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Identifying likely syphilis transmitters: Implications for control & evaluation* Stuart M Berman, MD, ScM Division of STD Prevention CDC, Atlanta, GA *Awaiting.

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Presentation on theme: "Identifying likely syphilis transmitters: Implications for control & evaluation* Stuart M Berman, MD, ScM Division of STD Prevention CDC, Atlanta, GA *Awaiting."— Presentation transcript:

1 Identifying likely syphilis transmitters: Implications for control & evaluation* Stuart M Berman, MD, ScM Division of STD Prevention CDC, Atlanta, GA *Awaiting publication in Sexually Transmitted Diseases. Authors: Richard H. Kahn, Thomas A Peterman, Janet Arno, Emmet John Coursey, and Stuart M Berman

2 Background Major syphilis case detection strategies in the United States: Partner notification STD clinic Dx/Rx Private provider testing/diagnosis Broad screening (premarital, military, prenatal) Targeted screening (jails, bathhouses) Implicit assumption: every early case found/Rxd contributes equally to control But prevention potential varies among cases Little evaluation of detection strategies and their prevention potential

3 Goals Determine which approaches were best for finding those syphilis cases that would contribute the most to disease control. i.e, finding cases of high prevention value High prevention value: –treatment was provided early in course of disease –individual was likely to expose multiple partners

4 Methods Retrospective evaluation of data from 2 cities with heterosexual syphilis epidemics Nashville and Louisville were cities with dramatic increases that had come under control

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8 Description of early syphilis cases, 1997-2002, both cities IndianapolisNashville Total15592011 P/S1126 (72%) 998 (50%) Early latent 433 (28%)1013 (50%) MSM <10% (males)9% (males)

9 Sites: Response to epidemic Indianapolis, IN jail screening improve partner notification (including cluster interviewing) enhanced community partnerships emergency department screening Nashville, TN jail screening improve partner notification enhanced community partnerships

10 Methods: Source Data Routinely collected data (local level) - Interview records - Laboratory records - Morbidity reports

11 Methods: Coding Case Detection

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13 Detection Method??

14 Methods: Coding Case Detection

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17 Methods: High prevention value Prevention value score for each case = Relative magnitude of transmission if case had not been identified: Relative # infectious days prevented by Rx X Expected number of (future) partners

18 Methods: High prevention value Prevention value score for each case = Relative magnitude of transmission if case had not been identified: Relative # infectious days prevented by Rx X Expected number of (future) partners

19 exposure 251234110 184 days primary latent secondary latent.24 probability of recurrence to secondary 365 days

20 exposure 251234110 184 days primary latent secondary latent.24 probability of recurrence to secondary Assume diagnosis occurs in the middle of a stage; Infectiousness occurs only during primary and secondary Then the number of infectious days prevented by stage are: 365 days

21 exposure 251234110 184 days primary latent secondary latent.24 probability of recurrence to secondary Assuming diagnosis occurs in the middle of a stage, and infectiousness occurs only during primary and secondary, the number of infectious days prevented by stage are: Stage of DiagnosisPrimarySecondary Recurrence Total infectious days prevented Primary 6 110 26 (.24 x 110) 142 Latent before secondary 110 26 (.24 x 110) 136 Secondary 55 26 (.24 x 110) 81 Latent after secondary 13 (.12 x 110) 13 Relative number of infectious days prevented: Primary 142 days = 4.3 Secondary 81 days = 2.5 *Latent 33 days = 1 365 days *Total duration of latent is 34+184=218 days. 34/218=.16 of latent is before secondary and 184/218=.84 is after secondary. Thus, the weighted average for latent is.16x136 days +.84x13 days = 33 days.

22 exposure 251234110 184 days primary latent secondary latent.24 probability of recurrence to secondary Assuming diagnosis occurs in the middle of a stage, and infectiousness occurs only during primary and secondary, the number of infectious days prevented by stage are: Stage of DiagnosisPrimarySecondary Recurrence Total infectious days prevented Primary 6 110 26 (.24 x 110) 142 Latent before secondary 110 26 (.24 x 110) 136 Secondary 55 26 (.24 x 110) 81 Latent after secondary 13 (.12 x 110) 13 Relative number of infectious days prevented: Primary 142 days = 4.3 Secondary 81 days = 2.5 *Latent 33 days = 1 365 days *Total duration of latent is 34+184=218 days. 34/218=.16 of latent is before secondary and 184/218=.84 is after secondary. Thus, the weighted average for latent is.16x136 days +.84x13 days = 33 days.

23 exposure 251234110 184 days primary latent secondary latent.24 probability of recurrence to secondary Assuming diagnosis occurs in the middle of a stage, and infectiousness occurs only during primary and secondary, the number of infectious days prevented by stage are: Stage of DiagnosisPrimarySecondary Recurrence Total infectious days prevented Primary 6 110 26 (.24 x 110) 142 Latent before secondary 110 26 (.24 x 110) 136 Secondary 55 26 (.24 x 110) 81 Latent after secondary 13 (.12 x 110) 13 Relative number of infectious days prevented: Primary 142 days = 4.3 Secondary 81 days = 2.5 *Latent 33 days = 1 365 days *Total duration of latent is 34+184=218 days. 34/218=.16 of latent is before secondary and 184/218=.84 is after secondary. Thus, the weighted average for latent is.16x136 days +.84x13 days = 33 days.

24 exposure 251234110 184 days primary latent secondary latent.24 probability of recurrence to secondary Assuming diagnosis occurs in the middle of a stage, and infectiousness occurs only during primary and secondary, the number of infectious days prevented by stage are: Stage of DiagnosisPrimarySecondary Recurrence Total infectious days prevented Primary 6 110 26 (.24 x 110) 142 Latent before secondary 110 26 (.24 x 110) 136 Secondary 55 26 (.24 x 110) 81 Latent after secondary 13 (.12 x 110) 13 Relative number of infectious days prevented: Primary 142 days = 4.3 Secondary 81 days = 2.5 *Latent 33 days = 1 365 days *Total duration of latent is 34+184=218 days. 34/218=.16 of latent is before secondary and 184/218=.84 is after secondary. Thus, the weighted average for latent is.16x136 days +.84x13 days = 33 days.

25 exposure 251234110 184 days primary latent secondary latent.24 probability of recurrence to secondary Assuming diagnosis occurs in the middle of a stage, and infectiousness occurs only during primary and secondary, the number of infectious days prevented by stage are: Stage of DiagnosisPrimarySecondary Recurrence Total infectious days prevented Primary 6 110 26 (.24 x 110) 142 Latent before secondary 110 26 (.24 x 110) 136 Secondary 55 26 (.24 x 110) 81 Latent after secondary 13 (.12 x 110) 13 Relative number of infectious days prevented: Primary 142 days = 4.3 Secondary 81 days = 2.5 *Latent 33 days = 1 365 days *Total duration of latent is 34+184=218 days. 34/218=.16 of latent is before secondary and 184/218=.84 is after secondary. Thus, the weighted average for latent is.16x136 days +.84x13 days = 33 days.

26 Methods: High prevention value Prevention value score for each identified case = Relative magnitude of transmission if case had not been identified: Relative # infectious days prevented by Rx X Expected number of (future) partners

27 Methods: High prevention value For expected number of future partners: Used number of critical period sex partners Primary = 4.3x number of interview period partners (3m) Secondary=2.5 x number of interview period partners (6m) Early latent=1 x number of interview period partners (12m) o Number of interview partners was similar regardless of stage used

28 Methods: High prevention value Primary = 4.3x number of interview period partners (3m) Secondary=2.5 x number of interview period partners (6m) Early latent=1 x number of interview period partners (12m) High prevention value: >10 StageSex partners Primary 3 (3 months) Secondary 5 (6 months) Early latent 11 (12 months)

29 Finding high value cases: Women with early syphilis, Indianapolis All cases (825)High-value (111) -- 13% Primary87 (11%)21 (19%) Secondary479 (58%)66 (59%) EL259 (31%)24 (22%) Identified by: PN 156 (19%)13 (11%) Cluster 14 (2%) 4 (4%) STD clinic 84 (10%)14 (13%) PMD 229 (28%)20 (18%) Jail 103 (12%)38 (34%) Hospital124 (15%)13 (11%) Other115 (14%) 9 (8%)

30 Finding high value cases: Women with early syphilis,Indianapolis All cases (825)High-value (111) – 13% Primary87 (11%)21 (19%) Secondary479 (58%)66 (59) EL259 (31%)24 (22%) Identified by: PN 156 (19%)13 (11%) Cluster 14 (2%) 4 (4%) STD clinic 84 (10%)14 (13%) PMD 229 (28%)20 (18%) Jail 103 (12%)38 (34%) Hospital124 (15%)13 (11%) Other115 (14%) 9 (8%)

31 Finding high value cases: Men with early syphilis,Indianapolis All cases (734)High-value (149) -- 20% Primary275 (37%)90 (60%) Secondary285 (39%)52 (35%) EL174 (24%) 7 (5%) Identified by: PN 151 (21%)18 (12%) Cluster 13 (2%) 5 (4%) STD clinic 233 (32%)66 (44%) PMD 156 (32%)28 (19%) Jail 66 (9%)13 (9%) Hospital 64 (9%) 8 (5%) Other 51 (7%)11 (7%)

32 Finding high value cases: Men with early syphilis,Indianapolis All cases (734)High-value (149) -- 20% Primary275 (37%)90 (60%) Secondary285 (39%)52 (35%) EL174 (24%) 7 (5%) Identified by: PN 151 (21%)18 (12%) Cluster 13 (2%) 5 (4%) STD clinic 233 (32%)66 (44%) PMD 156 (32%)28 (19%) Jail 66 (9%)13 (9%) Hospital 64 (9%) 8 (5%) Other 51 (7%)11 (7%)

33 Finding high value cases: Women with early syphilis, Nashville All cases (875)High-value (63) -- 7% Primary 61 (7%) 8 (13%) Secondary364 (42%)30 (48%) EL450 (51%)25 (39%) Identified by: PN 110 (13%) 5 (8%) Cluster 8 (1%) 0 STD clinic 75 (9%) 9 (14%) PMD 248 (29%) 8 (13%) Jail 221 (25%)31 (49%) Hospital 31 (4%) 5 (8%) Other182 (21%) 5 (8%)

34 Finding high value cases: Women with early syphilis, Nashville All cases (875)High-value (63) -- 7% Primary 61 (7%) 8 (13%) Secondary364 (42%)30 (48%) EL450 (51%)25 (39%) Identified by: PN 110 (13%) 5 (8%) Cluster 8 (1%) 0 STD clinic 75 (9%) 9 (14%) PMD 248 (29%) 8 (13%) Jail 221 (25%)31 (49%) Hospital 31 (4%) 5 (8%) Other182 (21%) 5 (8%)

35 Finding high value cases: Men with early syphilis, Nashville All cases (1117)High-value (79) -- 7% Primary251 (22%)42 (53%) Secondary311 (28%)25 (32%) EL555 (50%)12 (15%) Identified by: PN 104 (9%) 7 (9%) Cluster 2 (0.2%) 0 STD clinic 159 (14%)22 (28%) PMD 161 (14%)11 (14%) Jail 433 (39%)19 (24%) Hospital 43 (4%) 2 (3%) Other215 (19%)18 (23)

36 Finding high value cases: Men with early syphilis, Nashville All cases (1117)High-value (79) -- 7% Primary251 (22%)42 (53%) Secondary311 (28%)25 (32%) EL555 (50%)12 (15%) Identified by: PN 104 (9%) 7 (9%) Cluster 2 (0.2%) 0 STD clinic 159 (14%)22 (28%) PMD 161 (14%)11 (14%) Jail 433 (39%)19 (24%) Hospital 43 (4%) 2 (3%) Other215 (19%)18 (23%)

37 Limitations Parameter estimates are from old studies; still valid? Depends upon estimation of future number of partners; valid? Assumes consistent classification of cases across sites; Jails?

38 Conclusions For women: jail screening best for high-value cases (both sites) For men: STD clinic was the important site for high- value cases (both sites) Partner notification/cluster: Relatively few high value cases (Note: Didnt assess contribution of preventive treatment provided to exposed but seronegative partners)

39 Conclusions (cont) Primary cases: relatively large contribution (esp for males) EL cases: contributed few high-value cases among males; greater contribution among females (greater number of partners) Approach may help to focus efforts on finding high value cases Plan to evaluate approach in other contexts: MSM outbreaks, uncontrolled outbreaks, etc

40 The findings and conclusions in this presentation are those of the authors and do not necessarily represent the views of the Centers for Disease Control and Prevention/the Agency for Toxic Substances and Disease Registry


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