Retrospective Evaluation for ORCA Surveillance Comparison with Prescription Surveillance

Ueno, Tomoaki; Sugawara, Tamie; Ohkusa, Yasushi; Kawanohara, Hirokazu; Kamei, Miwako

doi:10.4236/jbm.2019.712001

Cited by 2 publications

(2 citation statements)

References 13 publications

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“…Online Receipt Computer Advantage (ORCA) surveillance data compiled since 2010 have been provided for public use [13]. The data include estimated daily numbers of patients by prefecture or municipality in Japan for influenza, hand-foot-and-mouth disease (HFMD), erythema infectiosum (EI), pharyngoconjunctival fever (PCF), respiratory syncytial (RS) virus infection, measles, rubella, and insolation from ORCA, an electronic medical claim system (http://infect.orca.med.or.jp/) with data produced and then provided freely to medical facilities by the Japan Medical Association.…”

Section: Discussionmentioning

confidence: 99%

Surveillance by age-class and prefecture for emerging infectious febrile diseases with respiratory symptoms, including COVID-19

Ueno¹,

Kurita²,

Sugawara

et al. 2020

Preprint

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Object The COVID-19 outbreak emerged in late 2019 in China, expanding rapidly thereafter. Even in Japan, epidemiological linkage of transmission was probably lost already by February 18, 2020. From that time, it has been necessary to detect clusters using syndromic surveillance. Method We identified common symptoms of COVID-19 as fever and respiratory symptoms. Therefore, we constructed a model to predict the number of patients with antipyretic analgesics (AP) and multi-ingredient cold medications (MIC) controlling well-known pediatric infectious diseases including influenza or RS virus infection. To do so, we used the National Official Sentinel Surveillance for Infectious Diseases (NOSSID), even though NOSSID data are weekly data with 10 day delays, on average. The probability of a cluster with unknown febrile disease with respiratory symptoms is a product of the probabilities of aberrations in AP and MIC, which is defined as one minus the probability of the number of patients prescribed a certain type of drug in PS compared to the number predicted using a model. This analysis was conducted prospectively in 2020 using data from October 1, 2010 through 2019 by prefecture and by age-class. Results The probability of unknown febrile disease with respiratory symptom cluster was estimated as less than 60% in 2020. Discussion The most severe limitation of the present study is that the proposed model cannot be validated. A large outbreak of an unknown febrile disease with respiratory symptoms must be experienced, at which time, practitioners will have to wing it. We expect that no actual cluster of unknown febrile disease with respiratory symptoms will occur, but if it should occur, we hope to detect it.

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Section: Discussionmentioning

confidence: 99%

Surveillance by age-class and prefecture for emerging infectious febrile diseases with respiratory symptoms, including COVID-19

Ueno¹,

Kurita²,

Sugawara

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Recently, the probability model for starting period to initiate to take palivizumab was examined [5]. It used ORCA surveillance, which is daily reporting system for influenza, hand-foot-and-mouth disease, Erythema infectiosum, Pharyngoconjunctival fever, RS virus infection, measles, rubella and insolation from ORCA [6], which is an electronic medical claim system (http://infect.orca.med.or.jp/). ORCA was abbreviation for "Online Receipt Computer Advantage" which is online medical claim service produced and provided medical facilities freely by Japan Medical Association.…”

Section: Introductionmentioning

confidence: 99%

Application of the Probability Model for Starting Period to Initiate to Take Palivizumab by Prefecture Using National Official Sentinel Surveillance in Japan

Kurita¹,

Sugawara²,

Ohkusa³

et al. 2020

JBM

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Background: Palivizumab were used for the premature infant or a high-risk infant with congenital heart disease. However, recently outbreak pattern of respiratory syncytial (RS) virus infection has been varying year by year. Moreover, it also has some regional difference. Therefore, the object of the present study was to develop early detection of the timing of that outbreak had started in each prefecture. Method: We used data in National Official Sentinel Surveillance for Infectious Diseases (NOSSID). Study period was March 16th, 2011 to December 30th, 2018. We defined stating period to initiate to take palivizumab as 8-12 weeks before from the peak of outbreak. We estimated whether the week is included in starting period or not from April 1st to the peak of outbreak by the past number of patients of RS virus infection on week and its squared. Additionally, we have to take delay in NOSSID into consideration. Results: In nationwide, the last two seasons, the model predicted precisely the starting period. At prefectural level, the model predicted the starting period precisely in 16.6% of all year and prefectures pairs. When we consider the delay in NOSSID into consideration, the patients can start to take in 14.9% of all year and prefectures pairs. Discussion and Conclusion: The result of the probability model was not good, and thus we have to develop more sophisticated model for prediction at prefecture level.

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Retrospective Evaluation for ORCA Surveillance Comparison with Prescription Surveillance

Cited by 2 publications

References 13 publications

Surveillance by age-class and prefecture for emerging infectious febrile diseases with respiratory symptoms, including COVID-19

Surveillance by age-class and prefecture for emerging infectious febrile diseases with respiratory symptoms, including COVID-19

Application of the Probability Model for Starting Period to Initiate to Take Palivizumab by Prefecture Using National Official Sentinel Surveillance in Japan

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