San Francisco Department of Public Health Program Collaboration and Service Integration Surveillance Baseline Assessment

Transcription

1 Background and Purpose San Francisco Department of Public Health This syndemics assessment is the first step in developing a sustainable system of primary prevention and clinical care in San Francisco that comprehensively addresses HIV, other STDs, viral hepatitis, and TB to prevent transmission, disease, disability, and death; to reduce co-infections; and to increase health equity. CDC s definition and origin of the term syndemic is as follows: When used as a noun, a syndemic is defined as two or more afflictions (diseases), interacting synergistically, contributing to increase transmission and/or worsen outcomes of either or all diseases in a population. Related concepts include: linked epidemics, interacting epidemics, connected epidemics, co-occurring epidemics, co-morbidities, and clusters of health-related crises. The word syndemic was coined by anthropologist Merrill Singer and first published in 1992 to convey what he and his colleagues saw as inextricable and mutually reinforcing connections between health problems such as substance abuse, violence, and AIDS among urban women in the US. 1 The sharing of surveillance data among the HIV, STD, viral hepatitis, and TB sections provided the Department of Public Health with the opportunity to develop a surveillance baseline assessment to understand the syndemic relationship of HIV/AIDS, viral hepatitis, STDs, and TB. The federal government has encouraged the sharing of surveillance data so that it may be used in planning, implementation and evaluation of overall public health practice. In this first phase of the PCSI project, we assessed surveillance registries and conducted a match to establish the first baseline syndemic report across these four registries for San Francisco. The assessment aims to use surveillance data from HIV/AIDS, viral hepatitis, STD, and TB to identify the populations/communities in San Francisco that are impacted by co-morbid conditions and to identify the challenges in the current surveillance system to monitor and track co-morbid conditions. Challenges It is important to note that there are limitations in the data. Each disease had unique epidemiologic characteristics (mode of transmission, population affected, length of infection, curability, amount of follow-up time), reporting laws, and clinical and programmatic needs. Thus, epidemiologic and surveillance data were collected differently for each disease. Also, since this is the first pass at this data, the first time all four disease registries have been matched at the same time, we acknowledge that there is room to improve the match in the future for specific data and/or policy needs. Another limitation at the systemic level is the issue of Out of Jurisdiction (OOJ) cases. For all HIV-related labs that are reported to HIV Surveillance, 15-20% of them belong to cases that did not live in San Francisco at the time of their diagnoses. However, they receive care in San Francisco. For STD Clinic, about 15% of their cases are OOJ. We are not able to match OOJ cases since we do not collect as much data for those cases. This is a limitation for matching cases to look at syndemics. Despite these limitations, the assessment provides SFDPH with its first cross-sectional assessment that will be utilized to establish a baseline. For more information on the limitations, a surveillance registry data comparison can be found in Appendix A P age

2 Methods We evaluated the four sepa disease registries and identified challenges with obtaining and linking data in preparation for performing a registry match of HIV, TB, VH, and STD. Distinct case inclusion criteria appropriate to each disease registry were developed to gene cases for matching. HIV registry included cases living as of December 31, VH included all cases in the registry comprised of chronic HBV and past or present HCV infection; TB included all living active and latent cases. STD included any case with a Syphilis, Gonorrhea, and/or Chlamydia diagnosis in Cases were matched by name and date of birth. Key Findings Syndemics in San Francisco! In the overall match, 3% (=4,296) of people affected by one disease had at least one additional co-morbidity.! Highest syndemics within-population s for San Francisco were among those infected with Hepatitis B, HIV, Hepatitis C, and Latent TB.! Highest syndemics within-disease s were among syphilis, gonorrhea, and chlamydia. ulations Impacted by Co-morbidities Overall! Male, middle-aged, African-American, and Latino/a were more likely to have two or more diseases. HIV! IDU, MSM-IDU, age 20-59, African-American, Asian, and Latino/a were more likely to have additional diseases in addition to HIV.! ulations with higher s of HIV infection are also at higher risk for co-infection with other transmittable diseases. HBV/HCV! Under age 60, Male, and African-American were more likely to have syndemics with HBV.! Age 20-59, Male, Asian, African-American, and Latino/a were more likely to have HCV co-morbidities. STD! There were no significant characteristics that were most at risk for a syndemic with syphilis.! MSM, Transgender, and African-American were more likely to have chlamydia and another disease.! MSM and African-American were more likely to have co-morbidities with gonorrhea. TB! Correlates of active TB co-morbidities include ages 20-59, Homeless, and Male.! Correlates of latent TB co-morbidities include African-American, ages 30-59, history of incarceration, Male, and Homeless. 2 P age

3 Results Syndemics! Table 1 shows the highest within-population syndemics were for hepatitis B with other co-morbidities (388 per 100,000 San Franciscans), HIV (282 per 100,000 San Franciscans), hepatitis C (229 per 100,000 San Franciscans), and latent TB (199 per 100,000 San Franciscans).! The highest within-disease s for syndemics were syphilis (61,614 per 100,000 syphilis cases), gonorrhea (41,995 per 100,000 gonorrhea cases), and chlamydia (19,812 per 100,000 chlamydia cases). Table 1. Summary of registry match results per 100,000 Registry Within- Within-ulation HIV 13, TB Active TB Latent TB STD Syphilis Chlamydia Gonorrhea HBV/HCV HBV HCV 5,796 2,111 61,614 19,820 41,995 4,752 14, P age

4 ! Table 2 shows the registry match results by within disease s in each column. For example, in looking at the Syphilis column, the highest co-morbidity was for HIV (44,291 HIV and Syphilis cases per 100,000 Syphilis cases). In the Gonorrhea match column, there were 18,996 HIV and Gonorrhea cases per 100,000 Gonorrhea cases.! For a complete look at syndemics in San Francisco table, please view Appendix B. Table 2. Summary of registry match results per 100,000 of each disease Registry HIV Active TB Latent TB match Syphilis Chlamydia Gonorrhea HBV match HCV HIV /A TB Active TB Latent TB /A /A /A /A STD Syphilis Chlamydia Gonorrhea /A /A /A HBV/HCV HBV HCV /A /A 4 P age

5 ulations Impacted by Co-morbidities San Francisco Department of Public Health Overall co-morbidities! Males, middle-aged, African-American, and Latino/a were more likely to have two or more diseases. Sex Table 3. Correlates of syndemics (two or more diseases) Estimate 95% Confidence Limits Female Transgender Male (ref) Race/Ethnicity African-American Latino/a Asian Other White (ref) Age at diagnosis and up (ref) 5 P age

6 HIV co-morbidities! IDU, MSM-IDU, age 20-59, African-American, Asian, and Latino/a were more likely to have additional diseases in addition to HIV.! ulations with higher s of HIV infection are also at higher risk for co-infection with other transmittable diseases. Sex Table 4. Correlates of HIV co-morbidities 95% Confidence Estimate Limits Female Transgender Male (ref) Race/Ethnicity African-American Latino/a Asian Other White (ref) Age at diagnosis and up (ref) Risk* IDU MSM - IDU Other risk MSM (ref) *HIV Surveillance data include behavioral risk for HIV information. 6 P age

7 HBV and HCV Co-morbidities! Under age 60, Male, and African-American were more likely to have syndemics with HBV.! Age 20-59, Male, Asian, African-American, and Latino/a were more likely to have HCV co-morbidities. Sex Table 5. Correlates of HBV and HCV co-morbidities Correlates of HBV co-morbidities Correlates of HCV co-morbidities 95% Confidence 95% Confidence Estimate Limits Estimate Limits Female Male (ref) Race/Ethnicity African-American Latino/a Asian Other White (ref) Age at diagnosis and up (ref) Homeless* Yes o (ref) * The Viral Hepatitis Registry collects homeless information. 7 P age

8 STD Co-morbidities! There were no significant characteristics that were most at risk for a syndemic with syphilis.! MSM, transgender, and African-American were more likely to have chlamydia and another disease.! MSM and African-American were more likely to have co-morbidities with gonorrhea. Table 6. Correlates of Syphilis, Chlamydia, and Gonorrhea co-morbidities Correlates of Correlates of Syphilis co-morbidities Chlamydia co-morbidities 95% 95% Confidence Confidence Est Limits Est Limits Correlates of Gonorrhea co-morbidities 95% Confidence Est Limits Sex Female Transgender Male (ref) Race/Ethnicity African-American Latino/a Asian Other White (ref) Age at diagnosis and up (ref) MSM* Yes o (ref) *The STD registry collects information on sexual orientation. This variable was recoded to Men who have sex with men (MSM) as a Yes/o variable. 8 P age

9 Active and Latent TB co-morbidities San Francisco Department of Public Health! Correlates of active TB co-morbidities include ages 20-59, Homeless, and Male.! Correlates of latent TB co-morbidities include African-American, ages 30-59, ever been in jail, Male, and, Homeless. Table 7. Correlates of Active and Latent TB co-morbidities Correlates of Active TB co-morbidities Correlates of Latent TB co-morbidities 95% Confidence 95% Confidence Estimate Limits Estimate Limits Sex Female Male (ref) Race/ Ethnicity African-American Latino/a Asian Other White (ref) Age at diagnosis and up (ref) History of incarceration* Yes o (ref) Homeless* Yes o (ref) *The TB registry collects information on history of incarceration and homelessness. Conclusions and ext Steps There is more work to be done. In order to guide policy decisions, additional demographic analyses may be needed. 9 P age

10 Appendix A. PCSI Surveillance Registry Data Comparison s reported from this surveillance registry Epidemiology Surveillance type Out of Jurisdiction (OOJ) HIV STD TB VH HIV, AIDS Chlamydia Active TB Chronic HBV Gonorrhea Latent TB partially captured HCV (past or present Syphilis infection) Once infected, will be HIV+; chronic Active (medical chart review) and passive About 15-20% of reported HIV labs are for out of jurisdiction cases; they are not included in the analysis since there is less complete information on these cases Can have more than one STD at a time and be infected multiple times per year ot chronic Can get it once Can be latent/exposed (which could then become active) HBV: chronic HCV: chronic, acute Passive Passive (lab reports) Passive (lab reports) plus enhanced surveillance on 10% sample which includes a fax to the provider for further info (HBV and HCV), a subsequent phone interview with the case (formerly on HBV cases, now just HCV cases), and ( new activity this year) of subsequent chart review (HCV cases only) About 15% of clients seen at the STD clinic reside outside of San Francisco; these cases are not included in the analysis All cases are included in the analysis who are seen at the TB clinic, regardless of residence This registry and the match includes all reported cases, regardless of address 10 P age

11 Appendix A. PCSI Surveillance Registry Data Comparison HIV STD TB VH Age of registry Since 1980 Computer data since 1985 Data entered systematically since 1995 Data back to 1985 HBV: Since 1984 HCV: Reportable as of 2007 Chart review Yes on all active cases o (access LCR data) Yes for active TB Chart review for limited sample just started (enhanced follow-up) Follow-up on cases Every months on all living cases until death Data format SQL server / SAS Sent as Excel spreadsheet (resides on SQL server and can be formatted to any format) Aliases collected? (known AKAs for patient) Address Active case management of active TB cases LTBI are not followed prospectively Access database Yes Yes Yes Yes At time of diagnosis Started to collect current address 2010 Current (and prior) address Address at time of diagnosis Laboratory reporting Mandatory Mandatory Mandatory for active TB (what about latent TB?) Considered a case HIV positive test Lab confirmed (syphilis Lab confirmed for active TB Detectable VL can be reported without a lab test) one Sent as SAS database HBV mandatory HCV mandatory HBV: confirmed or suspected HCV: 11 P age

12 Appendix A. PCSI Surveillance Registry Data Comparison HIV STD TB VH Common fields First, Last, DOB Gender Race/ethnicity Date of diagnosis First, Last, DOB Gender Race/ethnicity Date of First, Last, DOB Gender Race/ethnicity Date of diagnosis (active) First, Last, DOB Gender Race/ethnicity Date of diagnosis (lab) diagnosis/diagnoses Other id fields MRO (Bnum), SS Bnum Bnum Other fields Behavioral risk Sexual orientation Partner services IDU Drug type Provider (where care rec d) Contacts for contact investigation Completeness of data complete complete complete Incomplete (incidence and prevalence cannot be determined) Treatable Yes Yes Yes Yes Communicable Yes Yes Yes Yes Integration Check for HCV, TB with STD annually Offer HAV, HBV vaccinations o HCV screen with HIV annually Interested in latent TB cases as they present opportunity for prevention; Have HIV data Have self-reported HBV, HCV Database doesn t link to LCR (match on Bnum) 12 P age

13 Appendix A. PCSI Surveillance Registry Data Comparison Time frame used for matching HIV STD TB VH Living cases as of December 31, 2009 Any STD(s) diagnosed in 2009; each individual with a case of Syphilis was counted once; each individual with Gonorrhea was counted once; and each individual with Chlamydia was counted once Entire database; cases not known to be deceased as of December 31, 2009 Entire database; includes all cases reported up to December 31, 2009, but may include persons who are no longer infected (for HCV), deceased, or who are residing outside of San Francisco 13 P age

14 Appendix B. Syndemics in San Francisco by disease, 2009 data HIV Active TB Latent TB HIV 16,786 2,190 13, , Active TB 4, , /A /A /A Latent TB 73, , /A /A /A 1,545 2, Syphilis , Chlamydia 3, , Gonorrhea 1, , HBV 37, , , HCV 10, , , Syphilis Chlamydia Gonorrhea HIV 16, , , , Active TB 4, Latent TB 73, , ,195 3 Syphilis , , , Chlamydia 3, , , , Gonorrhea 1, , , , HBV 37, , ,314 3 HCV 10, , ,732 4 Hepatitis B Virus Hepatitis C Virus HIV 16, , , Active TB 4, Latent TB 73, , , Syphilis Chlamydia 3, Gonorrhea 1, HBV 37,491 1,720 4, , HCV 10, , ,550 14, ote: all s are per 100,000; SF pop from 2000 census data 776,773; bolded rows are all co-infections within that particular disease. 14 P age