Narrow Results

To fight against Ebola virus disease, several measures have been adopted. Among them, isolation, safe burial and vaccination occupy a prominent place. In this paper, we present a model which takes into account these three control strategies as well as the indirect transmission through a polluted environment. The asymptotic behavior of our model is achieved. Namely, we determine a threshold value ${{ℛ}}_c^c$ of the control reproduction number ${{ℛ}}_c$, below which the disease is eliminated in the long run. Whenever the value of ${{ℛ}}_c$ ranges from ${{ℛ}}_c^c$ and 1, we prove the existence of a backward bifurcation phenomenon, which corresponds to the case, where a locally asymptotically stable positive equilibrium co-exists with the disease-free equilibrium, which is also locally asymptotically stable. The existence of this bifurcation complicates the control of Ebola, since the requirement of ${{ℛ}}_c$ below one, although necessary, is no longer sufficient for the elimination of Ebola, more efforts need to be deployed. When the value of ${{ℛ}}_c$ is greater than one, we prove the existence of a unique endemic equilibrium, locally asymptotically stable. That is the disease may persist and become endemic. Numerically, we fit our model to the reported data for the 2018–2020 Kivu Ebola outbreak which occurred in Democratic Republic of Congo. Through the sensitivity analysis of the control reproduction number, we prove that the transmission rates of infected alive who are outside hospital are the most influential parameters. Numerically, we explore the usefulness of isolation, safe burial combined with vaccination and investigate the importance to combine the latter control strategies to the educational campaigns or/and case finding.

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Ebola virus is a highly lethal filovirus, claimed thousands of people in its recent outbreak. Seven viral proteins constitute ebola viral structure, and four of them (nucleoprotein (NP), polymerase L, VP35 and VP30) participate majorly in viral replication and transcription. We have elucidated a conformation change of NP cleft by VP35 NP-binding protein domains through superimposing two experimental NP structure images and discussed the function of this conformation change in the replication and transcription with polymerase complex (L, VP35 and VP30). The important roles of VP30 in viral RNA synthesis have also been discussed. A “tapping” model has been proposed in this paper for a better understanding of the interplay among the four viral proteins (NP, polymerase L, VP35 and VP30). Moreover, we have pinpointed some key residue changes on NP (both NP N- and C-terminal) and L between Reston and Zaire by computational studies. Together, this paper provides a description of interactions among ebola viral proteins (NP, L, VP35, VP30 and VP40) in viral replication and transcription, and sheds light on the complex system of viral reproduction.

More than 20 outbreaks of Ebola virus disease have occurred in Africa since 1976, and yet no adequate treatment is available. Hence, prevention, control measures and supportive treatment remain the only means to avoid the disease. Among these measures, contact tracing occupies a prominent place. In this paper, we propose a simple mathematical model that incorporates imperfect contact tracing, quarantine and hospitalization (or isolation). The control reproduction number ${{ℛ}}_c$ of each sub-model and for the full model are computed. Theoretically, we prove that when ${{ℛ}}_c$ is less than one, the corresponding model has a unique globally asymptotically stable disease-free equilibrium. Conversely, when ${{ℛ}}_c$ is greater than one, the disease-free equilibrium becomes unstable and a unique globally asymptotically stable endemic equilibrium arises. Furthermore, we numerically support the analytical results and assess the efficiency of different control strategies. Our main observation is that, to eradicate EVD, the combination of high contact tracing (up to 90%) and effective isolation is better than all other control measures, namely: (1) perfect contact tracing, (2) effective isolation or full hospitalization, (3) combination of medium contact tracing and medium isolation.

We study the reaction–diffusion Ebola PDE model that consists of equations that govern the evolution of susceptible, infected, recovered and deceased human individuals, as well as Ebola virus pathogens in the environment, with diffusive terms in all except the equation of the deceased human individuals. Under the setting of a spatial domain that is bounded, we prove the global well-posedness of the system; in contrast to the previous work on similar models such as cholera, avian influenza, malaria and dengue fever, diffusion coefficients may be different. Moreover, we derive its basic reproduction number, and under the condition that the diffusion coefficients of the susceptible and infected hosts are same, we prove the global stability of the disease-free-equilibrium, and uniform persistence in cases when the basic reproduction number lies beneath and above one, respectively. Again, we do not require that the diffusion coefficients of the recovered hosts be the same as the diffusion coefficients of the susceptible and infected hosts, in contrast to previous work on other models of infectious diseases. Another technical difficulty in our model is that the solution semiflow is not compact due to the lack of diffusion in the equation of the deceased human individuals; we overcome this difficulty using functional analysis techniques concerning Kuratowski measure of non-compactness.

The increasingly frequent occurrence of natural, man-made and environmental disasters in recent years has resulted in both a large number of casualties and widespread property damage. To mitigate the damage caused, a lot of emergency supplies are required. However, due to the limited quantity of emergency supplies, the allocation of rescue resources is extremely important. Using the March 2014 Ebola outbreak in western Africa as an example, this paper uses Dijkstra's algorithm to build a system which determines the optimal allocation of emergency resource to cities in Sierra Leone. Each city's weightage is calculated using data provided before Dijkstra's algorithm is applied.

Online social media microblogs may be a valuable resource for timely identification of critical ad hoc health-related incidents or serious epidemic outbreaks. In this paper, we explore emotion classification of Twitter microblogs related to localized public health threats, and study whether the public mood can be effectively utilized in early discovery or alarming of such events. We analyse user tweets around recent incidents of Ebola, finding differences in the expression of emotions in tweets posted prior to and after the incidents have emerged. We also analyse differences in the nature of the tweets in the immediately affected area as compared to areas remote to the events. The results of this analysis suggest that emotions in social media microblogging data (from Twitter in particular) may be utilized effectively as a source of evidence for disease outbreak detection and monitoring.