HIV/AIDS in Special Population Groups in Texas
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HIV/AIDS in Special Population Groups in Texas

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  • The MPOWER Package
  • We are going to begin today with an overview of the impact of HIV on women. Then we will look at who’s infected, by exploring the demographic makeup of the female HIV population in Texas. Next we will examine the ways that women get HIV and testing behaviors in women. Then, we will discuss the population of HIV women who are having children and finally we will look at future steps in HIV research
  • Women represent a unique group that requires specific focus and attention. As of 2006, women accounted for over a quarter of adult and adolescent HIV cases in the US. In addition, HIV was the 5 th leading cause of death in women, aged 35 to 44 and the 6 th leading cause of death in women 25-34. HIV is also in the top ten causes of death for women of all age groups between 20-54. Finally, women are biologically more likely to be infected with HIV during sex.
  • In Texas, there are over 13,000 women in Texas living with HIV, which means that 11 women per 10,000 are HIV positive. Women represent 22% of living cases. Approximately 980 new female HIV cases diagnosed were 2008.
  • Historically, males have comprised the majority of HIV case, and while this still remains true, women are representing an increasing larger proportion of cases. This chart shows the proportion of HIV/AIDS cases diagnosed each year. As you can see, since the beginning of the epidemic, the number of women diagnosed each year has increased dramatically since the beginning of the epidemic. In 1984 at the beginning of the epidemic, women represented just 3% of the diagnosed cases. The number of cases diagnosed each year increased steadily until 2000. Since 2000, the number of cases diagnosed each year has remained relatively steady. Thus, it is important for us to understand who is at the highest risk by exploring demographic and risk characteristics in conjunction with analyzing testing behavior and length of infection on diagnosis.
  • We will begin by using HIV/AIDS Surveillance data from the enhanced HIV/AIDS Reporting System, also called eHARS, to look at the demographic makeup of women with HIV in Texas. This chart shows the racial distribution of cases diagnosed between 2000 and 2008. One if the most striking factors here is the disproportionate impact of HIV in black women, comprising 60% of the population. In 2008, the rate of new diagnoses in black women was 8 times higher than that of hispanic women and 14 times higher than the rate in white women. The national statistics are similar, with black women comprising about 65% of the female HIV population in the US. In addition, on a nation scale for the most recent reporting year, HIV was the leading cause of death for black women, aged 25-34.
  • In addition, the proportion of female HIV cases who are black is much higher than the proportion of male cases who are black with black males comprising 35% of the male HIV population.
  • Next we will look at the age at which women were diagnosis. This chart shows that women under 39 make up close to 70% of the HIV infected female population. This is similar to the national trends, with the largest number of HIV infections in the 15-39 year old age group.
  • Compared to males, a greater proportion of women are diagnosed at a younger age. This chart shows that women diagnosed between 13-19 account for a much greater proportion of cases than in older age groups, comprising 40% of the diagnosed cases. The second largest age group are women between 20 and 29.
  • This chart shows the breakdown of women with HIV by age and race. There are several interesting facts that I would like to point out on this chart. First, for all races other than white, a larger proportion of women are between 13 and 29 at diagnosis, comprising between 35 and 41% of the population for each racial group. White women show marked differences in age distributions. In contrast to other races, 37% of the white female HIV population were diagnosed between the ages of 40 and 49.
  • Next we will discuss primary modes of transmission in women, by looking at HIV/AIDS Surveillance data from eHARS. Potential risk factor information is capture for as many cases as possible. A hierarchical algorithm is applied, which calculates the risk factor that was the primary mode of transmission. For each person, only one risk can be specified as the primary mode of transmission. Risk factors for females include, intravenous drug use, heterosexual sex with an intervenous drug user, a bisexual male, a male with another, less common risk factor, or a male with a documented HIV infection but an undocumented risk, and other less common risk factors, such as recipeit of tranfusion, transplant and receipt of clotting factor.
  • There is one important data limitation to note when analyzing risk factors. To be categorized in the heterosexual risk category, women must have a partner with either a documented infection or another known high risk factor, such as injection drug use. If a female cases indicates that she had heterosexual sex with male but does not know whether the partner fell into one of the high risk categories, her risk would be categorized as unknown. Thus, the risk for these cases must be imputed using risk and demographic characteristics. For cases reported in 2008, 39% of female cases required risk. 31% of all of the Female cases reported in 2008 answered yes to sex with male, but could not be categorized into the heterosexual risk category
  • This chart shows the distribution of risk among women with HIV in Texas, using imputed risk information for cases that were missing risk. As you can see, heterosexual contact is the most common risk category for women with Injection drug use is the second most common risk. The other risk factor category includes receipt of transfusions, transplants, or clotting factor.
  • Next we will look at how risk is distributed by race. As you can see, the Hispanic female population has the largest proportion of heterosexual contact as the primary mode of exposure, comprising 83% of female population. In contrast, non-Hispanic white women have a much higher proportion of injection drug use as the primary mode of exposure.
  • Next we will look at how risk is distributed by age group. From this chart, you can see that the 40-49 year old population group has a higher proportion of injection drug use as the primary mode of exposure, while the 13-29 age group has a higher proportion of heterosexual sex.
  • Next we are going to talk about testing behaviors in women. The cues for testing are different in males than in females. Thus it’s important to look at testing behaviors to determine how frequently women are testing. HIV/AIDS surveillance data from eHARS shows that 31% of cases were diagnosed with AIDS within a year of initial HIV diagnosis. This indicates that the women were infected with HIV many years before they ever tested and they were then diagnosed very late in the course of the disease. If these women test very late in the course of the disease and come into care when they are already very sick, the implications can be detrimental. In addition, early testing is essential in reducing the spread of HIV
  • Incidence estimates indicate that 50% of women diagnosed in 2008 did not have recent infections. This supports the previous information that women are testing later in infection.
  • Finally, we will talk about HIV perinatal surveillance because it illuminates another reason why women are a unique population that requires special focus. HIV specifically impacts women of childbearing age, and there is a potential for women to pass the infection on to their children, especially if they do not know their status. All pregnancies and births in HIV positive women in Texas are tracked through the enhance perinatal surveillance system, also called EPS. Data from EPS indicates that, of the 13,751 HIV positive women in Texas, 60% are considered to be in child bearing age. In 2008, 361 women have delivered and HIV exposed infant.
  • All women at pregnancy and delivery must either get an HIV test or opt out of testing. Each year HIV infected women in Texas deliver between 300 and 400 children. This chart shows the number of perinatal exposures each year, in dark blue. The purple line represents the percent of babies infected each year, which has decreased from close to 7% in 1999 to under 3% in 2008.
  • The earlier in pregnancy that women test, the more likely they will be to receive the appropriate medications necessary for preventing transmission of HIV to the baby. This chart compares the timing of diagnosis to the infection of children. The dark blue show the number of women who delivered an exposed infant in 2008 by their timing of their HIV diagnosis. Of the 361 women, 229 were diagnosed prior to the pregnancy. 105 women learned of their status during routine testing during pregancy. The remaining 24 cases did not learn of their diagnosis until delivery. As you can see, proportion of infected children was much lower in those women who knew their HIV status prior to delivery.
  • In conclusion, we can see that sub-populations of women with HIV show unique characteristics that warrant targeted approaches. The primary mode of transmission also varies depending on age and race in HIV positive women, and this information can also be used to target prevention efforts. In addition, education on early and routine testing in women would provide a great benefit. Finally, it is vital to test women during pregnancy to reduce perinatal HIV transmission.
  • There are several future steps that would improve evaluation and analysis. First, much more information could be obtained on cases if we change the way that risk factors are defined for women by adding a presumed heterosexual sex category. The evaluation of socio-economic characteristics would provide more information on HIV positive individuals in low income communities and how this relates to racial distribution. Finally, additional research on testing behaviors and cues for testing in women would provide additional information on where to focus education efforts.

HIV/AIDS in Special Population Groups in Texas HIV/AIDS in Special Population Groups in Texas Presentation Transcript

  • Miranda Fanning, MPH TB/HIV/STD Epidemiology and Surveillance Texas Department of State Health Services Women with HIV in Texas
  • Outline
    • Overview
    • Demographic Makeup
    • Risk Distribution
    • Testing Behaviors
    • Perinatal Surveillance
    • Future Steps
  • Overview
    • Women account for 26% of all adult and adolescent HIV cases in the US*
    • Nationally, HIV is:
      • 5 th leading cause of death in women, 35-44*
      • 6 th leading cause of death in women, 25-34*
    • Biologically, women are more likely to be infected with HIV during sex**
    • * “CDC HIV/AIDS Facts Sheet” CDC.gov
    • ** “HIV/AIDS Policy Facts Sheet” KFF.org
  • Overview
    • As of the end of 2008, 13,751 women were living with HIV/AIDS in Texas
      • 11 women per 10,000 are living with HIV
      • 22% of total living HIV cases
    • 980 new female HIV cases diagnosed in 2008
  • Women with HIV, by year of diagnosis, Diagnosed 2000-2008
  • Demographic Makeup: Women with HIV, by Race/Ethnicity, Diagnosed 2000-2008
  • Demographic Makeup: HIV Cases by Race/Ethnicity and Sex, Diagnosed 2000-2008
  • Demographic Makeup: Women with HIV, by Age Group, Diagnosed 2000-2008
  • Demographic Makeup: Adult HIV Cases, by Age and Sex, Diagnosed 2000-2008
  • Demographic Makeup: Women with HIV, by Age and Race/Ethnicity, Diagnosed 2000-2008
    • Risk factor information is captured for reported cases
    • Hierarchical approach used to determine which risk factor was the primary mode of transmission
    • Only one risk category determined for each individual
    • Primary mode of transmission for females inlcudes:
      • Intravenous Drug Use
      • Heterosexual sex with
        • An intravenous drug user
        • A bisexual male
        • A male with other risk factors
        • A male with document HIV infection, risk unspecified
      • Other Less Common Risk Factors
    Collecting Risk Information
  • Risk Factor Data Limitations
    • To be categorized in Heterosexual Risk category, women must have a partner with:
      • A documented infection; or
      • Another known risk factor
    • If a case does not have a risk factor or does not meet the qualifications for Heterosexual Risk category, risk must be imputed
    • In 2008, 39% of female cases required risk imputation
  • Risk Distribution of Women with HIV, Diagnosed 2000-2008
  • Risk Distribution: Women with HIV, by Race/Ethnicity, Diagnosed 2000-2008
  • Risk Distribution: Women with HIV, by Age, Diagnosed 2000-2008
  • Testing Behaviors: Women with HIV, Time between HIV and AIDS Diagnosis, Initial diagnosis 2000-2008
  • Testing Behaviors
    • Incidence Estimates indicated 50% of women diagnosed in 2008 were long term late testers
  • Perinatal Surveillance
    • 13,751 HIV+ women living in Texas
      • 8,201 (60%) are women of childbearing age (15-44 years)
      • 361 (3%) delivered an HIV exposed infant
  • Perinatally Exposed and Infected Children, Texas, 1999-2008
  • Perinatal Surveillance: Timing of HIV Diagnosis among HIV+ Women Delivering an Exposed Child, 2008 *Note: Excluding 3 women with unknown timing of HIV diagnosis
  • Conclusions
    • Sub-populations of women with HIV show unique characteristics that warrant targeted approaches
    • Primary mode of transmission varies depending on age and race in HIV positive women in Texas
    • Education on early and routine testing in women would be advantageous
    • Testing during pregnancy is vital to reducing perinatal HIV transmission
  • Future Steps- Evaluation and Analysis
    • Addition of presumed heterosexual category
    • Evaluate socio-economic characteristics to identify the proportion of HIV positive individuals in low-income communities
    • Additional research on testing behavior and cues for testing in women
  • Questions
  • Acknowledgements
    • Presentation contributors:
        • Elvia Ledezma, MPH
        • Margaret Hawthorne, MPH