The transmissibility estimation of influenza with early stage data of small-scale outbreaks in Changsha, China, 2005–2013

Tm, Chen; Chen, QP; Rc, Liu; Szot, A; Sl, Chen; Zhao, Jin; Ss, Zhou

doi:10.1017/s0950268816002508

Cited by 18 publications

(26 citation statements)

References 14 publications

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“…The methods which Li et al employed were based on the epidemic growth rate of the epidemic curve and the serial interval [3]. Our previous study showed that several methods could be used to calculate the R 0 based on the epidemic growth rate of the epidemic curve and the serial interval, and different methods might result in different values of R 0 [26]. Our results also showed that the R 0 of SARS-CoV-2 was 2.30 from reservoir to person which was lower than that of person to person.…”

Section: Discussionmentioning

confidence: 99%

A mathematical model for simulating the phase-based transmissibility of a novel coronavirus

et al. 2020

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Background: As reported by the World Health Organization, a novel coronavirus (2019-nCoV) was identified as the causative virus of Wuhan pneumonia of unknown etiology by Chinese authorities on 7 January, 2020. The virus was named as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by International Committee on Taxonomy of Viruses on 11 February, 2020. This study aimed to develop a mathematical model for calculating the transmissibility of the virus. Methods: In this study, we developed a Bats-Hosts-Reservoir-People transmission network model for simulating the potential transmission from the infection source (probably be bats) to the human infection. Since the Bats-Hosts-Reservoir network was hard to explore clearly and public concerns were focusing on the transmission from Huanan Seafood Wholesale Market (reservoir) to people, we simplified the model as Reservoir-People (RP) transmission network model. The next generation matrix approach was adopted to calculate the basic reproduction number (R 0 ) from the RP model to assess the transmissibility of the SARS-CoV-2. Results: The value of R 0 was estimated of 2.30 from reservoir to person and 3.58 from person to person which means that the expected number of secondary infections that result from introducing a single infected individual into an otherwise susceptible population was 3.58. Conclusions: Our model showed that the transmissibility of SARS-CoV-2 was higher than the Middle East respiratory syndrome in the Middle East countries, similar to severe acute respiratory syndrome, but lower than MERS in the Republic of Korea.

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Section: Discussionmentioning

confidence: 99%

A mathematical model for simulating the phase-based transmissibility of a novel coronavirus

et al. 2020

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“…Our results showed that the mean value of R eff of Shigellosis was 1.19, meaning that the expected number of secondary infections that resulted from introducing a single infected individual into an otherwise susceptible population was only 1.19 on average. This revealed that the transmissibility of shigellosis is lower than many other infectious diseases such as influenza, Ebola virus disease, and Norovirus infection [12,14,15,34].…”

Section: The Transmissibility Of Shigellosismentioning

confidence: 99%

“…The transmissibility of an infectious disease is commonly quantified by basic reproduction number (R 0 ), which is defined as the expected number of secondary infections that result from introducing a single infected individual into an otherwise susceptible population [12][13][14][15]. However, because of the disease intervention or the decreasing proportion of susceptible individuals due to the spread of the pathogen, it is hard to estimate R 0 .…”

Section: Introductionmentioning

confidence: 99%

Epidemiological characteristics and transmissibility of shigellosis in Hubei Province, China, 2005 – 2017

Chen

Rui

et al. 2020

BMC Infect Dis

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Background: Shigellosis is one of the main diarrhea diseases in developing countries. However, the transmissibility of shigellosis remains unclear. Methods: We used the dataset of shigellosis cases reported between January 2005 and December 2017, from Hubei Province, China. A mathematical model was developed based on the natural history and the transmission mechanism of the disease. By fitting the data using the model, transmission relative rate from person to person (b) and from reservoir to person (b w ), and the effective reproduction number (R eff ) were estimated. To simulate the contribution of b and b w during the transmission, we performed a "knock-out" simulation in four scenarios:Results: A total of 130,770 shigellosis cases were reported in Hubei province, among which 13 cases were dead. The median annual incidence was 19.96 per 100,000 persons (range: 5.99 per 100,000 persons -29.47 per 100,000 persons) with a decreased trend (trend χ 2 = 25,470.27, P < 0.001). The mean values of b and b w were 0.0898 (95% confidence interval [CI]: 0.0851-0.0946) and 1.1264 × 10 − 9 (95% CI: 4.1123 × 10 − 10 -1.8416 × 10 − 9 ), respectively. The "knock-out" simulation showed that the number of cases simulated by scenario A was almost the same as scenario B, and scenario C was almost the same as scenario D. The mean value of R eff of shigellosis was 1.19 (95% CI: 1.13-1.25) and decreased slightly with a Linear model until it decreased to an epidemic threshold of 0.99 (95% CI: 0.65-1.34) in 2029. Conclusions:The incidence of shigellosis is still in high level. The transmissibility of the disease is low in Hubei Province. The transmission would be interrupted in the year of 2029.

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“…isolated at home for mild cases until all the symptoms disappeared after 2 days. 2,7 The model simulated the vaccination strategy that is vaccination prior to the outbreak (V P ) and d 0 was set as the proportion of V P .…”

Section: Model With Interventionsmentioning

confidence: 99%

Simulation of key interventions for seasonal influenza outbreak control at school in Changsha, China

et al. 2018

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Objective To use a mathematical model to simulate an influenza outbreak in a school in order to assess the effectiveness of isolation (Iso), antiviral therapeutics, antiviral prophylactics (P), vaccination prior to the outbreak, and school closure (for 1 [S1w], 2 or 3 weeks). Methods This study developed a susceptible-exposed-infectious/asymptomatic-recovered model to estimate the effectiveness of commonly used interventions for seasonal influenza outbreaks in school. Results The most effective single-intervention strategy was isolation with a total attack rate of 1.99% and an outbreak duration of 30 days. The additional effectiveness of antiviral therapeutics and prophylactics and vaccination (prior to the outbreak) strategies were not obvious. Although Iso+P, P+Iso+S1w, four-, and five-combined intervention strategies had commendable effectiveness, total attack rate decreased only slightly, and outbreak duration was shortened by 9 days maximum, compared with the single-intervention isolation strategy. School closure for 1, 2 or 3 weeks was futile or even counterproductive. Conclusion Isolation, as a single intervention, was the most effective in terms of reducing the total attack rate and the duration of the outbreak.

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The transmissibility estimation of influenza with early stage data of small-scale outbreaks in Changsha, China, 2005–2013

Cited by 18 publications

References 14 publications

A mathematical model for simulating the phase-based transmissibility of a novel coronavirus

A mathematical model for simulating the phase-based transmissibility of a novel coronavirus

Epidemiological characteristics and transmissibility of shigellosis in Hubei Province, China, 2005 – 2017

Simulation of key interventions for seasonal influenza outbreak control at school in Changsha, China

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