Elizabeth Styffe has been involved in HIV education, advocacy, public policy and nursing care since 1982. She co-founded and directed the Local and Global HIV/AIDS Initiatives at Saddleback Church with Kay Warren and directed the initiative, including the Orphan Care and Rwanda Healthcare Initiatives for fourteen years. An author, consultant and international speaker, Elizabeth combines her background in pediatric nursing, loss, grief and trauma with a passion to see the church at the center of ending both the HIV and Orphan Crisis through mobilization, compassionate care and collaborative partnerships. Having received a BSN from Biola University and Master's Degree in Nursing from UCLA, she develops robust programs and tools for churches across the globe with an emphasis on orphan care and permanency as the right of every child.
Epidemiology, clinical manifestations, and diagnosis of Pneumocystis pneumonia in HIV-uninfected patients
Acute and early HIV infection: Treatment
Acute and early HIV infection: Pathogenesis and epidemiology
Overview of prevention of opportunistic infections in HIV-infected patients
Screening and diagnostic testing for HIV infection
Techniques and interpretation of measurement of the CD4 cell count in HIV-infected patients
The adolescent with HIV infection
Global epidemiology of HIV infection
The natural history and clinical features of HIV infection in adults and adolescents
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Of course, the actual numbers vary depending on the testing population. This is because interpreting of the results of any medical test (assuming no test is 100% accurate) depends upon the initial degree of belief, or the prior probability that an individual has, or does not have a disease. Generally the prior probability is estimated using the prevalence of a disease within a population or at a given testing location. The positive predictive value and negative predictive value of all tests, including HIV tests, take into account the prior probability of having a disease along with the accuracy of the testing method to determine a new degree of belief that an individual has or does not have a disease (also known as the posterior probability ). The chance that a positive test accurately indicates an HIV infection increases as the prevalence or rate of HIV infection increases in the population. Conversely, the negative predictive value will decrease as the HIV prevalence rises. Thus a positive test in a high-risk population, such as people who frequently engage in unprotected anal intercourse with unknown partners, is more likely to correctly represent HIV infection than a positive test in a very low-risk population, such as unpaid blood donors.