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Sudarat Chadsuthi

Other affiliations: Mahidol University
Bio: Sudarat Chadsuthi is an academic researcher from Naresuan University. The author has contributed to research in topics: Medicine & Leptospirosis. The author has an hindex of 9, co-authored 22 publications receiving 401 citations. Previous affiliations of Sudarat Chadsuthi include Mahidol University.

Papers
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Journal ArticleDOI
TL;DR: In this article, the authors used time series analysis to study the time variations in the number of leptospirosis cases in relation to the seasonal pattern, and its association with climate factors.

93 citations

Journal ArticleDOI
TL;DR: The results indicated that livestock is more susceptible to infection by serovar Shermani when compared to humans, which may guide public health policy makers to implement appropriate control measures and help to reduce the impact of leptospirosis in Thailand.
Abstract: Background Leptospirosis is a worldwide zoonotic bacterial disease caused by infection with leptospires. Leptospirosis in humans and livestock is an endemic and epidemic disease in Thailand. Livestock may act as reservoirs for leptospires and source for human infection. Methodology/Principal findings Data on leptospirosis infection in humans and livestock (Buffaloes, Cattle, and Pigs) species during 2010 to 2015 were analyzed. Serum samples were examined using Microscopic Agglutination Test (MAT) to identify antibodies against Leptospira serovars using a cut-off titer ≥ 1:100. The seroprevalence was 23.7% in humans, 24.8% in buffaloes, 28.1% in cattle, and 11.3% in pigs. Region specific prevalence among humans and livestock was found in a wide range. The most predominant serovars were Shermani, followed by Bratislava, Panama, and Sejroe in human, Shermani, Ranarum, and Tarassovi in buffaloes, and Shermani and Ranarum in cattle and pigs. Equally highest MAT titers against multiple serovars per one sample were found mainly in buffaloes and cattle showing equally titers against Ranarum and Shermani. The correlations of distribution of serovars across Thailand’s regions were found to be similar in pattern for cattle but not for buffaloes. In humans, the serovar distribution in the south differed from other regions. By logistic regression, the results indicated that livestock is more susceptible to infection by serovar Shermani when compared to humans. Conclusions/Significance This study gives a detailed picture of the predominance of Leptospira serovars in relation to region, humans and typical livestock. The broad spatial distribution of seroprevalence was analyzed across and within species as well as regions in Thailand. Our finding may guide public health policy makers to implement appropriate control measures and help to reduce the impact of leptospirosis in Thailand.

70 citations

Journal ArticleDOI
TL;DR: Cost-efficient, but insensitive serological methods dominate the diagnostic landscape and urgently need improvement toward greater compliance with some of the point-of-care criteria.
Abstract: Leptospirosis is re-emerging as a worldwide zoonosis and is caused by bacteria of the genus Leptospira. Human leptospirosis is associated with high temperature and humidity. Laboratory tests are indispensible for the early diagnosis and proper disease management. The demand for suitable leptospirosis point-of-care diagnostic tests grows with the awareness and number of incidences. Confirmation is achieved by the microscopic agglutination test, bacterial cultivation, PCR or histopathologic methods. However, high costs, poor standardization and/or elaborate sample preparation prevent routine use at the point of care. Cost-efficient, but insensitive serological methods dominate the diagnostic landscape and, likewise, urgently need improvement toward greater compliance with some of the point-of-care criteria. Combined application of antigen and antibody detection methods increases accuracy, but also new development or transfer of diagnostic technologies should be considered useful. Nano- and microparticle technology may play a key role in improving future antigen detection methods.

61 citations

Journal ArticleDOI
TL;DR: This substantial review of the literature on the state of the art of research over the past decades identified six main issues to be explored and analyzed: the available data sources; 2) data preparation techniques; 3) data representations; 4) forecasting models and methods; 5) dengue forecasting models evaluation approaches; and 6) future challenges and possibilities in forecasting modeling of d Dengue outbreaks.
Abstract: Dengue infection is a mosquitoborne disease caused by dengue viruses, which are carried by several species of mosquito of the genus Aedes , principally Ae. aegypti . Dengue outbreaks are endemic in tropical and sub-tropical regions of the world, mainly in urban and sub-urban areas. The outbreak is one of the top 10 diseases causing the most deaths worldwide. According to the World Health Organization, dengue infection has increased 30-fold globally over the past five decades. About 50–100 million new infections occur annually in more than 80 countries. Many researchers are working on measures to prevent and control the spread. One avenue of research is collaboration between computer science and the epidemiology researchers in developing methods of predicting potential outbreaks of dengue infection. An important research objective is to develop models that enable, or enhance, forecasting of outbreaks of dengue, giving medical professionals the opportunity to develop plans for handling the outbreak, well in advance. Researchers have been gathering and analyzing data to better identify the relational factors driving the spread of the disease, as well as the development of a variety of methods of predictive modeling using statistical and mathematical analysis and machine learning. In this substantial review of the literature on the state of the art of research over the past decades, we identified six main issues to be explored and analyzed: 1) the available data sources; 2) data preparation techniques; 3) data representations; 4) forecasting models and methods; 5) dengue forecasting models evaluation approaches; and 6) future challenges and possibilities in forecasting modeling of dengue outbreaks. Our comprehensive exploration of the issues provides a valuable information foundation for new researchers in this important area of public health research and epidemiology.

45 citations


Cited by
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Journal ArticleDOI
TL;DR: It is concluded that multiple Imputation for Nonresponse in Surveys should be considered as a legitimate method for answering the question of why people do not respond to survey questions.
Abstract: 25. Multiple Imputation for Nonresponse in Surveys. By D. B. Rubin. ISBN 0 471 08705 X. Wiley, Chichester, 1987. 258 pp. £30.25.

3,216 citations

01 Jul 1986
TL;DR: Structures in Other Domains The methodology of structural analysis discussed in this article has been applied beyond the narrow realm of natural language syntax that we have discussed in this paper, and it has been found that variation in the types of sentences that are used, whether during the course of children's acquisition of their native languages or in the centuries-long periods of linguistic change, are best characterized not as super cial and haphazard alterations, but rather in terms of parametric modi cations to the fundamental underlying grammatical rules and constraints.
Abstract: Structures in Other Domains The methodology of structural analysis discussed in this article has been applied beyond the narrow realm of natural language syntax that we have discussed in this article. Within the study of language, similar methods of analysis have been pervasively applied to the study of sounds (phonology), words (morphology), and meanings (semantics), yielding a range of of abstract structural representations whose properties bear considerable explanatory burden. There are a wealth of cases in each of these domains analogous to those discussed here, though space prevents us from going in these (see Akmajian, Demers, Farmer and Harnish 1995 for a traditional overview, and Jackendo 1994 for one more focused on connections with cognitive science). Additionally, these representations have shed substantial light on the processes of language acquisition and language change. It has been found that variation in the types of sentences that are used, whether during the course of children's acquisition of their native languages or in the centuries-long periods of linguistic change, are best characterized not as super cial and haphazard alterations, but rather in terms of parametric modi cations to the fundamental underlying grammatical rules and constraints. Moving outside the domain of language, one application of these same methods has been in the study of music cognition. Just as the representations of linguistic theory arise out of an attempt to model speakers' intuitions about well-formedness and possible meanings of the sentences of their

761 citations

Book ChapterDOI
TL;DR: Data emerging from prospective surveillance studies suggest that most human leptospiral infections in endemic areas are mild or asymptomatic, and patients progressing to multisystem organ failure have widespread hematogenous dissemination of pathogens.
Abstract: Leptospirosis is a widespread and potentially fatal zoonosis that is endemic in many tropical regions and causes large epidemics after heavy rainfall and flooding. Infection results from direct or indirect exposure to infected reservoir host animals that carry the pathogen in their renal tubules and shed pathogenic leptospires in their urine. Although many wild and domestic animals can serve as reservoir hosts , the brown rat (Rattus norvegicus) is the most important source of human infections. Individuals living in urban slum environments characterized by inadequate sanitation and poor housing are at high risk of rat exposure and leptospirosis. The global burden of leptospirosis is expected to rise with demographic shifts that favor increases in the number of urban poor in tropical regions subject to worsening storms and urban flooding due to climate change. Data emerging from prospective surveillance studies suggest that most human leptospiral infections in endemic areas are mild or asymptomatic. Development of more severe outcomes likely depends on three factors: epidemiological conditions, host susceptibility, and pathogen virulence (Fig. 1). Mortality increases with age, particularly in patients older than 60 years of age. High levels of bacteremia are associated with poor clinical outcomes and, based on animal model and in vitro studies, are related in part to poor recognition of leptospiral LPS by human TLR4. Patients with severe leptospirosis experience a cytokine storm characterized by high levels of IL-6, TNF-alpha, and IL-10. Patients with the HLA DQ6 allele are at higher risk of disease, suggesting a role for lymphocyte stimulation by a leptospiral superantigen. Leptospirosis typically presents as a nonspecific, acute febrile illness characterized by fever, myalgia, and headache and may be confused with other entities such as influenza and dengue fever. Newer diagnostic methods facilitate early diagnosis and antibiotic treatment. Patients progressing to multisystem organ failure have widespread hematogenous dissemination of pathogens. Nonoliguric (high output) renal dysfunction should be supported with fluids and electrolytes. When oliguric renal failure occurs, prompt initiation of dialysis can be life saving. Elevated bilirubin levels are due to hepatocellular damage and disruption of intercellular junctions between hepatocytes, resulting in leaking of bilirubin out of bile caniliculi. Hemorrhagic complications are common and are associated with coagulation abnormalities. Severe pulmonary hemorrhage syndrome due to extensive alveolar hemorrhage has a fatality rate of >50 %. Readers are referred to earlier, excellent summaries related to this subject (Adler and de la Pena-Moctezuma 2010; Bharti et al. 2003; Hartskeerl et al. 2011; Ko et al. 2009; Levett 2001; McBride et al. 2005).

721 citations

DOI
15 Jun 1977
TL;DR: In 1915 some Japanese Investigators associated a slender coiled oigan with a severe febrile attack, usually accompanied by jaundice, that occurred in both cPiclemic and sporadic form in Japan, this 0rganism they recovered from the blood and patients during life, and from the kidneys post mortem.
Abstract: Asevere type of jaundice that appeared in epidemic form was described by Adolf W eil of " eisbaden in 1880, and from this time for some years there was a tendency to refer to all cases ? severe jaundice that appeared in epidemic !?nn as Weil's disease. In 1915 some Japanese Investigators associated a slender coiled oiganwith a severe febrile attack, usually accompanied by jaundice, that occurred in both cPiclemic and sporadic form in Japan, this 0rganism they recovered from the blood and **** ^ Patients during life, and from the livci 'n(> kidneys post mortem.

696 citations

Journal ArticleDOI
TL;DR: Random Forest time series modeling provides enhanced predictive ability over existing time series models for the prediction of infectious disease outbreaks and provides a new approach to predicting these dangerous outbreaks in bird populations based on existing, freely available data.
Abstract: Time series models can play an important role in disease prediction. Incidence data can be used to predict the future occurrence of disease events. Developments in modeling approaches provide an opportunity to compare different time series models for predictive power. We applied ARIMA and Random Forest time series models to incidence data of outbreaks of highly pathogenic avian influenza (H5N1) in Egypt, available through the online EMPRES-I system. We found that the Random Forest model outperformed the ARIMA model in predictive ability. Furthermore, we found that the Random Forest model is effective for predicting outbreaks of H5N1 in Egypt. Random Forest time series modeling provides enhanced predictive ability over existing time series models for the prediction of infectious disease outbreaks. This result, along with those showing the concordance between bird and human outbreaks (Rabinowitz et al. 2012), provides a new approach to predicting these dangerous outbreaks in bird populations based on existing, freely available data. Our analysis uncovers the time-series structure of outbreak severity for highly pathogenic avain influenza (H5N1) in Egypt.

270 citations