Literature DB >> 18686236

A geospatial risk assessment model for leprosy in Ethiopia based on environmental thermal-hydrological regime analysis.

Azeb Tadesse Argaw1, E J Shannon, Abraham Assefa, Fekade Silassie Mikru, Berhane Kidane Mariam, John B Malone.   

Abstract

Geospatial methods were used to study the associations of the environmental thermal-hydrological regime with leprosy prevalence in the Oromia and Amhara regions of Ethiopia. Prediction models were developed that indicated leprosy prevalence was related to: (i) long-term normal climate grid data on temperature and moisture balance (rain/potential evapo-transpiration); (ii) satellite surveillance data on the Normalized Difference Vegetation Index (NDVI) and daytime earth surface temperature (Tmax) from the Advanced Very High Resolution Radiometer (AVHRR); and (iii) a Genetic Algorithm Rule-Set Prediction (GARP) model based on NDVI and Tmax data in relation to leprosy prevalence data. Our results suggest that vertical transmission is not the only means of acquiring leprosy and support earlier reports that a major factor that governs transmission of leprosy is the viability of Mycobacterium leprae outside the human body which is related to the thermal-hydrologic regime of the environment.

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Year:  2006        PMID: 18686236     DOI: 10.4081/gh.2006.285

Source DB:  PubMed          Journal:  Geospat Health        ISSN: 1827-1987            Impact factor:   1.212


  6 in total

1.  Geographic information systems and applied spatial statistics are efficient tools to study Hansen's disease (leprosy) and to determine areas of greater risk of disease.

Authors:  José Wilton Queiroz; Gutemberg H Dias; Maurício Lisboa Nobre; Márcia C De Sousa Dias; Sérgio F Araújo; James D Barbosa; Pedro Bezerra da Trindade-Neto; Jenefer M Blackwell; Selma M B Jeronimo
Journal:  Am J Trop Med Hyg       Date:  2010-02       Impact factor: 2.345

2.  Population-based molecular epidemiology of leprosy in Cebu, Philippines.

Authors:  Rama Murthy Sakamuri; Miyako Kimura; Wei Li; Hyun-Chul Kim; Hyeyoung Lee; Madanahally D Kiran; William C Black; Marivic Balagon; Robert Gelber; Sang-Nae Cho; Patrick J Brennan; Varalakshmi Vissa
Journal:  J Clin Microbiol       Date:  2009-07-01       Impact factor: 5.948

3.  Prediction of leprosy in the Chinese population based on a weighted genetic risk score.

Authors:  Na Wang; Zhenzhen Wang; Chuan Wang; Xi'an Fu; Gongqi Yu; Zhenhua Yue; Tingting Liu; Huimin Zhang; Lulu Li; Mingfei Chen; Honglei Wang; Guiye Niu; Dan Liu; Mingkai Zhang; Yuanyuan Xu; Yan Zhang; Jinghui Li; Zhen Li; Jiabao You; Tongsheng Chu; Furong Li; Dianchang Liu; Hong Liu; Furen Zhang
Journal:  PLoS Negl Trop Dis       Date:  2018-09-19

4.  Ticks as potential vectors of Mycobacterium leprae: Use of tick cell lines to culture the bacilli and generate transgenic strains.

Authors:  Jéssica da Silva Ferreira; Diego Augusto Souza Oliveira; João Pedro Santos; Carla Carolina Dias Uzedo Ribeiro; Bruna A Baêta; Rafaella Câmara Teixeira; Arthur da Silva Neumann; Patricia Sammarco Rosa; Maria Cristina Vidal Pessolani; Milton Ozório Moraes; Gervásio Henrique Bechara; Pedro L de Oliveira; Marcos Henrique Ferreira Sorgine; Philip Noel Suffys; Amanda Nogueira Brum Fontes; Lesley Bell-Sakyi; Adivaldo H Fonseca; Flavio Alves Lara
Journal:  PLoS Negl Trop Dis       Date:  2018-12-19

5.  Bayesian model, ecological factors & transmission of leprosy in an endemic area of South India.

Authors:  Vasna Joshua; S Mehendale; M D Gupte
Journal:  Indian J Med Res       Date:  2016-01       Impact factor: 2.375

Review 6.  Unsolved matters in leprosy: a descriptive review and call for further research.

Authors:  Carlos Franco-Paredes; Alfonso J Rodriguez-Morales
Journal:  Ann Clin Microbiol Antimicrob       Date:  2016-05-21       Impact factor: 3.944

  6 in total

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