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Inter-annual variation in seasonal dengue epidemics driven by multiple interacting factors in Guangzhou, China

Inter-annual variation in seasonal dengue epidemics driven by multiple interacting factors in Guangzhou, China
Inter-annual variation in seasonal dengue epidemics driven by multiple interacting factors in Guangzhou, China
Vector-borne diseases display wide inter-annual variation in seasonal epidemic size due to their complex dependence on temporally variable environmental conditions and other factors. In 2014, Guangzhou, China experienced its worst dengue epidemic on record, with incidence exceeding the historical average by two orders of magnitude. To disentangle contributions from multiple factors to inter-annual variation in epidemic size, we fitted a semi-mechanistic model to time series data from 2005–2015 and performed a series of factorial simulation experiments in which seasonal epidemics were simulated under all combinations of year-specific patterns of four time-varying factors: imported cases, mosquito density, temperature, and residual variation in local conditions not explicitly represented in the model. Our results indicate that while epidemics in most years were limited by unfavorable conditions with respect to one or more factors, the epidemic in 2014 was made possible by the combination of favorable conditions for all factors considered in our analysis.
2041-1723
Oidtman, Rachel J.
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Lai, Shengjie
b57a5fe8-cfb6-4fa7-b414-a98bb891b001
Huang, Zhoujie
3387e5c5-d0f2-40c6-96f9-6c6281446722
Yang, Juan
7d6bb0a9-7886-457c-97d6-be0b4dfd89cf
Siraj, Amir S.
04c56878-d633-4728-a824-b1db6a6aa4df
Reiner, Robert C.
1c284400-d853-4cb1-93c5-cc3ac6f6fa49
Tatem, Andrew J.
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Perkins, T. Alex
6a3765cc-2473-4aff-8735-b8174b64b34e
Yu, Hongjie
f6a43c0c-0da8-4124-bd15-cd832d6fee7c
Oidtman, Rachel J.
667a3214-3342-414c-99b8-de7fe5eecd00
Lai, Shengjie
b57a5fe8-cfb6-4fa7-b414-a98bb891b001
Huang, Zhoujie
3387e5c5-d0f2-40c6-96f9-6c6281446722
Yang, Juan
7d6bb0a9-7886-457c-97d6-be0b4dfd89cf
Siraj, Amir S.
04c56878-d633-4728-a824-b1db6a6aa4df
Reiner, Robert C.
1c284400-d853-4cb1-93c5-cc3ac6f6fa49
Tatem, Andrew J.
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Perkins, T. Alex
6a3765cc-2473-4aff-8735-b8174b64b34e
Yu, Hongjie
f6a43c0c-0da8-4124-bd15-cd832d6fee7c

Oidtman, Rachel J., Lai, Shengjie, Huang, Zhoujie, Yang, Juan, Siraj, Amir S., Reiner, Robert C., Tatem, Andrew J., Perkins, T. Alex and Yu, Hongjie (2019) Inter-annual variation in seasonal dengue epidemics driven by multiple interacting factors in Guangzhou, China. Nature Communications, 10 (1), [1148]. (doi:10.1038/s41467-019-09035-x).

Record type: Article

Abstract

Vector-borne diseases display wide inter-annual variation in seasonal epidemic size due to their complex dependence on temporally variable environmental conditions and other factors. In 2014, Guangzhou, China experienced its worst dengue epidemic on record, with incidence exceeding the historical average by two orders of magnitude. To disentangle contributions from multiple factors to inter-annual variation in epidemic size, we fitted a semi-mechanistic model to time series data from 2005–2015 and performed a series of factorial simulation experiments in which seasonal epidemics were simulated under all combinations of year-specific patterns of four time-varying factors: imported cases, mosquito density, temperature, and residual variation in local conditions not explicitly represented in the model. Our results indicate that while epidemics in most years were limited by unfavorable conditions with respect to one or more factors, the epidemic in 2014 was made possible by the combination of favorable conditions for all factors considered in our analysis.

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Accepted/In Press date: 12 February 2019
Published date: 8 March 2019

Identifiers

Local EPrints ID: 429110
URI: http://eprints.soton.ac.uk/id/eprint/429110
ISSN: 2041-1723
PURE UUID: f72d9e79-e4a8-4823-bf86-9d2fc96a5e48
ORCID for Shengjie Lai: ORCID iD orcid.org/0000-0001-9781-8148
ORCID for Andrew J. Tatem: ORCID iD orcid.org/0000-0002-7270-941X

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Date deposited: 21 Mar 2019 17:30
Last modified: 17 Dec 2019 01:38

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