Home Current Issue Previous Issues Published Ahead-of-Print Collections For Authors Journal Info
Skip Navigation LinksHome > August 15, 2012 - Volume 60 - Issue > The Use of Epidemiological Data to Inform the PEPFAR Respons...
JAIDS Journal of Acquired Immune Deficiency Syndromes:
doi: 10.1097/QAI.0b013e31825d279a
Supplement Article

The Use of Epidemiological Data to Inform the PEPFAR Response

Lyerla, Rob PhD*; Murrill, Christopher S. PhD, MPH; Ghys, Peter D. MD; Calleja-Garcia, Jesus M. MD§; DeCock, Kevin M. MD, FRCP(UK), DTM&H

Free Access
Article Outline
Collapse Box

Author Information

*Office of the US Global AIDS Coordinator, Washington, DC

Division of Global HIV/AIDS, Centers for Disease Control and Prevention, Atlanta, GA

Joint United Nations Programme on HIV/AIDS, Geneva, Switzerland

§World Health Organization, Geneva, Switzerland

Center for Global Health, Centers for Disease Control and Prevention, Atlanta, GA.

Correspondence to: Rob Lyerla, PhD, Office of the US Global AIDS Coordinator, U.S. Department of State, 2201 C Street NW, Washington, DC 20520 (e-mail: Lyerlarl@state.gov).

Various authors have professional relationships with PEPFAR (either as employees of PEPFAR-supported US Government agencies or as grantees/contractors) as outlined in the Copyright Transfer Agreement forms.

The authors have no other funding or conflicts of interest to disclose.

The findings and conclusions in this article are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention, the US Government, UNAIDS, or the World Health Organization.

Collapse Box

Abstract

Abstract: The history of the HIV epidemic and the response to the epidemic is fundamentally a history of an emergency response to a global crisis. Trends and projections from initially available data were instrumental in establishing the President's Emergency Plan for AIDS Relief (PEPFAR) and in determining the direction of the program. Additionally, PEPFAR was built on data and the potential impact of interventions, and required the constant monitoring of the epidemic to report on the progress of the program. The response to the HIV epidemic saw the development of international guidelines and recommendations for data collection and epidemiological modeling. Although it is true that the urgency of the response often meant that data from data-poor countries suffered from incompleteness and bias, fortunately, as the response matured, the quality of the data and the infrastructure supporting data collection also matured. PEPFAR investments in surveillance and surveys were and remain critical for responding to the epidemic. The future of the response is reflected in growing country capacities to collect valid and reliable data, and using those data for decision making.

Back to Top | Article Outline

INTRODUCTION

Over 30 years ago, the United States reported the first cases of a disease that would eventually be known as AIDS.1 For Americans, the initial public health reaction to this epidemic was almost exclusively focused on the situation in the United States; however, it was not long before AIDS cases were reported in large numbers from African countries.2 By the early 1980s, the AIDS epidemic had spread extensively throughout Central and East Africa and had infected large numbers of the region's population.3 Public health professionals' early expectations were that because the most common route of transmission was through unprotected heterosexual intercourse, great numbers of people would be infected.4 Further reports fueled speculation that the generalized epidemic in Africa would also be replicated in Asia, but fortunately this did not happen.5 However, soon the epidemic in Southern Africa was apparent and prevalence rates were high.6 Because initial global estimates and results from early epidemiological studies indicated the need for a global response, in 1986, the World Health Organization (WHO) launched the Special Program on AIDS, later renamed the Global Programme on AIDS. At the same time, several United Nations (UN) agencies launched AIDS programs to respond to the epidemic. Ultimately, these efforts were brought together under the Joint UN Program on HIV/AIDS (UNAIDS), created in 1996.7

In 2001, the Global Fund to Fight AIDS, Tuberculosis, and Malaria was established with support from the United States and other countries and partners. The US Government (USG) established in 2003 the President's Emergency Plan for AIDS Relief (PEPFAR), the largest foreign assistance program in the country's history. Before the establishment of PEPFAR, the Clinton Administration used a USG multiagency platform, Leadership and Investment in Fighting an Epidemic initiative, as the vehicle for the USG response to the global AIDS pandemic by providing $100 million USD, earmarked primarily for sub-Saharan Africa. In 1998, the Drug Access Initiative was launched by UNAIDS and WHO, followed by the development of the “3 by 5” initiative.8 This campaign, with a goal of providing antiretroviral treatment (ART) to 3 million persons living in resource-limited countries by the end of 2005, coincided with a larger global and USG response in Africa.

In January 2003, President George W. Bush announced the commitment of $15 billion USD over a 5-year period to address the international AIDS epidemic through PEPFAR. The amount of commitment was based on estimates of required resource needs for the global response9 and the 2001 UN Declaration of Commitment.10 This first phase of PEPFAR proved to be a successful public health and diplomatic intervention; in May 2007, at the time of PEPFAR's reauthorization, President Bush asked Congress to authorize an additional $30 billion USD over the following 5 years, doubling PEPFAR's funding.

Back to Top | Article Outline

EARLY PEPFAR

Choosing the focus countries and interventions were the first tasks associated with the implementation of PEPFAR (Table 1). Early epidemiological models for those decisions were dependent upon limited data, but suggested that countries with the largest disease burden would gain the most from interventions. Missing in these estimates generated by UNAIDS were historical trends and data representing rural areas.11 Early estimates of the impact of the epidemic were biased by available surveillance data from only the hardest-hit global regions, including urban centers at the country level, because it was in those regions that programs were typically first launched and where surveillance data were first collected. Surveillance data for key high-risk populations such as sex workers (SWs), men who have sex with men (MSM), and injection drug users (IDUs), were also very limited.

Table 1
Table 1
Image Tools

The lack of available epidemiological data in the first group of focus countries led PEPFAR to invest heavily in surveillance and monitoring and evaluation programs, including data collection, data quality assurance, data management, and data analysis. As these programs and other data collection efforts became more comprehensive and established in these countries, the availability of data from these PEPFAR programs supported interventions and also provided data to improve the epidemic modeling to monitor trends in the epidemic.

Although early methods of monitoring the epidemic have been described elsewhere,12 it is important to note that PEPFAR-supported data collection programs were critical for collecting useful and accurate information. At the time, the prevailing methodologies used to track the success of PEPFAR programs were dominated by mathematical models that used data of varying quality and quantity.12–15 These early models were developed to use the available data; and, as such, data from seroprevalence surveys conducted among women at antenatal clinics (ANC) became the most common source of data in estimating the course of the epidemic.

Despite the more limited nature of the surveillance data available from PEPFAR-supported countries, epidemiological and research data about the routes of transmission and programs to interrupt them existed in the United States and Europe.16–18 Research had already established these as the most common methods of acquiring HIV; epidemiological data collected through PEPFAR programs were supporting earlier discoveries about HIV transmission and those data were being used when planning and implementing PEPFAR's prevention programs and treatment targets. In Africa, where PEPFAR programs continue to be the most active, prevention efforts included prevention of mother-to-child transmission (PMTCT) and blood safety, condom distribution, and HIV counseling and testing. Both PMTCT and blood safety programs were quite successful early on and PMTCT prevention continues to be a priority for PEPFAR country teams.

In the early years, however, some elements of the prevention programs were controversial. Although the “Zero Grazing” campaign in Uganda seemed to suggest that behavioral intervention could alter the course of the epidemic,19 PEPFAR's ABC strategy was based on a 3-pronged approach to behavior change (abstinence, be faithful, correct and consistent condom use).20 Although there is considerable consensus among public health professionals that all 3 of these elements are important at different life stages for reducing the number of new HIV infections, PEPFAR programs were heavily weighted to emphasize the A and B components of this program. In 2005, PEPFAR directed country teams to spend over 30% of their prevention funds on these 2 components, and to use the remaining funds to cover HIV testing programs and condom distribution. The impact of the ABC approach to preventing new infections has not yet been rigorously evaluated.

Although a review of the epidemiological data indicated the effectiveness of needle exchange programs (NEPs) and replacement therapy programs,21,22 and although many Western countries (Switzerland, Canada, United Kingdom, Australia) fund domestic NEPs,23 PEPFAR prevention programs at this time did not provide support for NEPs during epidemics among IDUs.

Finally, prevention programs for SWs including community mobilization, condom distribution, and sexually transmitted infection (STI) screening and treatment were also affected by existing policies.24 Funding from PEPFAR to countries required a commitment by a recipient country to have a written policy explicitly opposing prostitution and sex trafficking.25

Back to Top | Article Outline

MID-PEPFAR

Recognizing the bias in ANC HIV prevalence data in representing the general population, additional data sources were needed. PEPFAR began supporting nationally representative household surveys (NHS) in many countries to measure HIV prevalence and to provide additional data for modeling the epidemic in general populations. Data from these NHS (including the Demographic and Health Surveys) also allowed countries and PEPFAR programs to assess behavioral trends and validate findings in modeling exercises.26

The models could project short-term trends in the epidemic and predict the impact of various programs in both scope and scale. Although PEPFAR was improving the collection of data, methods used to estimate the impact of the epidemic and interventions were also improving.12 Improvements in the data and associated methodologies led UNAIDS to realize that the early estimates overstated the global disease burden and in 2007 released a major adjustment (Table 2).27 An example of adjustments made to the modeling methodology included using a correction factor obtained by comparing ANC-based prevalence and NHS for adjusting prevalence estimates in countries that had not yet conducted an NHS.28

Table 2
Table 2
Image Tools

In 2008, PEPFAR was reauthorized through the US Congress for an additional $36 billion USD. This included supporting more advanced national surveillance systems to collect and disseminate a greater variety of epidemiological data including behavioral risk and HIV prevalence data from populations at risk for HIV infection. At the time, the best data available suggested that the epidemic was being altered in several countries.29 The improved availability of these data led to better information about the impact of the PEPFAR program, allowed for an adjustment to the use of the data,30 thereby allowing better use of the data in setting program targets and measuring program successes.

For continued improvements in HIV surveillance methods and reinforcement of resource-constrained countries' capacity to design and implement strategic HIV surveillance programs, PEPFAR supported 2 global conferences on surveillance, one in Addis Ababa in 2004, and one in Bangkok in 2009, to discuss developments and new strategies for HIV surveillance.31,32 PEPFAR has also supported the development and implementation of guidelines for using standard approaches and methods for conducting various surveillance activities. This includes integrating into national surveillance programs newly developed survey methods to monitor the epidemic in key at-risk populations such as MSM, IDUs, and SWs. In addition, PEPFAR also supported regional estimation workshops enabling countries to estimate the national burden of HIV disease.33

Monitoring the epidemic shifted from a focus on prevalent infections to incident infections as a better indicator for evaluating prevention effectiveness. Historical efforts to track the HIV epidemic had used blood and blood samples to test for HIV antibodies. However, a laboratory assay that could be used widely to differentiate incident from prevalent infections was not available. PEPFAR has supported work to develop different assays, although none of them are completely effective in differentiating recent (incident) from long-standing infection.35

As an alternative, trends in prevalent infections among young pregnant women aged 15–24 years have been used as a proxy for trends in new, that is, incident, infections.34 Use of this proxy method has suggested that behavioral intervention and treatment and care efforts in Africa have had an impact on incidence trends.36,37 The findings from these efforts suggested that trends in incidence over time could be estimated by tracking prevalence among young women, and that the impact of programs, both behavioral and biomedical, could be assessed by this method. Additional attempts to look at other proxy metrics, for example, individuals who had “newly initiated” higher risk behavior, including IDUs and commercial SWs, are in process, using length of time as an IDU or time as an SW as a proxy for “newly at risk.”38,39 However, efforts to promote this methodology have met with limited success.

PEPFAR also supported continued development of methods used to model the global epidemic, including the effect of persons being on ART when calculating HIV incidence from trends in HIV prevalence and considering the reduced infectivity of those receiving ART.30 Additional data from established national surveillance programs continue to be increasingly available for input into the global epidemiological models.

Data from PEPFAR-supported surveillance and epidemiological programs were also instrumental in prioritizing interventions for opportunistic infections. In particular, interventions for tuberculosis and STIs were recommended as a priority prevention activity by WHO.40 Evidence does support that STIs are a risk factor for HIV. The evidence, however, does not support that STI treatment has a significant effect on incidence of HIV, especially in generalized epidemics. However, STI control remains important for key populations among whom untreated STIs may facilitate HIV transmission.41

Back to Top | Article Outline

FUTURE PEPFAR

Currently, epidemiological and research data serve an important role for PEPFAR to inform and adjust programs, and to institute and support new prevention programs. Recent research in PMTCT has provided data that have led to changes in recommendations about drug regimens and infant feeding options to prevent HIV transmission and optimize child survival.42

Data on the benefits of starting treatment earlier and the consequent guidelines from WHO led to adjusting PEPFAR treatment protocols. Although scale-up has been incremental, the data supported the recommendations that instead of using a CD4 count of 200 cells per millimeter, treatment should begin at CD4 counts of ≤350 cells per millimeter.42,43 Currently, several PEPFAR-funded studies aim to evaluate the impact of treatment as a component of a package of prevention programs on HIV incidence at a population level.44

Results from randomized controlled trials45,46 provided the definitive data needed to recommend male circumcision as an effective prevention intervention. To date, the scale-up of male circumcision efforts in Africa has been primarily supported by PEPFAR.

PEPFAR programs and the epidemiological data systems used to monitor the global HIV epidemic continue to evolve. As more data become available, programmatic efforts are adjusted, and modeling efforts continue to be modified.47 Additionally, data collection techniques are examined and transformed as the global community faces specific challenges, such as the appropriate use of unlinked anonymous testing (UAT) to measure HIV prevalence.31 For many years, data from unlinked blood samples from ANC programs have been crucial for national HIV surveillance programs. Such data have been used to assess levels and trends in national epidemics, including in estimation models. As PEPFAR considers transitioning away from using UAT for ANC surveillance surveys toward using available PMTCT program data to measure HIV prevalence among pregnant women, the comparability of ANC survey data and PMTCT program data, PMTCT program data quality, and the potential loss of longitudinal data comparisons over time must be considered.48 Additional program data systems may be important sources of epidemiological data for future decision making and policy planning, such as clinic-based health information systems as a source of HIV case reporting.

The HIV epidemic in populations of IDUs, MSM, or SWs continues to be poorly monitored, although data collection efforts have improved in recent years.49 Population size estimates, survey techniques, and evaluation of programs targeting these population groups continue to be supported by PEPFAR. For IDUs, the access to NEPs continues to be an effective intervention for preventing HIV infection,21,23 and PEPFAR now supports a comprehensive HIV prevention package for IDUs, which includes the following 3 central elements: (1) community-based outreach programs, (2) sterile needle and syringe programs, and (3) drug dependence treatment, including medication-assisted treatment with methadone or buprenorphine and/or other effective medications as appropriate, based on the country context.50

The use of epidemiological and research data to inform the future directions for the next phase of PEPFAR will continue to be critical for an evidence-based decision making, funding prioritization, and intervention design. For example, in response to the HPTN 052 Study,51 the optimal strategies for expanding access to ART need to be decided, those who those who are infected but not symptomatic will need to be identified earlier, and adherence to care and treatment of these people will need to be maximized. The rollout of treatment as prevention will require rigorous comparative studies followed by monitoring and evaluation to ensure program success and sustainability.52,53

The past 8 years of PEPFAR funding have supported the global community in creating and maintaining large sources of epidemiological data. PEPFAR will continue to support development of key areas in surveillance including improved methods and standards for estimation of incidence,35 assessing and transitioning to the use of available program data for surveillance purposes (eg, PMTCT data), establishment of pediatric HIV surveillance systems, and methods for estimating the size of populations at higher risk for HIV infection.54 The need remains for complete, comprehensive, and reliable vital registration systems, as does the support and development of adequate patient monitoring systems. Ongoing support to further develop and refine the methods used for data collection, analysis, and modeling of the global epidemic, and to improve existing national HIV surveillance systems to more effectively monitor other facets of the epidemic, including improved mortality measurement, will be instrumental in the coming years. Global HIV epidemiological data will also continue to support the monitoring and evaluation efforts to measure program effectiveness. Finally, in future years, PEPFAR will work to transfer knowledge and expertise to partner countries, to allow them to exert full ownership over data collection methods and systems, and data analyses and interpretation.

Back to Top | Article Outline

REFERENCES

1. Centers for Disease Control. Pneumocystis pneumonia—Los Angeles. MMWR Morb Mortal Wkly Rep. 1981;30:250–252.

2. Centers for Disease Control. Prevention of acquired immune deficiency syndrome (AIDS): report of inter-agency recommendations. MMWR Morb Mortal Weekly Rep. 1983;32:101–104.

3. Clumeck N, Sonnet J, Taelman H, et al.. Acquired immunodeficiency syndrome in African patients. N Engl J Med. 1984;310:492–497.

4. May R, Anderson R. Transmission dynamics of HIV infection. Nature. 1987;326:137–142.

5. UNAIDS. HIV/AIDS: China's titanic peril. Available at: http://www.hivpolicy.org/Library/HPP000056.pdf. Accessed March 16, 2012.

6. Buve A, Bishikwabo-Nsahaza K, Mutangadura G. The spread and effect of HIV-1 infection in sub-Saharan Africa. Lancet. 2002;359:2011–2017.

7. The AIDS 2031 Consortium. AIDS: Taking the Long-term View. Upper Saddle, NJ: Financial Times Science Press; 2010.

8. Schwartländer B, Grubb I, Perriens J. The 10 year struggle to provide antiretroviral treatment to people with HIV in the developing world. Lancet. 2006;368:541–546.

9. Schwartländer B, Stover J, Walker N, et al.. AIDS. Resource needs for AIDS. Science. 2001;292:2436.

10. United Nations. Declaration of commitment on HIV/AIDS—global crisis, global action. Available at: http://www.un.org/ga/aids/coverage/FinalDeclarationHIVAIDS.html. Accessed March 16, 2012.

11. Grassley NC, Morgan M, Walker N, et al.. Uncertainty in estimates of HIV/AIDS: the estimation and application of plausibility bounds. Sex Transm Infect. 2004;80(suppl 1):i31–i38.

12. Ghys PD, Brown T, Grassly NC, et al.. The UNAIDS estimation and projection package: a software package to estimate and project national HIV epidemics. Sex Transm Infect. 2004:80(suppl 1):i5–i9.

13. Walker N, Stanecki K, Brown T, et al.. Methods and procedures for estimating HIV/AIDS and its impact: the UNAIDS/WHO estimates for the end of 2001. AIDS. 2003;17:2215–2225.

14. Stover J. Projecting the demographic consequences of adult HIV prevalence trends: the Spectrum Projection Package. Sex Transm Infect. 2004:80(suppl 1):i4–i18.

15. Walker N, Stover J, Stanecki K, et al.. The workbook approach to making estimates and projecting future scenarios of HIV/AIDS in countries with low level and concentrated epidemics. Sex Transm Infect. 2004:80(suppl 1):i10–i13.

16. Curran JW, Jaffe HW, Hardy AM, et al.. Epidemiology of HIV infection and AIDS in the Unites States. Science. 1988;239:610–616.

17. Centers for Disease Control. US Public Health Service recommendations for human immunodeficiency virus counseling and voluntary testing for pregnant women. MMWR Morb Mortal Weekly Rep. 1995;44:1–15.

18. Merson M, Dayton JM, O'Reilly K. Effectiveness of HIV prevention interventions in developing countries. AIDS. 2000;14(suppl 2):S68–S84.

19. Stoneburner RL, Low-Beer D. Population-level HIV declines and behavioral risk avoidance in Uganda. Science. 2004;304:714–718.

20. Collins C, Coates TJ, Curran J. Moving beyond the alphabet soup of HIV prevention. AIDS. 2008;22(suppl 2):5–8.

21. Strathdee S, Vlahov D. The effectiveness of needle exchange programs: a review of the science and policy. AIDScience. 2001;1:1–31.

22. Committee on the Prevention of HIV Infection Among Injecting Drug Users in High Risk Countries. Preventing HIV Infection Among Injecting Drug Users in High Risk Countries: An Assessment of the Evidence. Washington, DC: Institute of Medicine; 2006.

23. Harm Reduction International. The global state of harm reduction. 2012. Available at: http://www.ihra.net/contents/535. Accessed March 16, 2012.

24. Ghys P, Diallo M, Ettiegne-Traore V, et al.. Increase in condom use and decline in HIV and sexually transmitted diseases among female sex workers in Abidjan, Cote D'Ivoire, 1999-1998. AIDS. 2002;16–258:251–258.

25. Tom Lantos and Henry J. Hyde United States Global Leadership Against HIV/AIDS, Tuberculosis, and Malaria Reauthorization Act of 2008. Pub L. No. 110-293, 122 Stat 2918.

26. Gouws E, Mishra V, Fowler TB. Comparison of adult HIV prevalence from national population-based surveys and antenatal clinic surveillance in countries with generalized epidemics: implications for calibrating surveillance data. Sex Transm Infect. 2008;84(suppl 1):i17–i23.

27. Brown T, Salomon JA, Alkema L, et al.. Progress and challenges in modeling country-level HIV/AIDS epidemics: the UNAIDS estimation and projection package 2007. Sex Transm Infect. 2008;84(suppl 1):i5–i10.

28. UNAIDS. 2008 report on the global AIDS epidemic. Available at: http://www.unaids.org/en/dataanalysis/epidemiology/2008reportontheglobalaidsepidemic. Accessed March 25, 2012.

29. Ghys PD, McFarland W, Walker N, et al.. Improved data, methods and tools for the 2007 HIV and AIDS estimates and projections. Sex Transm Infect. 2008;84–i4:i1–i4.

30. Brown T, Bao L, Raftery AE, et al.. Modelling HIV epidemics in the antiretroviral era: the UNAIDS Estimation and Projection package 2009. Sex Transm Infect. 2010;86(suppl 2):ii3–ii10.

31. Diaz T, De Cock K, Brown T, et al.. New strategies for HIV surveillance in low and middle income settings: an overview. AIDS. 2005;19(suppl 2):1–8.

32. Ghys PD, Diaz T, Sabin K. New strategies and methods for HIV surveillance in low and middle income countries. J HIV AIDS Surveill Epidemiol. 2010;2:1.

33. Hladik W, Musinguzi J, Kirungi W, et al.. The estimated burden of HIV/AIDS in Uganda, 2005-10. AIDS. 2008;22:503–510.

34. UNAIDS. 2010 report on the global AIDS epidemic. Available at: http://www.unaids.org/en/dataanalysis/epidemiology/2010reportontheglobalaidsepidemic. Accessed March 25, 2012.

35. Duong YT, Qiu1 M, De AK, et al.. Detection of recent HIV-1 infection using a new limiting-antigen avidity assay: potential for HIV-1 incidence estimates and avidity maturation studies. PloS One. 2012;7:e33328.

36. Gouws E, Stanecki KA, Lyerla R, et al.. The epidemiology of HIV infection among young people aged 15-24 years in southern Africa. AIDS. 2008;22(suppl 4):5–16.

37. Ghys PD, Kufa E, George MV. Measuring trends in prevalence and incidence of HIV infection in countries with generalized epidemics. Sex Transm Infect. 2006;82(suppl 1):i52–i56.

38. Sun LP. Proxy measures for HIV incidence trends. Proceedings from the 2nd Global HIV/AIDS Surveillance Meeting, Bangkok, Thailand, 2009. Available at: www.hivsurveillance2009.org/docs/session_xiii/pres10.ppt. Accessed March 25, 2012.

39. Mahy M, Chhea C, Saliuk O, et al.. A proxy measure for HIV incidence among populations at increased risk to HIV. J HIV AIDS Surveill Epidemiol. 2010;2:8.

40. World Health Organization. Priority interventions in HIV/AIDS prevention, treatment and care in the health section 2010. Available at: http://whqlibdoc.who.int/publications/2010/9789241500234_eng.pdf.

41. Steen R, Wi TE, Kamali A, et al.. Control of Sexually Transmitted Infections and Prevention of HIV Transmission: Mending a Fractured Paradigm. Geneva, Switzerland: World Health Organization; 2006.

42. World Health Organization. Antiretroviral drugs for treating pregnant women and preventing HIV infection in infants: recommendations for a public health approach (2010 version). Available at: http://www.who.int/hiv/pub/mtct/antiretroviral2010/en/index.html. Accessed March 16, 2012.

43. World Health Organization. Antiretroviral therapy for HIV infection in adults and adolescents. Recommendations for a public health approach: 2010 revision. Available at: http://www.who.int/hiv/pub/arv/adult2010/en/index.html. Accessed March 16, 2012.

44. Padian N, McCoy S, Karim S, et al.. HIV prevention transformed: the new prevention research agenda. Lancet. 2011;378:269–278.

45. Auvert B, Taljaard D, Lagarde E, et al.. Randomized, controlled intervention trial of male circumcision for reduction of HIV infection risk: the ANRS 1265 Trial. PLoS Med. 2005;2:e298.

46. Bailey R, Moses S, Parker C, et al.. Male circumcision for HIV prevention in young men in Kisumu, Kenya: a randomised controlled trial. Lancet. 2007;369:643–656.

47. Stover J, Johnson P, Zaba B, et al.. The spectrum projection package: improvements in estimating mortality, ART needs, PMTCT impact and uncertainty bounds. Sex Transm Infect. 2008;84:i24–i30.

48. Marsh KA, Bodika S, Seipone K, et al.. How can PMTCT program data be used for the purposes of HIV surveillance? J HIV AIDS Surveill Epidemiol. 2010;2:5.

49. Lyerla R, Gouws E, Garcia-Calleja JM. The quality of sero-surveillance in low- and middle-income countries: status and trends through 2007. Sex Transm Infect. 2008;84:i85–i91.

50. The U.S. President's Emergency Plan for AIDS Relief (PEPFAR). Comprehensive Prevention for People Who Inject Drugs, Revised Guidance. July 2010. Available at: http://www.pepfar.gov/documents/organization/144970.pdf. Accessed March 25, 2012.

51. Cohen M, Chen Y, McCauley M, et al.. Prevention of HIV-1 infection with early antiretroviral therapy. N Engl J Med. 2011;365:493–505.


53. US Department of State. The path to an AIDS free generation. Available at: http://www.state.gov/r/pa/prs/ps/2011/11/176770.htm. Accessed March 16, 2012.

54. Bernard R, Hallett T, Johnsen E, et al.. Counting hard-to-count populations: the network scale-up method for public health. Sex Transm Infect. 2010;86–i15:ii11–i15.

Keywords:

PEPFAR; epidemiology; surveillance; data

© 2012 Lippincott Williams & Wilkins, Inc.

Login

Search for Similar Articles
You may search for similar articles that contain these same keywords or you may modify the keyword list to augment your search.