Temperature dependent transmission potential model for chikungunya in India

Kakarla, Satya Ganesh; Mopuri, Rajasekhar; Mutheneni, Srinivasa Rao; Bhimala, Kantha Rao; Kumaraswamy, Sriram; Kadiri, Madhusudhan Rao; Gouda, K. C.; Upadhyayula, Suryanaryana Murty

doi:10.1016/j.scitotenv.2018.07.461

Cited by 27 publications

(13 citation statements)

References 46 publications

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“…However, the WP method does require an estimated range of possible serial intervals. Herein we assumed a possible serial interval of 1 or 2 weeks so that the unit of time matched the incidence data (as we do not know the distribution of cases in days within each epidemiological week), which allows for some range in estimation of CHIKV serial interval that could be related to variability in EIP [21–24]. The likelihood-based method used for the estimation of the R 0 and the serial interval (time between the onset of symptoms of first case and the onset of symptoms of the secondary case [8]) is as follows: where , N t is the incidence data; P j is the serial interval with j = 1, …, k ; and t is the time of epidemiological data.…”

Section: Methodsmentioning

confidence: 99%

“…This is appropriate, as it takes into account the properties of virus transmission both within the vector as well as the vertebrate and is the definition for serial interval we use herein. However, it is important to acknowledge that while the intrinsic incubation period for CHIKV has been estimated to be approximately 3 days, there are several estimates of the extrinsic incubation period, which depend on other extrinsic factors, most notably temperature, leading to a range of possible serial intervals [11–15].…”

Section: Introductionmentioning

confidence: 99%

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Correlation of the basic reproduction number (R0) and eco-environmental variables in Colombian municipalities with chikungunya outbreaks during 2014-2016

Peña-García

Christofferson

2019

PLoS Negl Trop Dis

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Chikungunya virus (CHIKV) emerged in Colombia in 2014 into a population presumed fully susceptible. This resulted in a quick and intense spread across Colombia, resulting in an epidemic that affected an estimated 450,000 people. The reported Colombian cases accounted for over 49% of all the cases reported to the PAHO. Eco-environmental factors are known to be associated with the spread of arboviruses such as CHIKV, and likely contribute to the differences in transmission profiles that were observed across several municipalities. To determine the association of eco-environmental factors and CHIKV, the basic reproduction number (R0) in 85 municipalities, which accounted for 65.6% of reported CHIKV cases in Colombia, was estimated. Estimates of R0 ranged from 1 to 9, where over 76% of municipalities had R0 values between 1 and 2. When we looked at the distribution of R0, the cumulative proportions were 20% with R0>2, 14% with R0>3, and 9% with R0>4. Next, we determined that there were different patterns of correlation between environmental and/or ecological variables and R0 when we considered different R0 lower-thresholds. Broadly, we found that temperature-related variables are significantly and positively correlated to R0 regardless of the lower threshold, while other variables like duration of outbreak and size of the urban area are inversely related to R0. Specifically, we conclude that high values of temperature-related variables where R0 > 1 will result in a fast growth of cases in a shorter time period (with faster cessation of outbreak transmission) but will result overall in a fewer total cases compared to outbreak areas (R0 > 1, but classified as lower). Thus, in the absence of vector control, a less explosive outbreak may be more advantageous for the virus in terms of transmission.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Correlation of the basic reproduction number (R0) and eco-environmental variables in Colombian municipalities with chikungunya outbreaks during 2014-2016

Peña-García

Christofferson

2019

PLoS Negl Trop Dis

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“…The Aedes aegypti mosquito is the principal responsible for the propagation of viruses such as Dengue, Zika, and Chikungunya (Kakarla et al, 2019). The infection is transmitted by a bite of a female mosquito of this species, and for that reason, in this research were only considered females mosquitoes to be modeled.…”

Section: Natural History Of the Virusmentioning

confidence: 99%

Modeling the propagation of the Dengue, Zika and Chikungunya virus in the city of Bello using Agent-Based Modeling and Simulation

Carrion¹,

Zuluaga²,

Orozco³

et al. 2021

Preprint

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Agent-Based Models (ABM) have become a very useful tool to simulate the propagation of infectious diseases. To enhance the scope of these simulation models, some authors have combined ABMs with ODE models which are called Hybrid ABMs, and allows the simulation of models that demand a very high computational cost. In the present project, the main approach is to develop hybrid ABMs to understand the transmission dynamics of vector-borne diseases such as Dengue, Zika, and Chikungunya considering some geospatial characteristics of the city of Bello, Colombia. Some assumptions were considered to develop the computational model to understand and verify if the transmission dynamics were happening according to their theoretical behavior. The results obtained were satisfactory, and for future work, the idea is to integrate more components and make the model more realistic.

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“…The Zika virus spreads by the effective contact between an infected mosquito with a susceptible individual and vice-versa. This effective contact depends on several environmental factors such as weather, temperature, altitude, clothes, bednets, and mosquito bite rate [3,[25][26][27]. Varying these factors would generate different outcomes of transmission of the disease.…”

Section: Mathematical Modelmentioning

confidence: 99%

Optimization of the Controls against the Spread of Zika Virus in Populations

2020

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In this paper, we study and explore two control strategies to decrease the spread of Zika virus in the human and mosquito populations. The control strategies that we consider in this study are awareness and spraying campaigns. We solve several optimal control problems relying on a mathematical epidemic model of Zika that considers both human and mosquito populations. The first control strategy is broad and includes using information campaigns, encouraging people to use bednetting, wear long-sleeve shirts, or similar protection actions. The second control is more specific and relies on spraying insecticides. The control system relies on a Zika mathematical model with control functions. To develop the optimal control problem, we use Pontryagins’ maximum principle, which is numerically solved as a boundary value problem. For the mathematical model of the Zika epidemic, we use parameter values extracted from real data from an outbreak in Colombia. We study the effect of the costs related to the controls and infected populations. These costs are important in real life since they can change the outcomes and recommendations for health authorities dramatically. Finally, we explore different options regarding which control measures are more cost-efficient for society.

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Temperature dependent transmission potential model for chikungunya in India

Cited by 27 publications

References 46 publications

Correlation of the basic reproduction number (R0) and eco-environmental variables in Colombian municipalities with chikungunya outbreaks during 2014-2016

Correlation of the basic reproduction number (R0) and eco-environmental variables in Colombian municipalities with chikungunya outbreaks during 2014-2016

Modeling the propagation of the Dengue, Zika and Chikungunya virus in the city of Bello using Agent-Based Modeling and Simulation

Optimization of the Controls against the Spread of Zika Virus in Populations

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