Veterinary Epidemiology and Economics Unit, Kenya Ministry of Agriculture, livestock and Fisheries, Nairobi, Kenya.
College of Veterinary Medicine, Kansas State University, Manhattan, Kansas, United States of America.
PLoS Negl Trop Dis. 2018 Apr 26;12(4):e0006353. doi: 10.1371/journal.pntd.0006353. eCollection 2018 Apr.
In mid-2015, the United States' Pandemic Prediction and Forecasting Science and Technical Working Group of the National Science and Technology Council, Food and Agriculture Organization Emergency Prevention Systems, and Kenya Meteorological Department issued an alert predicting a high possibility of El-Niño rainfall and Rift Valley Fever (RVF) epidemic in Eastern Africa.
METHODOLOGY/PRINCIPAL FINDINGS: In response to the alert, the Kenya Directorate of Veterinary Services (KDVS) carried out an enhanced syndromic surveillance system between November 2015 and February 2016, targeting 22 RVF high-risk counties in the country as identified previously through risk mapping. The surveillance collected data on RVF-associated syndromes in cattle, sheep, goats, and camels from >1100 farmers through 66 surveillance officers. During the 14-week surveillance period, the KDVS received 10,958 reports from participating farmers and surveillance officers, of which 362 (3.3%) had at least one syndrome. The reported syndromes included 196 (54.1%) deaths in young livestock, 133 (36.7%) abortions, and 33 (9.1%) hemorrhagic diseases, with most occurring in November and December, the period of heaviest rainfall. Of the 69 herds that met the suspect RVF herd definition (abortion in flooded area), 24 (34.8%) were defined as probable (abortions, mortalities in the young ones, and/or hemorrhagic signs) but none were confirmed.
CONCLUSION/SIGNIFICANCE: This surveillance activity served as an early warning system that could detect RVF disease in animals before spillover to humans. It was also an excellent pilot for designing and implementing syndromic surveillance in animals in the country, which is now being rolled out using a mobile phone-based data reporting technology as part of the global health security system.
2015 年年中,美国国家科学技术委员会大流行性疾病预测和预报科学与技术工作组、粮农组织紧急预防系统以及肯尼亚气象部门发布预警称,东非地区发生厄尔尼诺现象降雨及裂谷热(RVF)疫情的可能性很高。
方法/主要发现:针对该预警,肯尼亚兽医服务局(KDVS)于 2015 年 11 月至 2016 年 2 月期间实施了强化综合征监测系统,针对此前通过风险图确定的该国 22 个 RVF 高风险县。该监测系统通过 66 名监测官员从 1100 多名农民那里收集了与 RVF 相关的牛、绵羊、山羊和骆驼综合征数据。在 14 周监测期间,KDVS 收到了来自参与农民和监测官员的 10958 份报告,其中 362 份(3.3%)至少有一个综合征。报告的综合征包括 196 例(54.1%)幼畜死亡、133 例(36.7%)流产和 33 例(9.1%)出血性疾病,大多数发生在 11 月和 12 月降雨量最大的时期。在符合疑似 RVF 畜群定义(洪水地区流产)的 69 个畜群中,有 24 个(34.8%)被定义为可能(流产、幼畜死亡和/或出血迹象),但没有一个得到证实。
结论/意义:这项监测活动是一种早期预警系统,可在疾病向人类溢出之前检测动物中的 RVF 疾病。这也是在该国开展动物综合征监测的出色试点,目前正在利用基于移动电话的数据报告技术在全球卫生安全系统中推广。