9 results on '"Boonyasiri A"'
Search Results
2. Systematic review of electronic surveillance of infectious diseases with emphasis on antimicrobial resistance surveillance in resource-limited settings.
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Rattanaumpawan, Pinyo, Boonyasiri, Adhiratha, Vong, Sirenda, and Thamlikitkul, Visanu
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Background Electronic surveillance of infectious diseases involves rapidly collecting, collating, and analyzing vast amounts of data from interrelated multiple databases. Although many developed countries have invested in electronic surveillance for infectious diseases, the system still presents a challenge for resource-limited health care settings. Methods We conducted a systematic review by performing a comprehensive literature search on MEDLINE (January 2000-December 2015) to identify studies relevant to electronic surveillance of infectious diseases. Study characteristics and results were extracted and systematically reviewed by 3 infectious disease physicians. Results A total of 110 studies were included. Most surveillance systems were developed and implemented in high-income countries; less than one-quarter were conducted in low-or middle-income countries. Information technologies can be used to facilitate the process of obtaining laboratory, clinical, and pharmacologic data for the surveillance of infectious diseases, including antimicrobial resistance (AMR) infections. These novel systems require greater resources; however, we found that using electronic surveillance systems could result in shorter times to detect targeted infectious diseases and improvement of data collection. Conclusions This study highlights a lack of resources in areas where an effective, rapid surveillance system is most needed. The availability of information technology for the electronic surveillance of infectious diseases, including AMR infections, will facilitate the prevention and containment of such emerging infectious diseases. [ABSTRACT FROM AUTHOR]
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- 2018
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3. Clinical risk stratification and antibiotic management of NDM and OXA-48 carbapenemase-producing Enterobacteriaceae bloodstream infections in the UK.
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Ming, D.K., Otter, J.A., Ghani, R., Brannigan, E.T., Boonyasiri, A., Mookerjee, S., Gilchrist, M., Holmes, A.H., and Davies, F.
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- 2019
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4. Genomic epidemiology of carbapenemase-producing Enterobacteriaceae in hospitalised patients in Bangkok, Thailand from 2015 to 2017.
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Boonyasiri, A., Jauneikaite, E., Brinkac, L.M., Greco, C., Lerdlamyong, K., Tangkoskul, T., Nguyen, K., Thamlikitkul, V., and Fouts, D.E.
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KLEBSIELLA infections , *EPIDEMIOLOGY , *ENTEROBACTERIACEAE , *KLEBSIELLA , *MOLECULAR epidemiology , *CLINICAL epidemiology , *SINGLE nucleotide polymorphisms , *KLEBSIELLA pneumoniae - Abstract
Few antimicrobial treatment options are available at this time for treatment of CPE infections, and only a few studies have thus far described the epidemiology of CPE in hospitalised patients. B Methods and materials: b The clinical characteristics of 33 hospitalised patients with CPE, including patient history and factors associated with the development of CPE infections, were examined. B Background: b Infections due to carbapenemase-producing Enterobacteriaceae (CPE) have continually grown as a global public health threat, with significant related mortality rates observed. [Extracted from the article]
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- 2020
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5. Risk predictors of progression to severe disease during the febrile phase of dengue: a systematic review and meta-analysis.
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Sangkaew, Sorawat, Ming, Damien, Boonyasiri, Adhiratha, Honeyford, Kate, Kalayanarooj, Siripen, Yacoub, Sophie, Dorigatti, Ilaria, and Holmes, Alison
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DENGUE hemorrhagic fever , *FORECASTING , *DISEASE progression , *DENGUE , *CARDIOVASCULAR diseases , *DENGUE viruses , *RESEARCH , *FEVER , *META-analysis , *RESEARCH methodology , *SYSTEMATIC reviews , *MEDICAL cooperation , *EVALUATION research , *SERUM albumin , *SEX distribution , *VOMITING , *COMPARATIVE studies , *PLATELET count , *MIXED infections , *RESEARCH funding , *ABDOMINAL pain , *COMORBIDITY - Abstract
Background: The ability to accurately predict early progression of dengue to severe disease is crucial for patient triage and clinical management. Previous systematic reviews and meta-analyses have found significant heterogeneity in predictors of severe disease due to large variation in these factors during the time course of the illness. We aimed to identify factors associated with progression to severe dengue disease that are detectable specifically in the febrile phase.Methods: We did a systematic review and meta-analysis to identify predictors identifiable during the febrile phase associated with progression to severe disease defined according to WHO criteria. Eight medical databases were searched for studies published from Jan 1, 1997, to Jan 31, 2020. Original clinical studies in English assessing the association of factors detected during the febrile phase with progression to severe dengue were selected and assessed by three reviewers, with discrepancies resolved by consensus. Meta-analyses were done using random-effects models to estimate pooled effect sizes. Only predictors reported in at least four studies were included in the meta-analyses. Heterogeneity was assessed using the Cochrane Q and I2 statistics, and publication bias was assessed by Egger's test. We did subgroup analyses of studies with children and adults. The study is registered with PROSPERO, CRD42018093363.Findings: Of 6643 studies identified, 150 articles were included in the systematic review, and 122 articles comprising 25 potential predictors were included in the meta-analyses. Female patients had a higher risk of severe dengue than male patients in the main analysis (2674 [16·2%] of 16 481 vs 3052 [10·5%] of 29 142; odds ratio [OR] 1·13 [95% CI 1·01-1·26) but not in the subgroup analysis of studies with children. Pre-existing comorbidities associated with severe disease were diabetes (135 [31·3%] of 431 with vs 868 [16·0%] of 5421 without; crude OR 4·38 [2·58-7·43]), hypertension (240 [35·0%] of 685 vs 763 [20·6%] of 3695; 2·19 [1·36-3·53]), renal disease (44 [45·8%] of 96 vs 271 [16·0%] of 1690; 4·67 [2·21-9·88]), and cardiovascular disease (nine [23·1%] of 39 vs 155 [8·6%] of 1793; 2·79 [1·04-7·50]). Clinical features during the febrile phase associated with progression to severe disease were vomiting (329 [13·5%] of 2432 with vs 258 [6·8%] of 3797 without; 2·25 [1·87-2·71]), abdominal pain and tenderness (321 [17·7%] of 1814 vs 435 [8·1%] of 5357; 1·92 [1·35-2·74]), spontaneous or mucosal bleeding (147 [17·9%] of 822 vs 676 [10·8%] of 6235; 1·57 [1·13-2·19]), and the presence of clinical fluid accumulation (40 [42·1%] of 95 vs 212 [14·9%] of 1425; 4·61 [2·29-9·26]). During the first 4 days of illness, platelet count was lower (standardised mean difference -0·34 [95% CI -0·54 to -0·15]), serum albumin was lower (-0·5 [-0·86 to -0·15]), and aminotransferase concentrations were higher (aspartate aminotransferase [AST] 1·06 [0·54 to 1·57] and alanine aminotransferase [ALT] 0·73 [0·36 to 1·09]) among individuals who progressed to severe disease. Dengue virus serotype 2 was associated with severe disease in children. Secondary infections (vs primary infections) were also associated with severe disease (1682 [11·8%] of 14 252 with vs 507 [5·2%] of 9660 without; OR 2·26 [95% CI 1·65-3·09]). Although the included studies had a moderate to high risk of bias in terms of study confounding, the risk of bias was low to moderate in other domains. Heterogeneity of the pooled results varied from low to high on different factors.Interpretation: This analysis supports monitoring of the warning signs described in the 2009 WHO guidelines on dengue. In addition, testing for infecting serotype and monitoring platelet count and serum albumin, AST, and ALT concentrations during the febrile phase of illness could improve the early prediction of severe dengue.Funding: Wellcome Trust, National Institute for Health Research, Collaborative Project to Increase Production of Rural Doctors, and Royal Thai Government. [ABSTRACT FROM AUTHOR]- Published
- 2021
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6. Transaminases and serum albumin as early predictors of severe dengue - Authors' reply.
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Sangkaew, Sorawat, Ming, Damien, Boonyasiri, Adhiratha, Honeyford, Kate, Kalayanarooj, Siripen, Yacoub, Sophie, Dorigatti, Ilaria, and Holmes, Alison
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SERUM albumin , *DENGUE hemorrhagic fever , *AMINOTRANSFERASES , *DENGUE - Published
- 2021
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7. Enhancing risk prediction of progression to severe disease during the febrile phase of dengue: A systematic review and meta-analysis.
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Sangkaew, S., Ming, D., Boonyasiri, A., Honeyford, K., Kalayanarooj, S., Yacoub, S., Dorigatti, I., and Holmes, A.H.
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DISEASE progression , *DENGUE , *DENGUE hemorrhagic fever , *PROGNOSIS , *FORECASTING , *DENGUE viruses - Abstract
In addition, testing for infecting serotype and monitoring platelet count, serum albumin, AST or ALT during the febrile phase of illness would improve the early prediction of severe dengue. Dengue virus serotype 2 and secondary infections were also associated with progression to severe disease. [Extracted from the article]
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- 2020
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8. Database of epidemic trends and control measures during the first wave of COVID-19 in mainland China.
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Fu, Han, Wang, Haowei, Xi, Xiaoyue, Boonyasiri, Adhiratha, Wang, Yuanrong, Hinsley, Wes, Fraser, Keith J., McCabe, Ruth, Olivera Mesa, Daniela, Skarp, Janetta, Ledda, Alice, Dewé, Tamsin, Dighe, Amy, Winskill, Peter, van Elsland, Sabine L., Ainslie, Kylie E.C., Baguelin, Marc, Bhatt, Samir, Boyd, Olivia, and Brazeau, Nicholas F.
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COVID-19 , *H7N9 Influenza , *CONTACT tracing , *EPIDEMICS , *SCHOOL closings , *TRAVEL restrictions - Abstract
• COVID-19 measures were applied on similar dates in provinces throughout China. • Disease severity was much greater in Hubei compared with other provinces. • Provincial data on epidemics and interventions is available for further research. In this data collation study, we aimed to provide a comprehensive database describing the epidemic trends and responses during the first wave of coronavirus disease 2019 (COVID-19) throughout the main provinces in China. From mid-January to March 2020, we extracted publicly available data regarding the spread and control of COVID-19 from 31 provincial health authorities and major media outlets in mainland China. Based on these data, we conducted descriptive analyses of the epidemic in the six most-affected provinces. School closures, travel restrictions, community-level lockdown, and contact tracing were introduced concurrently around late January but subsequent epidemic trends differed among provinces. Compared with Hubei, the other five most-affected provinces reported a lower crude case fatality ratio and proportion of critical and severe hospitalised cases. From March 2020, as the local transmission of COVID-19 declined, switching the focus of measures to the testing and quarantine of inbound travellers may have helped to sustain the control of the epidemic. Aggregated indicators of case notifications and severity distributions are essential for monitoring an epidemic. A publicly available database containing these indicators and information regarding control measures is a useful resource for further research and policy planning in response to the COVID-19 epidemic. [ABSTRACT FROM AUTHOR]
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- 2021
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9. Estimates of the severity of coronavirus disease 2019: a model-based analysis.
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Verity, Robert, Okell, Lucy C, Dorigatti, Ilaria, Winskill, Peter, Whittaker, Charles, Imai, Natsuko, Cuomo-Dannenburg, Gina, Thompson, Hayley, Walker, Patrick G T, Fu, Han, Dighe, Amy, Griffin, Jamie T, Baguelin, Marc, Bhatia, Sangeeta, Boonyasiri, Adhiratha, Cori, Anne, Cucunubá, Zulma, FitzJohn, Rich, Gaythorpe, Katy, and Green, Will
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COVID-19 , *HOSPITAL admission & discharge , *HEALTH websites , *AGE groups , *ESTIMATES , *VIRAL pneumonia , *RESEARCH , *RESEARCH methodology , *DISEASE incidence , *EVALUATION research , *MEDICAL cooperation , *COMPARATIVE studies , *EPIDEMICS , *HOSPITAL care , *RESEARCH funding , *STATISTICAL models - Abstract
Background: In the face of rapidly changing data, a range of case fatality ratio estimates for coronavirus disease 2019 (COVID-19) have been produced that differ substantially in magnitude. We aimed to provide robust estimates, accounting for censoring and ascertainment biases.Methods: We collected individual-case data for patients who died from COVID-19 in Hubei, mainland China (reported by national and provincial health commissions to Feb 8, 2020), and for cases outside of mainland China (from government or ministry of health websites and media reports for 37 countries, as well as Hong Kong and Macau, until Feb 25, 2020). These individual-case data were used to estimate the time between onset of symptoms and outcome (death or discharge from hospital). We next obtained age-stratified estimates of the case fatality ratio by relating the aggregate distribution of cases to the observed cumulative deaths in China, assuming a constant attack rate by age and adjusting for demography and age-based and location-based under-ascertainment. We also estimated the case fatality ratio from individual line-list data on 1334 cases identified outside of mainland China. Using data on the prevalence of PCR-confirmed cases in international residents repatriated from China, we obtained age-stratified estimates of the infection fatality ratio. Furthermore, data on age-stratified severity in a subset of 3665 cases from China were used to estimate the proportion of infected individuals who are likely to require hospitalisation.Findings: Using data on 24 deaths that occurred in mainland China and 165 recoveries outside of China, we estimated the mean duration from onset of symptoms to death to be 17·8 days (95% credible interval [CrI] 16·9-19·2) and to hospital discharge to be 24·7 days (22·9-28·1). In all laboratory confirmed and clinically diagnosed cases from mainland China (n=70 117), we estimated a crude case fatality ratio (adjusted for censoring) of 3·67% (95% CrI 3·56-3·80). However, after further adjusting for demography and under-ascertainment, we obtained a best estimate of the case fatality ratio in China of 1·38% (1·23-1·53), with substantially higher ratios in older age groups (0·32% [0·27-0·38] in those aged <60 years vs 6·4% [5·7-7·2] in those aged ≥60 years), up to 13·4% (11·2-15·9) in those aged 80 years or older. Estimates of case fatality ratio from international cases stratified by age were consistent with those from China (parametric estimate 1·4% [0·4-3·5] in those aged <60 years [n=360] and 4·5% [1·8-11·1] in those aged ≥60 years [n=151]). Our estimated overall infection fatality ratio for China was 0·66% (0·39-1·33), with an increasing profile with age. Similarly, estimates of the proportion of infected individuals likely to be hospitalised increased with age up to a maximum of 18·4% (11·0-37·6) in those aged 80 years or older.Interpretation: These early estimates give an indication of the fatality ratio across the spectrum of COVID-19 disease and show a strong age gradient in risk of death.Funding: UK Medical Research Council. [ABSTRACT FROM AUTHOR]- Published
- 2020
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