logging in or signing up 30711 Rachele Download Post to : URL : Related Presentations : Share Add to Flag Embed Email Send to Blogs and Networks Add to Channel Uploaded from authorPOINTLite Insert YouTube videos in PowerPont slides with aS Desktop Copy embed code: (To copy code, click on the text box) Embed: URL: Thumbnail: WordPress Embed Customize Embed The presentation is successfully added In Your Favorites. Views: 188 Category: Education License: All Rights Reserved Like it (0) Dislike it (0) Added: April 07, 2008 This Presentation is Public Favorites: 0 Presentation Description No description available. Comments Posting comment... Premium member Presentation Transcript Slide1: The Most Probable Past, Present, and Future of the AIDS Pandemic JAMES (Jim) CHIN MD, MPH Clinical Professor of Epidemiology School of Public Health University of California at Berkeley Slide2: ? ? ? ? Probable Routes of Initial Global Spread of HIV-1 in the 1960s and 1970sSlide3: AIDSSlide4: Who is at Risk of Acquiring or Transmitting HIV Infection?Slide5: Factors that can Facilitate or Limit Epidemic Sexual HIV Transmission *Facilitating factors are not co-factors since they are not required for HIV transmission but can “facilitate” or increase the risk of transmissionSlide6: The Reproductive Number (R0) of HIV R0 for HIV via sexual transmission is dependent on: probability a sex partner is infected with HIV [p]; probability of HIV transmission per coital act [r]; number of unprotected coital acts with different sex partners [n1, n2…] R0 = (p x r x n1) + (p x r x n2)…Slide7: Risk of Sexual HIV Transmission Based on Pattern of Sex Partner ExchangeSlide8: Question Why is epidemic (R0 >1) heterosexual HIV transmission almost non-existent in most countries in the world but is so prevalent in sub-Saharan African countries and to a lesser extent in several Caribbean countries and in only a few countries in South and Southeast Asia?Slide9: HIV Prevalence by Wealth Quintiles – KenyaSlide10: Understanding HIV/AIDS Numbers Reported Official Estimated Actual HIV incidence HIV prevalence AIDS incidenceSlide11: How Accurate are HIV Prevalence Estimates? Estimation of HIV prevalence is more of an art than a science. With the many uncertainties in HIV serologic data and the limitations of the data, methods, and assumptions used, estimation of HIV numbers cannot be precise. Current HIV prevalence estimates tend to be high because of insufficient data on urban/rural differentials.HIV Prevalence Rates in Selected sub-Saharan African Countries: HIV Prevalence Rates in Selected sub-Saharan African Countries Percent HIV positive among population age 15-49 2001-2003 national estimates based mostly on sentinel ANC data 2002-2006 national estimates based mostly on population based data 1.2 0.3 1.2 0.9 0.1 0.03 0.5 0.4 0.3 Number overestimated in millions Total overestimation for these SSA countries about 5 million 7/25/07HIV Prevalence Rates in Selected African,Caribbean and Asian Countries: HIV Prevalence Rates in Selected African, Caribbean and Asian Countries Percent HIV positive among population age 15-49 2001-2003 national estimates based mostly on sentinel ANC data 2002-2006 national estimates based mostly on population based data 0.05 0.15 0.15 3 7/25/07 1.4 0.05 Number overestimated in millions Slide14: Percent of Global Population Infected with HIV - 2007 Infected Not Infected Sub-Saharan Africa 3.0% 97.0% Rest of World 0.2% 99.8% Total Global 0.5% 99.5% The “Glorious” Myth of “Generalized” HIV Epidemics Influenza pandemics >50% <50% Slide15: Estimated HIV Prevalence in Global Regions: 2001- 2006 * In early July, 2007 estimated HIV prevalence in India was reduced from close to 6 million (0.9%) to less than 2.5 million (0.36%). Slide16: 7/04/07 Highest Estimated HIV Prevalence Countries - 2006Slide17: Estimated HIV Prevalence in 10,000 Females - 2006Slide18: Estimated HIV Prevalence and Incidence – California - 2000 * Population age 20-44 - Estimates developed by a consensus meeting of about 50 California HIV/AIDS experts in 2001Slide19: HIV Epidemics in IDU Populations in AsiaSlide20: * In a prior study, HIV prevalence in underground FSW not using drugs was 2.2%. ** HIV prevalence in IDU tested in detention camps in 2000 was about 25%. HIV Prevalence In Female Sex Workers and Truck Drivers in Yunnan, China, 1999-2000Slide21: 87 97 94/95 88 94 95 93 87 95 93 Uganda Kenya Botswana Slide22: UNAIDS Report to UNGASS – May 30, 2006 OVERVIEW OF THE GLOBAL A I D S EPIDEMIC “Overall globally, the HIV incidence rate (the annual number of new HIV infections as a proportion of previously uninfected persons) is believed to have peaked in the late 1990s and to have stabilized subsequently… …Changes in incidence along with rising AIDS mortality have caused global HIV prevalence (the proportion of people living with HIV) to level off….” Slide23: UNAIDS 2006 Estimates of Annual HIV Incidence and Annual AIDS Deaths in Selected Regions *Numbers are in millions **When HIV incidence peaks, the ratio of new HIV infections to AIDS deaths is about 2:1; after 5 years it is 1.5:1; and after 10 years close to 1:1 Slide24: UN Millennium target “Have halted by 2015 and begun to reverse the spread of HIV/AIDS”Slide25: Increase of responsible sexual behaviors, i.e., sexual Abstinence and/or Being faithful Increase of consistent Condom use for risky sex behaviors Saturation of infection in those with the highest sexual risk behaviors All of the above, but perhaps saturation of infection may be the most important factor! What are the Major Factors Responsible for Peaking of Sexual HIV Epidemics?Slide26: Peak annual HIV incidence numbers Peak annual numbers of AIDS deaths Modeling HIV/AIDS in Cambodia “Riding to glory on the down slope of the epidemic curve!” Start of national 100% condom programSlide27: Estimated Annual TB CasesSlide28: HIV/AIDS # 10 - 2.5% HIV/AIDS # 8 – 2% Data source: Version 3 revisions of the Global Burden of Disease (GBD) study. Top Two Leading Causes of Death in Global “Regions” - 2001Slide29: The Impact of AIDS on the San Francisco Gay Men’s ChorusSlide30: Can You Believe This? Source: WHO’s World Health Report 2004Slide31: Estimated and Projected Annual HIV Incidence in sub-Saharan Africa UNAIDS modeled baseline scenario Jim Chin’s more logical scenario UNAIDS’ comprehensive prevention & treatment scenarioSlide32: Estimation and Projection of HIV Prevalence to 2020 ALL OTHER REGIONS Overestimates and projections by UNAIDS & UN Population Division SOUTH & SE ASIA Most likely scenario Most likely scenario SUB-SAHARAN AFRICASlide33: James (Jim) Chin, MD, MPH Clinical Professor of Epidemiology, School of Public Health University of California, Berkeley Formerly, Chief of the Surveillance, Forecasting, and Impact Assessment (SFI) unit of the Global Programme on AIDS (GPA), World Health Organization (WHO), Geneva, Switzerland Forward by Jeffery Koplan, MD, MPH Vice President, Academic Health Affairs, Emory University, Atlanta Formerly Director, Centers for Disease Control and Prevention (CDC) **** The AIDS Pandemic argues that the story of HIV/AIDS has been distorted by UNAIDS and AIDS activists in order to support the myth of the high potential risk of HIV epidemics spreading into the general population. Radcliffe-Oxford, 2007 www.theaidspandemic.com You do not have the permission to view this presentation. In order to view it, please contact the author of the presentation.
30711 Rachele Download Post to : URL : Related Presentations : Share Add to Flag Embed Email Send to Blogs and Networks Add to Channel Uploaded from authorPOINTLite Insert YouTube videos in PowerPont slides with aS Desktop Copy embed code: (To copy code, click on the text box) Embed: URL: Thumbnail: WordPress Embed Customize Embed The presentation is successfully added In Your Favorites. Views: 188 Category: Education License: All Rights Reserved Like it (0) Dislike it (0) Added: April 07, 2008 This Presentation is Public Favorites: 0 Presentation Description No description available. Comments Posting comment... Premium member Presentation Transcript Slide1: The Most Probable Past, Present, and Future of the AIDS Pandemic JAMES (Jim) CHIN MD, MPH Clinical Professor of Epidemiology School of Public Health University of California at Berkeley Slide2: ? ? ? ? Probable Routes of Initial Global Spread of HIV-1 in the 1960s and 1970sSlide3: AIDSSlide4: Who is at Risk of Acquiring or Transmitting HIV Infection?Slide5: Factors that can Facilitate or Limit Epidemic Sexual HIV Transmission *Facilitating factors are not co-factors since they are not required for HIV transmission but can “facilitate” or increase the risk of transmissionSlide6: The Reproductive Number (R0) of HIV R0 for HIV via sexual transmission is dependent on: probability a sex partner is infected with HIV [p]; probability of HIV transmission per coital act [r]; number of unprotected coital acts with different sex partners [n1, n2…] R0 = (p x r x n1) + (p x r x n2)…Slide7: Risk of Sexual HIV Transmission Based on Pattern of Sex Partner ExchangeSlide8: Question Why is epidemic (R0 >1) heterosexual HIV transmission almost non-existent in most countries in the world but is so prevalent in sub-Saharan African countries and to a lesser extent in several Caribbean countries and in only a few countries in South and Southeast Asia?Slide9: HIV Prevalence by Wealth Quintiles – KenyaSlide10: Understanding HIV/AIDS Numbers Reported Official Estimated Actual HIV incidence HIV prevalence AIDS incidenceSlide11: How Accurate are HIV Prevalence Estimates? Estimation of HIV prevalence is more of an art than a science. With the many uncertainties in HIV serologic data and the limitations of the data, methods, and assumptions used, estimation of HIV numbers cannot be precise. Current HIV prevalence estimates tend to be high because of insufficient data on urban/rural differentials.HIV Prevalence Rates in Selected sub-Saharan African Countries: HIV Prevalence Rates in Selected sub-Saharan African Countries Percent HIV positive among population age 15-49 2001-2003 national estimates based mostly on sentinel ANC data 2002-2006 national estimates based mostly on population based data 1.2 0.3 1.2 0.9 0.1 0.03 0.5 0.4 0.3 Number overestimated in millions Total overestimation for these SSA countries about 5 million 7/25/07HIV Prevalence Rates in Selected African,Caribbean and Asian Countries: HIV Prevalence Rates in Selected African, Caribbean and Asian Countries Percent HIV positive among population age 15-49 2001-2003 national estimates based mostly on sentinel ANC data 2002-2006 national estimates based mostly on population based data 0.05 0.15 0.15 3 7/25/07 1.4 0.05 Number overestimated in millions Slide14: Percent of Global Population Infected with HIV - 2007 Infected Not Infected Sub-Saharan Africa 3.0% 97.0% Rest of World 0.2% 99.8% Total Global 0.5% 99.5% The “Glorious” Myth of “Generalized” HIV Epidemics Influenza pandemics >50% <50% Slide15: Estimated HIV Prevalence in Global Regions: 2001- 2006 * In early July, 2007 estimated HIV prevalence in India was reduced from close to 6 million (0.9%) to less than 2.5 million (0.36%). Slide16: 7/04/07 Highest Estimated HIV Prevalence Countries - 2006Slide17: Estimated HIV Prevalence in 10,000 Females - 2006Slide18: Estimated HIV Prevalence and Incidence – California - 2000 * Population age 20-44 - Estimates developed by a consensus meeting of about 50 California HIV/AIDS experts in 2001Slide19: HIV Epidemics in IDU Populations in AsiaSlide20: * In a prior study, HIV prevalence in underground FSW not using drugs was 2.2%. ** HIV prevalence in IDU tested in detention camps in 2000 was about 25%. HIV Prevalence In Female Sex Workers and Truck Drivers in Yunnan, China, 1999-2000Slide21: 87 97 94/95 88 94 95 93 87 95 93 Uganda Kenya Botswana Slide22: UNAIDS Report to UNGASS – May 30, 2006 OVERVIEW OF THE GLOBAL A I D S EPIDEMIC “Overall globally, the HIV incidence rate (the annual number of new HIV infections as a proportion of previously uninfected persons) is believed to have peaked in the late 1990s and to have stabilized subsequently… …Changes in incidence along with rising AIDS mortality have caused global HIV prevalence (the proportion of people living with HIV) to level off….” Slide23: UNAIDS 2006 Estimates of Annual HIV Incidence and Annual AIDS Deaths in Selected Regions *Numbers are in millions **When HIV incidence peaks, the ratio of new HIV infections to AIDS deaths is about 2:1; after 5 years it is 1.5:1; and after 10 years close to 1:1 Slide24: UN Millennium target “Have halted by 2015 and begun to reverse the spread of HIV/AIDS”Slide25: Increase of responsible sexual behaviors, i.e., sexual Abstinence and/or Being faithful Increase of consistent Condom use for risky sex behaviors Saturation of infection in those with the highest sexual risk behaviors All of the above, but perhaps saturation of infection may be the most important factor! What are the Major Factors Responsible for Peaking of Sexual HIV Epidemics?Slide26: Peak annual HIV incidence numbers Peak annual numbers of AIDS deaths Modeling HIV/AIDS in Cambodia “Riding to glory on the down slope of the epidemic curve!” Start of national 100% condom programSlide27: Estimated Annual TB CasesSlide28: HIV/AIDS # 10 - 2.5% HIV/AIDS # 8 – 2% Data source: Version 3 revisions of the Global Burden of Disease (GBD) study. Top Two Leading Causes of Death in Global “Regions” - 2001Slide29: The Impact of AIDS on the San Francisco Gay Men’s ChorusSlide30: Can You Believe This? Source: WHO’s World Health Report 2004Slide31: Estimated and Projected Annual HIV Incidence in sub-Saharan Africa UNAIDS modeled baseline scenario Jim Chin’s more logical scenario UNAIDS’ comprehensive prevention & treatment scenarioSlide32: Estimation and Projection of HIV Prevalence to 2020 ALL OTHER REGIONS Overestimates and projections by UNAIDS & UN Population Division SOUTH & SE ASIA Most likely scenario Most likely scenario SUB-SAHARAN AFRICASlide33: James (Jim) Chin, MD, MPH Clinical Professor of Epidemiology, School of Public Health University of California, Berkeley Formerly, Chief of the Surveillance, Forecasting, and Impact Assessment (SFI) unit of the Global Programme on AIDS (GPA), World Health Organization (WHO), Geneva, Switzerland Forward by Jeffery Koplan, MD, MPH Vice President, Academic Health Affairs, Emory University, Atlanta Formerly Director, Centers for Disease Control and Prevention (CDC) **** The AIDS Pandemic argues that the story of HIV/AIDS has been distorted by UNAIDS and AIDS activists in order to support the myth of the high potential risk of HIV epidemics spreading into the general population. Radcliffe-Oxford, 2007 www.theaidspandemic.com