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: 581

Full Length Research Paper

Meteorological factors associated with a high prevalence of leishmaniasis in Nicaragua

Santiago E. Hernandez
  • Santiago E. Hernandez
  • Global and Planetary Health, College of Public Health, University of South Florida, Tampa, Florida USA.
  • Google Scholar
Jeegan Parikh
  • Jeegan Parikh
  • Global and Planetary Health, College of Public Health, University of South Florida, Tampa, Florida USA.
  • Google Scholar
Gerardo Blass-Alfaro
  • Gerardo Blass-Alfaro
  • Department of Microbiology and Parasitology, Faculty of Medical Sciences, Universidad Nacional Autónoma de Nicaragua-Managua, Nicaragua.
  • Google Scholar
Marissa Anne Rickloff
  • Marissa Anne Rickloff
  • Epidemiology.College of Public Health, University of South Florida. Tampa, Florida USA.
  • Google Scholar
Benjamin G. Jacob
  • Benjamin G. Jacob
  • Global and Planetary Health, College of Public Health, University of South Florida, Tampa, Florida USA.
  • Google Scholar


  •  Received: 12 October 2020
  •  Accepted: 25 November 2020
  •  Published: 31 December 2020

Abstract

Nicaragua has an alarmingly high prevalence of cutaneous (CL) and mucocutaneous (MCL) leishmaniasis in recent years with environmental factors creating a perfect habitat for vector-mammalian reservoirs and transmission of the parasite. The aim of this study is to identify environmental risk factors that may play a role in the high prevalence of CL in Nicaragua. The epidemiological, clinical, and tissue sample diagnosis data for the study was collected from the Ministry of Health’s surveillance database. The land cover and clinical geospatial data were analyzed by ArcGIS. Poisson and negative binomial regression models were created to study environmental and epidemiological risk factors for CL in Nicaragua. CL and MCL were reported predominantly in the north- central (76.54%) and Atlantic (21.63%) regions of the country. Poisson regression analysis suggested mean annual temperature at 2 m (MAT), specific humidity in meters, altitude in meters, and median average rainfall as significant risk factors. The negative binomial regression model suggested that MAT and median annual rainfall were significant risk factors for CL and MCL occurrence. It is concluded that providing anticipated warning systems using ArcGIS predictive maps based on MAT and median annual rainfall may help design vector and reservoir control for leishmaniasis in Nicaragua.

Key words: Cutaneous leishmaniasis, geographic information systems, temperature, rain, environmental risk factors.