Abstract：
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.
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.
摘要：
背景：未诊断的结核病（TB）病例是尼日利亚结核病控制的主要挑战。早期预警爆发识别系统（EWORS）是主要用于检测传染病爆发的系统；该系统可以用作基于案例的地理空间工具，用于实时识别具有结核病患者集群的热点区域。针对此类热点的TB筛查应比针对非热点的筛查产生更多的TB病例。
目的：我们的目的是证明EWORS作为检测尼日利亚高结核病负担州中结核病病例产量增加区域的工具的结核病热点图谱的有效性。
方法：尼日利亚KNCV结核病基金会向尼日利亚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结核病患者的集群，使其能够预测疾病传播增加的地区(即，热点)在病房级别。在同一社区中选择的121个热点病房和213个非热点病房，使用世界卫生组织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射线对确定的推定病例进行TB评估。来自这两个地区的确诊结核病病例与治疗有关。本研究对热点和非热点病房的数据进行了回顾性分析。
结果：在16个月的干预期间，共有1,962,042人(n=734,384，男性37.4%，n=1,227,658，62.6％女性）和2,025,286人（n=701,103，34.6％男性，n=1,324,183,女性占65.4%)参加热点地区和非热点地区的社区结核病筛查外展,分别。所有筛查患者中的推定病例为268,264例（N=3,987,328，6.7％），确诊的TB病例为22,618例（N=222,270，10.1％）。在热点地区和非热点地区诊断结核病病例所需的筛查人数分别为每万人146人和193人,分别。
结论：在尼日利亚14个高负担州中，在EWORS映射的热点地区发现的活动性结核病病例比非热点地区产生的结核病病例更高。随着EWORS的应用,在推定病例中诊断结核病的准确率从0.077上升至0.103,诊断结核病病例所需的推定病例数从14.047下降至10.255/10,000人.
目的：我们的目的是证明EWORS作为检测尼日利亚高结核病负担州中结核病病例产量增加区域的工具的结核病热点图谱的有效性。
方法：尼日利亚KNCV结核病基金会向尼日利亚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结核病患者的集群，使其能够预测疾病传播增加的地区(即，热点)在病房级别。在同一社区中选择的121个热点病房和213个非热点病房，使用世界卫生组织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射线对确定的推定病例进行TB评估。来自这两个地区的确诊结核病病例与治疗有关。本研究对热点和非热点病房的数据进行了回顾性分析。
结果：在16个月的干预期间，共有1,962,042人(n=734,384，男性37.4%，n=1,227,658，62.6％女性）和2,025,286人（n=701,103，34.6％男性，n=1,324,183,女性占65.4%)参加热点地区和非热点地区的社区结核病筛查外展,分别。所有筛查患者中的推定病例为268,264例（N=3,987,328，6.7％），确诊的TB病例为22,618例（N=222,270，10.1％）。在热点地区和非热点地区诊断结核病病例所需的筛查人数分别为每万人146人和193人,分别。
结论：在尼日利亚14个高负担州中，在EWORS映射的热点地区发现的活动性结核病病例比非热点地区产生的结核病病例更高。随着EWORS的应用,在推定病例中诊断结核病的准确率从0.077上升至0.103,诊断结核病病例所需的推定病例数从14.047下降至10.255/10,000人.
