DYNAMICS OF A DENGUE FEVER MODEL WITH UNREPORTED CASES AND ASYMPTOMATIC INFECTED CLASSES IN SINGAPORE, 2020

Transfer diagram for the model (2.1).

Disease free equilibrium $ E_{0} $ is locally asymptotically stable. (a)$ E_{h}, A_{h} $ and $ I_{h} $; (b)$ P, H_{m} $ and $ H_{s} $.

Forward bifurcation diagram taking one parameter $ \beta_{h} $ in $ R_{0} $ as bifurcation parameter.

The influence of $ \beta_{h} $ and $ \beta_{m} $ on $ R_{0} $

The influence of each parameter on $ R_{0} $. (a) $ \beta_{h} $ and $ \gamma_{i} $; (b) $ \beta_{m} $ and $ \mu_{m} $; (c) $ \beta_{h} $ and $ l $; (d) $ \gamma_{i} $ and $ l $.

The actual number of people infected in Singapore from 15 to 52 weeks in 2020 years.

Sample values of $ R_{0} $ and infectivity parameters and sample distributions. (a)The Markov chain of the last 300000 samples of $ R_{0} $. The blue dots indicate the value of $ R_{0} $ within the 95% credible intervals, the red pluses indicate the value of $ R_{0} $ outside the 95% credible intervals, and the black lines indicate the upper and lower credible limits. The frequency distribution of $ R_{0} $. The red curve is the probability density function curve of $ R_{0} $. (b)$ \beta_{h} $ and $ \beta_{m} $'s Markov Chain Monte Carlo (MCMC) parameters distribution.

The Partial Rank Correlation Coefficients of $ R_{0} $ in model (2.1).

The influence of partial parameter variation on $ R_{0} $. (a) The variation trend between $ \beta_{m} $ and $ R_{0} $. (b) The variation trend between $ \gamma_{p} $ and $ R_{0} $. (c) The variation trend between $ \gamma_{m} $ and $ R_{0} $. (d) The variation trend between $ \beta_{h} $ and $ R_{0} $.

Number of people in different compartment with $ c_{1}=100; c_{2}=500; c_{3}=1000 $ and different optimal control strategies. (a) $ A_{h} $; (b) $ H_{s} $; (c) $ I_{h} $; (d) $ E_{h} $; (e) $ P $; (f) $ H_{m} $.