Surveillance, Thailand

Transcription

1 BED-CEIA HIV Sero-incidence Surveillance, Thailand Window 127 day (subtype AE) FRR 0.05 BUREAU OF EPIDEMIOLOGY DEPARTMENT OF DISEASE CONTROL MINISTRY OF PUBLIC HEALTH, THAILAND

2 Limitations of Interpretation of HIV Sero-prevalence in Thailand HIV epidemic has been more than 20 years Antiretroviral treatment program has successfully implemented nationwide HIV testing cannot differentiate new and old infection, especially among population who were repeated enrolled in annual surveillance, i.e., IDUs, FSW Monitoring of HIV prevalence may be less sensitive than monitoring of HIV incidence in the near future

3 Concept of BED-CEIA for Diagnosis of Recent Infection L E V E L Sensitive EIA Less sensitive EIA cutoff ~ 160 d Time since infection A competitive IgG-Capture EIA detect an increasing proportion of HIV IgG in the serum following seroconversion BED-Biotin Peptide (gp41)

4 Methodology Survey design: Annual survey integrated with national HIV serosurveillance Sentinel sites and target population - Sentinel provinces ANC pregnant women Direct & indirect venue based female sex workers Exclusion criteria - Advanced disease and/or receiving ARV treatment (2006)

5 Specimen Collection and Transfer HIV testing at local laboratories Blood samples of target population HIV- HIV+ Transfer to NIH and AFRIMS Confirm HIV Diagnosis All FW sample will be transferred to center in threshold survey year BED-CEIA

6 Recent HIV Infection Diagnostic Algorithm Confirmation of anti HIV Positive Transferred sera EIA1: Murex Ab NR R Negative NR EIA2: Ortho R Long Term Infections Negative Serodia Particle Agglutination ODn > 0.8 NR Negative Anti HIV Positive BED IgG CEIA ODn 0.8 Recent Infections

7 HIV test Example of HIV incident analysis Serum specimen among ANC attendees year 2006 N = 28,659 (25 provinces) HIV- (28,415) Adjusted Incidence 0.09% per year (95% CI ) BED CEIA HIV+ (244; Prevalence 0.85%) Available HIV ve BED test (21) Sent for testing -ve BED test

8 I. Incidence Estimation Data Analysis Incidence = (365/w) X (# who test incident) # at risk X 100 Incidence = (365/w) N incident N seronegative + (365/w) N incident /2 X % confidence interval = Incidence [SQRT of N incident ] Assumes constant incidence + 1 year w = window period (153 days for Thai data)

9 II. Adjusted Incidence by Sensitivity and Dual Parameter Specificity True number recent = (P t /P o ) x observed number recent P t / P o is ratio of true number or proportion incident to observed number or proportion incident P t P o + [spec 2 ] - 1 = P o P o ([sens] [spec 1 ] + 2[spec 2 ] Adjusted Incidence = (Pt/Po)(365/w)Ninc Nsneg + (Pt/Po)(365/w)Ninc/2 x 100

10 Note Estimated incidence from this method is Incidence density (ID) that is not cumulative incidence (CI) CI = 1 - exp [-ID (Δ) ]

11 Template

12 Result

13 Median HIV Prevalence and BED Adjusted Incidence among ANC Pregnant Women in Sentinel Provinces Prevalence BED-estimated Incidence Prevalence BED-estimated Incidence lower limit upper limit

14 Median HIV Prevalence and BED Estimated Incidence among Female Direct Sex Workers in Sentinel Provinces Prevalence BED-estimated Incidence Prevalence BED-estimated Incidence lower limit upper limit

15 Median HIV Prevalence and BED Estimated Incidence among Female Indirect Sex Workers in Sentinel Provinces 6 5 Prevalence BED-estimated Incidence Prevalence BED-estimated Incidence lower limit upper limit

16 Median HIV Prevalence and BED Estimated Incidence among Military by AFRIM Thailand Prevalence BED-estimated Incidence พย พย พย พย พย พย พย พย พย พย Prevalence BED-estimated Incidence lower limit upper limit

17 Assumptions: Sentinel population is steady state (stationary) No movement of population Population rate is stable such as prevalence incidence and death rate Rare disease

18 Program summary and limitation BED-CEIA has been successfully integrated to the existing national HIV sero-surveillance system Low HIV prevalence requires a large sample size to estimate HIV incidence Estimation BED-CEIA of HIV incidence to the other population, i.e., MSM, IDU, street based SW, etc. Estimating BED-CEIA HIV incidence at the provincial level is limited due to small sample sizes; system modification is needed

19 Conclusion The new technologies has been integrated to the national systems and are feasible to be implemented using governmental resources Results has provided essential information used for determining current HIV and STI epidemic The recent data has been used as Early warning sign of rising HIV epidemic The National AIDS Committee Provincial AIDS Committee

20 Acknowledgement Bureau of Epidemiology Bureau of AIDS, TB and STI National Institute of Health Disease Control Regional Offices BMA and Provincial Health Offices AFRIMS Thailand MOPH-US CDC Collaboration