Lessons learned from previous dengue outbreaks

Wiwanitkit, Viroj

doi:10.1016/s2222-1808(14)60317-0

Cited by 4 publications

(2 citation statements)

References 17 publications

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“…Thus, in our study elevated liver enzymes, PCV and thrombocytopenia on admission were associated with progression to more severe disease and can be used in Sri Lankan patients as predictors of dengue disease severity. However, studies done elsewhere have suggested that PCV, WBC, and platelet counts alone on admissions cannot predict the progression of the disease into shock [Wiwanitkit, ].…”

Section: Discussionmentioning

confidence: 99%

Characterization of dengue virus infections in a sample of patients suggests unique clinical, immunological, and virological profiles that impact on the diagnosis of dengue and dengue hemorrhagic fever

Senaratne

Wimalaratne

Alahakoon

et al. 2016

Journal of Medical Virology

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Dengue virus (DENV) infections are increasing with respect to incidence and severity in the Central Province of Sri Lanka. The objective of this study was to define the clinical, immunological, and virological profiles of patients admitted to the General Hospital, Kandy with clinically apparent dengue. Demographic, clinical, hematological parameters, liver enzymes (ALT and AST), and blood samples were collected from 292 patients with fever <5 days post onset and fulfilling the WHO criteria for the diagnosis of dengue fever/dengue hemorrhagic fever (DF/DHF). Samples were analyzed for, anti-DENV IgM, IgG, and DENV nucleic acid. Myalgia was the commonest complaint by 65% of the patients. Packed cell volume was >45% in 27% of the patients while 42.12% had reduced platelets and 62.67% had reduced white blood cell counts. In contrast to other studies, positive tourniquet test (PTT) and petechiae were not major indicators of DENV infection or severity of the disease. Clinical profiles were significantly different between DF and DHF/DSS and showed many similarities to that reported elsewhere. Altogether, 43 patients (14.73%) were viremic as detected by RT-PCR; 181 patients (62%) were positive for anti-DENV IgM, and 245 (84%) patients were positive for anti-DENV IgG. In combination, anti-DENV IgM and RT-PCR assays detected 224 (77.5%) of DENV infected cases, thus improving the DENV diagnosis rate. Hence, the diagnostic utility of PTT, anti-DENV IgM/IgG serology, or RT-PCR used alone in the early phase of illness is low in Sri Lanka but the diagnostic value can be improved by a combination of serology and RT-PCR. J. Med. Virol. 88:1703-1710, 2016. © 2016 Wiley Periodicals, Inc.

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Section: Discussionmentioning

confidence: 99%

Characterization of dengue virus infections in a sample of patients suggests unique clinical, immunological, and virological profiles that impact on the diagnosis of dengue and dengue hemorrhagic fever

Senaratne

Wimalaratne

Alahakoon

et al. 2016

Journal of Medical Virology

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“…The dengue control program in Indonesia aims to halt and prevent the transmission of disease through vector control [ 8 ]. Vector control is widely used and the methods to control dengue, but is frequently unsuccessful [ 24 ]. One main reason for vector control being less successful is thought related to the poor and reactive management targeting interventions too late in the epidemics.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Dengue Outbreaks Based on Disease Surveillance and Meteorological Data

et al. 2016

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Research is needed to create early warnings of dengue outbreaks to inform stakeholders and control the disease. This analysis composes of a comparative set of prediction models including only meteorological variables; only lag variables of disease surveillance; as well as combinations of meteorological and lag disease surveillance variables. Generalized linear regression models were used to fit relationships between the predictor variables and the dengue surveillance data as outcome variable on the basis of data from 2001 to 2010. Data from 2011 to 2013 were used for external validation purposed of prediction accuracy of the model. Model fit were evaluated based on prediction performance in terms of detecting epidemics, and for number of predicted cases according to RMSE and SRMSE, as well as AIC. An optimal combination of meteorology and autoregressive lag terms of dengue counts in the past were identified best in predicting dengue incidence and the occurrence of dengue epidemics. Past data on disease surveillance, as predictor alone, visually gave reasonably accurate results for outbreak periods, but not for non-outbreaks periods. A combination of surveillance and meteorological data including lag patterns up to a few years in the past showed most predictive of dengue incidence and occurrence in Yogyakarta, Indonesia. The external validation showed poorer results than the internal validation, but still showed skill in detecting outbreaks up to two months ahead. Prior studies support the fact that past meteorology and surveillance data can be predictive of dengue. However, to a less extent has prior research shown how the longer-term past disease incidence data, up to years, can play a role in predicting outbreaks in the coming years, possibly indicating cross-immunity status of the population.

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Modelling the interdependent relationships among epidemic antecedents using fuzzy multiple attribute decision making (F-MADM) approaches

Abellana

2021

Open Computer Science

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With the high incidence of the dengue epidemic in developing countries, it is crucial to understand its dynamics from a holistic perspective. This paper analyzes different types of antecedents from a cybernetics perspective using a structural modelling approach. The novelty of this paper is twofold. First, it analyzes antecedents that may be social, institutional, environmental, or economic in nature. Since this type of study has not been done in the context of the dengue epidemic modelling, this paper offers a fresh perspective on this topic. Second, the paper pioneers the use of fuzzy multiple attribute decision making (F-MADM) approaches for the modelling of epidemic antecedents. As such, the paper has provided an avenue for the cross-fertilization of knowledge between scholars working in soft computing and epidemiological modelling domains.

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Lessons learned from previous dengue outbreaks

Cited by 4 publications

References 17 publications

Characterization of dengue virus infections in a sample of patients suggests unique clinical, immunological, and virological profiles that impact on the diagnosis of dengue and dengue hemorrhagic fever

Characterization of dengue virus infections in a sample of patients suggests unique clinical, immunological, and virological profiles that impact on the diagnosis of dengue and dengue hemorrhagic fever

Prediction of Dengue Outbreaks Based on Disease Surveillance and Meteorological Data

Modelling the interdependent relationships among epidemic antecedents using fuzzy multiple attribute decision making (F-MADM) approaches

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