1. Reassessment of a large-scale syphilis epidemic: using an estimated infection date Schumacher CM, Bernstein KT, Zenilman JM, Rompalo AM Baltimore City Health Department Johns Hopkins University

2. Introduction Timely surveillance and early identification of syphilis outbreaks crucial to Elimination Plan Epidemic curves illustrate disease dynamics –Traditionally defined by date health department receives notice of infection –Approach does not account for lag time between date of infection and date of report Hypothesis: Date of infection is more accurate depiction of syphilis dynamics

3. Introduction, cont’d Large outbreak in Baltimore City, Maryland provided model for evaluation of infection date curve Source: CDC. MMWR. March 2, 1996 45 (8):166-169.

4. Methods Records of early syphilis cases (primary, secondary, early latent) reported to Baltimore City Health Department January 1994 and June 2003 Stratified by sex and disease stage 2 epidemic curves –Date case received by BCHD (report date) –Estimated date of infection (Infection Date) Infection Date = Diagnosis Date – Median incubation time –45 days primary –60 days secondary –183 days early latent

5. Results 8409 syphilis cases reported to Baltimore City Health Department (BCHD) 7806 (92.8%) diagnosed with Primary, Secondary or Early Latent Syphilis 7663 (98%) included in Final Analysis –Exclusions 19 (0.2%) missing sex 1 (0.01%) missing report date 123 (1.6%) missing diagnosis date

6. Results (cont’d) 1.Reports fail to account for large increases in infections during development period 2.Report curves do not follow shape or appropriate lag-times during epidemic period 3.Reports underestimate infections during development period 4.Reports overestimate infections during epidemic period

7. 1. Failure to account for increases in infections, P&S syphilis, males For display purposes, data was restricted to years 1993 - 1999 +29% -51%

8. 1.Failure to account for increases in infections, Early Latent Syphilis, males +40% -48%

9. 2. Report Curve does not reflect shape of infection curve

10. 3. Reports underestimate Infections during development period P&S, males –1Q 1995 – 4Q 1995, 279 infections –2Q 1995 – 1Q 1996, 232 reports (83%) Early Latent, males –1Q 1995 – 4Q 1995, 386 infections –3Q 1995 – 2Q 1996, 330 reports (85%)

11. 4. Reports overestimate infections during epidemic period P&S, males –3Q 1996 – 2Q 1997, 370 infections –4Q 1996 – 3Q 1997, 404 reports (109%) Early Latent, males –2Q 1996 – 1Q 1997, 507 infections –4Q 1996 – 3Q 1997, 534 reports (105%)

12. Findings Lag-time bias may be present when defining epidemic period based on date of report –Ascertaining changes in demographics and social factors between pre-epidemic and epidemic periods provides insight into causes and control methods Using infection date as timeframe of epidemic removes bias due to incubation time of disease stage and time between diagnosis and reporting

13. Findings, cont’d Difference of curves in 1995 show reporting not prompt after diagnosis –Timely reporting necessary to find and treat potential contacts before contacts become infectious –Delayed reporting further impedes Health departments ability to reach contacts, allowing for epidemic propagation

14. Findings cont’d Report overestimation and overlap of curves during epidemic period likely due to increased physician awareness and more intense case seeking

15. Limitations Those in highest risk populations likely not included –Should not bias results since missing from both curves –Effect on either curve unknown Effect of disease stage misclassification also unknown

16. Conclusions Using estimated date of infection as epidemic timeframe more accurate depiction –Understanding community dynamics at time of transmission may be more useful in determining causes and methods of control especially when overlapping epidemics present Comparison on two curves can serve as check on communication between providers and health departments

17. Recommendations With electronic data, algorithm relatively easy, fast and inexpensive Health departments should consider using estimated dates of infection as timeframe for epidemic investigations

19. P&S Syphilis in Males

20. P&S Syphilis in Females

21. Development Period P&S in Females +18 % - 42%

22. Epidemic Period P&S in Females

23. Early Latent Syphilis in Males

24. Epidemic Period Early Latent in Males

25. Early Latent Syphilis in Females

26. Development Period Early Latent in Females + 96% -46%

27. Epidemic Period Early Latent in Females

28. Reports underestimate infections during development period P&S Females –1Q 1995 – 4Q 1995, 204 infections –2Q 1995 – 1Q 1996, 152 reports (75%) Early Latent, Females –1Q 1995 – 4Q 1995, 301 infections –3Q 1995 – 2Q 1996, 258 reports (86%)

29. Reports overestimate infections during epidemic period P&S, Females –3Q 1996 – 2Q 1997, 323 infections –4Q 1996 – 3Q 1997, 346 reports, (107%) Early Latent, Females –1Q 1996 – 3Q 1997, 797 infections –3Q 1996 – 1Q 1998, 862 reports, (108%)