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A time series analysis of gonorrhea surveillance data
Author(s) -
Schnell Daniel,
Zaidi Akbar,
Reynolds Gladys
Publication year - 1989
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.4780080315
Subject(s) - gonorrhea , series (stratigraphy) , time series , computer science , statistics , medicine , virology , mathematics , machine learning , biology , paleontology , human immunodeficiency virus (hiv)
Gonorrhea is the most frequently reported communicable disease in the United States. In response to rapidly rising rates in the late 1960s, the Public Health Service instituted a gonorrhea control programme. An important component of the programme is the screening of women for gonococcal infections. We use a time series intervention model to estimate the initial increase in reporting of cases in women associated with the control programme. From the middle 1970s to the middle 1980s, a regular seasonal pattern in the data is conspicuous. We use a second time series model to quantify the seasonal variation during this period and to construct forecasts.