ABSTRACT
Introduction: The current study aims to assess the performance of data mining techniques in detecting safety signals for adverse events following immunization (AEFI) using routinely obtained data in China. Four different methods for detecting vaccine safety signals were evaluated. Methods: The AEFI data from 2011 to 2015 was collected for our study. We analyzed the data using four different methods to detect signals: the proportional reporting ratio (PRR), reporting odds ratio (ROR), Bayesian confidence propagation neural network (BCPNN), and multi-item gamma Poisson shrinker (MGPS). Each method was evaluated at 1-3 thresholds for positivity. To assess the performance of these methods, we used the published signal rates as gold standards to determine the sensitivity and specificity. Results: The number of identified signals varied from 602 for PRR1 (with a threshold of 1) to 127 for MGPS1. When considering the common reactions as the reference standard, the sensitivity ranged from 0.9% for MGPS1/2 to 38.2% for PRR1/2, and the specificity ranged from 85.2% for PRR1 and ROR1 to 96.7% for MGPS1. When considering the rare reactions as the reference standard, PRR1, PRR2, ROR1, ROR2, and BCPNN exhibited the highest sensitivity (73.3%), while MGPS1 exhibited the highest specificity (96.9%). Discussion: For common reactions, the sensitivities were modest and the specificities were high. For rare reactions, both the sensitivities and specificities were high. Our study provides valuable insights into the selection of signal detection methods and thresholds for AEFI data in China.
ABSTRACT
OBJECTIVE: A total of 131 cases of avian-originated H7N9 infection have been confirmed in China mainland from February 2013 to May 2013. We calculated the overall burden of H7N9 cases in China as of 31 May 2013 to provide an example of comprehensive burden of disease in the 21st century from an acute animal-borne emerging infectious disease. DESIGN: We present an accurate and operable method for estimating the burden of H7N9 cases in China. The main drivers of economic loss were identified. Costs were broken down into direct (outpatient and inpatient examination and treatment) and indirect costs (cost of disability-adjusted life years (DALYs) and losses in the poultry industry), which were estimated based on field surveys and China statistical year book. SETTING: Models were applied to estimate the overall burden of H7N9 cases in China. PARTICIPANTS: 131 laboratory-confirmed H7N9 cases by 31 May 2013. OUTCOME MEASURE: Burden of H7N9 cases including direct and indirect losses. RESULTS: The total direct medical cost was ¥16 422 535 (US$2 627 606). The mean cost for each patient was ¥10 117 (US$1619) for mild patients, ¥139 323 (US$22 292) for severe cases without death and ¥205 976 (US$32 956) for severe cases with death. The total cost of DALYs was ¥17 356 561 (US$2 777 050). The poultry industry losses amounted to ¥7.75 billion (US$1.24 billion) in 10 affected provinces and ¥3.68 billion (USD$0.59 billion) in eight non-affected adjacent provinces. CONCLUSIONS: The huge poultry industry losses followed live poultry markets closing down and poultry slaughtering in some areas. Though the proportion of direct medical losses and DALYs losses in the estimate of H7N9 burden was small, the medical costs per case were extremely high (particularly for addressing the use of modern medical devices). A cost-effectiveness assessment for the intervention should be conducted in a future study.
