Unreported cases in the 2014-2016 Ebola epidemic: Spatiotemporal variation, and implications for estimating transmission

In the recent 2014–2016 Ebola epidemic in West Africa, non-hospitalized cases were an important component of the chain of transmission. However, non-hospitalized cases are at increased risk of going unreported because of barriers to access to healthcare. Furthermore, underreporting rates may fluctuate over space and time, biasing estimates of disease transmission rates, which are important for understanding spread and planning control measures. We performed a retrospective analysis on community deaths during the recent Ebola epidemic in Sierra Leone to estimate the number of unreported non-hospitalized cases, and to quantify how Ebola reporting rates varied across locations and over time. We then tested if variation in reporting rates affected the estimates of disease transmission rates that were used in surveillance and response. We found significant variation in reporting rates among districts, and district-specific rates of increase in reporting over time. Correcting time series of numbers of cases for variable reporting rates led, in some instances, to different estimates of the time-varying reproduction number of the epidemic, particularly outside the capital. Future analyses that compare Ebola transmission rates over time and across locations may be improved by considering the impacts of differential reporting rates.2014—2016年西非埃博拉疫情期间，非住院病例是疫情传播链的重要组成环节。然而，由于存在就医可及性障碍，非住院病例的漏报风险显著升高。此外，漏报率可能随空间与时间发生波动，进而对疾病传播率的估算结果产生偏倚，而传播率对于解析疫情传播规律、制定防控策略均具有重要意义。本研究针对塞拉利昂本轮埃博拉疫情期间的社区死亡病例开展回顾性分析，旨在估算未被报告的非住院病例总数，并量化埃博拉报告率在不同地区与不同时段的变化特征。随后，本研究检验了报告率差异是否会影响监测与响应工作中所采用的疾病传播率估算结果。研究发现，各行政区的报告率存在显著差异，且不同行政区的报告率随时间的增长速率各不相同。针对可变报告率的病例数时间序列进行校正后，在部分场景下，疫情时变再生数的估算结果会出现变化，尤其是在首都以外的区域。未来开展埃博拉传播率跨时间、跨地区的对比分析时，若纳入报告率差异的影响因素，可有效提升分析结果的可靠性与准确性。