A potential roadmap to overcome the current eastern DRC Ebola virus disease outbreak: From a computational perspective

The Kivu Ebola Epidemic

The Kivu Ebola epidemic began on 1 August 2018, when four cases of Ebola virus disease (EVD) were confirmed in the eastern region of Kivu in the Democratic Republic of the Congo (DRC). The disease affected the DRC, Uganda, and is suspected to have also affected Tanzania, though the Ministry of Health there never shared information with the WHO. The outbreak was declared ended on 25 June 2020, with a total of 3,470 cases and 2,280 deaths. Other locations in the DRC affected included the Ituri Province, where the first case was confirmed on 13 August 2018. In November 2018, it became the biggest Ebola outbreak in the DRC's history, and by November, it had become the second-largest Ebola outbreak in recorded history, behind only the 2013–2016 Western Africa epidemic. On 3 May 2019, 9 months into the outbreak, the DRC death toll surpassed 1,000. In June 2019, the virus reached Uganda, having infected a 5-year-old Congolese boy who entered with his family, but this was contained. Since January 2015, the affected province and general area have been experiencing a military conflict, which hindered treatment and prevention efforts. The World Health Organization (WHO) has described the combination of military conflict and civilian distress as a potential "perfect storm" that could lead to a rapid worsening of the situation. In May 2019, the WHO reported that, since January of that year, there had been 42 attacks on health facilities and 85 health workers had been wounded or killed. In some areas, aid organizations have had to stop their work due to violence. Health workers also had to deal with misinformation spread by opposing politicians. Due to the deteriorating security situation in North Kivu and surrounding areas, the WHO raised the risk assessment at the national and regional level from "high" to "very high" in September 2018. In October, the United Nations Security Council stressed that all armed hostility in the DRC should come to a stop to address the ongoing outbreak better. A confirmed case in Goma triggered the decision by the WHO to convene an emergency committee for the fourth time, and on 17 July 2019, the WHO announced a Public Health Emergency of International Concern (PHEIC), the highest level of alarm the WHO can sound. On 15 September 2019, some slowdown of cases was noted in the DRC. However, contact tracing continued to be less than 100%; at the time, it was at 89%. In mid-October the transmission of the virus had significantly reduced; by then it was confined to the Mandima region near where the outbreak began, and was only affecting 27 health zones in the DRC (down from a peak of 207). New cases decreased to zero by 17 February 2020, but after 52 days without a case, surveillance and response teams confirmed three new cases in mid-April. As a new and separate outbreak, was reported on 1 June 2020 in Équateur Province in north-western DRC, described as the eleventh Ebola outbreak since records began; after almost two years the tenth outbreak was declared ended on 25 June 2020, with a total of 3,470 cases and 2,280 deaths.

Numerical Simulation of the Fractal-Fractional Ebola Virus

In this work we present three new models of the fractal-fractional Ebola virus. We investigate the numerical solutions of the fractal-fractional Ebola virus in the sense of three different kernels based on the power law, the exponential decay and the generalized Mittag-Leffler function by using the concepts of the fractal differentiation and fractional differentiation. These operators have two parameters: The first parameter ρ is considered as the fractal dimension and the second parameter k is the fractional order. We evaluate the numerical solutions of the fractal-fractional Ebola virus for these operators with the theory of fractional calculus and the help of the Lagrange polynomial functions. In the case of ρ=k=1, all of the numerical solutions based on the power kernel, the exponential kernel and the generalized Mittag-Leffler kernel are found to be close to each other and, therefore, one of the kernels is compared with such numerical methods as the finite difference methods. This has led to an excellent agreement. For the effect of fractal-fractional on the behavior, we study the numerical solutions for different values of ρ and k. All calculations in this work are accomplished by using the Mathematica package.