Regression Analysis on Scorpion Envenomation and Climate Variables in M'Sila Province, Algeria from 2001 to 2010

  IJMTT-book-cover
 
International Journal of Mathematical Trends and Technology (IJMTT)          
 
© 2014 by IJMTT Journal
Volume-13 Number-1
Year of Publication : 2014
Authors : Schehrazad Selmane , Mohamed L'hadj
  10.14445/22315373/IJMTT-V13P501

MLA

Schehrazad Selmane , Mohamed L'hadj. "Regression Analysis on Scorpion Envenomation and Climate Variables in M'Sila Province, Algeria from 2001 to 2010 ", International Journal of Mathematical Trends and Technology (IJMTT). V13:1-9 Sep 2014. ISSN:2231-5373. www.ijmttjournal.org. Published by Seventh Sense Research Group.

Abstract
Scorpionism represents a serious public health problem in Algeria. More than 68% of the national population is at risk of scorpion stings. M'Sila ranks among the endemic provinces of the country and records every year a high incidence of scorpion stings.A survey on epidemiological characteristics of scorpion stings was established. Using the monthly recorded scorpion sting data for the period 2001-2010 for M'Sila province, the linkage between scorpion stings and weather conditions was demonstrated through time series analysis and regression analysis considering the number of scorpion stings as dependent variable and climatic conditions as independent variables. The temperature, precipitation and wind are the retained climate factors, and the temperature has the higher effect. The model predicted the number of scorpion stings in 2011 with a good accuracy. The model could be used by public health makers of the province to anticipate the demand for antivenoms and symptomatic drugs so that they can be distributed in advance. This raises optimism for forecasting scorpion stings provided the availability of appropriate climate information.

References

[1] J. P. Chippaux and M. Goyffon, Epidemiology of scorpionism: A global appraisal, Acta Trop 107(2):71{79, 2008.
[2] G. Chowell, J. M. Hyman JM, P. Diaz-Duenas, and N. W. Hengartne, Predicting scorpion sting incidence in an endemic region using climatologically variables, Int J Environ health Res 15(6):425{435, 2005.
[3] J. Fox, Applied Regression Analysis, Linear Models, and Related Methods, SAGE Publications, Social Science, 1997.
[4] M. Goyffon, Le role de l'homme dans l'expansion territoriale de quelques espèces de scorpions, Bulletin de la Société Zoologique de France Evolution et Zoologie 1171: 15{19, 1992.
[5] M. Goyffon, J. P. Chippaux, Les envenimations scorpioniques en Afrique, Rev. Medicopharmaceutique 53(4):17{21, 2009.
[6] P. McCullagh and J. A. Nelder, Generalized Linear Models, London Chapman and Hall, 1989.
[7] J. Neter, M. Kutner, W. Wasserman, Applied Linear Statistical Models, 1996.
[8] Office national de météorologie. URL : http://www.onm.meteo.dz
[9] Office national des statistiques. URL : http://www.ons.dz
[10] Prise en charge de l'envenimation scorpionique, Comite national de lutte contre l'envenimation scorpionique, 2009.
[11] Relevé épidémiologique mensuel, Institut national de la santé publique. URL: http://www.ands.dz/insp/scorpionisme.html.
[12] S. Selmane, H. ElHadj, and L. Benferhat, “The Impact of Climate Variables on the Incidence of Scorpion Stings in Humans in M'Sila's Province in Algeria”, IAENG proceedings ISBN 978-988-19252-7-5: 2014.
[13] M. Vachon, Etude sur les scorpions, Institut Pasteur d'Algérie. Alger, 1952.

Keywords
Climate, Forecasting, Regression Analysis, Scorpion, Temperature.