Phase 1 Summary
The project aims to maximise the usefulness of data collected by HIV study sites established in nine African communities. These studies have made repeated measurements of the HIV status of people living in well-defined geographical areas; recorded mortality, fertility and migration rates; and described trends in sexual behaviour, family composition and socio-economic consequences of the epidemic. Each site has independently developed its own data collection methods and a specific research agenda.
Analyses produced in one study are replicated using data from the others, showing whether findings are generalisable across different communities or peculiar to specific localities. The collaborative network trains local statisticians working in member studies in advanced analysis techniques, and will communicate research findings to policy makers in each country.
In addition, studies pool their data to generate powerful new information on infection patterns, risks and social consequences for national AIDS control programmes and agencies involved in forecasting epidemic spread and designing interventions.
In phase 1, studies included:
- Age patterns of HIV incidence, life time risk of infection
- Impact of HIV on evolution of family structure
- "Net" mortality from HIV and survival post infection
- Sexual behaviour and marriage
- Uptake of Voluntary Counselling and Testing and Anti-Retroviral Therapy for HIV
Studies planned for phase 2 include:
- The impacts of HIV on fertility
- Impact on mobility of children
- Child mortality and paediatric HIV
- Investigations of the impact of anti-retroviral therapy on mortality and new infection rates
- Description of sexual partnership formation and dissolution
The long-term aim of the ALPHA network is to maximise the usefulness of data generated in community-based longitudinal HIV studies in sub-Saharan Africa with respect to the needs of national and international agencies involved in planning interventions to prevent the spread of HIV or mitigate its consequences 1 ,2. It also generates information for use by modellers involved in forecasting epidemic trends and demographic consequences 3 ,4 . This is achieved by linking existing HIV cohort studies, facilitating replication of analyses previously undertaken by individual sites, and undertaking meta-analysis of pooled data to detect underlying regularities in spatial, temporal and demographic patterns of infection and behavioural risk factors.
We use existing data, employing methods geared to the availability of repeated measures on well characterised individuals, which identify and exploit family linkages. Study leaders in ALPHA member sites can learn about survey instruments and protocols used elsewhere and thereby improve their own data collection procedures. Our disciplinary focus is demographic, concentrating on the inter-action between HIV infection and mortality, fertility, partnership and household formation, and population mobility.
The project has two important subsidiary aims: building capacity among local scientists with respect to analytical, statistical and communication skills; and the development and maintenance of a pooled data set. This data set is edited and cleaned ready for use (formatted in the widely used statistical computing package, Stata 5 ), and is shared by member sites, facilitators and outside collaborators, to allow meta-analyses and development of new exploratory investigations.
The ALPHA network started in 2005 , with five HIV cohorts: the Kyamulibwa general population cohort managed by MRC/UVRI in the Masaka district of Uganda ; the Kisesa open cohort managed by the TAZAMA programme at NIMR (Mwanza), Tanzania ; the Karonga Prevention Study in Northern Malawi managed by LSHTM ; the Manicaland Study in Eastern Zimbabwe managed by Imperial College and the Blair Research Training Institute ; and the Umkhanyakude cohort in Hlabisa district managed by the Africa Centre in KwaZulu Natal, South Africa . The Rakai study, managed by Makerere University and Johns Hopkins School of Public Health joined in 2006 . Two recently established HIV cohort studies from Kenya will join the network at the start of the next phase: the Nairobi urban cohort study operated by the Africa Population Health Research Centre  and the CDC/KEMRI study site in Kisumu .
It is a mark of the success and reputation of the ALPHA network that all existing African HIV cohort studies have joined or are about to join. We have already been approached by two demographic surveillance sites that recently obtained funding for HIV surveillance, and wish to join as soon as they have the necessary data: one in Tanzania - the Kilombero cohort operated by the Ifakara Health Institute , and one in South Africa – the Agincourt study in Mpumalanga Province .
Prior to forming the network, member sites were individually responsible for important advances in knowledge about the spread of HIV in Africa [17 -25], risk factor epidemiology [26 -36], evaluation of prevention and care strategies [37 -40] and development of field and analytical methodology [41 -45]. They therefore bring important scientific experience to the network – updating these historical analyses and replicating them in the other member sites is made possible by senior scientists from these sites acting as workshop facilitators.
Analysis workshops are the core activity of the network, bringing together junior researchers from all the member sites, with senior staff from host sites where specific topics have been researched to a greater depth in the past, and with facilitators from LSHTM. The facilitators prepare for the workshops by studying past publications and evaluating the data currently available at each member site. For each workshop topic they propose a set of basic analyses that can be replicated across the sites, and develop data specifications that are circulated to the member sites to enable them to prepare the required data in a common format. The facilitators develop teaching materials explaining the statistical methods used, and express the theoretical procedures in Stata programming code in such a general way that it can be applied to all the ALPHA site data sets.
Workshops start with short presentations by participants explaining how their site collects data on a particular topic, and summarising relevant past publications. These are followed by teaching sessions in which the epidemiological problems are considered, the statistical theory is explained, and the Stata code is clarified. Participants then work analyse data from their own sites, helped by the facilitators. They present and contrast results across sites, and a pooled data set is formed if the data from each site prove to be truly comparable and of high enough quality. A plan is agreed for comparative and meta analyses and a publication plan is adopted. Teaching materials (presentations, lecture notes, statistical analysis programmes and collections of sample questionnaires) are available to members through our web site  after each workshop.
The ALPHA network conducted five analytical workshops, attended by forty participants from the member sites, most of whom came to two or more workshops. LSHTM provided four workshop facilitators, and a further seven facilitators came from senior staff working for the member sites. Seven guest participants from studies outside of the ALPHA network attended selected workshops. Outputs from the first four workshops include 44 papers published in scientific journals, and 14 conference presentations and posters. Two special journal issues have been devoted to ALPHA publications: supplement 6 of vol. 21 of AIDS (2007) about AIDS mortality; and supplement 1 of vol. 85 of STI (2009) about sexual behaviour. A third special issue is currently being negotiated with the Journal of the International AIDS Society to cover the outputs of the final workshop on uptake of Voluntary Counselling and Testing (VCT) and access to Anti-Retroviral Therapy (ART).
Studies initiated during our HIV incidence workshop built on analyses previously carried out in Kisesa, and showed that changes in numbers infected due to population mobility were generally larger than changes due to new infections or deaths of infected residents [46 -48]. This finding cautions against using prevalence change in small geographical areas, or catchment sites of surveillance clinics, as a surrogate measure for incidence. However, at a national level, where migratory change is generally negligible, prevalence change can be a useful guide to incidence, provided suitable adjustments are made for HIV-related mortality in the interval. Simple, spreadsheet-based procedures for making these estimates were developed collaboratively by the ALPHA sites and published electronically in an open-access format  to enable national statistical offices and AIDS control programmes to use these methods instead of relying on more complex models that ignore national evidence on HIV age patterns.
Our joint incidence study also showed that the age-sex distribution of HIV incidence followed a common pattern at young ages in all the ALPHA sites, but with larger inter-site variation at older ages. By applying hazard analysis tools demonstrated in the workshops, secondary incidence peaks were discovered in many sites, at older ages, for both sexes . We found that in the four longest running sites (Kyamulibwa, Rakai, Kisesa and Manicaland) the age dispersion of incidence became wider over time, contrary to expectations that infection of the more susceptible sub-populations with high risk behaviour early in the epidemic would cause the incidence age distribution to become narrower. This has prompted a new look at risk factors affecting all age groups [51 -53], rather than focussing only on young people.
The second workshop on HIV impacts on households, built on earlier work done at the Africa Centre [54 -56] and developed a new typology of household structure that has since been applied in member sites [57 -61], particularly in the analysis of the family structure of households bringing up orphan children. Our joint analysis showed that child headed households were extremely rare and short lived, and that even skipped generation households were uncommon. This finding is at odds with the preoccupations of many NGOs that set out to deliver care to HIV affected households, and points to a need for revising the priorities of support programmes which miss the majority of HIV affected households by focussing mainly on these very rare household types.
Furthermore, we found that many children of living HIV infected parents lived apart from their natural parents, cared for by other relatives, pointing to the need to investigate family and household circumstances of such children before the death of their parents. Households providing foster care to children with living HIV infected parents are affected by HIV even if they contain no HIV infected members. Longitudinal studies such as those of the ALPHA network can identify these affected households, but they cannot be identified in cross-sectional surveys using simple questions on orphanhood, or HIV status of adult members. This suggests that surveys such as the international Demographic and Health Survey (DHS) programme should expand their orphanhood questions to record place of residence of living parents, and a further question should be considered regarding non-co-resident parents to find out whether they contribute to the support of the child, or if they are unable to do so because of illness. This would help further in the appropriate targeting of assistance to households caring for non-orphaned needy children.
Our workshop on survival following HIV infection was hosted in Entebbe by the MRC/UVRI study, which had previously done the most work on this topic in their Kyamulibwa cohort [62 ,63], although findings from other ALPHA sites on mortality differentials between infected and uninfected persons [64 -66] were also important in structuring our ensuing studies. This workshop was co-sponsored by UNAIDS , to allow for the involvement of occupational  and clinic based cohorts , including some from Thailand and Haiti [70 ,71], since it was felt that accurate determination of infection time was more important than selection from a community based study in identifying factors determining survival.
Site specific [72 -74] and meta analyses [75 -77] of survival published as a result of this workshop showed that median survival times in community, clinical and occupational cohorts in Africa, ranging from 9 to 11 years, were comparable to survival times in developed countries before the advent of Highly Active Anti-Retroviral Therapy (HAART), and considerably higher than median survival times in Thailand and Haiti (around 7 years). This has prompted a renewed interest in research into host- and viral- genetic factors as determinants of disease progression , to verify the findings from the Rakai site suggesting that sub-type A is associated with slower progression, and sub-type D with faster progession.
All our analyses confirmed that age at infection was the most important determinant of survival, with persons infected after 45 experiencing nearly five times the mortality rates of those infected before age 25. Median survival time for those infected after age 45 was under 6 years, whereas for those infected before age 25 it was nearly 13 years. Similar findings concerning age at infection had been reported in earlier developed country studies, but these assumed that background mortality from non-HIV related causes could be ignored. Since developing countries experience much heavier all cause adult mortality, the ALPHA network developed a new method for estimating net mortality (eliminating the impact of mortality from non-HIV related causes)  which demonstrated conclusively that the accelerated deterioration in the health of older people infected with HIV was not simply a consequence of increased mortality at older ages due to other causes. The development of net mortality methods also provides a way of comparing HIV-related mortality across countries with different levels of background mortality.
The ALPHA network also published new site specific and pooled estimates of age specific mortality for persons infected by HIV [80 -82]. This showed an unexpected regularity in patterns across sites, with no impact of sex or age at infection – only epidemic maturity was identified as an important determinant of age specific HIV mortality, with an impact on overall level but not on pattern. Age-specific mortality schedules described by ALPHA are now used as input into population projection programmes by the UN population division . The survival analysis outputs of this workshop formed a major input into the methods used by UNAIDS for estimating and projecting the scale of the HIV epidemic and contributed to the downward revision of the numbers of HIV infected persons in Africa in the 2007 AIDS epidemic update [84 ,85]
The workshop on sexual behaviour built on work done earlier in Manicaland [88 -91], and developed new methods for assessing quality and consistency of sexual behaviour reports [92 ,93], focussing in particular on age at sexual debut, subsequent age patterns of partner acquisition, and age at first marriage. The number of life time partners reported by men in Southern Africa went down over time when successive birth cohorts were compared at the same ages, but this favourable change was not seen in the East African cohort studies.
We discovered that in general female reports of age at sexual debut were more consistent than male reports, and that reporting of age at first marriage was less consistent than reporting of age at first sex [94 -104]. This finding brings into question the widely accepted practice (e.g. in analysis of DHS data ) of correcting reported age at first sex to conform with age at first marriage. In fact the pattern of reporting inconsistencies for age at first sex (identified by comparing reports obtained in successive survey rounds) suggested that they were due to random misdating of events, introducing noise rather than bias into cohort estimates of median age at sexual debut.
In general, age at first sex decreased for men, whilst age at first marriage increased, lengthening the time spent single but sexually active. In most study sites time spent single but sexually active by women also increased, mainly because age at first marriage increased faster than age at first sex. The time between sexual debut and marriage was a high risk time, especially for men, since new sexual partners are acquired at a more rapid rate than at other times in the life cycle. Cross-country comparisons were also made of the age at which the second sexual partner is acquired, as this corresponds to the age at which an individual becomes capable of transmitting HIV to a sexual partner . The majority of men and women make this second transition in their 20s, but in contrast to sexual debut, second partner acquisition occurs earlier in men. Women continue to acquire second partners at ages over 30, in many women this corresponds to re-marriage.
First marriages commencing at older ages tended to be more stable than those between younger individuals , so there may be a trade-off between periods of high risk behaviour (rapid rates of new partner acquisition) at younger and older ages when people re-enter the “marriage market” following widowhood and divorce. This has prompted further study of risk behaviour in older cohort members [96 ,107 ,108]. However, when these aspects of sexual behaviour were compared across sites they did not explain the evolution or severity of the epidemic in different settings .
The final workshop dealt with VCT and ART uptake, building on earlier work in Karonga and preparatory analyses in Kisesa [110 -113]. Our subsequent analyses based on methods developed at the workshop [114 ,115] show that VCT uptake has increased dramatically since ART became available, with most of the ALPHA sites reporting a doubling of the proportion who know their HIV status during the last 8 years. Sites that approach study participants in their own homes achieve a higher rate of VCT uptake, and the switch to “rapid” test kits (whereby the result is available within half an hour rather than the following day) has also been associated with increased VCT uptake.
Many of the ALPHA member sites had earlier conducted HIV testing rounds in which participants had the option of not being informed of the test result – this makes it possible to compare uptake of VCT among infected and uninfected study subjects. We found that VCT uptake was higher among infected people in all the ALPHA sites. From a programmatic point of view this is good news, as infected persons can only be referred to clinics providing ART after they have undergone VCT.
Surprisingly, many sites showed that infected persons were more likely than uninfected persons to repeat VCT – qualitative work in selected sites suggest that this is due to disbelief and denial after the first test, and to persons wishing to test the claims of traditional healers and charismatic preachers to have cured them of the disease. The findings that VCT testing patterns are strongly influenced by HIV status caution against the naive use of data from VCT test centres in disease surveillance – this has been communicated to UNAIDS and may lead to further modelling work about interpreting test result trends from VCT clinics allowing for repeat testing patterns.
The ALPHA network has developed methods of assessing population level ART need by applying the age specific mortality patterns described in the earlier workshop to the age distribution of infected persons, assuming that ART should be started three years before the expected death of an infected person. This enables sites to compare observed ART access with estimated need. The results show that proportions needing treatment are highest among older infected individuals, who have the highest HIV-related mortality rates.
The biggest barrier to accessing ART remains the initial step of agreeing to VCT, but comparing results obtained by ALPHA sites that could follow individuals through the process of testing and referral, we discovered that inefficient referral systems, delays in referral uptake and failure to return for repeat CD4 assessment by those not yet eligible for treatment all contribute to lower than expected uptake of ART. In general, infected persons who lived in more remote areas and older people were found to have lower rates of uptake of ART, and to experience longer delays between referral and ART clinic visit than younger people living closer to the clinics.
Finally, workshop participants measured the community-level mortality impact of introducing ART, and sites were able to demonstrate a convincing fall in mortality amongst HIV-infected people compared to the pre-ART era, a temporal change that was not echoed in mortality of uninfected persons. This is a very important positive message that National AIDS Control Programmes (NACP) will want to use to encourage more people to undergo VCT and to take up ART referrals.
Entries in bold type are outputs from phase one of the ALPHA network, 2005-09
Background and Uses of ALPHA Data
2. Maher D, Biraro S, Hosegood V, Isingo R, Lutalo T, Mushati P, Ngwira B, Nyirenda M, Todd J, Zaba B on behalf of the collaborators in the ALPHA network. Translating global health research aims into action: the example of the ALPHA network. TMIH in press 2009
3. Walker N, Stanecki KA, Brown T, Stover J, Lazzari S, Garcia-Calleja JM, Schwartländer B, Ghys PD. Methods and procedures for estimating HIV/AIDS and its impact: the UNAIDS/WHO estimates for 2001. AIDS. 2003;17(15):2215-25.
4. Stover J, Johnson P, Zaba B, Zwahlen M, Dabis F, Ekpini R. The Spectrum projection package: improvements in estimating mortality, ART needs, PMTCT impact and uncertainty bounds. STI, Aug 2008. 84 Suppl I:i24-i30
Network and Member Study Websites
17. Kengeya-Kayondo JF, Kamali A, Nunn AJ, Ruberantwari A, Wagner HU, Mulder DW. 1996. Incidence of HIV-1 infection in adults and socio-demographic characteristics of seroconverters in a rural population in Uganda : 1990-94. Int J Epid. 25(5):1077-82.
18. Boerma JT, Urassa M, Senkoro K, Klokke A, Zaba B, Ng'weshemi JZL. 1999. Spread of HIV infection in a rural area in Tanzania . AIDS 13: 1233-1240.
19. Glynn JR, Pönnighaus JM, Crampin AC, Sibande F, Sichali L, Nkhosa P, Broadbent P, Fine PEM. The development of the HIV epidemic in Karonga District, Malawi . AIDS 2001; 15: 2025-2029.
20. Crampin AC, Glynn JR, Ngwira BMM, Mwaungulu FD, Pönnighaus JM, Warndorff DK, Fine PEM. Trends and measurement of HIV prevalence in northern Malawi , 1988-2001. AIDS 2003; 17: 1817-1825.
21. Gregson S; Mason PR; Garnett GP; Zhuwau T; Nyamukapa CA; Anderson RM; Chandiwana SK. (Mar 2001). A rural HIV epidemic in Zimbabwe ? Findings from a population-based survey. Int J STD AIDS. 12:189-196.
22. Welz T, Hosegood V, Jaffar S, Batzing-Feigenbaum J, Herbst K, and Newell ML. Continued very high prevalence of HIV infection in rural KwaZulu-Natal, South Africa: a population-based longitudinal study. AIDS, 2007. 21(11): p. 1467-1472.
23. Travers SA, Clewley JP, Glynn JR, Fine PEM, Crampin AC, Sibande F, Mulawa D, McInerney JO, McCormack GP. Timing and Reconstruction of the most recent common ancestor of the subtype C clade of Human Immunodeficiency Virus Type 1. Journal of Virology 2004; 78: 10501-10506.
24. McCormack GP, Glynn JR, Crampin AC, Sibande F, Mulawa D, Bliss L, Broadbent P, Abarca K, Pönnighaus JM, Fine PEM, Clewley JP. Early evolution of the Human Immunodeficiency Virus type 1 subtype C epidemic in rural Malawi . Journal of Virology 2002; 76: 12890-12899.
25. Steain MC, Wang B, Yang C, Shi YP, Nahlen B, Lal RB, Saksena NK. HIV type 1 sequence diversity and dual infections in Kenya . AIDS Res Hum Retroviruses. 2005 Oct;21(10):882-5.
Risk Factor Studies
26. Whitworth JA, Biraro S, Shafer LA, Morison LA, Quigley M, White RG, Mayanja BN, Ruberantwari A, Van der Paal L. HIV incidence and recent injections among adults in rural southwestern Uganda. AIDS. 2007 May 11;21(8):1056-8
27. Lieve VP, Shafer LA, Mayanja BN, Whitworth JA, Grosskurth H. Effect of pregnancy on HIV disease progression and survival among women in rural Uganda. Trop Med Int Health. 2007 Aug;12(8):920-8.
28. Quigley MA, Hewitt K, Mayanja B, Morgan D, Eotu H, Ojwiya A, Whitworth JA. The effect of malaria on mortality in a cohort of HIV-infected Ugandan adults. Trop Med Int Health. 2005 Sep;10(9):894-900.
29. Kamali A, Carpenter LM, Whitworth JAG, Pool R, Ruberantwari A and Ojwiya A. (2000) Seven-year trends in HIV-1 infection rates, and changes in sexual behaviour among adults in rural Uganda AIDS vol 14 pp: 427-434
30. Mwaluko G, Urassa M, Isingo R, Zaba B, Boerma JT. Trends in HIV and sexual behaviour in a longitudinal study in a rural population in Tanzania, 1994-2000. AIDS. 17(18):2645-2651, Dec, 2003.
32. Urassa M, Kumogola Y, Isingo R, Mwaluko G, Makelemo B, Mugeye K, Calleja T, Slaymaker E, Zaba B. HIV prevalence and sexual behaviour changes measured in an Ante-Natal Clinic setting in northern Tanzania . STI 2006; 82(4):301-306
33. Kishamawe C, Vissers D, Urassa M, Isingo R, Mwaluko G, Borsboom G, Voeten H, Zaba B, Habbema J, de Vlas S. 2006. Mobility and HIV in Tanzanian couples: both mobile persons and their partners show increased risk. AIDS, 20(4):601-608
34. Barnighausen, T., et al., The socioeconomic determinants of HIV incidence: a population-based study in rural South Africa . AIDS, 2007. 21(supp 17): p. S29-S38.
35. van Eijk AM, Ayisi JG, Ter Kuile FO, Slutsker L, Shi YP, Udhayakumar V, Otieno JA, Kager PA, Lal RB, Steketee RW, Nahlen BL. HIV, malaria, and infant anemia as risk factors for postneonatal infant mortality among HIV-seropositive women in Kisumu, Kenya . J Infect Dis. 2007 Jul 1;196(1):30-7.
36. Boerma JT; Gregson S; Nyamukapa C; Urassa M. 2003. Understanding the uneven spread of HIV within Africa: comparative study of biologic, behavioral, and contextual factors in rural populations in Tanzania and Zimbabwe . Sex Transm Dis. 30:779-787.
Evaluation of Prevention and Care Strategies
37. Pickering JM, Whitworth JA, Hughes P, Kasse M, Morgan D, Mayanja B, Van der Paal L, Mayaud P. Aetiology of sexually transmitted infections and response to syndromic treatment in SW Uganda. Sex Transm Infect. 2005 Dec;81(6):488-93.
38. Mshana G, Wamoyi J, Busza J, Zaba B, Urassa M. Barriers to accessing antiretroviral therapy in Kisesa, Tanzania: a qualitative study of early rural referrals to the national programme. AIDS Patient Care STDS. 2006 Sep;20(9):649-57
39. Gray RH, Kigozi G, Serwadda D, Makumbi F, Watya S, Nalugoda F, Kiwanuka N, Moulton LH, Chaudhary MA, Chen MZ, Sewankambo N, Wabwire-Mangen F, Bacon MC, Williams CFM, Opendi P, Reynolds SJ, Laeyendecker O,Quinn TC, Wawer MJ. Male circumcision for HIV prevention in men in Rakai, Uganda : a randomised trial. The Lancet, Volume 369, Issue 9562, 24 February 2007-2 March 2007, Page 615.
40. Bailey RC, Moses S, Parker CB, Agot K, Maclean I, Krieger JN, Williams CF, Campbell RT, Ndinya-Achola JO. Male circumcision for HIV prevention in young men in Kisumu, Kenya : a randomised controlled trial. Lancet. 2007 Feb 24;369(9562):643-56.
Development of Methodology
41. Pool R, Kamali A, Whitworth JA. Understanding sexual behaviour change in rural southwest Uganda : a multi-method study. AIDS Care. 2006 Jul;18(5):479-88.
42. Mwaluko G, Wringe A, Todd J, Glynn J, Crampin M, Jaffar S, Kalluvya S, Zaba B. The use of data from HIV counselling and testing services for HIV surveillance in Africa. Lancet 2007; 369:612-613.
43. Zaba B, Slaymaker E, Urassa M, Boerma T. The role of behavioral data in HIV surveillance. AIDS. 2005 May; 19 Suppl 2:S39-52.
44. Crampin AC, Floyd S, Glynn JR, Sibande F, Mulawa D, Nyondo A, Broadbent P, Bliss L, Ngwira B, Fine PEM. Long term follow-up of HIV positive and negative individuals in rural Malawi . AIDS 2002; 16: 1545-1550.
45. Gregson, S, Zhuwau, T, Ndlovu, J and Nyamukapa, CA (2002) Methods to reduce social desirability bias in sex surveys in low-development settings - Experience in Zimbabwe Sexually Transmitted Diseases vol 29 (10) pgs:568-5
47. Mwita W, Urassa M, Isingo R, Ndege M, Marston M, Slaymaker E, Mngara J, Boerma T, Zaba B. 2007. HIV prevalence and incidence in rural Tanzania : results from 10 year follow-up in an open cohort study. J.AIDS 46(5) 616-623
48. Maher D, Todd J, Shafer L, Biraro S, Kasamba I, Grosskurth, H. Impact of migration on prevalence and incidence estimates of HIV among adults in a longitudinal population-based cohort in rural Uganda . Paper presented at IUSSP XXVI International Population Congress, Marrakech, September 2009. http://iussp2009.princeton.edu
49. Hallett TB; Zaba B; Todd J; Lopman B; Mwita W; Biraro S; Gregson S; Boerma JT; ALPHA Network. (Apr 2008). Estimating incidence from prevalence in generalised HIV epidemics: Methods and validation. PLOS MED. 5:611-622
50. Todd J, Biraro S, Shafer LA, Lutalo T, Ndyanabo A, Bwanika JB, Isingo R, Mwita W, Wringe A, Mushati P, Lopman B, Hallett T, Bärnighausen T, Nyirenda M, Hosegood V, Marston M, Żaba B. 2008. Diverse Age Patterns of HIV Incidence Rates in Africa. Abstract TUAC0201 presented at XVII conference of IAS, Mexico
51. Lopman B; Nyamukapa C; Mushati P; Mupambireyi Z; Mason P; Garnett GP; Gregson S. (Feb 2008). HIV incidence in 3 years of follow-up of a Zimbabwe cohort - 1998-2000 to 2001-03: contributions of proximate and underlying determinants to transmission. INT J EPIDEMIOL. 37:88-105.
52. Barnighausen T, Hosegood V, Timaeus IM, Newell ML. 2007. The socioeconomic determinants of HIV incidence: evidence from a longitudinal, population-based study in rural South Africa . AIDS. 21 Suppl 7:S29-38
53. Bärnighausen, T., Tanser, F., Gqwede, Z., Mbizana, C., Herbst, K., Newell, M.L., High HIV incidence in a community with high HIV prevalence in rural South Africa : findings from a prospective population-based study. AIDS 2008; 22: p.139-144.
Impact on Household and Family Structure
55. Hosegood V, McGrath N, Herbst K, Timaeus I.M. 2004. Impact of AIDS mortality on household dissolution and migration in rural South Africa . 18(11):1585-1590
56. Hosegood V.; Preston-Whyte E.; Busza J.; Moitse S.; Timaeus IM. 2007. Revealing the full extent of households' experiences of HIV and AIDS in rural South Africa . Soc Sci Med, 65:1249-1259
57. Floyd S, Crampin AC, Glynn JR, Madise N, Mwenebabu M, Mnkhondia S, Ngwira B, Zaba B, Fine PE. The social and economic impact of parental HIV on children in northern Malawi : AIDS Care, 2007; 19(6):781-90
58. Floyd S, Crampin AC, Glynn JR, Madise N, Mwenebabu M, Mnkhondia S, Ngwira B, Zaba B, Fine PEM. The long-term social and economic impact of HIV on the spouses of infected individuals in northern Malawi . Trop Med & Int Hlth 2008; 13(4): 520-31.
59. Hill C, Hosegood V, Newell ML, Children's care and living arrangements in a high HIV prevalence area in rural South Africa . Vulnerable Children and Youth Studies, 2008. 3(1): p65-77.
61. Hosegood V, Floyd S, Marston M, Hill C, McGrath N, Isingo R, Crampin A, Zaba B. 2007. Growing up in rural Africa: orphanhood and living arrangements of children in high HIV populations in Malawi, Tanzania and South Africa . Population Studies 61(3):327-336
Survival and Mortality
62. Morgan D, Mahe C, Mayanja B, Whitworth JA. Progression to symptomatic disease in people infected with HIV-1 in rural Uganda : prospective cohort study. BMJ 2002, 324:193-196.
63. Morgan D, Mahe C, Mayanja B, Okongo JM, Lubega R, Whitworth JA. HIV-1 infection in rural Africa: is there a difference in median time to AIDS and survival compared with that in industrialized countries? Aids 2002,16:597-603.
64. Boerma JT, Urassa M, Ngalula J, Isingo R, Senkoro K, Gabone R, Mkumbo EN: Levels and causes of adult mortality in rural Tanzania with special reference to HIV/AIDS, Health Transition Review 1997, Supplement 2-7:63-74.
65. Hosegood, V., A.M. Vanneste, and I.M. Timaeus, Levels and causes of adult mortality in rural South Africa : the impact of AIDS. AIDS, 2004. 18(4): p. 663-71.
67. Ghys P, Zaba B, Prins M. Survival and mortality of people infected with HIV in low- and middle income countries - results from the extended ALPHA network. 2007. Editorial introduction to AIDS vol 21 sup 6: S1-S4
68. Murray J, Sonnenberg P, Nelson G, Bester A, Shearer S, Glynn JR. Cause of death and presence of respiratory disease at autopsy in an HIV-1 seroconversion cohort of Southern African gold miners. AIDS 2007, 21 (suppl 6): S97-S104.
69. Peters PJ, Meinzen-Derr J, Karita E, Kayitenkore K, Kim D-J, Tichacek A, Allen SA for the Rwanda Zambia HIV Research Group. HIV-infected Rwandan women have a high frequency of long-term survival. AIDS 2007, 21 (suppl 6): S31-37.
70. Rangsin R, Piyaraj P, Sirisanthana T, Sirisopana N, Short O, Nelson KE. The natural history of HIV-1 subtype E infections in young men in Thailand with up to 14 years of follow-up. AIDS 2007, 21 (suppl 6): 6:S39-46.
71. Nelson KE, Costello C, Suriyanon V, Sennun S, Duerr A. Survival after HIV-1 subtype E (CRF01 A_E) among blood donors and their spouses in northern Thailand . AIDS 2007, 21 (suppl 6): S47-54.
72. Van der Paal L, Shafer LA, Todd J, Mayanja BN, Whitworth JAG, Grosskurth H. HIV-1 disease progression and mortality before the introduction of highly active antiretroviral therapy in rural Uganda . AIDS 2007, 21 (suppl 6): s21-29
73. Isingo R, Zaba B, Marston M, Ndege M, Mngara J, Mwita W, Wringe A, Beckles D, Changalucha J, Urassa M. Survival following HIV infection in the pre-ART era in a rural Tanzanian cohort. AIDS 2007; 21 (6): S5-S13;
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