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Analyzing epidemic heterogeneity and implications at various levels in the South Asia region. Understanding epidemic potential and phases, strategic responses for rural epidemics, and gaps in knowledge that require attention.
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HIV Epidemics in the South Asia Region – Strategic Considerations James Blanchard, MD, MPH, PhD University of Manitoba
Issues • Analyzing the heterogeneity of HIV epidemics: • Strategic implications at the macro, meso and micro levels • Understanding epidemic potential and epidemic phase • Rural HIV epidemics: • Strategic considerations for a response • What we don’t know, but must
Heterogeneity – Strategic Implications • Macro Level – Differences between countries • Overall design of the national plans • Relative emphasis on targeted, focused and broad-based prevention strategies • Geographic concentration vs. dispersion • Meso Level – Differences between states/provinces • Flexibility vs. standardization of implementation plans • Decentralized capacity and decision-making • Micro Level – Differences between/within districts • Requirement for fine-grained information at the local level • Flexibility/elasticity of intervention programs • Capacity building requirements of local implementers
Defining and Assessing Heterogeneity – Analytic Framework Apparent (observed) epidemic (i.e. HIV prevalence) reflects two constructs: • Epidemic potential (trajectory) • How an uninterrupted epidemic will evolve • Determined by factors influencing the transmission dynamics: sexual structure, IDU networks, transmissibility (e.g. circumcision) • Epidemic phase • Extent to which the epidemic has spread in various high risk networks and sub-populations • Depends on both time and connectivity to other epidemics (geography, mobility)
Truncated Epidemic High risk network (distal) Bridge Population Local Partners “Truncated” Epidemic
Local Concentrated Epidemic Local Partners High risk network (distal) Bridge Population High risk network (local) “Local Concentrated” Epidemic
Generalizing Epidemic Local Partners High risk network (distal) Bridge Population High risk network (local) “Generalizing” Epidemic
Pakistan • Epidemic Potential • “Local Concentrated” epidemics in several of the larger cities; information is lacking elsewhere • Intersection between IDU and female sex work and MSM can accelerate the transmission in several cities • “Truncated” epidemics are likely in many of the rural areas due to substantial male migration to large cities within the country, and externally • “Generalizing” epidemics are unlikely, though little is known about the sexual structure. • Epidemic Phase • Epidemic is emerging rapidly in some high risk sub-populations, especially in IDU and MSM networks in larger cities • It appears that FSW networks are still at an early epidemic phase
India • Epidemic Potential • Many “Local Concentrated” epidemics, most involving female sex work networks. IDU is important in the northeast. Insufficient information on MSM-related transmission dynamics. • “Generalizing” epidemic potential exists in some pockets. However, widespread generalizing epidemics are unlikely. • “Truncated” epidemics are likely in many of the rural areas due to substantial male migration to large cities within the country, and externally. • Paucity of information on sexual structure in much of N. India. • Epidemic Phase • “Local Concentrated” epidemics are advanced in many areas of S. India and the northeast. • Epidemics might be at an earlier phase in N. India, but information is insufficient.
Nepal • Epidemic Potential • “Local Concentrated” epidemics in a number of areas, most involving female sex work networks. FSW migration to Mumbai is likely an important epidemic amplifier. IDU is also likely an important component in some areas. • “Generalizing” epidemic potential does not appear to be substantial, though more information about population sexual structure is required. • “Truncated” epidemics are likely in areas with a substantial population of out-migrating men. • Epidemic Phase • “Local Concentrated” epidemics are advanced some areas, with acceleration related to FSW migration to Mumbai.
Bangladesh • Epidemic Potential • Substantial “Local Concentrated” epidemics in a number of areas, most involving female sex work networks. IDU is also likely an important component in some areas. • Intersection between IDU and female sex work will accelerate local epidemics in some locations • “Generalizing” epidemic potential does not appear to be substantial, though more information about population sexual structure is required. • “Truncated” epidemics are likely in areas with a substantial population of out-migrating men. • Epidemic Phase • “Local Concentrated” epidemics still appear to be relatively early in sex work networks. • Expansion is observed in some IDU networks
Sri Lanka • Epidemic Potential • Potential for “Local Concentrated” epidemics in some areas, particularly in relation to IDU, and FSW in some areas. • “Generalizing” epidemic is unlikely. • Limited “truncated” epidemics could occur in areas with a substantial population of out-migrating men, but this will depend largely on expansion of epidemics in high risk networks at migration destination locations. • Epidemic Phase • Still appears to be at an early epidemic phase.
Implications for a Prevention Strategy – “Scale up Focused Prevention” • Saturate major urban centres in all countries • In India… identify and saturate the large number of small and medium size “spread” networks fuelling local concentrated epidemics: • Restricting targeted intervention coverage to large clusters of high risk groups will result in low coverage overall. • Ensure that all risk networks are covered in intervention areas… FSWs, clients, IDUs, MSMs.
Scaling up at Macro and Micro Levels – “Geography and Networks” District Hot Spot HS Hot Spot Hot Spot HS Coverage – critical sexual networks Coverage – critical transmission “hot spots” “MACRO” “MICRO”
Example – Coverage of Karnataka “Sankalp” Project under BMGF’s Avahan Program (18 months) MACRO – “Geography” MICRO – “Networks” • 16 districts • All 138 towns & cities mapped • FSW programs in 117/138 towns • Est. 96% of urban FSWs in “covered” towns
Rural Epidemics in India –Some Strategic Issues • To what extent do rural epidemics exist? • “Do we need a rural strategy”? • What drives rural epidemics? • “Can we control rural epidemics through urban interventions?” • “What should be the focus of rural prevention programs?” • How much variability is there in rural epidemics? • “Can we prioritize intervention locations?”
India HIV Prevalence Estimates - 2004 Source: NACO 2004
HIV Prevalence (%) in Antenatal Sentinel Surveillance Sites – Karnataka Districts, 2002-2004 HIV prevalence: Rural > Urban in 15/27 districts
Size of FSW Population in Urban Centres and Villages of Karnataka Districts Mean: 6.6 Mean: 5.5 Urban Rural
Population: 1.65 million 6 Talukas (sub-district administrative units) Mix of irrigated and drought-prone areas Mainly agricultural (sugarcane), with some mining 71% live in rural areas 65% of workers are agricultural cultivators or labourers (38%) Recently completed large dam project Literacy rate: 49% (37% among females) ANC HIV Prevalence >3% Case Study: Bagalkot District
HIV prevalence by sex and residence – Bagalkot District, 2003
Distribution of Female Sex Workers – 3 Talukas of Bagalkot District 4.2 FSW/1000 10.4 FSW/1000 12.6 FSW/1000
Males with commercial and non-marital partners – Bagalkot Talukas, 2004
Variations in FSW client volume – Bagalkot Talukas Clients per week
Observations on Sexual Structure –3 Bagalkot Talukas • Taluka A – HIV prevalence 1.2% (1.4% rural) : • Lower sex worker population and client volume • Least males reporting commercial or non-marital sex partners • Less affluent, more drought-prone • Furthest away from state boundary (Maharashtra) • Taluka B – HIV prevalence 2.9% (3.3% rural) • Highest sex worker population overall, but intermediate in rural areas. Highest client volumes. • Intermediate males reporting commercial or non-marital sex partners • Relatively affluent (irrigated, sugar cane) • Closest to state boundary (Maharashtra) – tradition as vibrant sex work destination for clients. • Taluka C – HIV prevalence 4.9% (6.0% rural) • Intermediate sex worker population overall, highest in rural areas. • Highest males reporting commercial or non-marital partners. • Affluent (irrigated, sugar cane) • Intermediate distance from state boundary.
3 Talukas - Hypothesis • Rural HIV transmission dynamics are largely dependent on local sex work volume: • Taluka C – sex work volume is relatively high, and appears to cater mostly to local clients • Taluka B – sex work volume is highest, but a higher proportion of the sex involves “external” clients • Taluka A – low volume of sex work and fewer sex clients
Program Implications – Rural Strategy • HIV prevention for rural areas needs to be applied “locally” to interrupt local high risk sexual networks • High variability in the sexual structure, including sex work volume, indicates the need for “focused” prevention in rural areas • Some rural areas with high sex work volume involve sex clients from a large catchment area, and therefore require high priority for prevention programs • Non-commercial sexual networks are probably important in some locations, requiring a broader prevention program
What We Need to Know • Distribution and size of high risk sexual and IDU networks, especially outside of major urban centres (including rural areas) • Presence and characteristics of non-commercial sexual networks that could amplify or “generalize” HIV epidemics • Current epidemic “phase” – sub-population distribution of HIV (high risk, bridge, general) • How to efficiently identify local “high risk” zones in rural areas