Dengue Fever with Two Strains in Thailand

Janreung, Sutawas; Chinviriyasit, Wirawan

doi:10.7763/ijapm.2014.v4.255

Cited by 4 publications

(1 citation statement)

References 10 publications

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“…"Dengue is a viral mosquito-borne infection transmitted by the Aedes mosquitoes" [3,4]. It is one of the several emerging tropical diseases which progressively spread geographically to virtually all tropical countries, like the Philippines [5]. "it is transmitted primarily by the bite of infected female mosquitoes aedes aegypti, but it also has been associated with other species such as ae.…”

Section: Introductionmentioning

confidence: 99%

A Correlation Study between Dengue Incidence and Climatological Factors in the Philippines

Subido

Aniversario

2022

ARJOM

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Dengue is a viral mosquito-borne infection transmitted primarily by the Aedes mosquitoes. It is one of the several emerging tropical diseases which progressively spread geographically to virtually all tropical countries like the Philippines. Recent climate changes related to global warming have increased the potential risk of dengue outbreaks in the world. In this paper, we study and investigate temperature and precipitation as climatological factors affecting dengue incidence in the Philippines from the year 2015 to 2018. Monthly dengue cases and climate data were gathered for the said study period. A correlation and wavelet coherence analyses were performed to determine a relationship between dengue incidence and climatological factors in the Philippines. Results show that the amount of rainfall is strongly correlated to the increase of dengue cases in the country as compared to the temperature. Evidence shows that dengue incidence in the Philippines mostly occur during the rainy season. Thus, intensified surveillance and control of mosquitoes during the rainy season are recommended.

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Section: Introductionmentioning

confidence: 99%

A Correlation Study between Dengue Incidence and Climatological Factors in the Philippines

Subido

Aniversario

2022

ARJOM

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Prediction of dengue fever outbreaks using climate variability and Markov chain Monte Carlo techniques in a stochastic susceptible-infected-removed model

Martheswaran

Hamdi

Al-Barty

et al. 2022

Sci Rep

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The recent increase in the global incidence of dengue fever resulted in over 2.7 million cases in Latin America and many cases in Southeast Asia and has warranted the development and application of early warning systems (EWS) for futuristic outbreak prediction. EWS pertaining to dengue outbreaks is imperative; given the fact that dengue is linked to environmental factors owing to its dominance in the tropics. Prediction is an integral part of EWS, which is dependent on several factors, in particular, climate, geography, and environmental factors. In this study, we explore the role of increased susceptibility to a DENV serotype and climate variability in developing novel predictive models by analyzing RT-PCR and DENV-IgM confirmed cases in Singapore and Honduras, which reported high dengue incidence in 2019 and 2020, respectively. A random-sampling-based susceptible-infected-removed (SIR) model was used to obtain estimates of the susceptible fraction for modeling the dengue epidemic, in addition to the Bayesian Markov Chain Monte Carlo (MCMC) technique that was used to fit the model to Singapore and Honduras case report data from 2012 to 2020. Regression techniques were used to implement climate variability in two methods: a climate-based model, based on individual climate variables, and a seasonal model, based on trigonometrically varying transmission rates. The seasonal model accounted for 98.5% and 92.8% of the variance in case count in the 2020 Singapore and 2019 Honduras outbreaks, respectively. The climate model accounted for 75.3% and 68.3% of the variance in Singapore and Honduras outbreaks respectively, besides accounting for 75.4% of the variance in the major 2013 Singapore outbreak, 71.5% of the variance in the 2019 Singapore outbreak, and over 70% of the variance in 2015 and 2016 Honduras outbreaks. The seasonal model accounted for 14.2% and 83.1% of the variance in the 2013 and 2019 Singapore outbreaks, respectively, in addition to 91% and 59.5% of the variance in the 2015 and 2016 Honduras outbreaks, respectively. Autocorrelation lag tests showed that the climate model exhibited better prediction dynamics for Singapore outbreaks during the dry season from May to August and in the rainy season from June to October in Honduras. After incorporation of susceptible fractions, the seasonal model exhibited higher accuracy in predicting outbreaks of higher case magnitude, including those of the 2019–2020 dengue epidemic, in comparison to the climate model, which was more accurate in outbreaks of smaller magnitude. Such modeling studies could be further performed in various outbreaks, such as the ongoing COVID-19 pandemic to understand the outbreak dynamics and predict the occurrence of future outbreaks.

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Potential effects of climate change on dengue transmission dynamics in Korea

et al. 2018

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Dengue fever is a major international public health concern, with more than 55% of the world population at risk of infection. Recent climate changes related to global warming have increased the potential risk of domestic outbreaks of dengue in Korea. In this study, we develop a two-strain dengue model associated with climate-dependent parameters based on Representative Concentration Pathway (RCP) scenarios provided by the Korea Meteorological Administration. We assess the potential risks of dengue outbreaks by means of the vector capacity and intensity under various RCP scenarios. A sensitivity analysis of the temperature-dependent parameters is performed to explore the effects of climate change on dengue transmission dynamics. Our results demonstrate that a higher temperature significantly enhances the potential threat of domestic dengue outbreaks in Korea. Furthermore, we investigate the effects of countermeasures on the cumulative incidence of humans and vectors. The current main control measures (comprising only travel restrictions) for infected humans in Korea are not as effective as combined control measures (travel restrictions and vector control), dramatically reducing the possibilities of dengue outbreaks.

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Dengue Fever with Two Strains in Thailand

Cited by 4 publications

References 10 publications

A Correlation Study between Dengue Incidence and Climatological Factors in the Philippines

A Correlation Study between Dengue Incidence and Climatological Factors in the Philippines

Prediction of dengue fever outbreaks using climate variability and Markov chain Monte Carlo techniques in a stochastic susceptible-infected-removed model

Potential effects of climate change on dengue transmission dynamics in Korea

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