Journal of Family Medicine and Health Care

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Spatial Statistical Analysis in the Classification of Some Seasonal Diseases

Received: 22 July 2017    Accepted: 04 August 2017    Published: 26 September 2017
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Abstract

This paper made used of the ArcGIS environment where a geo-database was created showing the spatial distribution of the hospital, where each hospitals’ coordinate where taken using GPS device from Zaria, Kaduna State of Nigeria. The geo-database contained all the information generated with reference to the geographical location where attributes tools was used to query information about the various hospitals in the study area. The average temperature of the each location was taken with the help of Landsat thematic Mapper and compared with the number of patients that visited the hospital with the diseases under study.

DOI 10.11648/j.jfmhc.20170302.12
Published in Journal of Family Medicine and Health Care (Volume 3, Issue 2, June 2017)
Page(s) 36-44
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Spatial, Analysis, ArcGIS, Disease, Mapping, GPS, Patients

References
[1] Ali, M, M Emch, J. P Donnay, M Yunus, and RB Sack. "Identifying environmental risk factors for endemic cholera: a raster GIS approach." Health & place, 2002: 201-210.
[2] Anamzui-Ya, Jerry Asaana. Spatial Analysis and Mapping of Cholera causing factors in Kumasi, Ghana. Kumasi, 2012.
[3] Bailey, T. C, and A. C Gatrell. "Interactive spatial data analysis." Longman Scientific & Technical Essex, 1995.
[4] Basommi, Laari Prosper. SPATIAL ANALYSIS OF MALARIA EPIDEMIOLOGY IN THE AMANSE WEST DISTRICT. Ghana, 2011.
[5] C. Coll, J. M. Galve, J. M. Sánchez, and V. Caselles, “Validation of Landsat-7/ETM+ Thermal-Band Calibration and Atmospheric Correction With Ground-Based Measurements”, IEEE Trans. Geosci. Remote Sens., vol. 48, no. 1, pp. 547–555, Jan. 2010
[6] Elliott, P, and D Wartenberg. "Spatial epidemiology: current approaches and future challenges."Environmental health perspectives, 2004: 9.
[7] Elliott, P, JC Wakefield, NG Best, and DJ Briggs. "Spatial epidemiology: methods and applications." Spatial epidemiology, 2001: 3-15.
[8] Frank, B. "Spatial statistics of epidemic data: the case of cholera epidemiology in Ghana. PhD thesis." Osei, 2010.
[9] Harvell, C. D., and C. E., Ward, J. R., Altizer, S., Dobson, A., Ostfeld, R. S. et al. Mitchell. "Climate warming and disease risks for terrestrial and marine biota." (Science,) 296, no. 2158-2162 (2002).
[10] Hay, S., and G., Stern, D., Snow, R., Randolf, S. & Rogers, D. Shanks. "Climate variability andmalaria epidemics in the highlands of East Africa." (Trends Parasitol.,) 21, no. 52-53 (2005).
[11] Kandala, Ngianga-Bakwin, Chen Ji, Nigel Stallard, Saverio Stranges, and P. Francesco Cappuccio. "Spatial Analysis of Risk Factors for Childhood Morbidity in Nigeria." The American Society of Tropical Medicine and Hygiene, 2007: 770-778.
[12] Kouray, K, et al. "Spatial analysis of tuberculosis in an Urban West African setting: is there evidence of clustering?" Tropical Medicine and International Health, 2010: 664-672.
[13] Kulldorff, M. "A spatial scan statistics." Communication in statistics-theory and methods, 1997: 1481-1496.
[14] Osei, F. B, A. A Duker, E. W Augustijn, and A Stein. "Spatial dependency of cholera prevalence on potential cholera reservoirs in an urban area, Kumasi, Ghana." International journal of Applied Earth Observation and Geoinformation, 2010: 331-339.
[15] Pfeiffer, Dirk. "Spatial analysis in epidemiology." Oxford University Press, 2008.
[16] Pinzon, J., and J., Tucker, C., Arthur, R., Jahrling, P. & Formenty, P Wilcon. "Trigger events: enviroclimatic coupling of Ebola hemorrhagic fever outbreaks." (Am. J. Trop. Med Hyg.,) 71, no. 664-674 (2004).
[17] SD Walter. "Disease mapping: a historical perspective. Spatial epidemiology: methods and application." 2000: 223-239.
[18] Sinkala, Yona, Martin Simuuza, B. John Muma, U. Dirk Pfeiffer, J. Christopher Kasanga, and Aaron Mweene. "Foot and mouth disease in Zambia: Spatial and temporal distributions of outbreaks, assessment of clusters and implications for control." Onderstepoort Journal of Veterinary Research, 2014: 6.
[19] Tobler, W. R. "Cellular geography In Gales S, Olsson G (eds)." Philosophy in geography. Dordrecht, Reidel, 1979: 379-86.
[20] Toprak, D, and S Erdogan. "SPATIAL ANALYSIS OF THE DISTRIBUTION OF TYPHOID FEVER IN TURKEY." The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences., 2008: 8.
[21] Waller, L. A., Carlin, B. P., Xia, H. and Gelfand, A. E. "Hierarchical spatio-temporal mapping of diseases rates." (Journal of the American Statistical Association) 92, no. 607-617 (1997).
Author Information
  • Department of Statistics, Ahmadu Bello University, Zaria, Nigeria

  • Department of Statistics, Ahmadu Bello University, Zaria, Nigeria

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  • APA Style

    Samson Agboola, Mataimaki Benard Joel. (2017). Spatial Statistical Analysis in the Classification of Some Seasonal Diseases. Journal of Family Medicine and Health Care, 3(2), 36-44. https://doi.org/10.11648/j.jfmhc.20170302.12

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    ACS Style

    Samson Agboola; Mataimaki Benard Joel. Spatial Statistical Analysis in the Classification of Some Seasonal Diseases. J. Fam. Med. Health Care 2017, 3(2), 36-44. doi: 10.11648/j.jfmhc.20170302.12

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    AMA Style

    Samson Agboola, Mataimaki Benard Joel. Spatial Statistical Analysis in the Classification of Some Seasonal Diseases. J Fam Med Health Care. 2017;3(2):36-44. doi: 10.11648/j.jfmhc.20170302.12

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  • @article{10.11648/j.jfmhc.20170302.12,
      author = {Samson Agboola and Mataimaki Benard Joel},
      title = {Spatial Statistical Analysis in the Classification of Some Seasonal Diseases},
      journal = {Journal of Family Medicine and Health Care},
      volume = {3},
      number = {2},
      pages = {36-44},
      doi = {10.11648/j.jfmhc.20170302.12},
      url = {https://doi.org/10.11648/j.jfmhc.20170302.12},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.jfmhc.20170302.12},
      abstract = {This paper made used of the ArcGIS environment where a geo-database was created showing the spatial distribution of the hospital, where each hospitals’ coordinate where taken using GPS device from Zaria, Kaduna State of Nigeria. The geo-database contained all the information generated with reference to the geographical location where attributes tools was used to query information about the various hospitals in the study area. The average temperature of the each location was taken with the help of Landsat thematic Mapper and compared with the number of patients that visited the hospital with the diseases under study.},
     year = {2017}
    }
    

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    T1  - Spatial Statistical Analysis in the Classification of Some Seasonal Diseases
    AU  - Samson Agboola
    AU  - Mataimaki Benard Joel
    Y1  - 2017/09/26
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    DO  - 10.11648/j.jfmhc.20170302.12
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    JF  - Journal of Family Medicine and Health Care
    JO  - Journal of Family Medicine and Health Care
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    SN  - 2469-8342
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    AB  - This paper made used of the ArcGIS environment where a geo-database was created showing the spatial distribution of the hospital, where each hospitals’ coordinate where taken using GPS device from Zaria, Kaduna State of Nigeria. The geo-database contained all the information generated with reference to the geographical location where attributes tools was used to query information about the various hospitals in the study area. The average temperature of the each location was taken with the help of Landsat thematic Mapper and compared with the number of patients that visited the hospital with the diseases under study.
    VL  - 3
    IS  - 2
    ER  - 

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