Modeling Heterogeneity in Direct Infectious Disease Transmission in a Compartmental Model

Kong, Lingcai; Wang, Jinfeng; Han, Weiguo; Cao, Zhidong

doi:10.3390/ijerph13030253

Cited by 24 publications

(33 citation statements)

References 46 publications

(72 reference statements)

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“…Here, we assumed that the values of all

were different from person to person and that it followed a Gamma distribution with shape parameter

and a scale parameter. After some derivations [ 27 ], we obtained the NBD transmission function from infectious mosquitoes to susceptible humans:

where

characterized the level of heterogeneity of bites of susceptible humans by infectious mosquitoes.…”

Section: Methodsmentioning

confidence: 99%

“…Barlow used the NBD transmission function

to model a possum-tuberculosis (TB) system, where k denotes the level of heterogeneity and

is the transmission rate [ 26 ]. Kong et al developed an SEIR model with an NBD transmission function,

, to model the heterogeneity of contact rate for direct infectious disease [ 27 ]. The influence of different transmission functions was studied by Hoch et al [ 28 ].…”

Section: Introductionmentioning

confidence: 99%

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Modeling the Heterogeneity of Dengue Transmission in a City

Kong

Wang

et al. 2018

IJERPH

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Dengue fever is one of the most important vector-borne diseases in the world, and modeling its transmission dynamics allows for determining the key influence factors and helps to perform interventions. The heterogeneity of mosquito bites of humans during the spread of dengue virus is an important factor that should be considered when modeling the dynamics. However, traditional models generally assumed homogeneous mixing between humans and vectors, which is inconsistent with reality. In this study, we proposed a compartmental model with negative binomial distribution transmission terms to model this heterogeneity at the population level. By including the aquatic stage of mosquitoes and incorporating the impacts of the environment and climate factors, an extended model was used to simulate the 2014 dengue outbreak in Guangzhou, China, and to simulate the spread of dengue in different scenarios. The results showed that a high level of heterogeneity can result in a small peak size in an outbreak. As the level of heterogeneity decreases, the transmission dynamics approximate the dynamics predicted by the corresponding homogeneous mixing model. The simulation results from different scenarios showed that performing interventions early and decreasing the carrying capacity for mosquitoes are necessary for preventing and controlling dengue epidemics. This study contributes to a better understanding of the impact of heterogeneity during the spread of dengue virus.

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“…Here, we assumed that the values of all

were different from person to person and that it followed a Gamma distribution with shape parameter

and a scale parameter. After some derivations [ 27 ], we obtained the NBD transmission function from infectious mosquitoes to susceptible humans:

where

characterized the level of heterogeneity of bites of susceptible humans by infectious mosquitoes.…”

Section: Methodsmentioning

confidence: 99%

“…Barlow used the NBD transmission function

to model a possum-tuberculosis (TB) system, where k denotes the level of heterogeneity and

is the transmission rate [ 26 ]. Kong et al developed an SEIR model with an NBD transmission function,

, to model the heterogeneity of contact rate for direct infectious disease [ 27 ]. The influence of different transmission functions was studied by Hoch et al [ 28 ].…”

Section: Introductionmentioning

confidence: 99%

Modeling the Heterogeneity of Dengue Transmission in a City

Kong

Wang

et al. 2018

IJERPH

Self Cite

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“…The probability dynamics of interaction driven state transitions (Kong et al 2016) is now considered. Let be the number of effective contacts * between an individual in one population and the th individual in the other population.…”

Section: Methodsmentioning

confidence: 99%

New and Enhanced Tools for Civil Military Operations (NET-CMO)

Wayant¹,

Becker²,

Parker³

et al. 2020

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Civil Military Operations (CMO) associated geospatial modeling is intended to enable increased knowledge of regional stability, assist in Foreign Humanitarian Assistance (FHA), and provide support to Force Health Protection (FHP) operational planning tasks. However, current geoenabled methodologies and technologies are lacking in their overall capacity to support complex mission analysis efforts focused on understanding these important stability factors and mitigating threats to Army soldiers and civilian populations. CMO analysts, planners, and decision-makers do not have a robust capability to both spatially and quantitatively identify Regions of Interest (ROI), which may experience a proliferation in health risks such as vector-borne diseases in areas of future conflict. Additionally, due to this general absence of geoenabled health assessment models and derived end-products, CMO stakeholders are adversely impacted in their Military Decision Making Process (MDMP) capabilities to develop comprehensive area studies and plans such as Course of Action (COA). The NET-CMO project is focused on fostering emerging geoenabling capabilities and technologies to improve military situational awareness for assessment and planning of potential health threat-risk vulnerabilities.

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“…The model presents the following parameters, f : fraction of people infected with the dengue virus who have symptoms, 1 − f : fraction of people infected with dengue that are asymptomatic, λ 1 (t): incidence in the human population, λ 2 (t): incidence in the population of mosquitoes by the symptomatic people, λ 3 (t): incidence in the population of mosquitoes by the asymptomatic people, a: biting rate, β: is the probability of transmission of dengue virus from the mosquito carrier to the human, σ: probability of transmission of the virus from infected people to the non-carrier mosquito, : mortality rate of mosquitoes by natural conditions, k: indicator of dispersion of the infection, following a negative binomial distribution [15,16], ρ: increase of the mosquito not carrier of the virus and φ: increase of the mosquito carrying the virus by vertical transmission.…”

Section: The Modelmentioning

confidence: 99%

Numerical analysis of a model for dengue incidence with spreading factors in an endemic region

Munoz¹,

Aldana²,

Abello³

2018

ams

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A simulation model for the incidence of dengue is presented, including symptomatic and asymptomatic population, vertical transmission of the virus in the vector and dispersion of the carrier vector of a serotype of virus, as a source of disease propagation in an endemic population. The interpretation is done using ordinary nonlinear differential equations and the forces of infection are modeled following the negative binomial distribution with the dispersion parameter of the infection given by k, indicator of the level of agradation of the pathogen. The basic reproduction number is determined and calculated for different cases of k and the analysis is finalized simulating the dynamic system that interprets the process.

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Modeling Heterogeneity in Direct Infectious Disease Transmission in a Compartmental Model

Cited by 24 publications

References 46 publications

Modeling the Heterogeneity of Dengue Transmission in a City

Modeling the Heterogeneity of Dengue Transmission in a City

New and Enhanced Tools for Civil Military Operations (NET-CMO)

Numerical analysis of a model for dengue incidence with spreading factors in an endemic region

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