An SIR-Dengue transmission model with seasonal effects and impulsive control

2017 ◽  
Vol 289 ◽  
pp. 29-39 ◽  
Author(s):  
Joseph Páez Chávez ◽  
Thomas Götz ◽  
Stefan Siegmund ◽  
Karunia Putra Wijaya
Keyword(s):  
Impulsive Control ◽  
Seasonal Effects ◽  
Transmission Model ◽  
Dengue Transmission

scholarly journals Sensitivity, uncertainty and identifiability analyses to define a dengue transmission model with real data of an endemic municipality of Colombia

PLoS ONE ◽  
2020 ◽  
Vol 15 (3) ◽  
pp. e0229668
Author(s):  
Diana Paola Lizarralde-Bejarano ◽  
Daniel Rojas-Díaz ◽  
Sair Arboleda-Sánchez ◽  
María Eugenia Puerta-Yepes
Keyword(s):  
Real Data ◽  
Transmission Model ◽  
Dengue Transmission

scholarly journals Projections of increased and decreased dengue incidence under climate change

2016 ◽  
Vol 144 (14) ◽  
pp. 3091-3100 ◽  
Author(s):  
C. R. WILLIAMS ◽  
G. MINCHAM ◽  
H. FADDY ◽  
E. VIENNET ◽  
S. A. RITCHIE ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Warming ◽  
Carbon Emission ◽  
Climate Models ◽  
Virus Transmission ◽  
Transmission Model ◽  
Simple Relationship ◽  
Breeding Sites ◽  
Dengue Transmission ◽  
Dengue Epidemic

SUMMARYDengue is the world's most prevalent mosquito-borne disease, with more than 200 million people each year becoming infected. We used a mechanistic virus transmission model to determine whether climate warming would change dengue transmission in Australia. Using two climate models each with two carbon emission scenarios, we calculated future dengue epidemic potential for the period 2046–2064. Using the ECHAM5 model, decreased dengue transmission was predicted under the A2 carbon emission scenario, whereas some increases are likely under the B1 scenario. Dengue epidemic potential may decrease under climate warming due to mosquito breeding sites becoming drier and mosquito survivorship declining. These results contradict most previous studies that use correlative models to show increased dengue transmission under climate warming. Dengue epidemiology is determined by a complex interplay between climatic, human host, and pathogen factors. It is therefore naive to assume a simple relationship between climate and incidence, and incorrect to state that climate warming will uniformly increase dengue transmission, although in general the health impacts of climate change will be negative.

scholarly journals Parameter estimation and fractional derivatives of dengue transmission model

2020 ◽  
Vol 5 (3) ◽  
pp. 2758-2779 ◽  
Author(s):  
Windarto ◽  
◽  
Muhammad Altaf Khan ◽  
Fatmawati ◽  
Keyword(s):  
Parameter Estimation ◽  
Fractional Derivatives ◽  
Transmission Model ◽  
Dengue Transmission ◽  
Derivatives Of

scholarly journals Multiobjective approach to optimal control for a dengue transmission model

10.19139/144 ◽  
2015 ◽  
Vol 3 (3) ◽  
Author(s):  
Roman Denysiuk ◽  
Helena Sofia Rodrigues ◽  
M. Teresa T. Monteiro ◽  
Lino Costa ◽  
Isabel Espírito Santo ◽  
...  
Keyword(s):  
Optimal Control ◽  
Transmission Model ◽  
Dengue Transmission ◽  
Multiobjective Approach

Bistable equilibrium criteria in dengue transmission model for Malaysia

2018 ◽  
Author(s):  
Chai Jian Tay ◽  
Su Yean Teh ◽  
Hock Lye Koh
Keyword(s):  
Transmission Model ◽  
Dengue Transmission

The 2018–2019 weak El Niño: Predicting the risk of a dengue outbreak in Machala, Ecuador

2021 ◽  
Author(s):  
Desislava Petrova ◽  
Xavier Rodó ◽  
Rachel Sippy ◽  
Joan Ballester ◽  
Raul Mejía ◽  
...  
Keyword(s):  
Southern Oscillation ◽  
Climatic Conditions ◽  
Transmission Model ◽  
Local Climate ◽  
Climate Conditions ◽  
Dengue Outbreak ◽  
Dengue Transmission ◽  
Forecast Lead Time ◽  
Out Of Sample ◽  
Dengue Outbreaks

<p>Sea surface temperature conditions in the central-eastern tropical Pacific indicated a mild El Niño event in October 2018, which continued throughout the spring of 2019. The global El Niño Southern Oscillation (ENSO) forecast consensus was that these generally weak warm patterns would persist at least until the end of the summer. El Niño and its impact on local climatic conditions in southern coastal Ecuador influence the inter-annual transmission of dengue fever in the region. In this study, we use an ENSO model to issue forecasts of El Niño for the year 2019, which are then used to predict local climate variables, precipitation and minimum temperature, in the city of Machala, Ecuador. All these forecasts are incorporated in a dengue transmission model, specifically developed and tested for this area, to produce out-of-sample predictions of dengue risk. Predictions are issued at the beginning of January 2019 for the whole year, thus providing the longest forecast lead time of 12 months. Preliminary results indicated that the mild El Niño event did not provide the optimum climate conditions for dengue transmission, with the model predicting a very low probability of a dengue outbreak during the typical peak season in Machala in 2019. This is contrary to 2016, when a large El Niño event resulted in excess rainfall and warmer temperatures in the region, and a dengue outbreak occurred 3 months earlier than expected. This event was successfully predicted using a similar prediction framework to the one applied here. With the present study, we continue our  efforts to build and test a climate service tool to issue early warnings of dengue outbreaks in the region.</p>

scholarly journals Multiobjective approach to optimal control for a dengue transmission model

2015 ◽  
Vol 3 (3) ◽  
Author(s):  
Roman Denysiuk ◽  
Helena Sofia Rodrigues ◽  
M. Teresa T. Monteiro ◽  
Lino Costa ◽  
Isabel Espírito Santo ◽  
...  
Keyword(s):  
Optimal Control ◽  
Transmission Model ◽  
Dengue Transmission ◽  
Multiobjective Approach
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