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Time series analysis of syphilis surveillance data
A A Zaidi1, D J Schnell, G H Reynolds
1Division of Sexually Transmitted Diseases, Centers for Disease Control, Atlanta, Georgia 30333.
Statistics in Medicine
|March 1, 1989
Summary
Public health programs require accurate forecasting. Time series models predict rising syphilis cases in women and infants, indicating a need for updated control strategies.
Area of Science:
- Public Health
- Epidemiology
- Biostatistics
Background:
- Effective disease control programs necessitate setting objectives and priorities based on available resources.
- Estimating current and predicting future disease burdens are crucial for optimal resource allocation.
- The Centers for Disease Control and Prevention (CDC) manages a syphilis control program, tracking sexually transmitted disease cases quarterly.
Purpose of the Study:
- To forecast future syphilis case numbers using time series modeling.
- To analyze trends in primary, secondary, and congenital syphilis cases.
- To inform public health strategies for syphilis control.
Main Methods:
- Development of time series models for syphilis case forecasting.
- Analysis of historical data for primary and secondary syphilis in men and women.
- Forecasting congenital syphilis cases in infants under one year of age.
Main Results:
- Syphilis cases declined significantly from 1947 to 1956 but increased by 1986.
- Congenital syphilis cases decreased substantially from 1941 to 1983 but rose by 1986.
- Time series models indicated no change in the trend for male syphilis cases, but an increase for female and congenital cases in 1987.
Conclusions:
- The study highlights an increasing trend in syphilis among women and infants.
- Time series models provide valuable tools for predicting disease trends and informing public health interventions.
- The findings suggest a need to reassess and potentially adapt current syphilis control strategies to address emerging trends.