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. 2017 Jun 17;17(1):86.
doi: 10.1186/s12911-017-0484-7.

Using record linkage to validate notification and laboratory data for a more accurate assessment of notifiable infectious diseases

Faye J Lim  1 , Christopher C Blyth  2   3   4   5 , Avram Levy  5   6 , Parveen Fathima  2 , Nicholas de Klerk  2 , Carolien Giele  7 , Hannah C Moore  2
Affiliations

Using record linkage to validate notification and laboratory data for a more accurate assessment of notifiable infectious diseases

Faye J Lim et al. BMC Med Inform Decis Mak. .

Abstract

Background: Infectious disease burden is commonly assessed using notification data. Using retrospective record linkage in Western Australia, we described how well notification data captures laboratory detections of influenza, pertussis and invasive pneumococcal disease (IPD).

Methods: We linked data from the Western Australian Notifiable Infectious Diseases Database (WANIDD) and the PathWest Laboratory Database (PathWest) pertaining to the Triple I birth cohort, born in Western Australia in 1996-2012. These were combined to calculate the number of unique cases captured in each dataset alone or in both datasets. To assess the impact of under-ascertainment, we compared incidence rates calculated using WANIDD data alone and using combined data.

Results: Overall, there were 5550 influenza, 513 IPD (2001-2012) and 4434 pertussis cases (2000-2012). Approximately 2% of pertussis and IPD cases and 7% of influenza cases were solely recorded in PathWest. Notification of influenza and pertussis cases to WANIDD improved over time. Overall incidence rates of influenza in children aged <5 years using both datasets was 10% higher than using WANIDD data alone (IRR = 1.1, 95% CI = 1.1-1.2).

Conclusions: This is the first time WANIDD data have been validated against routinely collected laboratory data. We anticipated all cases would be captured in WANIDD but found additional laboratory-confirmed cases that were not notified. Studies investigating pathogen-specific infectious disease would benefit from using multiple data sources.

Keywords: Disease notification; Record linkage; Validation studies.

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Figures

Fig. 1
Fig. 1
Number of influenza, IPD and pertussis cases that were found in each datasets. IPD = invasive pneumococcal disease; WANIDD = Western Australian Notifiable Infectious Diseases Database; PathWest = PathWest Laboratory Medicine Western Australia Database. *Influenza and IPD data restricted to 2001–2012
Fig. 2
Fig. 2
Proportion of influenza cases recorded in each dataset by year of specimen collection (2001–2012). WANIDD = Western Australian Notifiable Infectious Diseases Database; PathWest = PathWest Laboratory Medicine Western Australia Database. Percentages may not equal to 100 due to rounding
Fig. 3
Fig. 3
Influenza incidence rates in children aged less than 5 years by year of specimen collection. WANIDD = Western Australian Notifiable Infectious Diseases Database; PathWest = PathWest Laboratory Medicine Western Australia Database
Fig. 4
Fig. 4
Pertussis incidence rates in children aged less than 5 years by year of specimen collection. WANIDD = Western Australian Notifiable Infectious Diseases Database; PathWest = PathWest Laboratory Medicine Western Australia Database
Fig. 5
Fig. 5
IPD incidence rates in children aged less than 5 years by year of specimen collection. WANIDD = Western Australian Notifiable Infectious Diseases Database; PathWest = PathWest Laboratory Medicine Western Australia Database
See this image and copyright information in PMC

References

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