/. Viewed on February 27, 2011. Visit Bulgaria. http://visitbulgaria.info/california-cover-cost-hiv-screening-0 Viewed on February 27, 2011.