Browsing by Author "Fathima, Sumana"

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    Bordetella pertussis in sporadic and outbreak settings in Alberta, Canada, July 2004 – December 2012
    (BioMed Central, 2014-01-30) Fathima, Sumana; Ferrato, Christina; Lee, Bonita E; Simmonds, Kimberley; Yan, Lin; Mukhi, Shamir N; Li, Vincent; Chui, Linda; Drews, Steven J
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    Epidemiology of pertussis in Alberta, Canada 2004–2015
    (2017-06-02) Liu, Xianfang C; Bell, Christopher A; Simmonds, Kimberley A; Svenson, Lawrence W; Fathima, Sumana; Drews, Steven J; Schopflocher, Donald P; Russell, Margaret L
    Abstract Background We describe the epidemiology of pertussis in Alberta, Canada by person, place, and time between 2004 and 2015, identify outbreak years, and examine vaccination coverage and vaccination timeliness. Methods We used health data from Alberta’s Communicable Disease Registry System for the period of January 1, 2004 through August 31, 2015 to identify unique cases of pertussis. Unique cases were deterministically linked to data in Alberta’s immunization repository and health care insurance plan registry. Population estimates and vaccination coverage were extracted from Alberta’s online Interactive Health Data Application. We estimated pertussis incidence rates per 100,000 persons by year, age group, gender, and health zone. Outbreak years were identified using a one-sided cumulative sum (CUSUM) analysis by comparing annual incidence rates to baseline rates. Results Over the period, 3510 cases of pertussis were confirmed by laboratory testing or epidemiological linkage. Incidence rates per 100,000 persons were highest in 2004 (20.5), 2005 (13.6), and 2015 (10.4) for all age groups. Incidence rates were highest among the youngest age groups and decreased as age groups increased. Based on CUSUM analysis, 2008 and 2012 met the criteria for outbreak years. Vaccination coverage was over 90% among the general population, however only 61% of cases received at least one dose. About 60% of cases were diagnosed 5+ years after receiving the vaccine. Approximately 87–91% of vaccinated cases did not receive the first three vaccine doses in a timely manner. Conclusion Pertussis incidence rates fluctuated over the period across all age groups. The majority of cases had no record of vaccination or were delayed in receiving vaccines. CUSUM analysis was an effective method for identifying outbreaks.
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    How well do ICD-9 physician claim diagnostic codes identify confirmed pertussis cases in Alberta, Canada? A Canadian Immunization Research Network (CIRN) Study
    (2017-07-12) Fathima, Sumana; Simmonds, Kimberley A; Drews, Steven J; Svenson, Lawrence W; Kwong, Jeffrey C; Mahmud, Salaheddin M; Quach, Susan; Johnson, Caitlin; Schwartz, Kevin L; Crowcroft, Natasha S; Russell, Margaret L
    Abstract Background Rates of Bordetella pertussis have been increasing in Alberta, Canada despite vaccination programs. Waning immunity from existing acellular component vaccines may be contributing to this. Vaccine effectiveness can be estimated using a variety of data sources including diagnostic codes from physician billing claims, public health records, reportable disease and laboratory databases. We sought to determine if diagnostic codes from billing claims (administrative data) are adequately sensitive and specific to identify pertussis cases among patients who had undergone disease-specific laboratory testing. Methods Data were extracted for 2004–2014 from a public health communicable disease database that contained data on patients under investigation for B. pertussis (both those who had laboratory tests and those who were epidemiologically linked to laboratory-confirmed cases) in Alberta, Canada. These were deterministically linked using a unique lifetime person identifier to the provincial billing claims database, which contains International Classification of Disease version 9 (ICD-9) diagnostic codes for physician visits. We examined visits within 90 days of laboratory testing. ICD-9 codes 033 (whooping cough), 033.0 (Bordetella pertussis), 033.1 (B. parapertussis), 033.8 (whooping cough, other specified organism), and 033.9 (whooping cough, other unspecified organism) in any of the three diagnostic fields for a claim were classified as being pertussis-specific codes. We calculated sensitivity, specificity, positive (PPV) and negative (NPV) predictive values. Results We identified 22,883 unique patients under investigation for B. pertussis. Of these, 22,095 underwent laboratory testing. Among those who had a laboratory test, 2360 tested positive for pertussis. The sensitivity of a pertussis-specific ICD-9 code for identifying a laboratory-confirmed case was 38.6%, specificity was 76.9%, PPV was 16.0%, and NPV was 91.6%. Conclusion ICD-9 codes from physician billing claims data have low sensitivity and moderate specificity to identify laboratory-confirmed pertussis among persons tested for pertussis.