Literature DB >> 34363777

Opisthorchis viverrini and Strongyloides stercoralis mono- and co-infections: Bayesian geostatistical analysis in an endemic area, Thailand.

Apiporn T Suwannatrai1, Kavin Thinkhamrop2, Kulwadee Suwannatrai3, Khanittha Pratumchart4, Kinley Wangdi5, Matthew Kelly5, Angela M Cadavid Restrepo6, Darren J Gray5, Archie C A Clements7, Sirikachorn Tangkawattana8, Banchob Sripa9.   

Abstract

Parasitic infections caused by Opisthorchis viverrini and Strongyloides stercoralis remain a major public health threat in the Greater Mekong Sub-region. An understanding of climate and other environmental influences on the geographical distribution and emergence of parasitic diseases is a crucial step to guide targeted control and prevention programs. A parasitological survey was conducted from 2008 to 2013 and included 12,554 individuals (age between 20 and 60 years) from 142 villages in five districts in Khon Kaen Province, Thailand. Geographical information systems, remote sensing technologies and a Bayesian geostatistical framework were used to develop models for O. viverrini and S. stercoralis mono- and co-infections in areas where both parasites are known to co-occur. The results indicate that male sex, increased age, altitude, precipitation, and land surface temperature have influenced the infection rate and geographical distribution of mono- and co-infections of O. viverrini and S. stercoralis in this area. Males were 6.69 times (95% CrI: 5.26-8.58) more likely to have O. viverrini - S. stercoralis co-infection. We observed that O.viverrini and S. stercoralis mono-infections display distinct spatial pattern, while co-infection is predicted in the center and southeast of the study area. The observed spatial clustering of O.viverrini and S. stercoralis provides valuable information for the spatial targeting of prevention interventions in this area.
Copyright © 2021. Published by Elsevier B.V.

Entities:  

Keywords:  Bayesian model-based geostatistics; Opisthorchis viverrini; Strongyloides stercoralis; co-infection; mono-infection

Year:  2021        PMID: 34363777     DOI: 10.1016/j.actatropica.2021.106079

Source DB:  PubMed          Journal:  Acta Trop        ISSN: 0001-706X            Impact factor:   3.112


  1 in total

1.  Association of Strongyloides stercoralis infection and type 2 diabetes mellitus in northeastern Thailand: Impact on diabetic complication-related renal biochemical parameters.

Authors:  Manachai Yingklang; Apisit Chaidee; Rungtiwa Dangtakot; Chanakan Jantawong; Ornuma Haonon; Chutima Sitthirach; Nguyen Thi Hai; Ubon Cha'on; Sirirat Anutrakulchai; Supot Kamsa-Ard; Somchai Pinlaor
Journal:  PLoS One       Date:  2022-05-31       Impact factor: 3.752

  1 in total

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