911. Assessment of Representativeness of IPD Surveillance Conducted by the National Microbiology Laboratory of Canada
Bibliographic record
Abstract
Abstract Background Understanding the evolving epidemiology of Streptococcus pneumoniae serotypes is important for assessing the current and potential future immunization programs. In Canada, Invasive pneumococcal disease (IPD) is mandatory reportable to provincial/territorial public health. Provinces and territories voluntarily submit annual IPD data to the Canadian Notifiable Disease Surveillance System (CNDSS), which publishes information on IPD cases and incidence rates, however serotype data are not available. Provinces/territories also voluntarily submit IPD isolates to the National Microbiology laboratory (NML) for serotyping; provinces that conduct their own serotyping submit this information. The NML produces comprehensive IPD surveillance reports including serotype distribution; due to lack of population denominator, no incidence rates are available. The two surveillance programs are not linked. The objective of the study is to assess the representativeness of the NML surveillance as compared to the CNDSS and provincial reportable diseases databases. Methods Over the study time period (2010-2017), we compared annual IPD case counts between the NML and CNDSS reports. Due to the difference in age grouping between CNDSS and NML, comparison was limited to these groups: all age, < 5, 5-14 and > 15 years. In addition, the IPD counts from NML were compared to data from four largest provinces. Results For < 5 group, NML reported 91% of CNDSS case count whereas for 5-14 and > 15 years of age, it was 81% and 79%, respectively. Compared to the corresponding provincial databases, NML reported 91%, 97%, and 93% case counts for Ontario, British Columbia, and Alberta, respectively, while it was only 47% for Quebec. Further analysis revealed that the discrepancy in Quebec is the result of under-representation of >5 populations. Figure 1: Comparison of age stratified IPD case counts between CNDSS and NML Figure 2. Comparison of all age IPD case counts between NML and provincial databases Conclusion IPD surveillance conducted by NML has been instrumental to gain insight into the evolving epidemiology of S. pneumoniae serotypes in Canada. Comparisons of IPD counts from NML surveillance reports with reportable disease databases revealed different levels of concordance across provinces and age groups. The limitations of NML surveillance including incomplete or inconsistent reporting should be taken into consideration when interpreting the data. Disclosures Rajeev M. Nepal, PhD, Pfizer (Employee) Stephane B. Dion, PhD, Pfizer (Employee) Ana Gabriela Grajales, MD, Pfizer (Employee) Maria Major, B.Sc., MPH, Pfizer (Employee) Alejandro Cane, MD, Pfizer (Employee) Jelena Vojicic, MD, Pfizer (Employee)
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".