Transmission dynamics of Zika virus with spatial structure—A case study in Rio de Janeiro, Brazil

Cai, Yongli; Ding, Zuqin; Yang, Bin; Peng, Zhihang; Wang, Weiming

doi:10.1016/j.physa.2018.09.100

Cited by 20 publications

(5 citation statements)

References 38 publications

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“…Easy to prove that region Ω is positively invariant with respect to system (1). e basic reproduction number R 0 , defined as the average number of secondary infections generated by a single infected individual introduced into a completely susceptible population [29][30][31][32][33], is one of the important quantities in epidemiology. For model (1), following the method in [30], we can obtain R 0 as follows:…”

Section: Dynamic Model Of Hfmdmentioning

confidence: 99%

Optimal Control Strategies of HFMD in Wenzhou, China

Ding

Cai

et al. 2020

Complexity

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In this paper, we investigate the dynamics and optimal control strategies of a modified hand, foot, and mouth disease (HFMD) model incorporating the EV-A71 vaccination in Wenzhou, China, analytically and numerically. We define the basic reproduction number R0 and show that it can be used to determine whether HFMD becomes extinct or not. Based on the monthly reported HFMD cases in Wenzhou for 76 months, we estimate the parameters in the dynamic model by using the method of minimum chi-square fitting, conduct the sensitivity analysis to investigate the influence of each uncertain parameter on R0 with the methods of Latin hypercube sampling and partial rank correlation coefficient, and find that the EV-A71 vaccination does not lead to the extinction of HFMD, but slightly reduces the incidence of HFMD. In order to control the spread of HFMD in Wenzhou, we need to increase the rate of EV-A71 vaccination, decrease the contact rates, and shorten the course of disease.

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Section: Dynamic Model Of Hfmdmentioning

confidence: 99%

Optimal Control Strategies of HFMD in Wenzhou, China

Ding

Cai

et al. 2020

Complexity

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“…Some studies have analysed the population's response to the epidemic and have found a negative effect of the Zika/microcephaly on fertility rates in Brazil (Castro, Han, Carvalho, Victora, & França, 2018; Junior & Rasul, 2019; Quintana‐Domeque, Carvalho, & de Oliveira, 2018; Rangel, Nobles, & Hamoudi, 2019; Ryu, 2019) and on birth rates in Colombia (Gamboa & Lesmes, 2019). However, although there is an extensive literature that shows the spatial dependence on the incidence of viral outbreaks such as dengue and Zika (Cai, Ding, Yang, Peng, & Wang, 2019; Fitzgibbon, Morgan, & Webb, 2017; Flórez‐Lozano et al, 2020; Martínez‐Bello, López‐Quílez, & Torres Prieto, 2018; Mondini & Chiaravalloti‐Neto, 2008), issues related to spatial interaction are not addressed in studies that sought to analyse the impact of Zika incidence on birth rates.…”

Section: Introductionmentioning

confidence: 99%

Mosquitoes, birth rates and regional spillovers: Evidence from the Zika epidemic in Brazil

Triaca

Ribeiro

Tejada

2021

Papers in Regional Science

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This paper investigates the impact of the incidence of the Zika virus on birth rates in Brazil. We estimated a difference‐in‐differences model that explicitly considers the spatial interaction of virus incidence, measuring its impact on the affected municipalities and their neighbours—not directly affected. Our results show that directly affected municipalities experienced a 1.7% decrease in birth rates in 2016 and 2.5% in 2017, while municipalities close to those affected—but not directly affected—showed reductions of 1.2% and 2.1% for the same periods. Moreover, the evidence shows that the effect was not guided by biological effects and was concentrated among younger women.

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“…Especially, the movements of people with infection, e.g., the exposed, symptomatic infected, and asymptomatic infected population are all infectious, which greatly increase the possibility of propagation of COVID-19 all over the world. There is a lots of important research on reaction-diffusion epidemic models focused on spatial structured diseases(see, e.g., [19,55,38,11,12,30,45,31] and references cited therein). Therefore, in order to effectively model the influence of temporal and spatial variation on the transmission of COVID-19, reaction-diffusion could be a better choice to characterize the local movements of key population, e.g., the exposed, infected people who has the ability of infection.…”

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confidence: 99%

Spatial dynamic analysis for COVID-19 epidemic model with diffusion and Beddington-DeAngelis type incidence

Zheng¹,

Luo²,

Xinran³

et al. 2023

CPAA

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<p style='text-indent:20px;'>A diffusion SEIAR model with Beddington-DeAngelis type incidence is proposed to characterize the spread of COVID-19 with spatial transmission. First, the well-posedness of solution is studied. Second, the basic reproduction number <inline-formula><tex-math id="M3">\begin{document}$ \mathcal R_{0} $\end{document}</tex-math></inline-formula> is derived and served as a threshold value to determine whether COVID-19 will spread. Meanwhile, we consider the effect of diffusion on the spread of COVID-19 in spatial homogenous environment, by which we can obtain that if <inline-formula><tex-math id="M4">\begin{document}$ \mathcal R_{0}<1 $\end{document}</tex-math></inline-formula>, then the infection-free steady state is globally asymptotically stable, while if <inline-formula><tex-math id="M5">\begin{document}$ \mathcal R_{0}>1 $\end{document}</tex-math></inline-formula>, then the endemic steady state is globally asymptotically stable. Furthermore, according to the official reporting data about COVID-19 in Wuhan, China, the actual value of <inline-formula><tex-math id="M6">\begin{document}$ \mathcal R_{0} $\end{document}</tex-math></inline-formula> is estimated, and comparing with other types of incidence, we find that the estimated peak with Beddington-DeAngelis type incidence is more close to the cases in reality. Finally, by numerical simulations, we can see that the diffusion behavior has evident impact on the spread of COVID-19 in spatial heterogeneity than homogeneity of environment.</p>

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Transmission dynamics of Zika virus with spatial structure—A case study in Rio de Janeiro, Brazil

Cited by 20 publications

References 38 publications

Optimal Control Strategies of HFMD in Wenzhou, China

Optimal Control Strategies of HFMD in Wenzhou, China

Mosquitoes, birth rates and regional spillovers: Evidence from the Zika epidemic in Brazil

Spatial dynamic analysis for COVID-19 epidemic model with diffusion and Beddington-DeAngelis type incidence

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