Center for Health Emergencies, Bruno Kessler Foundation, Trento, Italy.
Research and Innovation Centre, Fondazione Edmund Mach, San Michele all'Adige (TN), Italy.
PLoS Negl Trop Dis. 2023 Sep 14;17(9):e0011610. doi: 10.1371/journal.pntd.0011610. eCollection 2023 Sep.
Emerging arboviral diseases in Europe pose a challenge due to difficulties in detecting and diagnosing cases during the initial circulation of the pathogen. Early outbreak detection enables public health authorities to take effective actions to reduce disease transmission. Quantification of the reporting delays of cases is vital to plan and assess surveillance and control strategies. Here, we provide estimates of reporting delays during an emerging arboviral outbreak and indications on how delays may have impacted onward transmission.
METHODOLOGY/PRINCIPAL FINDINGS: Using descriptive statistics and Kaplan-Meyer curves we analyzed case reporting delays (the period between the date of symptom onset and the date of notification to the public health authorities) during the 2017 Italian chikungunya outbreak. We further investigated the effect of outbreak detection on reporting delays by means of a Cox proportional hazard model. We estimated that the overall median reporting delay was 15.5 days, but this was reduced to 8 days after the notification of the first case. Cases with symptom onset after outbreak detection had about a 3.5 times higher reporting rate, however only 3.6% were notified within 24h from symptom onset. Remarkably, we found that 45.9% of identified cases developed symptoms before the detection of the outbreak.
CONCLUSIONS/SIGNIFICANCE: These results suggest that efforts should be undertaken to improve the early detection and identification of arboviral cases, as well as the management of vector species to mitigate the impact of long reporting delays.
在欧洲新出现的虫媒病毒病由于病原体在初始传播期间难以检测和诊断病例而构成挑战。早期暴发检测使公共卫生当局能够采取有效行动减少疾病传播。量化病例报告的延迟对于规划和评估监测和控制策略至关重要。在这里,我们提供了在新兴虫媒病毒病暴发期间报告延迟的估计值,并说明了延迟可能如何影响传播。
方法/主要发现:使用描述性统计和 Kaplan-Meier 曲线,我们分析了 2017 年意大利基孔肯雅热暴发期间的病例报告延迟(从症状出现到向公共卫生当局通报的时间间隔)。我们进一步通过 Cox 比例风险模型调查了暴发检测对报告延迟的影响。我们估计,总体中位数报告延迟为 15.5 天,但在首例病例通报后,这一数字减少到 8 天。在暴发检测后出现症状的病例的报告率大约高出 3.5 倍,但只有 3.6%在症状出现后 24 小时内报告。值得注意的是,我们发现 45.9%已识别的病例在暴发检测之前出现症状。
结论/意义:这些结果表明,应努力改善虫媒病毒病病例的早期发现和识别,以及对病媒物种的管理,以减轻长报告延迟的影响。