Evaluation of a Multivariate Syndromic Surveillance System for West Nile Virus

Abstract

Background: Various methods are currently used for the early detection of West Nile virus (WNV) but their outputs are not quantitative and/or do not take into account all available information. Our study aimed to test a multivariate syndromic surveillance system to evaluate if the sensitivity and the specificity of detection of WNV could be improved. Methods: Weekly time series data on nervous syndromes in horses and mortality in both horses and wild birds were used. Baselines were fitted to the three time series and used to simulate 100 years of surveillance data. WNV outbreaks were simulated and inserted into the baselines based on historical data and expert opinion. Univariate and multivariate syndromic surveillance systems were tested to gauge how well they detected the outbreaks; detection was based on an empirical Bayesian approach. The systems' performances were compared using measures of sensitivity, specificity, and area under receiver operating characteristic curve (AUC). Results: When data sources were considered separately (i.e., univariate systems), the best detection performance was obtained using the data set of nervous symptoms in horses compared to those of bird and horse mortality (AUCs equal to 0.80, 0.75, and 0.50, respectively). A multivariate outbreak detection system that used nervous symptoms in horses and bird mortality generated the best performance (AUC = 0.87). Conclusions: The proposed approach is suitable for performing multivariate syndromic surveillance of WNV outbreaks. This is particularly relevant, given that a multivariate surveillance system performed better than a univariate approach. Such a surveillance system could be especially useful in serving as an alert for the possibility of human viral infections. This approach can be also used for other diseases for which multiple sources of evidence are available.

Methodological challenges to multivariate syndromic surveillance: a case study using Swiss animal health data

“…SPC methods are then applied to this single statistic [65]. The work presented in [66] would be a recent example of dimension reduction method used in animal SyS. In this example, assuming that the three sources of evidence were conditionally independent, the time series of nervous syndromes in horses, the time series of mortality in adult horses and the time series of the number of necropsied wild birds were added to provide evidence for or against the hypothesis of a West Nile outbreak.…”

Prospects of leveraging an existing mosquito-borne disease surveillance system to monitor other emerging mosquito-borne diseases: a systematic review of West Nile Virus surveillance in Canada (2000–2016)

“…Instead, active surveillance initiatives using "specific and structured outreach" methods are necessary (Glynn and Backer, 2010). Syndromic surveillance is also another initiative for supporting active and real-time early detection of infections or clusters of syndromes (in humans and animal vectors such as horses and birds) before diagnosis (Faverjon et al, 2016;Mandl et al, 2004;Public Health Ontario, 2012). Mandl et al (2004) evaluated syndromic surveillance of WNV infections in horses.…”

The challenges posed by equine arboviruses

“…For example, differential diagnosis for infections causing nonsuppurative encephalitis in horses in Australia includes MVEV, RRV, WNV (Kunjin strain), and Hendra virus [49]. For example, taking weekly time series data on occurrence of nervous signs consistent with encephalitic disease in horses and mortality in both horses and wild birds has been used to identify outbreaks of WNV in France [51]. A recent serosurvey of 246 horses in Costa Rica revealed prevalence of 57% for WNV, 62% for EEEV, 43% for VEEV, and 17% for WEEV [50].…”

“…Although challenging, clinical diagnosis remains the cheapest approach to surveillance for equine arbovirus outbreaks and can be enhanced by adopting a 'multivariate syndromic surveillance' system in which data are compiled from various sources. For example, taking weekly time series data on occurrence of nervous signs consistent with encephalitic disease in horses and mortality in both horses and wild birds has been used to identify outbreaks of WNV in France [51]. Laboratory confirmation is still required, and to be effective, this approach requires communication of data between various agencies including veterinary bodies and equine industry stakeholders.…”