- Soli, Kevin, Kas, Monalisa, Maure, Tobias, Umezaki, Masahiro, Morita, Ayako, Siba, Peter, Greenhill, Andrew, Horwood, Paul
- Authors: Soli, Kevin , Kas, Monalisa , Maure, Tobias , Umezaki, Masahiro , Morita, Ayako , Siba, Peter , Greenhill, Andrew , Horwood, Paul
- Date: 2013
- Type: Text , Journal article
- Relation: Diagnostic Microbiology and Infectious Disease Vol. 77, no. 4 (2013), p. 321-323
- Full Text: false
- Reviewed:
- Description: We evaluated loop-mediated isothermal amplification end-point detection methods for Salmonella, Shigella, and Vibrio cholerae. Detection sensitivities were comparable to real-time PCR methods. The colorimetric dyes hydroxynaphthol blue and SYBR Green I showed increased sensitivity when compared to visual and automated turbidity readings. End-point colorimetric dyes promise great utility in developing settings.
Detection of enteric viral and bacterial pathogens associated with paediatric diarrhoea in Goroka, Papua New Guinea
- Soli, Kevin, Maure, Tobias, Kas, Monalisa, Bande, Grace, Bebes, Sauli, Luang-Suarkia, Dagwin, Siba, Peter, Morita, Ayako, Umezaki, Masahiro, Greenhill, Andrew, Horwood, Paul
- Authors: Soli, Kevin , Maure, Tobias , Kas, Monalisa , Bande, Grace , Bebes, Sauli , Luang-Suarkia, Dagwin , Siba, Peter , Morita, Ayako , Umezaki, Masahiro , Greenhill, Andrew , Horwood, Paul
- Date: 2014
- Type: Text , Journal article
- Relation: International Journal of Infectious Diseases Vol. 27, no. (2014), p. 54-58
- Full Text:
- Reviewed:
- Description: Objectives: The aim of this study was to investigate the viral and bacterial causes of acute watery diarrhoea in hospitalized children in Papua New Guinea. Methods: A retrospective analysis was conducted on stool samples collected from 199 children (age > 5 years) admitted to the paediatric ward of Goroka General Hospital from August 2009 through November 2010. A large range of viral and bacterial enteric pathogens were targeted using real-time PCR/RT-PCR assays. Results: Young children were much more likely to be admitted with acute gastroenteritis, with 62.8% of patients aged >1 year and 88.4% aged >2 years. An enteric pathogen was detected in 69.8% (n= 138) of patients. The most commonly detected pathogens were Shigella spp (26.6%), rotavirus (25.6%), adenovirus types 40/41 (11.6%), enterotoxigenic Escherichia coli (11.1%), enteropathogenic E. coli (8.5%), norovirus G2 (6.0%), and Campylobacter spp (4.0%). Norovirus G1, sapovirus, and Salmonella spp were also detected, but below our statistical limit of detection. Vibrio cholerae and astrovirus were not detected in any patients. Mixed infections were detected in 22.1% of patients, with Shigella and rotavirus most commonly detected in co-infections with other pathogens. Conclusions: This study demonstrates that Shigella and rotavirus are the major pathogens associated with acute paediatric gastroenteritis in this setting. © 2014 The Authors.
- Authors: Soli, Kevin , Maure, Tobias , Kas, Monalisa , Bande, Grace , Bebes, Sauli , Luang-Suarkia, Dagwin , Siba, Peter , Morita, Ayako , Umezaki, Masahiro , Greenhill, Andrew , Horwood, Paul
- Date: 2014
- Type: Text , Journal article
- Relation: International Journal of Infectious Diseases Vol. 27, no. (2014), p. 54-58
- Full Text:
- Reviewed:
- Description: Objectives: The aim of this study was to investigate the viral and bacterial causes of acute watery diarrhoea in hospitalized children in Papua New Guinea. Methods: A retrospective analysis was conducted on stool samples collected from 199 children (age > 5 years) admitted to the paediatric ward of Goroka General Hospital from August 2009 through November 2010. A large range of viral and bacterial enteric pathogens were targeted using real-time PCR/RT-PCR assays. Results: Young children were much more likely to be admitted with acute gastroenteritis, with 62.8% of patients aged >1 year and 88.4% aged >2 years. An enteric pathogen was detected in 69.8% (n= 138) of patients. The most commonly detected pathogens were Shigella spp (26.6%), rotavirus (25.6%), adenovirus types 40/41 (11.6%), enterotoxigenic Escherichia coli (11.1%), enteropathogenic E. coli (8.5%), norovirus G2 (6.0%), and Campylobacter spp (4.0%). Norovirus G1, sapovirus, and Salmonella spp were also detected, but below our statistical limit of detection. Vibrio cholerae and astrovirus were not detected in any patients. Mixed infections were detected in 22.1% of patients, with Shigella and rotavirus most commonly detected in co-infections with other pathogens. Conclusions: This study demonstrates that Shigella and rotavirus are the major pathogens associated with acute paediatric gastroenteritis in this setting. © 2014 The Authors.
Spatio-temporal epidemiology of the cholera outbreak in Papua New Guinea, 2009-2011
- Horwood, Paul, Karl, Stephan, Mueller, Ivo, Jonduo, Marinjho, Pavlin, Boris, Dagina, Rosheila, Ropa, Berry, Bieb, Sibauk, Rosewell, Alexander, Umezaki, Masahiro, Siba, Peter, Greenhill, Andrew
- Authors: Horwood, Paul , Karl, Stephan , Mueller, Ivo , Jonduo, Marinjho , Pavlin, Boris , Dagina, Rosheila , Ropa, Berry , Bieb, Sibauk , Rosewell, Alexander , Umezaki, Masahiro , Siba, Peter , Greenhill, Andrew
- Date: 2014
- Type: Text , Journal article
- Relation: BMC Infectious Diseases Vol. 14, no. 1 (2014), p.
- Full Text:
- Reviewed:
- Description: Background: Cholera continues to be a devastating disease in many developing countries where inadequate safe water supply and poor sanitation facilitate spread. From July 2009 until late 2011 Papua New Guinea experienced the first outbreak of cholera recorded in the country, resulting in > 15,500 cases and > 500 deaths. Methods: Using the national cholera database, we analysed the spatio-temporal distribution and clustering of the Papua New Guinea cholera outbreak. The Kulldorff space-time permutation scan statistic, contained in the software package SatScan v9.2 was used to describe the first 8 weeks of the outbreak in Morobe Province before cholera cases spread throughout other regions of the country. Data were aggregated at the provincial level to describe the spread of the disease to other affected provinces. Results: Spatio-temporal and cluster analyses revealed that the outbreak was characterized by three distinct phases punctuated by explosive propagation of cases when the outbreak spread to a new region. The lack of road networks across most of Papua New Guinea is likely to have had a major influence on the slow spread of the disease during this outbreak. Conclusions: Identification of high risk areas and the likely mode of spread can guide government health authorities to formulate public health strategies to mitigate the spread of the disease through education campaigns, vaccination, increased surveillance in targeted areas and interventions to improve water, sanitation and hygiene.
- Authors: Horwood, Paul , Karl, Stephan , Mueller, Ivo , Jonduo, Marinjho , Pavlin, Boris , Dagina, Rosheila , Ropa, Berry , Bieb, Sibauk , Rosewell, Alexander , Umezaki, Masahiro , Siba, Peter , Greenhill, Andrew
- Date: 2014
- Type: Text , Journal article
- Relation: BMC Infectious Diseases Vol. 14, no. 1 (2014), p.
- Full Text:
- Reviewed:
- Description: Background: Cholera continues to be a devastating disease in many developing countries where inadequate safe water supply and poor sanitation facilitate spread. From July 2009 until late 2011 Papua New Guinea experienced the first outbreak of cholera recorded in the country, resulting in > 15,500 cases and > 500 deaths. Methods: Using the national cholera database, we analysed the spatio-temporal distribution and clustering of the Papua New Guinea cholera outbreak. The Kulldorff space-time permutation scan statistic, contained in the software package SatScan v9.2 was used to describe the first 8 weeks of the outbreak in Morobe Province before cholera cases spread throughout other regions of the country. Data were aggregated at the provincial level to describe the spread of the disease to other affected provinces. Results: Spatio-temporal and cluster analyses revealed that the outbreak was characterized by three distinct phases punctuated by explosive propagation of cases when the outbreak spread to a new region. The lack of road networks across most of Papua New Guinea is likely to have had a major influence on the slow spread of the disease during this outbreak. Conclusions: Identification of high risk areas and the likely mode of spread can guide government health authorities to formulate public health strategies to mitigate the spread of the disease through education campaigns, vaccination, increased surveillance in targeted areas and interventions to improve water, sanitation and hygiene.
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