Stochastic discrete epidemic modeling of COVID-19 transmission in the Province of Shaanxi incorporating public health intervention and case importation

Before the lock-down of Wuhan/Hubei/China, on January 23rd 2020, a large number of individuals infected by COVID-19 moved from the epicenter Wuhan and the Hubei province due to the Spring Festival, resulting in an epidemic in the other provinces including the Shaanxi province. The epidemic scale in Shaanxi was comparatively small and with half of cases being imported from the epicenter. Based on the complete epidemic data including the symptom onset time and transmission chains, we calculate the control reproduction number (1.48-1.69) in Xi’an. We could also compute the time transition, for each imported or local case, from the latent, to infected, to hospitalized compartment, as well as the effective reproduction number. This calculation enables us to revise our early deterministic transmission model to a stochastic discrete epidemic model with case importation and parameterize it. Our model-based analyses reveal that the newly generated infections decay to zero quickly; the cumulative number of case-driven quarantined individuals via contact tracing stabilize at a manageable level, indicating that the intervention strategies implemented in the Shaanxi province have been effective. Risk analyses, important for the consideration of “resumption of work”, show that a large second outbreak is expected if the level of case importation remains at the same level as between January 10th and February 4th 2020. However, if the case importation decreases by 30%, 60% and 90%, the second outbreak if happening will be of small-scale assuming contact tracing and quarantine/isolation remain as effective as before. Finally, we consider the effects of intermittent inflow with a Poisson distribution on the likelihood of multiple outbreaks. We believe the developed methodology and stochastic model provide an important model framework for the evaluation of revising travel restriction rules in the consideration of resuming social-economic activities while managing the disease control with potential case importation.

A discrete epidemic model and a zigzag strategy for curbing the Covid-19 outbreak and for lifting the lockdown

This study looks at the dynamics of a Covid-19 type epidemic with a dual purpose. The first objective is to propose a reliable temporal mathematical model, based on real data and integrating the course of illness. It is a daily discrete model with different delay times, and whose parameters are calibrated from the main indicators of the epidemic. The model can be broken down in two decoupled versions: a mortality-mortality version, which can be used with the data on the number of deaths, and an infection-infection version to be used when reliable estimates of infection rate are available. The model allows to describe realistically the evolution of the main markers of the epidemic. In addition, in terms of deaths and occupied ICU beds, the model is not very sensitive to the current uncertainties about IFR. The second objective is to study several original scenarios for the epidemic’s evolution, especially after the period of strict lockdown. A coherent strategy is therefore proposed to contain the outbreak and exit lockdown, without going into the risky herd immunity approach. This strategy, called zigzag strategy, is based on a classification of the interventions into four lanes, distinguished by a marker called the daily reproduction number. The model and strategy in question are flexible and easily adaptable to new developments such as mass screenings or infection surveys. They can also be used at different geographical scales (local, regional or national).

Travel-blocking Optimal Control Policy on Borders of a Chain of Regions Subject to SIRS Discrete Epidemic Model

With thousands of people moving from one area to another day by day, in a chain of regions tightly more interconnected than other regions in a given large domain, an epidemic may spread rapidly around it from any point of borders. It might be sometimes urgent to impose travel restrictions to inhibit the spread of infection. As we aim to protect susceptible people of this chain to contact infected travelers coming from its neighbors, we follow the so-called travel-blocking vicinity optimal control approach with the introduction of the notion of patch for representing our targeted group of regions when the epidemic modeling framework is in the form of a Susceptible-Infected-Removed-Susceptible (SIRS) discrete-time system to study the case of the removed class return to susceptibility because of their short-lived immunity. A discrete version of the Pontryagin’s maximum principle is employed for the characterization of the travel-blocking optimal control. Finally, with the help of discrete progressive-regressive iterative schemes, we provide cellular simulations of an example of a domain composed with 100 regions and where the targeted chain includes 7 regions.

A discrete epidemic model for bovine Babesiosis disease and tick populations

In this paper, we provide and study a discrete model for the transmission of Babesiosis disease in bovine and tick populations. This model supposes a discretization of the continuous-time model developed by us previously. The results, here obtained by discrete methods as opposed to continuous ones, show that similar conclusions can be obtained for the discrete model subject to the assumption of some parametric constraints which were not necessary in the continuous case. We prove that these parametric constraints are not artificial and, in fact, they can be deduced from the biological significance of the model. Finally, some numerical simulations are given to validate the model and verify our theoretical study.

Existence and Convergence of the Positive Solutions of a Discrete Epidemic Model

We consider a class of system of nonlinear difference equations arising from mathematical models describing a discrete epidemic model. Sufficient conditions are established that guarantee the existence of positive solutions, the existence of a unique nonnegative equilibrium, and the convergence of the positive solutions to the nonnegative equilibrium of the system of difference equations. The obtained results are new and they complement previously known results.