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. 2020 Sep 1;20(1):643.
doi: 10.1186/s12879-020-05353-4.

Feasibility of containing shigellosis in Hubei Province, China: a modelling study

Affiliations

Feasibility of containing shigellosis in Hubei Province, China: a modelling study

Jia Rui et al. BMC Infect Dis. .

Abstract

Background: The transmission features and the feasibility of containing shigellosis remain unclear among a population-based study in China.

Methods: A population-based Susceptible - Exposed - Infectious / Asymptomatic - Recovered (SEIAR) model was built including decreasing the infectious period (DIP) or isolation of shigellosis cases. We analyzed the distribution of the reported shigellosis cases in Hubei Province, China from January 2005 to December 2017, and divided the time series into several stages according to the heterogeneity of reported incidence during the period. In each stage, an epidemic season was selected for the modelling and assessing the effectiveness of DIP and case isolation.

Results: A total of 130,770 shigellosis cases were reported in Hubei Province. The median of Reff was 1.13 (range: 0.86-1.21), 1.10 (range: 0.91-1.13), 1.09 (range: 0.92-1.92), and 1.03 (range: 0.94-1.22) in 2005-2006 season, 2010-2011 season, 2013-2014 season, and 2016-2017 season, respectively. The reported incidence decreased significantly (trend χ2 = 8260.41, P < 0.001) among four stages. The incidence of shigellosis decreased sharply when DIP implemented in three scenarios (γ = 0.1, 0.1429, 0.3333) and when proportion of case isolation increased.

Conclusions: Year heterogeneity of reported shigellosis incidence exists in Hubei Province. It is feasible to contain the transmission by implementing DIP and case isolation.

Keywords: Feasibility; Mathematical model; Shigellosis; Transmission control.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
The flowchart of SEIARQ model
Fig. 2
Fig. 2
Reported incidences and stages of shigellosis transmission from 2005 to 2017
Fig. 3
Fig. 3
The results of model fitting of SEIAR model to reported data in different stages. a, Curve fitting in 2005–2006 season; b, Curve fitting in 2010–2011 season; c, Curve fitting in 2013–2014 season; d, Curve fitting in 2016–2017 season
Fig. 4
Fig. 4
The simulated incidence of different DIP scenarios in different stages. (*γ, infectious period relative rate of symptomatic individuals)
Fig. 5
Fig. 5
The simulated incidence of different case isolation scenarios in different stages. (*x, actual isolation ratio)
Fig. 6
Fig. 6
The simulated PR values of different case isolation scenarios in different epidemic seasons. a, total; b, 2005–2006 season; c, 2010–2011 season; d, 2013–2014 season; e, 2016–2017 season. (*PR, percentage of reduction)

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