2019
DOI: 10.1038/s41598-019-53062-z
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Impact of weather seasonality and sexual transmission on the spread of Zika fever

Abstract: We establish a compartmental model to study the transmission of Zika virus disease including spread through sexual contacts and the role of asymptomatic carriers. To incorporate the impact of the seasonality of weather on the spread of Zika, we apply a nonautonomous model with time-dependent mosquito birth rate and biting rate, which allows us to explain the differing outcome of the epidemic in different countries of South America: using Latin Hypercube Sampling for fitting, we were able to reproduce the diffe… Show more

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Cited by 23 publications
(16 citation statements)
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“…We emphasize that a similar model was established and studied in Dénes et al. ( 2019 ), which also included differentiation of the two sexes. However, no stability analysis was performed in that paper, only numerical results were presented.…”
Section: Mathematical Modelmentioning
confidence: 85%
See 1 more Smart Citation
“…We emphasize that a similar model was established and studied in Dénes et al. ( 2019 ), which also included differentiation of the two sexes. However, no stability analysis was performed in that paper, only numerical results were presented.…”
Section: Mathematical Modelmentioning
confidence: 85%
“…In Dénes et al. ( 2019 ) a non-autonomous model was established considering most of the important features regarding Zika transmission: sexual and vector-borne transmission, the role of asymptomatically infected humans, the prolonged period of infectiousness after recovery and assessed the importance of the seasonality of weather. In (Ibrahim and Dénes 2019 ), this model was extended to improve the estimation of microcephaly risk due to Zika.…”
Section: Introductionmentioning
confidence: 99%
“…To perform a sensitivity analysis of the modelled parameters, we used the Partial Rank Correlation Coefficients (PRCC) technique 44 , 45 . Then, we used Latin hypercube sampling (l h), which is a statistical Monte Carlo sampling technique, to sample the parameters using the lhs package in R 46 .…”
Section: Methodsmentioning
confidence: 99%
“…When the second wave will start in Egypt is an interesting question. To predict the second wave of the COVID-19 pandemic in Egypt, we assume that β ≡ β(t) is a continuous, time-periodic transmission rate with one year as the period and, following, e.g., [35][36][37], it is assumed to be of the form β(t) = β 0 • sin 2π 366 t + b) + a , where a, b are free adjustment parameters and β 0 is the (constant) baseline value of β(t). This function was used to model the periodic recurrence of infectious diseases such as malaria, Zika virus, and Lassa virus.…”
Section: Prediction Of the Second Wave Of The Covid-19 Epidemic In Egyptmentioning
confidence: 99%