Surveillance is a foundation of the public health response to the HIV pandemic. The ability to understand the important sources of recent infections, to monitor the spread of infection and the trends in specific groups, and to measure the associated morbidity is critical for intervening against further transmission and allocating resources.
The establishment of the Global Fund to Fight AIDS, Tuberculosis and Malaria (GFATM) in 2001 and the President's Emergency Plan for AIDS Relief (PEPFAR) in 2003 brought an unparalleled infusion of funding to combat HIV. Since 2003, investments in fighting the epidemic have risen from US$300 million to US$8 billion a year . With these investments came a greater demand for accountability, trend analysis, and impact evaluation. Surveillance data are critical for these analyses.
In January 2004, over 250 HIV surveillance experts gathered in Addis Ababa, Ethiopia to review the status of HIV/AIDS surveillance methods and activities in low- and middle-income countries. The meeting proceedings [2–10] highlighted new methods in use, the limitations and gaps in HIV surveillance, and recommended future strategies. Advances made since 2004 included implementation of strategies that were suggested at the Ethiopia conference. Recent downward revisions in global HIV estimates in part reflect these improvements .
This article reviews some key advances in HIV surveillance in preparation for a second conference on Global HIV/AIDS Surveillance that took place in Bangkok, Thailand in February of 2009. The study is organized according to the framework of HIV infection and its progression to AIDS and death (Fig. 1).
Surveillance of risk for HIV transmission
The advent of second-generation HIV surveillance guidelines in 2000 recognized the importance of behavioral surveillance . Surveillance of behaviors that place people at greater risk for HIV transmission is critical to an understanding of the trajectory of an epidemic and the required response.
In countries where HIV transmission is largely through heterosexual behaviors in the general population, population-based household surveys of behaviors are warranted . Between 2001 and 2008, 30 countries implemented national population-based surveys with HIV testing . Six countries (Botswana, Côte d'Ivoire, Guyana, Kenya, Tanzania, Uganda, and Vietnam) completed AIDS Indicators Surveys (AIS). AIS are shorter and less expensive as compared with multipurpose surveys such as Demographic Health Surveys (DHS). General national population surveys are usually conducted every 5 years with AIS between these, to discern trends faster.
The standard approach for countries with epidemics concentrated among well defined subpopulations, for example men who have sex with men (MSM), injection drug users (IDUs) and female sex workers (FSWs), was, prior to 2004, serial behavioral surveillance surveys of these groups, typically without HIV testing and using convenience sampling . Major developments since 2004 include routine specimen collection for testing and probability sampling methods [14–17]. Between January 2003 and 1 October 2007, at least 122 behavioral surveys, with and without HIV testing have used respondent-driven sampling (RDS), a technique that often yields a more representative sample. Some countries have collected multiple surveillance rounds, permitting valid trend analyses . Despite the potential of RDS, the methods for analyses of these data are complicated and still being modified . Other sampling methods such as venue-based (e.g., bars and brothels) and time-location sampling (e.g., identifying days and times when the target population gathers at specific venues) continue to be used for populations that congregate in identifiable locations [20,21].
The increased use of qualitative methods (e.g., focus groups and key informants interviews) to inform and enrich surveys represents another advance. Unfortunately, few formative ethnographic works [22,23] are published but these reports demonstrate that the understanding of behaviors in a cultural context can improve the implementation of behavioral surveys.
When data are collected in the general population or among high-risk groups, bias is always possible (e.g., recall and social desirability) and some biases may change over time, rendering interpretation of behavioral trends difficult. Newer survey techniques, such as audio computer-assisted self-interviews (ACASIs), may introduce less bias and can be used despite illiteracy and lack of computer experience .
Sexually transmitted infection (STI) surveillance should also be conducted because high levels of STIs may indicate high levels of risky sexual behavior, putting persons at risk of acquiring HIV . STI prevalence assessments should be incorporated into HIV prevalence surveys, especially in high-risk populations (MSM and FSWs) who acquire HIV through sex.
HIV surveillance of newly infected persons
HIV incidence is estimated in developing countries mostly by mathematical modeling, using data from prevalence surveys [26–28]. These models typically require many assumptions, (mortality rates, risk behaviors, and HIV-transmission probabilities). Since 2004, HIV incidence estimates using data from serological assays that detect recent HIV infections have been used more frequently. Current serologic assays are based on measurement of degrees of antibody maturation (quantitative, qualitative, or both). One such assay is the immunoglobin G capture BED enzyme immunoassay, BED-CEIA. This assay tends to misclassify a substantial proportion of persons with long-standing infection as recent, resulting in overestimations of HIV incidence [29,30]. The USA used BED-CEIA results and HIV case reports [which contains information on antiretroviral therapy (ART) treatment and length of infection] in combination with modeling to report HIV incidence, but low- and middle-income countries lack comprehensive HIV case reporting systems [31,32]. The BED-CEIA assay has been used in some sentinel surveillance and population-based surveys in low- and middle-income countries [33–37]. To avoid biased HIV incidence estimates using BED-CEIA, individuals known to be infected for many years, on ART, or with very low CD4 cell counts need to be identified and removed from the dataset. Locally appropriate adjustments should be made to account for misclassification of persons with long-standing HIV infection as incident [38–42].
Other laboratory assays to measure HIV incidence are being validated. Most of these assays are based on antibody avidity, the low sensitivity of the HIV test, or the order of appearance of antibodies to different proteins [43,44]. A two-test algorithm may be required to increase the accuracy of detecting recent HIV infections and incidence estimates.
Given the increased emphasis on early infant diagnosis and the scarcity of surveillance data among children, the development of national systems to report HIV cases among infants identified by laboratory diagnosis is a critical part of comprehensive HIV case reporting systems.
Among recently infected persons, the rate of transmitted HIV drug resistance (HIVDR) should be measured, especially in countries with extensive treatment coverage . At least seven countries have conducted threshold surveys to measure HIVDR. As of 2008, little or no resistance has been found [46–52].
HIV prevalence surveillance
AIDS case reporting was the standard for surveillance for the past two decades. Increased access to ART has reduced its utility except to monitor therapeutic failure or ability to access certain populations with therapy. Several different case definitions that did not coincide with clinical staging were used for case reporting. The WHO now recommends reporting HIV cases and advanced HIV infection. Since March 2006, WHO's recommended HIV case surveillance definition includes four clinical stages corresponding to clinical treatment determinations .
The number of low-income countries conducting HIV case reporting has not increased since the change of the case definition. New HIV testing policies and the scale-up of care and treatment should increase the number of people tested for HIV. HIV reporting can provide a good measure of the number of persons with HIV who will access healthcare, allowing countries to plan for the burden on their healthcare systems.
HIV sentinel surveillance among antenatal care (ANC) clients has been implemented since the late 1980s . This surveillance is recommended for countries with generalized epidemics  and entails using leftover blood from routine ANC testing, unlinking samples from identifying information and testing for HIV, referred to as unlinked anonymized testing (UAT). This procedure is typically done over a 12-week period.
The major advances in antenatal sentinel surveillance include the expansion of testing sites in urban and rural areas, increased sample size, and improvement in quality and analysis of these surveys [56•]. In 2003–2004, there were slightly more than 1000 ANC sentinel surveillance sites in 32 African countries. By 2005–2006, this figure rose to almost 2500 in 31 African countries .
Correct trend analysis is critical. Appropriate analyses include nonparametric methods (e.g., Paired Sign test and Wilcoxon sign-rank test) and linear regression applied to data from consistent sites to ensure that additional sites do not erroneously change reported national prevalence or random effects regression to data from all sites. Ideally, trend analysis uses more than one method.
Because prevention of mother-to-child transmission (PMTCT) services has increased, several studies [58–60] have examined the use of PMTCT HIV prevalence data in place of UAT ANC sentinel surveillance. These studies have found substantial variations in HIV prevalence between these data. PMTCT data are often of poor quality and cumbersome to use for surveillance purposes [3,61].
Since 2000, there has been an increase in countries conducting population-based surveys with HIV testing. Compared with ANC surveillance, these surveys are more geographically representative of the country, include more rural areas, larger age ranges, and men [62,63]. Since 2000, around 25 African countries have conducted such surveys . These surveys usually find lower HIV prevalence than that estimated by UAT ANC sentinel surveillance. In countries where most HIV transmission takes place in the general population, the HIV prevalence measured in these surveys is believed to be close to the true population level .
Population-based surveys with HIV testing are not useful to estimate HIV prevalence in settings in which HIV infection is concentrated in groups with high-risk behaviors  For example, Vietnam's Hai Phong province has very high HIV prevalence. Among IDUs (≈60%), but prevalence was 0.5% in a 2005 AIS.
With more countries conducting population-based surveys with HIV testing, associations between HIV status and reported behaviors can be analyzed, although interpretation of cross-sectional data must be undertaken cautiously. Behaviors of HIV-positive persons can also be examined more closely. Additional testing for infectious diseases relevant to HIV progression or coinfection (e.g., syphilis, hepatitis, and HSV2) were added to surveys in Kenya  and Uganda, and CD4 cell count was added in Kenya . HIV prevalence trends can be better assessed as countries repeat these surveys.
A majority of countries (140), representing approximately one-third of all persons living with HIV, have HIV epidemics concentrated in one or more subpopulations, typically MSM, IDUs, sex workers, or all. HIV surveillance of these groups is critical to a strong understanding of the epidemic, yet recent analyses show that major gaps in surveillance of these groups persist in many countries [56•]. Even in generalized epidemics tracking HIV among groups with high-risk behaviors is important because the higher HIV prevalence in these groups can influence the national epidemic. Since 2004, surveillance of high-risk groups frequently combines biological and behavioral data collection.
Morbidity, HIV drug resistance, and mortality surveillance
As more people access treatment and live longer, it is critical to monitor morbidity and mortality. HIVDR surveillance has expanded to include the monitoring of drug resistance among newly infected individuals to assess the transmission of drug-resistant virus and to examine resistance among patients undergoing treatment [67,68].
Surveillance for opportunistic infections, especially tuberculosis (TB), is critical to monitoring the quality and impact of treatment and prophylaxis. Although guidelines exist on HIV surveillance among TB patients, little has been done regarding other opportunistic infections. Instituting HIV or advanced HIV infection case reporting should allow for improved reporting and monitoring of morbidity.
Unfortunately, mortality surveillance has not improved. Although the methods to perform Sample Vital Registration with Verbal Autopsies have been elucidated in training materials, very few countries have implemented this system . Other sources of mortality data, such as burial and demographic surveillance sites, have little coverage and rarely parse out AIDS-related mortality [70,71]. Improving vital registration systems is critical to enhancing the understanding of causes of mortality, including HIV/AIDS and their trends.
Since 2004, HIV surveillance systems have expanded and improved considerably, providing more reliable data for modeling estimates of number of persons with HIV infection. There have been great advances in modeling estimates and projections since 2004. Joint United Nations Programme on HIV/AIDS (UNAIDS) Estimation and Projection Package (EPP), Workbook and Spectrum tools generate an HIV prevalence curve based on HIV prevalence data from surveillance, surveys, and special studies, and allow to estimate the number of people living with HIV, HIV incidence, ART needs, and orphanhood due to AIDS and mortality. Data from national surveys have been used in several countries with generalized epidemics to adjust HIV prevalence [72,73]. Findings from multiple studies have resulted in the increase in assumed time from seroconversion to ART eligibility and assumed median survival time from 9 to 11 years in most low and middle-income countries . These changes yielded a higher estimate of the number of people requiring ART . Improved methods have produced more appropriate plausibility ranges around the estimates .
One of the best ways for countries to guide their prevention programs is to examine where the newest infections arise. Analysis of data in Ghana and Benin showed a large proportion of adult male infections were likely due to sex with a commercial sex worker, whereas only 1% of World Bank prevention funding goes toward programs for sex workers . UNAIDS has led the development of an analytic tool to estimate HIV incidence by mode of transmission, which uses surveillance data, population size estimates, and transmission probabilities .
Triangulation, examining different surveillance and program data together, has been used in several countries to determine the overall trend of HIV prevalence and the reach and coverage of prevention programs based on these trends or the impact of ART programs on mortality [79,80].
Surveillance data should be used for impact evaluation by measuring the extent to which change in a population-based outcome can be attributed to program intervention. To this end, in November 2006, GFATM began to study the impact of its investments and those of other funding partners in reducing the health burden of HIV, TB, and malaria in select countries. The study uses HIV surveillance data and modeling to compare incidence, prevalence, mortality, and behavior change trends with changes in prevention and treatment program coverage .
One challenge of surveillance for HIV infection is to collect valid data while maintaining ethical standards of confidentiality and not harming individuals . The current debate focuses on the rights of persons to know their HIV test results when their blood is used for surveillance purposes, either knowingly or unknowingly . A component of the challenge is when and how to incorporate a program to return HIV test results with counseling. When conducting surveillance, governments should follow the Declaration of Helsinki, which states that individual autonomy should be respected; the endeavor should benefit the population, if not individuals, and no harm should be done .
The future of surveillance activities should concentrate on the implementation of sentinel surveillance in groups with high-risk behaviors in a large number of countries, improving methods to estimate HIV incidence, improving our ability to monitor trends in prevalence, implementing HIV infection, case reporting, using data from ART treatment programs, increasing mortality surveillance, and improving overall vital registration systems. Greater attention should be paid to improving the quality of behavioral survey instruments through cognitive research and anthropology, understanding risky behaviors, including concurrent sexual partnerships. Additionally, the introduction of social network data and analysis to further enrich surveillance data requires exploration. As more antiretroviral treatment and prophylaxis is provided to HIV-infected mothers, national-level information on mother-to-child HIV transmission rates and HIV treatment outcomes is urgently needed. It is vital to improve surveillance quality and emphasize local capacity building to collect, analyze, evaluate, and utilize data.
Countries should move away from basing programmatic decisions on narrow categories that have been used to classify epidemics in the past (e.g., generalized and concentrated), and instead focus on the local importance of different population groups for HIV transmission.
Finally, we must use data more effectively. We have entered a data-rich time in the history of this epidemic and we need to use the data to support decisions on resource allocation, program planning, and impact assessment.
In the past 5 years, there have been substantial improvements in the quantity and quality of HIV surveillance studies in resource-constrained countries. Challenges still exist in measuring incidence, morbidity, and mortality. Data have been used more frequently to plan for HIV care, treatment, and prevention activities, but given the substantial increase in data, more analyses and interpretation are needed.
References and recommended reading
Papers of particular interest, published within the annual period of review, have been highlighted as:
• of special interest
•• of outstanding interest
Additional references related to this topic can also be found in the Current World Literature section in this issue (p. 336).
1 Joint United Nations Programme on HIV/AIDS. Report on the Global HIV/AIDS Epidemic 2008; 2008. Report No. UNAIDS/08.2E/JC1510E.
2 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):S1–S8.
3 Hladik W, Masupu K, Roels T, et al
. Prevention of mother-to-child transmission and voluntary counseling and testing programme data: what is their utility for HIV surveillance? AIDS 2005; 19(Suppl 2):S19–S24.
4 Zaba B, Slaymaker E, Urassa M, Boerma JT. The role of behavioral data in HIV surveillance. AIDS 2005; 19(Suppl 2):S39–S52.
5 Diaz T, Loth G, Whitworth J, Sutherland D. Surveillance methods to monitor the impact of HIV therapy programmes in resource-constrained countries. AIDS 2005; 19(Suppl 2):S31–S37.
6 McDougal JS, Pilcher CD, Parekh BS, et al
. Surveillance for HIV-1 incidence using tests for recent infection in resource-constrained countries. AIDS 2005; 19(Suppl 2):S25–S30.
7 Calleja JM, Marum LH, Cárcamo CP, et al
. Lessons learned in the conduct, validation, and interpretation of national population-based HIV surveys. AIDS 2005; 19(Suppl 2):S9–S17.
8 Magnani R, Sabin K, Saidel T, Heckathorn D. Review of sampling hard-to-reach and hidden populations for HIV surveillance. AIDS 2005; 19(Suppl 2):S67–S72.
9 Martin R, Hearn TL, Ridderhof JC, Demby A. Implementation of a quality systems approach for laboratory practice in resource-constrained countries. AIDS 2005; 19(Suppl 2):S59–S65.
10 Pervilhac C, Stover J, Pisani E, et al
. Using HIV surveillance data: recent experiences and avenues for the future. AIDS 2005; 19(Suppl 2):S53–S58.
11 World Health Organization and Joint United Nations Programme on HIV/AIDS. Second generation surveillance of HIV; 2000. Report No. WHO/CDS/EDC/200.5, UNAIDS/00/03.
12 Garcia-Calljea JM, Couws E, Ghys PD. National population-based HV prevalence surveys in sub-Saharan Africa: results and implications for HIV and AIDS estimates. Sex Transm Infect 2006; 82(Suppl 3):iii64–iii70.
13 World Health Organization. Towards universal access: scaling HIV/AIDS priority interventions in the health sector – progress report 2008 [ISBN 9789241596886]; 2008.
14 Abudul-Quader AS, Heckathorn D, Sabin K, Saidel T. Implementation and analysis of respondent driven sampling: lessons learned from the field. J Urban Health 2006; 83(Suppl):i1–i5.
15 Milean S, Johnston LG, Baros S, et al
. Exposing barriers to ‘Respondent driven sampling’ in sex worker and drug injecting sex worker populations in Eastern Europe. J Urban Health 2006; 83(Suppl):i6–i15.
16 Johnston LG, Sabin K, Hien MT, Hunon PT. Assessment of respondent driven sampling for recruiting female sex workers in two Vietnamese cities: reaching the unseen sex worker. J Urban Health 2006; 83(Suppl):i16–i28.
17 Yeja W, Maibani-Michele G, Prybylski D, Colby D. Application of respondent driven sampling to collect baseline data on FSWs and MSM for HIV risk reduction intervention in two urban centers in Papua, New Guinea. J Urban Health 2006; 83(Suppl):i60–i72.
18 Malekinejad M, Johnston LG, Kendall C, et al
. Using respondent-driven sampling methodology for HIV biological and behavioral surveillance in international settings: a systematic review. AIDS Behav 2008; 12(4 Suppl):S105–S130.
19 Johnston LG, Malekinejad M, Kendall C, et al
. Implementation challenges to using respondent-driven sampling methodology for HIV biological and behavioral surveillance: field experiences in international settings. AIDS Behav 2008; 12(4 Suppl):S131–S141.
21 Saidel T, Adhikang R, Mainkarm M, et al
. Baseline integrated behavioural and biological assessment among most at-risk populations in six high-prevalence states of India: design and implementation challenges. AIDS 2008; Suppl 5:S17–S34.
22 Sabin M, Luber G, Paredes M, Monterroso E. Rapid ethnographic assessment of HIV/AIDS among Garífuna communities in Honduras: informing HIV surveillance among Garífuna women. J Hum Behav Social Environ 2008; 17:237–257.
23 Gallagher KM, Denning PD, Allen DR, et al
. Use of rapid behavioral assessments to determine the prevalence of HIV risk behaviors in high-risk populations. Public Health Rep 122(S1):56–62.
24 NIMH Collaborative HIV/STD Prevention Trial Group. The feasibility of audio computer-assisted self-interviewing in international settings. AIDS 2007; 21 (Suppl 2):S49–S58.
25 UNAIDS/WHO Global Working Group on HIV/AIDS/STI Surveillance. Guidelines for sexually transmitted infections surveillance; 1999. Report No. WHO/CDS/CSR/EDC/99.3.
26 Hallett TB, Zaba B, Todd J, et al
. Estimating incidence from prevalence in generalised HIV epidemics: methods and validation. PLoS Med 2008; 5:e80.
27 Stoneburner RL, Low-Beer D, Tembo GS, et al
. Human immunodeficiency virus infection dynamics in east Africa deduced from surveillance data. Am J Epidemiol 1996; 144:682–695.
28 Heyward WL, Osmanov S, Saba J, et al
. Preparation for phase III HIV vaccine efficacy trials: methods for the determination of HIV incidence. AIDS 1994; 8:1285–1291.
29 Murphy G, Parry JV. Assays for the detection of recent infections with human immunodeficiency virus type 1. Euro Surveill 2008; 13. pii: 18966.
30 Le Vu S, Pillonel J, Semaille C, et al
. Principles and uses of HIV incidence estimation from recent infection testing: a review. Euro Surveill 2008; 13. pii: 18969.
31 Karon JM, Song R, Brookmeyer R, et al
. Estimating HIV incidence in the United States from HIV/AIDS surveillance data and biomarker HIV test results. Stat Med 2008; 27:4617–4633.
32 Hall HI, Song R, Rhodes P, et al
. Estimation of HIV incidence in the United States. JAMA 2008; 300:520–529.
33 Rehle T, Shisan O, Pillay V, et al
. National HIV incidence measures: new insights into the South African epidemic. S Afr Med J 2007; 97:194–199.
34 Jian Y, Wan M, Ni M. HIV-1 incidence estimates using IgG-capture BED-enzyme immunoassay from surveillance site of injection drug users in three cities of China. AIDS 2007; 21(Suppl 8):S47–S51.
35 Wolday D, Meles H, Hailu E, et al
. Temporal trends in the incidence of HIV infections in antenatal clinic attendees in Addis Ababa, Ethiopia, 1995–2003. J Intern Med 2007; 261:132–137.
36 Saphonn V, Parekh BS, Dobbs T, et al
. Trends of HIV-1 seroincidence among HIV-1 sentinel surveillance groups in Cambodia, 1999–2002. J Acquir Immune Defic Syndr 2005; 39:587–592.
37 Mermin J, Musinguzi J, Opio A, et al
. Risk factors for recent HIV infection in Uganda. JAMA 2008; 300:540–549.
38 Sakarovitch C, Rouet F, Murphy G, et al
. Do tests devised to detect recent HIV-1 infection provide reliable estimates of incidence in Africa? J Acquire Immune Defic Syndr 2007; 45:115–122.
39 Karita E, Price M, Hunter E, et al
. Investigating the utility of the HIV-1 BED capture enzyme immunoassay using cross-sections and longitudinal seroconverter specimens from Africa. AIDS 2007; 21:403–408.
40 Bärnighausen T, Wallrauch C, Welte A, et al
. HIV incidence in rural South Africa: comparison of estimates from longitudinal surveillance and cross-sectional BED assay testing. PLoS ONE 2008; 3:e3640.
41 Hargrove JW, Humphrey JH, Mutasa K, et al
. Improved HIV-1 incidence estimates using the BED capture enzyme immunoassay. AIDS 2008; 22:511–518.
42 McDougal JS, Parekh BS, Peterson ML, et al
. Comparison of HIV Type 1 incidence observed during longitudinal follow-up with incidence estimated by cross-sectional analysis using the BED capture enzyme immunoassay. AIDS Res Hum Retroviruses 2006; 22:945–952.
43 Loschen S, Batzing-Feigenbaum J, Poggensee G. Comparison of the human immunodeficiency virus (HIV) type 1-specific immunoglobulin G capture enzyme-linked immunosorbent assay and the avidity index method for identification of recent HIV infections. J Clin Microbiol 2008; 46:341–345.
44 Schupbach J, Gebhardt MD, Tomasik Z. Assessment of recent HIV-1 infection by a line immunoassay for HIV-1/2 confirmation. PLoS Med 2007; 4:e347.
45 Bennett DE, Myatt M, Bertagnoli S, et al
. Recommendations for surveillance of transmitted HIV drug resistance in countries scaling up antiretroviral treatment. Antivir Ther 2008; 13(Suppl 2):25–36.
46 Somi GR, Kibuka T, Dialio K, et al
. Surveillance of transmitted HIV drug resistance among women attending antenatal clinics in Dar es Salaam, Tanzania. Antivir Ther 2008; 13(Suppl 2):77–82.
47 Kamot K, Aberle-Grasse J, Malawi HIV Drug Resistance Task Force. Surveillance of transmitted HIV drug resistance with the World Health Organization threshold survey method in Lilongwe, Malawi. Antivir Ther 2008; 13(Suppl 2):83–87.
48 Abegaz WE, Grossman Z, Wolday D, et al
. Threshold survey evaluation of transmitted HIV drug resistance among public antenatal clinic clients in Addis Ababa, Ethiopia. Antivir Ther 2008; 13(Suppl 2):89–94.
49 Maphalal G, Okell V, Mndzebele S, et al
. Surveillance of transmitted HIV drug resistance in the Manzini-Mbabane Corridor, Swaziland, in 2006. Antivir Ther 2008; 13(Suppl 2):95–100.
50 Pillay V, Ledwaba J, Hunt G, et al
. Antiretroviral drug resistance surveillance among drug-naïve HIV-1-infected individuals in Gauteng Province, South Africa 2002 and 2004. Antivir Ther 2008; 13(Suppl 2):101–107.
51 Sirivichayakul S, Phanuphak P, Pankam T, et al
. HIV drug resistance transmission threshold survey in Bangkok, Thailand. Antivir Ther 2008; 13(Suppl 2):108–112.
52 Nguyen HT, Bui Duc N, Shrivastava R, et al
. HIV drug resistance threshold survey using specimens from voluntary counselling and testing sites in Hanoi, Vietnam. Antivir Ther 2008; 13(Suppl 2):115–121.
54 World Health Organization/Global Program on AIDS. Field guidelines for HIV sentinel surveillance: a manual for national AIDS control programmes. Geneva, Switzerland: WHO; 1989.
55 WHO/UNAIDS. Technical guidelines for conducting HIV sentinel serosurveys among pregnant women and other groups. Geneva: Centers for Disease Control and Prevention/WHO/UNAIDS; 2003.
56• 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(Suppl 1):85–91. This paper describes the most recent analysis of the quality of serosurveillance systems in low- and middle-income countries, documenting improvements and expansion of HIV surveillance throughout the world.
57 World Health Organization, Regional Office for Africa. Epidemiological surveillance report for the WHO African Region 2007 update [ISBN 9789290231059]; 2008.
58 Bolu O, Anand A, Swartzendruber A, et al
. Utility of antenatal HIV surveillance data to monitor and evaluate prevention of mother-to-child HIV transmission programs in resource-limited settings. Am J Obstet Gynecol 2007; 197(Suppl):S17–S24.
59 Fabiani M, Yoti Z, Nattabi B, et al
. Adjusting HIV prevalence data from a program for the prevention of mother-to-child transmission for surveillance purposes in Uganda. J Acquire Immune Defic Syndr 2007; 46:328–331.
60 Mpairwe H, Muhangi L, Namujju PB, et al
. HIV risk perception and prevalence in a program for prevention of mother-to-child HIV transmission: comparison of women who accept voluntary counseling and testing and those tested anonymously. J Acquir Immune Defic Syndr 2005; 39:354–358.
61 Seguy N, Hladik W, Munyisia E, et al
. Can data from program for the prevention of mother-to-child transmission of HIV be used for HIV surveillance in Kenya? Public Health Rep 2006; 121:695–702.
62 Gouws E, Mishra V, Fowler TB. Comparison of adult HIV prevalence from national population-based surveys and antenatal clinic surveillance in countries with generalised epidemics: implications for calibrating surveillance data. Sex Transm Infect 2008; 84(Suppl 1):i17–i23.
63 Montana LS, Mishra V, Hong R. Comparison of HIV prevalence estimates from antenatal care surveillance and population-based surveys in sub-Saharan Africa. Sex Transm Infect 2008; 84:i78–i84.
64 Garcia-Callej JM, Gouws E, Ghy PD. National population-based HIV prevalence surveys in Sub-Saharan Africa: results and implications for HIV and AIDS estimates. Sex Transm Infection 2006; 82(Suppl 3):iii64–iii70.
65 Mishra V, Barrere B, Hong R, Khan S. Evaluation of bias in HIV seroprevalence estimates from national household surveys. Sex Transm Infect 2008; 84:i63–i70.
66 National AIDS and STI Control Programme Ministry of Health, Kenya. AIDS Indicator Survey 2007, preliminary report; 2008; Nairobi, Kenya.
67 Jordan MR, Benett DE, Bertagnolio S, et al
. World Health Organization surveys to monitor HIV drug resistance prevention and associated factors in sentinel antiretroviral treatment sites. Antivir Ther 2008; 13(Suppl 2):15–23.
68 Bennett DE, Myatt M, Bertagnolio S, et al
. Recommendations for surveillance of transmitted HIV drug resistance in countries scaling up antiretroviral treatment. Antivir Ther 2008; 13(Suppl 2):25–36.
69 Baiden F, Bawah A, Biai S, et al
. Setting international standards for verbal autopsy. Bull WHO 2007; 85:569–648.
70 Sanders E, Araya T, Kebede D, et al
. Mortality impact of AIDS in Addis Ababa, Ethiopia [abstract #TuPeC4694]. Int Conf AIDS 7–12 July; 2002. p. 14.
71 Baiden F, Hodgson A, Binka FN. Demographic surveillance sites and emerging challenges in international health. Bull WHO 2006; 84:161–256.
72 Ghys PD, Walker N, McFarland W, et al
. Improved data, methods and tools for the 2007 HIV and AIDS estimates and projections. Sex Transm Infect 2008; 84:i1–i4.
73 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:i5–i10.
74 The eligibility for ART in lower income countries (eART-linc) collaboration. Duration from seroconversion to eligibility for antiretroviral therapy and from ART eligibility to death in adult HIV-infected patients from low and middle-income countries: collaborative analysis of prospective studies. Sex Transm Infect 2008; 84:i31–i36.
75 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.
76 Alkema L, Raftery AE, Brown T. Bayesian melding for estimating uncertainty in national HIV prevalence estimates. Sex Transm Infect 2008; 84:i11–i16.
78 Gouws E, White PJ, Stover J, Brown T. Short term estimates of adult HIV incidence by mode of transmission: Kenya and Thailand as examples. Sex Transm Infect 2006; 82(Suppl 3):iii51–iii55.
79 World Health Organization and Joint United Nations Programme on HIV/AIDS and Global Fund for HIV, TB and Malaria. HIV triangulation resource guide. WHO/UNAIDS; 2008.
80 Republic of Malawi. Report of the Malawi Triangulation Project. Version 17; November 2006.
81 The Global Fund to fight AIDS, Tuberculosis and Malaria. Technical background document on the scale and scope of five-year evaluation; 2006.
83 Rennie S, Turner AN, Mupend B, Behets F. Conducting unlinked anonymous HIV surveillance in developing countries: ethical, epidemiological, and public health concerns. PLoS Med 2008; 6:30–34.
84 World Medical Association Declaration of Helsinki. Ethical principles for medical research involving human subjects (first adopted by the 18th WMA General Assembly, Helsinki, Finland; June 1964), amended in 1975, 1983, 1989, 1996, 2000, 2002, 2004, 2008. http://www.wma.net/e/policy/b3.htm
. [Accessed 18 Nov. 2008].