Assessment of tuberculosis case notification rate: spatial mapping of hotspot, coverage and diagnostics in Katsina State, north-western Nigeria
Accepted: 29 May 2022
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Tuberculosis (TB) is prevalent in Nigeria, and Katsina, along with other 12 states in the country, accounts for a high proportion of unnotified TB cases: constituting the high priority-intervention States in the country. Interventions focused on TB detection and coverage in the state could benefit from a better understanding of hotspot Local Government Areas (LGAs) that trigger and sustain the disease. Therefore, this study investigated the spatial distribution of TB Case Notification Rates (CNRs), diagnostics and coverage across the LGAs. Using 2017 to 2019 TB case finding data, the geocoordinates of diagnostic facilities and shapefiles, a retrospective ecological study was conducted. The data were analysed with QGIS and GeoDa. Moran’s I and LISA were used to locate and quantify hotspots. The coverage of microscopy and GeneXpert facilities was assessed on QGIS using a 5 km and 20 km radius, respectively. The CNR in the state, and 29 of the 34 LGAs, increased steadily from 2017 to 2019. Hotspots of high CNRs were also identified in 2017 (Moran’s I=0.106, p-value=0.090) and 2018 (Moran’s I=-0.020, p-value=0.370). While CNRs increased along with presumptive TB rates across most LGAs over the years, the positivity yield and bacteriological and Xpert diagnostic rates decreased. Bacteriological and GeneXpert coverage were 78% and 49% respectively. Additionally, only 51% of the state’s population lived within 20km of a GeneXpert facility. These results suggest that TB program interventions had some positive impact on the CNR, however, diagnostic facilities need to be equitably distributed and more innovative approaches need to be explored to find the missing cases.
2. WHO. World Health Organisation Tuberculosis Facts Sheet [Internet]. 2019 [cited 2020 Mar 4]. Available from: https://www.who.int/en/news-room/fact-sheets/detail/tuberculosis
3. WHO. Global Tuberculosis Report [Internet]. 2019 [cited 2020 Mar 3]. Available from: http://apps.who.int/bookorders.
4. WHO. Active case finding: Systematic screening for active tuberculosis. World Health Organization. [Internet]. WHO. World Health Organization; 2015 [cited 2020 May 14]. Available from: https://www.who.int/tb/areas-of-work/laboratory/active-case-finding/en/
5. Bakker M, Rood E, Mergenthaler C, Blok L, Van Gurp M, Straetemans M, et al. Mapping and Analysis for Tailored Disease Control and Health System Strengthening (MATCH): National Tuberculosis Programme User’s Manual. Version 1.0. [Internet]. Amsterdam; 2017 Oct [cited 2020 Jun 30]. Available from: https://www.kit.nl/health/theme/epidemiology/
6. WHO. Nigeria Tuberculosis Country Profile; World Health Organization. 2019.
7. NTBLCP. The National Strategic Plan for Tuberculosis Control. Towards Universal Access to Prevention, Diagnosis and Treatment. 2015 -2020. 2015;
8. Obasanya J, Abdurrahman ST, Oladimeji O, Lawson L, Dacombe R, Chukwueme N, et al. Tuberculosis case detection in Nigeria, the unfinished agenda. Trop Med Int Heal [Internet]. 2015 Oct 1 [cited 2020 May 10];20(10):1396–402. Available from: http://doi.wiley.com/10.1111/tmi.12558
9. Khashoggi BF, Murad A. Issues of Healthcare Planning and GIS: A Review. ISPRS Int J Geo-Information 2020, Vol 9, Page 352 [Internet]. 2020 May 27 [cited 2021 Sep 17];9(6):352. Available from: https://www.mdpi.com/2220-9964/9/6/352/htm
10. Moonan PK, Bayona M, Quitugua TN, Oppong J, Dunbar D, Jost KC, et al. Using GIS technology to identify areas of tuberculosis transmission and incidence. Int J Health Geogr. 2004 Oct 13;3:23.
11. Rood E, Khan A, Modak P, Mergenthaler C, van Gurp M, Blok L, et al. A Spatial Analysis Framework to Monitor and Accelerate Progress towards SDG 3 to End TB in Bangladesh. ISPRS Int J Geo-Information [Internet]. 2018 Dec 29 [cited 2020 Jan 12];8(1):14. Available from: http://www.mdpi.com/2220-9964/8/1/14
12. Touray K, Adetifa IM, Jallow A, Rigby J, Jeffries D, Cheung YB, et al. Spatial analysis of tuberculosis in an Urban West African setting: is there evidence of clustering? Trop Med Int Heal [Internet]. 2010 Jun [cited 2020 May 13];15(6):664–72. Available from: http://www.chg.ie/content/pdfs/spatialanalysisofTB.pdf
13. GADM. GADM maps [Internet]. 2018 [cited 2020 Jul 5]. Available from: https://gadm.org/maps.html
14. Federal Republic of Nigeria. Katsina State [Internet]. 2020 [cited 2020 Jun 22]. Available from: https://nigeria.gov.ng/north-west/katsina-state/
15. United Nations. Nigeria [Internet]. 2014 [cited 2020 Jul 17]. Available from: https://www.un.org/Depts/Cartographic/map/profile/nigeria.pdf
16. City Population. Katsina (State, Nigeria) - Population Statistics, Charts, Map and Location [Internet]. 2017 [cited 2020 Jun 22]. Available from: http://www.citypopulation.de/php/nigeria-admin.php?adm1id=NGA021
17. National Bureau of Statistics. 2019 Poverty and Inequality in Nigeria: Executive Summary. 2020.
18. NTBLCP. NTBLCP GeneXpert sites. [Internet]. 2018 [cited 2020 Aug 10]. Available from: http://ntblcp.org.ng/resources/ntblcp-genexpert-sites
19. Federal Ministry of Health. Nigeria Health Facility Registry [Internet]. 2019 [cited 2020 Jun 28]. Available from: https://hfr.health.gov.ng/facilities/hospitals-search?_token=aokiJiviYyDEVN0Lw7LdAMOntrODGojnoPJtOI7h&state_id=120&lga_id=1&ward_id=0&facility_level_id=0&ownership_id=0&operational_status_id=1®istration_status_id=0&license_status_id=0&geo_codes=0&service_type=0&service_category_id=0&facility_name=&entries_per_page=20
20. Fischer MM, Getis A. Handbook of Applied Spatial Analysis: Software Tools, Methods and Applications [Internet]. 2010 [cited 2020 Jul 3]. Available from: www.springer.com
21. KNCV. Nigeria - KNCV - Tuberculosefonds [Internet]. 2020 [cited 2020 Jul 29]. Available from: https://www.kncvtbc.org/en/land/nigeria/
22. Dangisso MH, Datiko DG, Lindtjørn B. Accessibility to tuberculosis control services and tuberculosis programme performance in southern ethiopia. Glob Health Action [Internet]. 2015 [cited 2020 Jun 29];8(1). Available from: /pmc/articles/PMC4655224/?report=abstract
23. Okpani AI, Abimbola S. Operationalizing universal health coverage in Nigeria through social health insurance. Niger Med J [Internet]. 2015 [cited 2020 Jun 3];56(5):305. Available from: http://www.nigeriamedj.com/text.asp?2015/56/5/305/170382
24. Jibril UN, Badaki O, Aminat U, Ibraheem AM, Abdulkadir K, Abubakar IA, et al. Determinant of Health risk behaviours among secondary school students in Kwara State, Nigeria. Integr J Educ Train. 2018;
25. Kanabus A. High burden TB countries - 2018 List [Internet]. 2019 [cited 2020 Jul 29]. Available from: https://tbfacts.org/high-burden-tb/
26. Yuen C, Becerra M, Codlin A, Creswell J, Ditiu L, Keshavjee S, et al. A Best-Practice Framework of Program Indicators for Monitoring a Comprehensive Approach to the Tuberculosis Epidemic. 2017 Dec.
27. Adejumo AO, Azuogu B, Okorie O, Lawal OM, Onazi OJ, Gidado M, et al. Community referral for presumptive TB in Nigeria: A comparison of four models of active case finding. BMC Public Health [Internet]. 2016 Feb 23 [cited 2020 Jul 30];16(1):177. Available from: http://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-016-2769-7
28. Stop TB Partnership. Nigeria: Active case finding in designated health facilities increases notifications [Internet]. The Strategic Initiative to Find Missing People with TB. 2018 [cited 2020 Jul 30]. Available from: https://stoptb-strategicinitiative.org/index.php/2019/02/11/nigeria-active-case-finding-in-designated-health-facilities-increases-notifications/
29. Parija D, Patra TK, Kumar AMV, Swain BK, Satyanarayana S, Sreenivas A, et al. Impact of awareness drives and community-based active tuberculosis case finding in Odisha, India. Int J Tuberc Lung Dis [Internet]. 2014 Sep 1 [cited 2020 Jul 30];18(9):1105–7. Available from: /pmc/articles/PMC4866500/?report=abstract
30. Aye S, Majumdar SS, Minn Oo M, Tripathy JP, Satyanarayana S, Thu N, et al. Evaluation of a tuberculosis active case finding project in peri-urban areas, Myanmar: 2014-2016. 2018 [cited 2020 Jul 30]; Available from: https://doi.org/10.1016/j.ijid.2018.02.012
31. Alene KA, Viney K, Moore HC, Wagaw M, Clements ACA. Spatial patterns of tuberculosis and HIV co-infection in Ethiopia. EHTESHAM HS, editor. PLoS One [Internet]. 2019 Dec 5 [cited 2020 Jun 23];14(12):e0226127. Available from: https://dx.plos.org/10.1371/journal.pone.0226127
32. Mngomezulu N, Cameron D, Olorunju S, Luthuli T, Dunbar R, Naidoo P. Reasons for the low bacteriological coverage of tuberculosis reported in Mpumalanga Province, South Africa. Public Heal Action [Internet]. 2015 [cited 2020 Aug 4];5(2):122–6. Available from: /pmc/articles/PMC4487486/?report=abstract
33. Harries A, Kumar A. Challenges and Progress with Diagnosing Pulmonary Tuberculosis in Low- and Middle-Income Countries. Diagnostics [Internet]. 2018 Nov 23 [cited 2020 Aug 4];8(4):78. Available from: /pmc/articles/PMC6315832/?report=abstract
34. Gidado M. Assessment of Tuberculosis Under-reporting by Level of Reporting System in Lagos, Nigeria [Internet]. 2019 [cited 2020 Aug 7]. Available from: https://scholarworks.waldenu.edu/dissertations
35. Gidado M, Nwokoye N, Ogbudebe C, Nsa B, Nwadike P, Ajiboye P, et al. Assessment of GeneXpert MTB/RIF performance by type and level of health-care facilities in Nigeria. Niger Med J [Internet]. 2019 [cited 2020 Aug 4];60(1):33. Available from: /pmc/articles/PMC6677003/?report=abstract
36. Churchyard GJ, Stevens WS, Mametja LD, McCarthy KM, Chihota V, Nicol MP, et al. Xpert MTB/RIF versus sputum microscopy as the initial diagnostic test for tuberculosis: A cluster-randomised trial embedded in South African roll-out of Xpert MTB/RIF. Lancet Glob Heal. 2015 Aug 1;3(8):e450–7.
37. Awoyemi TT, Obayelu OA, Opaluwa HI. Effect of Distance on Utilization of Health Care Services in Rural Kogi State, Nigeria. J Hum Ecol [Internet]. 2011 Jul 24 [cited 2020 Aug 2];35(1):1–9. Available from: https://www.tandfonline.com/doi/full/10.1080/09709274.2011.11906385
38. Olubadewo-Joshua O, Ugom KM. Application of Geospatial Techniques in the Locational Planning of Health Care Centres in Minna, Nigeria. [Internet]. 2018 [cited 2020 Aug 2]. Available from: https://jurnal.unej.ac.id/index.php/GEOSI/article/view/8754/6335
39. Vassall A, van Kampen S, Sohn H, Michael JS, John KR, den Boon S, et al. Rapid Diagnosis of Tuberculosis with the Xpert MTB/RIF Assay in High Burden Countries: A Cost-Effectiveness Analysis. Wilson D, editor. PLoS Med [Internet]. 2011 Nov 8 [cited 2020 Aug 3];8(11):e1001120. Available from: https://dx.plos.org/10.1371/journal.pmed.1001120
40. Houben RMGJ, Lalli M, Kranzer K, Menzies NA, Schumacher SG, Dowdy DW. What if They Don’t Have Tuberculosis? The Consequences and Trade-offs Involved in False-positive Diagnoses of Tuberculosis. Clin Infect Dis [Internet]. 2019 Jan [cited 2020 Aug 3];68(1):150–6. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6293007/
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