Technical Division, KNCV Tuberculosis Foundation, Abuja, Nigeria.
University of Texas, Dallas, TX, United States.
JMIR Public Health Surveill. 2023 Feb 8;9:e40311. doi: 10.2196/40311.
Undiagnosed tuberculosis (TB) cases are the major challenge to TB control in Nigeria. An early warning outbreak recognition system (EWORS) is a system that is primarily used to detect infectious disease outbreaks; this system can be used as a case-based geospatial tool for the real-time identification of hot spot areas with clusters of TB patients. TB screening targeted at such hot spots should yield more TB cases than screening targeted at non-hot spots.
We aimed to demonstrate the effectiveness of an EWORS for TB hot spot mapping as a tool for detecting areas with increased TB case yields in high TB-burden states of Nigeria.
KNCV Tuberculosis Foundation Nigeria deployed an EWORS to 14 high-burden states in Nigeria. The system used an advanced surveillance mechanism to identify TB patients' residences in clusters, enabling it to predict areas with elevated disease spread (ie, hot spots) at the ward level. TB screening outreach using the World Health Organization 4-symptom screening method was conducted in 121 hot spot wards and 213 non-hot spot wards selected from the same communities. Presumptive cases identified were evaluated for TB using the GeneXpert instrument or chest X-ray. Confirmed TB cases from both areas were linked to treatment. Data from the hot spot and non-hot spot wards were analyzed retrospectively for this study.
During the 16-month intervention, a total of 1,962,042 persons (n=734,384, 37.4% male, n=1,227,658, 62.6% female) and 2,025,286 persons (n=701,103, 34.6% male, n=1,324,183, 65.4% female) participated in the community TB screening outreaches in the hot spot and non-hot spot areas, respectively. Presumptive cases among all patients screened were 268,264 (N=3,987,328, 6.7%) and confirmed TB cases were 22,618 (N=222,270, 10.1%). The number needed to screen to diagnose a TB case in the hot spot and non-hot spot areas was 146 and 193 per 10,000 people, respectively.
Active TB case finding in EWORS-mapped hot spot areas yielded higher TB cases than the non-hot spot areas in the 14 high-burden states of Nigeria. With the application of EWORS, the precision of diagnosing TB among presumptive cases increased from 0.077 to 0.103, and the number of presumptive cases needed to diagnose a TB case decreased from 14.047 to 10.255 per 10,000 people.
未确诊的结核病（TB）病例是尼日利亚结核病控制的主要挑战。早期预警暴发识别系统（EWORS）是一种主要用于检测传染病暴发的系统；该系统可用作基于病例的地理空间工具，实时识别结核病患者集群的热点地区。针对这些热点地区进行结核病筛查应比针对非热点地区进行筛查产生更多的结核病病例。
我们旨在展示 EWORS 作为一种工具在尼日利亚高结核病负担州识别结核病热点地图的有效性，以检测结核病发病率增加的地区。
KNCV 结核病基金会尼日利亚在尼日利亚的 14 个高负担州部署了 EWORS。该系统使用先进的监测机制来识别集群中的结核病患者居住地，从而能够预测疾病传播加剧的地区（即热点地区），具体到病房层面。在从同一社区中选择的 121 个热点病房和 213 个非热点病房中，使用世界卫生组织的 4 症状筛查方法进行了结核病筛查外展。使用 GeneXpert 仪器或胸部 X 射线对发现的疑似病例进行结核病评估。来自这两个地区的确诊结核病病例都被纳入治疗。对这项研究，对热点病房和非热点病房的数据进行了回顾性分析。
在 16 个月的干预期间，共有 1962042 人（n=734384，男性占 37.4%，n=1227658，女性占 62.6%）和 2025286 人（n=701103，男性占 34.6%，n=1324183，女性占 65.4%）分别参加了热点和非热点地区的社区结核病筛查外展。所有筛查患者中的疑似病例为 268264 例（N=3987328，6.7%），确诊结核病病例为 22618 例（N=222270，10.1%）。在热点和非热点地区，每 10000 人筛查诊断 1 例结核病病例所需的人数分别为 146 和 193。
在尼日利亚的 14 个高结核病负担州，对 EWORS 绘制的热点地区进行活动性结核病病例发现比非热点地区产生了更多的结核病病例。应用 EWORS 后，从 0.077 提高到 0.103，从 14047 例减少到 10255 例，每 10000 人诊断 1 例结核病病例所需的疑似病例数量。
