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DeFelice NB, Birger R, DeFelice N, et al. Modeling and Surveillance of Reporting Delays of Mosquitoes and Humans Infected With West Nile Virus and Associations With Accuracy of West Nile Virus Forecasts. JAMA Netw Open. 2019;2(4):e193175. doi:10.1001/jamanetworkopen.2019.3175
What are the operational challenges limiting effective implementation of a real-time West Nile virus (WNV) forecasting system?
In this modeling study of historical and real-time mosquito WNV assay results and human medical records, delays in data reporting for both infected mosquitoes and human WNV cases were associated with a reduction in average WNV forecast accuracy.
For public health departments and mosquito abatement districts to integrate forecasting effectively into operational decision making, the relaying of real-time health and environmental surveillance data should be prioritized.
West Nile virus (WNV) is the leading cause of domestically acquired arboviral disease.
To develop real-time WNV forecasts of infected mosquitoes and human cases.
Design, Setting, and Participants
Real-time forecasts of WNV in 4 geographically dispersed locations in the United States were generated using a WNV model-inference forecasting system previously validated with retrospective data. Analysis was performed to evaluate how observational reporting delays of mosquito WNV assay results and human medical records were associated with real-time forecast accuracy.
Mosquitoes positive for WNV and human cases.
Main Outcomes and Measures
Delays in reporting mosquito WNV assay results and human medical records and the association of these delays with real-time WNV forecast accuracy.
Substantial delays in data reporting exist for both infected mosquitoes and human WNV cases. For human cases, confirmed data (n = 37) lagged behind the onset of illness by a mean (SD) of 5.5 (2.3) weeks (range, 2-14 weeks). These human case reporting lags reduced mean forecast accuracy for the total number of human cases over the season in 110 simulated outbreaks for 2 forecasting systems by 26% and 14%, from 2 weeks before to 3 weeks after the predicted peak of infected mosquitoes. This period is the time span during which 47% of human cases are reported. Of 7064 mosquito pools, 500 (7%) tested positive; the reporting lag for these data associated with viral testing at a state laboratory was a mean (SD) of 6.6 (2.6) days (range, 4-11 days). This reporting lag was associated with decreased mean forecast accuracy for the 3 mosquito infection indicators, timing, magnitude, and season, by approximately 5% for both forecasting systems.
Conclusions and Relevance
Delays in reporting human WNV disease and infected mosquito information are associated with difficulties in outbreak surveillance and decreased real-time forecast accuracy. Infected mosquito lags were short enough that skillful forecasts could still be generated for mosquito infection indicators, but the human WNV case lags were too great to support accurate forecasting in real time. Forecasting WNV is potentially an important evidence-based decision support tool for public health officials and mosquito abatement districts; however, to operationalize real-time forecasting, more resources are needed to reduce human case reporting lags between illness onset and case confirmation.
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