A Comparative Analysis of Spatial Interpolation Incidence of Tuberculosis Prevalence in Karnataka

Authors(5) :-Talluri Rameshwari K R, Rakshitha Rani N, Sunila, Ravi Kumar M, Sumana K

Tuberculosis is a bacterial air borne respiratory infectious disease caused by the Mycobacterium tuberculosis. Documented reports from 2011-16 by Revised National Tuberculosis Control Programme (RNTCP) revealed 26,628,020 Tuberculosis cases in India and 1,800,921 cases in Karnataka alone. The intensity of incidence, spread and the hotspots in Karnataka were focused using the tools of Geographical Information System (GIS), with comparative analytical procedure of spatial interpolation, cluster analysis and modeling the spatial pattern. It compares global and local indicators of spatial interpolation association for locating hotspot in spatial interpolation map. In the present study, Arc-GIS (Geographic Information System) interpolation tool is applied to identify the tuberculosis incidence hotspots in the Karnataka. Data for this study was obtained from the RNTCP. Statistical Package for the Social Sciences (SPSS) statistics revealed that the overall TB incidence in Karnataka is re-emerging from 2011-2016. The current study revealed the hotspots of TB incidence in Karnataka. The TB incidence in Bangalore, Belgaum, Mysore, Gulbarga and Raichur is recorded to be 18%, 21.78%, 11.88%, 11.66% and 22.1% respectively. Variation in incidence was observed during 2011-16, 28% incidence (2011-13), 1.765% decrease (2014-15) and 11.425% increase (2016), indicating re-emergence with more virulence and increased intonation pertaining to the incidence and spread. The present study is a novel concept with the intersection of GIS tool and the data analyzed targets the hotspots in these provinces, further, controlled management strategies may be intensified as remedial measures in the above geographical area.

Authors and Affiliations

Talluri Rameshwari K R
Division of Microbiology, Department of Water and Health, Faculty of Life Sciences, JSS Academy of Higher Education and Research, Sri Shivarathreeshwara Nagar, Mysuru, India
Rakshitha Rani N
Division of Microbiology, Department of Water and Health, Faculty of Life Sciences, JSS Academy of Higher Education and Research, Sri Shivarathreeshwara Nagar, Mysuru, India
Sunila
Department of Pathology, JSS Medical College and Hospital, JSS Academy of Higher Education and Research, Sri Shivarathreeshwara Nagar, Mysuru, India
Ravi Kumar M
Division of Geo-informatics, Department of Water and Health, Faculty of Life Sciences, JSS Academy of Higher Education and Research, Sri Shivarathreeshwara Nagar, Mysuru, India
Sumana K
Division of Microbiology, Department of Water and Health, Faculty of Life Sciences, JSS Academy of Higher Education and Research, Sri Shivarathreeshwara Nagar, Mysuru, India

Tuberculosis Cases in Karnataka, Arc-GIS software (Demo Version), Spatial Interpolation, IDW method, Spatial Scan Statistics, SPSS Software for Statistical Graph.

  1. World Health Organization. Global Tuberculosis Report 2014 [Internet]. 2014. WHO/HTM/TB/2014.08
  2. National Tuberculosis Center. Brief History of Tuberculosis. New Jersey: New Jersey Medical School; c1996 [Updated 1996 Jul 23]; [Cited 2009 Feb 26].
  3. Anderson LF, Tamne S, Brown T, Watson JP, Mullarkey C, Zenner D, et al. Transmission of multidrugresistant tuberculosis in the UK: a cross-sectional molecular and epidemiological study of clustering and contact tracing. Lancet Infect Dis. 2014; 14: 406–15. doi: 10.1016/S1473-3099(14)70022-2PMID:24602842
  4. World Health Organization: Highlights of activities from 1989 to 1998. World Health Forum1988; 9: 441-56
  5. Murray M, Nardell E. Molecular epidemiology of tuberculosis: Achievements and challenges to current knowledge. Bull World Health Organ. 2002; 80: 477–482. PMID: 12132006
  6. Munch Z, Van Lill SWP, Booysen CN, Zietsman HL, Enarson D a, Beyers N. Tuberculosis transmission patterns in a high-incidence area: a spatial analysis. Int J Tuberc Lung Dis. 2003; 7: 271–7.
  7. Tiwari, N.; Adhikari, C.M.S.; Tewari, A.; Kandpal, V. Investigation of geo-spatial hotspots for the occurrence of tuberculosis in Almora district, India, using GIS and spatial scan statistic. Int. J. Health Geogr. 2006, 5. [CrossRef] [PubMed]
  8. Onozuka, D.; Hagihara, A. Geographic prediction of tuberculosis clusters in Fukuoka, Japan, using the space-time scan statistic. BMC Infect. Dis. 2007, 7. [CrossRef] [PubMed]
  9.  Couceiro, L.; Santana, P.; Nunes, C. Pulmonary tuberculosis and risk factors in Portugal: A spatial analysis. Int. J. Tuberc. Lung Dis. 2011, 15, 1445–1454. [CrossRef] [PubMed]
  10.  Jones, S.G. & Kulldorff, M. 2012, "Influence of spatial resolution on space-time disease cluster detection", PLoS One, vol. 7, no. 10, pp. e48036.
  11.  Chan-yeung M, Yeh a GO, Tam CM, Kam KM, Leung CC, Yew WW, et al. Socio-demographic and geographic indicators and distribution of tuberculosis in Hong Kong: a spatial analysis. Int J Tuberc Lung Dis. 2005; 9: 1320–6.
  12.  Onozuka D, Hagihara A. Geographic prediction of tuberculosis clusters in Fukuoka, Japan, using the space-time scan statistic. BMC Infect Dis. 2007; 7. doi: 10.1186/1471-2334-7-26
  13.  SouzaWV, Carvalho MS, Albuquerque MDFPM, Barcellos CC, Ximenes R a a. Tuberculosis in intraurban settings: a Bayesian approach. Trop Med Int Heal. 2007; 12: 323–30. doi: 10.1111/j.1365-3156. 2006.01797.x
  14.  Maciel ELN, PanW, Dietze R, Peres RL, Vinhas SA, Ribeiro FK, et al. Spatial patterns of pulmonary tuberculosis incidence and their relationship to socio-economic status in Vitoria, Brazil. Int J Tuberc Lung Dis. 2010;
  15. Alvarez-Hernández G, Lara-Valencia F, Reyes-Castro P a, Rascón-Pacheco R a. An analysis of spatial and socio-economic determinants of tuberculosis in Hermosillo, Mexico, 2000–2006. Int J Tuberc Lung Dis. 2010; 14: 708–13.
  16. Barr RG, Diez-Roux A V., Knirsch CA, Pablos-Méndez A. Neighborhood poverty and the resurgence of tuberculosis in New York City, 1984–1992. Am J Public Health. 2001; 91: 1487–93.
  17. Feske ML, Teeter LD, Musser JM, Graviss EA. Including the third dimension: a spatial analysis of TB
  18. cases in Houston Harris County. Tuberculosis. 2011; 91: S24–33. doi: 10.1016/j.tube.2011.10.006 PMID: 22094150
  19.  Tsai P-J. Spatial analysis of tuberculosis in four main ethnic communities in Taiwan during 2005 to 2009. Open J Prev Med. 2011; 01: 125–134. doi: 10.4236/ojpm.2011.13017
  20.  Haase I, Olson S, Behr M a, Wanyeki I, Thibert L, Scott A, et al. Use of geographic and genotyping tools to characterise tuberculosis transmission in Montreal. Int J Tuberc Lung Dis. 2007; 11: 632–8.
  21.  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; 3. doi: 10.1186/1476-072X-3-23
  22.  Bishai WR, Graham NMH, Harrington S, Pope DS, Hooper N, Astemborski J, et al. Molecular and geographic patterns of tuberculosis transmission after 15 years of directly observed therapy. J Am Med Assoc. 1998; 280: 1679–84.
  23.  Moran PA. Notes on continuous stochastic phenomena. Biometrika. 1950; 37: 17–23. Available: http://www.ncbi.nlm.nih.gov/pubmed/15420245 PMID: 15420245
  24.  Getis A, Ord JK. The Analysis of Spatial Association. Geogr Anal. 1992; 24: 189–206. doi: 10.1111/j. 1538-4632.1992.tb00261.x
  25.  Ord JK, Getis A. Local Spatial Autocorrelation Statistics: Distributional Issues and an Application.
  26. Geogr Anal. 1995; 27: 286–306. doi: 10.1111/j.1538-4632.1995.tb00912.x
  27.  Lai, P.C.; So, F.M.; Chan, K.W. Spatial Epidemiological Approaches in Disease Mapping and Analysis; CRC Press: New York, NY, USA, 2009.
  28. Moran, P.A.P. Notes on continuous stochastic phenomena. Biometrika 1950, 37, 17–23. [CrossRef] [PubMed.}
  29.  Pfeiffer, D.U.; Robinson, T.P.; Stevenson, M.; Stevens, K.B.; Rogers, D.J.; Clements, A.C.A. Spatial Analysis in Epidemiology; Oxford University Press Inc.: New York, NY, USA, 2008.
  30. Cliff, A.D.; Ord, J.K. Spatial Autocorrelation; Pion: London, UK, 1973; volume 178.
  31. Cliff, A.D.; Ord, J.K. Spatial Processes: Models and Applications; Pion: London, UK, 1981.
  32.  Overmars, K.P.; de Koning, G.H.J.; Veldkamp, A. Spatial autocorrelation in multi-scale land use models. Ecol. Model. 2003, 164, 257–270.
  33.  Goodchild, M.F. Spatial Autocorrelation. CATMOG 47; Geobooks: Norwich, UK, 1986; pp.6–25.
  34.  Zhang, C.S.; McGrath, D. Geostatistical and GIS analyses on soil organic carbon concentrations in grassland of southeastern Ireland from two different periods. Geoderma 2004, 119, 261–275.
  35.  Legendre, P.; Fortin, M.J. Spatial pattern and ecological analysis. Plant Ecol. 1989, 80, 107–138.
  36. Zhang, C.S.; Tao, S.; Yuan, G.P.; Liu, S. Spatial autocorrelation analysis of trace element contents of soil in Tianjin plain area (in Chinese, with English abstract). Acta Pedol. Sin. 1995, 32, 50–57.
  37.  Zhang, C.S.; Zhang, S.; He, J.B. Spatial distribution characteristics of heavy metals in the sediments of Changjiang River system—Spatial autocorrelation and fractal methods (in Chinese, with English abstract). Acta Geogr. Sin. 1998, 53, 87–96.
  38.  Anselin, L. Local indicators of association—LISA. Geogr. Anal. 1995, 27, 93–115
  39. Julious, S.A.; Nicholl, J.; George, S. Why do we continue to use standardized mortality ratios for small area comparison? J. Public Health Med. 2001, 23, 40–46. [CrossRef] [PubMed]
  40. Pickle, L.W.; White, A.A. Effects of the choice of age-adjustment method on maps of death rates. Stat. Med. 1995, 14, 615–627. [CrossRef] [PubMed]
  41. Shannon, J. & Harvey, F. 2013, "Modifying areal interpolation techniques for analysis of data on food assistance benefits" in Advances in Spatial Data Handling Springer, pp. 125-141.
  42. Faramnuayphol, P.; Chongsuvivatwong, V.; Pannarunothai, S. Geographical variation of mortality in Thailand. J. Med. Assoc. Thai. 2008, 91, 1455–1460. [PubMed]
  43.  Leung, C.C.; Yew, W.W.; Tam, C.M.; Chan, C.K.; Chang, K.C.; Law, W.S.; Wong, M.Y.; Au, K.F.
  44. Socio-economic factors and tuberculosis: A district-based ecological analysis in Hong Kong. Int. J. Tuberc. Lung Dis. 2004, 8, 958–964. [PubMed]
  45. Mangtani, P.; Jolley, D.J.; Watson, J.M.; Rodrigues, L.C. Socioeconomic deprivation and notification rates for tuberculosis in London during 1982–1991. BMJ 1995, 310, 963–966. [CrossRef] [PubMed]
  46. Sasson, C.; Cudnik, M.T.; Nassel, A.; Semple, H.; Magid, D.J.; Sayre, M.; Keseg, D.; Haukoos, J.S.;Warden, C.R. Identifying high-risk geographic areas for cardiac arrest using three methods for clusteranalysis. Acad. Emerg. Med. 2012, 19, 139–146. [CrossRef] [PubMed]
  47. Mansoer, J.R.; Kibuga, D.K.; Borgdorff, M.W. Altitude: A determinant for tuberculosis in Kenya? Int. J. Tuberc. Lung Dis. 1999, 3, 156–161. [PubMed]
  48. Vargas, M.H.; Furuya, M.E.Y.; Pérez-Guzmán, C. Effect of altitude on the frequency of pulmonary tuberculosis. Int. J. Tuberc. Lung Dis. 2004, 8, 1321–1324. [PubMed]
  49. Vree, M.; Hoa, N.B.; Sy, D.N.; Co, N.V.; Cobelens, F.G.J.; Borgdorff, M.W. Low tuberculosis notification in mountainous Vietnam is not due to low case detection: A cross-sectional survey. BMC Infect. Dis. 2007, 7. [CrossRef] [PubMed]
  50. Tanrikulu, A.C.; Acemoglu, H.; Palanci, Y.; Dagli, C.E. Tuberculosis in Turkey: High altitude and other socio-economic risk factors. Public Health 2008, 122, 613–619. [CrossRef] [PubMed]
  51. Kakchapati, S.; Yotthanoo, S.; Choonpradup, C. Modeling tuberculosis incidence in Nepal. Asian Biomed. 2010, 4, 355–360.
  52. Goovaerts, P. 2010, "Combining areal and point data in geo-statistical interpolation: Applications to soil science and medical geography", Mathematical geosciences, vol. 42, no. 5, pp. 535-554.

Publication Details

Published in : Volume 3 | Issue 8 | November-December 2017
Date of Publication : 2017-12-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 964-975
Manuscript Number : IJSRST1738208
Publisher : Technoscience Academy

Print ISSN : 2395-6011, Online ISSN : 2395-602X

Cite This Article :

Talluri Rameshwari K R, Rakshitha Rani N, Sunila, Ravi Kumar M, Sumana K, " A Comparative Analysis of Spatial Interpolation Incidence of Tuberculosis Prevalence in Karnataka ", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 3, Issue 8, pp.964-975, November-December-2017.
Journal URL : http://ijsrst.com/IJSRST1738208

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