Reassessment of a large-scale syphilis epidemic: using an estimated infection date

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) • Reports fail to account for large increases in infections during development period • Report curves do not follow shape or appropriate lag-times during epidemic period • Reports underestimate infections during development period • Reports overestimate infections during epidemic period

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

8. 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 PeriodP&S in Females +18 % - 42%

22. Epidemic PeriodP&S in Females

23. Early Latent Syphilis in Males

24. Epidemic PeriodEarly Latent in Males

25. Early Latent Syphilis in Females

26. Development PeriodEarly Latent in Females + 96% -46%

27. Epidemic PeriodEarly 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%)