The ALPHA network

WHAT MAKES ALPHA DATA UNIQUE? An introduction to the network and its data resources Basia Żaba ALPHA network PI

ALPHA network aims Analyse community-based HIV surveillance data Pool data to strengthen analytical conclusions Present analyses to health policy makers Build data analysis and data management capability of partner institutions

Independent institutions Located in six high prevalence countries of Eastern and Southern Africa Managed by ten independent African research institutions Surveillance studies pre- date the network formation Facilitated by LSHTM secretariat to manage the pooled data resource and plan joint analyses ALPHA partner studies

ALPHA history Phase funding: Wellcome, UNAIDS six members investigations: (i) incidence & prevalence; (ii) household impact; (iii) survival post infection; (iv) sexual behaviour; (v) testing & treatment uptake Phase funding: Wellcome, UNAIDS, WHO, Nuffield, Gates ten members investigations: (i) incidence & prevalence; (ii) fertility; (iii) cause of death; (iv) mortality following ART roll out; (v) impacts on children; (vi) partnership stability

Data collection in partner studies + demographic surveillancex HIV surveillancex combined surveys uMkhanyakude NCDs leprosy,TB malaria urban poverty

RakaiKisumuKisesa Karonga Agincourt Masaka Nairobi IfakaraManicalanduMkhanyakude in all studies HIV status not known includes refusals & non-contacts; in Kisumu, Nairobi, Manicaland and Agincourt also includes out of sample households Size of populations with known HIV status at recent sero-surveys Largest number of known negatives for incidence estimates Largest numbers of known positives for mortality estimates

Demographic surveillance achieves very high participation rates – in most studies ~99% of households. Captures date of death for ~98% of deaths, verbal autopsy interviews identify cause for >70% of deaths Household based data provide family and life-cycle information Open structure ensures populations do not become selective over time Includes experience of those not yet / never attending treatment clinics Provides information on those who stop attending clinics Generates opportunity to link to data collected in treatment clinics Provides platforms for special surveys and qualitative research Observational studies reflect broad national experience (not trials) Historical HIV testing protocols “informed consent without disclosure” yielded information on voluntary testing uptake classified by HIV status Advantages of ALPHA data

Widely used in pre-ART era Individuals had little to gain from knowing HIV status Overcomes fear/shame of discovering infection Community justification: helps advance science Recent changes in test protocols Move to “opt out” counselling and result feedback Special reporting arrangements for HIV positive to avoid repeat counselling Informed consent without disclosure

Data harmonisation across studies with different protocols and data management practices Small populations, not nationally representative Participation fatigue Growth of social desirability bias Self-reports of clinic experience are less reliable and rapidly become stale dated Classification of people who take unorthodox routes through the treatment cascade Data interpretation challenges

Measuring HIV incidence individual data, not aggregate models risk factors measured ahead of sero-conversion long observation of exposure imply smaller sample sizes needed for good precision Where ALPHA data make a difference Mortality of HIV positive measurement possible from time of sero-conversion capture experience outside of clinic populations enable longitudinal measures of changing risk factors, including family circumstances

Qualitative approaches and facility studies Comparative reviews of the national policy environment Surveys of local health facilities to assess extent of policy implementation Qualitative research to understand bottlenecks in accessing testing, care and treatment Beyond deaths and person-years

“good news, bad news and ugly news …” –comprehensive policies, reasonably well implemented, mortality improvements –where on the cascade is mortality still far too high, what we learn from the families of those who died of AIDS –the paradox of male disadvantage and further feminization of the epidemic breaking news: external use of ALPHA findings –applications of our new Verbal Autopsy tools –how ALPHA findings help us to interpret routine data discussion The symposium presentations

Phase start-up Phase studies leading to this seminar Phase More accessible data Comprehensive clinic connections Focus on transmission and incidence ALPHA future plans