Journal of
Public Health and Epidemiology

  • Abbreviation: J. Public Health Epidemiol.
  • Language: English
  • ISSN: 2141-2316
  • DOI: 10.5897/JPHE
  • Start Year: 2009
  • Published Articles: 569

Full Length Research Paper

Denoising a model employing automated bandwidth selection procedures and pre-whitened Euclidean-based quadratic surrogates in PROC ARIMA for optimizing asymptotic expansions and simulations of onchocerciasis endemic transmission zones in Burkina Faso

Benjamin G. Jacob
  • Benjamin G. Jacob
  • Department of Global Health, College of Public Health, University of South Florida, Tampa, FL, USA
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Robert J. Novak
  • Robert J. Novak
  • Department of Global Health, College of Public Health, University of South Florida, Tampa, FL, USA
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Laurent Toe
  • Laurent Toe
  • Multi-Disease Surveillance Centre (MDSC), 1473 Avenue Naba Zombré - Ouagadougou, Burkina Faso.
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Moussas S. Sanfo
  • Moussas S. Sanfo
  • Multi-Disease Surveillance Centre (MDSC), 1473 Avenue Naba Zombré - Ouagadougou, Burkina Faso.
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Rose Tibgueria
  • Rose Tibgueria
  • United Nations Office for the Coordination of Humanitarian Affairs (OCHA) Ouagadougou Burkina Faso.
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Alain Pare
  • Alain Pare
  • African Programs for Onchocerciasis Control (APOC), Epidemiology and Vector Elimination, 1473 Avenue Naba Zombré, Ouagadougou, Burkina Faso.
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Mounkaila Noma
  • Mounkaila Noma
  • African Programs for Onchocerciasis Control (APOC), Epidemiology and Vector Elimination, 1473 Avenue Naba Zombré, Ouagadougou, Burkina Faso
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Daniel Griffith
  • Daniel Griffith
  • United Nations Office for the Coordination of Humanitarian Affairs (OCHA) Ouagadougou Burkina Faso.
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Thomas R. Unnasch
  • Thomas R. Unnasch
  • Department of Global Health, College of Public Health, University of South Florida, Tampa, FL, USA
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Benjamin G. Jacob*
  • Benjamin G. Jacob*
  • Department of Global Health, College of Public Health, University of South Florida, Tampa, FL, USA.
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Robert J. Novak
  • Robert J. Novak
  • Department of Global Health, College of Public Health, University of South Florida, Tampa, FL, USA.
  • Google Scholar
Laurent Toe
  • Laurent Toe
  • Multi-Disease Surveillance Centre (MDSC), 1473 Avenue Naba Zombré - Ouagadougou, Burkina Faso.
  • Google Scholar
Moussas S. Sanfo
  • Moussas S. Sanfo
  • Multi-Disease Surveillance Centre (MDSC), 1473 Avenue Naba Zombré - Ouagadougou, Burkina Faso.
  • Google Scholar
Rose Tibgueria
  • Rose Tibgueria
  • United Nations Office for the Coordination of Humanitarian Affairs (OCHA) Ouagadougou, Burkina Faso.
  • Google Scholar
Alain Pare
  • Alain Pare
  • African Programs for Onchocerciasis Control (APOC), Epidemiology and Vector Elimination, 1473 Avenue Naba Zombré, Ouagadougou, Burkina Faso.
  • Google Scholar
Mounkaila Noma
  • Mounkaila Noma
  • African Programs for Onchocerciasis Control (APOC), Epidemiology and Vector Elimination, 1473 Avenue Naba Zombré, Ouagadougou, Burkina Faso.
  • Google Scholar
Daniel Griffith
  • Daniel Griffith
  • United Nations Office for the Coordination of Humanitarian Affairs (OCHA) Ouagadougou, Burkina Faso.
  • Google Scholar
Thomas R. Unnasch
  • Thomas R. Unnasch
  • Department of Global Health, College of Public Health, University of South Florida, Tampa, FL, USA.
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  •  Received: 15 February 2014
  •  Accepted: 22 August 2014
  •  Published: 30 November 2014

Abstract

 

In this research we constructed multiple predictive ArcGIS Euclidean distance–based autoregressive infectious disease transmission oriented models for predicting geographic locations of endemic onchocerciasis (“river blindness”) transmission risk zones in Burkina Faso. We employed multiple spatiotemporal-sampled empirical ecological data sets of georeferenced covariates of riverine larval habitats of Similium damnosum s.l., a black fly vector of onchocerciasis and their surrounding villages with their retrospective tabulated prevalence rates. The estimators were regressed employing the modified sum of squares technique. The model also revealed that 5 to 10 km was mesoendemic, 10 to 15 was hypoendemic and after 15 km there was no transmission. Semi-parametric spatial filtering matrices, orthogonal eigenvectors and interpolated endmember signatures can be used to render robust ARIMA risk model residual forecasts by reducing latent unobservable error coefficients in regressed spatiotemporal field-sampled immature S. damnosum s.l. density count data for optimizing risk mapping of seasonal onchocerciasis endemic transmission zones.

 

Key words: Autoregressive integrated moving average (ARIMA), QuickBird, Similium damnosum s.l., onchocerciasis, Burkina Faso.