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Modeling the heterogeneity of Dengue transmission in a city

Modeling the heterogeneity of Dengue transmission in a city
Modeling the heterogeneity of Dengue transmission in a city
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.
dengue fever, heterogeneity, transmission terms, negative binomial distribution
1660-4601
Kong, Lingcai
bffb7391-5a96-4cb5-a66c-485684d5ac43
Wang, Jinfeng
3b2e15d2-baff-451c-8a30-d05c3970059f
Li, Zhongjie
f89a98f7-f6d3-4312-995a-bc658ae9a93f
Lai, Shengjie
b57a5fe8-cfb6-4fa7-b414-a98bb891b001
Liu, Qiyong
81cc75e6-95dd-49eb-b4e4-9ef5ab9104e7
Wu, Haixia
60e2fe29-7abe-4629-ab9f-94bd634850ec
Yang, Weizhong
65d18fbc-d752-42a7-ac38-01534ceda15c
Kong, Lingcai
bffb7391-5a96-4cb5-a66c-485684d5ac43
Wang, Jinfeng
3b2e15d2-baff-451c-8a30-d05c3970059f
Li, Zhongjie
f89a98f7-f6d3-4312-995a-bc658ae9a93f
Lai, Shengjie
b57a5fe8-cfb6-4fa7-b414-a98bb891b001
Liu, Qiyong
81cc75e6-95dd-49eb-b4e4-9ef5ab9104e7
Wu, Haixia
60e2fe29-7abe-4629-ab9f-94bd634850ec
Yang, Weizhong
65d18fbc-d752-42a7-ac38-01534ceda15c

Kong, Lingcai, Wang, Jinfeng, Li, Zhongjie, Lai, Shengjie, Liu, Qiyong, Wu, Haixia and Yang, Weizhong (2018) Modeling the heterogeneity of Dengue transmission in a city. International Journal of Environmental Research and Public Health, 15 (6). (doi:10.3390/ijerph15061128).

Record type: Article

Abstract

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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More information

Submitted date: 5 February 2018
Accepted/In Press date: 19 May 2018
e-pub ahead of print date: 31 May 2018
Published date: 31 May 2018
Keywords: dengue fever, heterogeneity, transmission terms, negative binomial distribution

Identifiers

Local EPrints ID: 421535
URI: https://eprints.soton.ac.uk/id/eprint/421535
ISSN: 1660-4601
PURE UUID: 941b0743-fbd3-4485-a413-be5cf09b4acf
ORCID for Shengjie Lai: ORCID iD orcid.org/0000-0001-9781-8148

Catalogue record

Date deposited: 14 Jun 2018 16:30
Last modified: 22 May 2019 00:22

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