Identifying Hotspots of Tuberculosis in Nigeria using EWORS: Implications for Active Case Finding and Intervention (Preprint)

Author:

Ogbudebe ChidubemORCID,Odume Bethrand,Chukwuogo Ogoamaka,Useni Sani,Dim Cyril,Okuzu OkeyORCID,Jeong Dohyo,Malolan Chenchita,Kim Dohyeong,Nwariaku Fiemu,Nkiru Nwokoye,Gande Stephanie,Nongo Debby,Eneogu Rupert,Odusote Temitayo,Oyelaran Salewa,Chijioke-Akaniro Obioma,Gidado MustaphaORCID,Anyaike Chukwuma

Abstract

BACKGROUND

Undiagnosed tuberculosis (TB) cases are the major challenge to TB control in Nigeria. Though the Early Warning Outbreak Recognition System (EWORS) is primarily used to detect infectious disease outbreaks, it can be used as a case-based geospatial tool for the real-time identification of hotspot areas with TB patients' residence in clusters. TB screening targeted at such hotspot wards should yield more TB cases when compared to non-hotspot areas.

OBJECTIVE

To demonstrate the effectiveness of EWORS TB hotspot mapping as a tool for detecting areas with increased TB case yields in high TB burden States of Nigeria.

METHODS

KNCV Nigeria deployed EWORS to the 14 high burden States of Nigeria. The system used an advanced surveillance mechanism to identify TB patients’ residences in clusters, enabling it to identify areas with elevated disease spread (hotspots) at the ward level. TB screening outreach using the WHO-four-symptom screen was conducted in 175 hotspot wards and 173 non-hotspot 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 hotspot and non-hotspot wards were analyzed retrospectively for this study.

RESULTS

A total of 1,962,042 persons (37.4% males, 62.6% females) versus 2,025,286 persons (34.6% males, 65.4% females) participated in the community TB screening outreaches in the hotspot and non-hotspot areas, respectively. Presumptive cases among all clients screened were 268,264 clients (6.7%) and confirmed TB cases were 22,618 clients (8.4%). The number needed to screen for the hotspot and non-hotspot areas was 146.22 versus 193.44 per 10,000 population, respectively.

CONCLUSIONS

Active TB case finding in EWORS-mapped hotspot areas yielded higher TB cases than the non-hotspot areas of 14 high burden States of Nigeria. After the intervention of EWORS, the precision to diagnose TB from presumptive increased from 0.077 to 0.103. The number of presumptive needed to diagnose a TB case decreased from 14.047 to 10.255 per 10,000 population.

Publisher

JMIR Publications Inc.

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