At the end of 2019 the novel coronavirus disease (COVID-19) was declared as a major health hazard by the world health organization (WHO) and the only available way of stopping this threat was via non-pharmaceutical approach. Most authors have studied COVID-19 transmission dynamics using mathematical modeling by involving the basic (major) compartments. In this study we have formulated a mathematical model for the transmission dynamics of COVID-19 which incorporates almost all possible scenarios at present. We have also analyzed the impact of prevention and control strategies. The model has satisfied all the basic properties that infectious disease model should fulfill; Boundedness, positivity of its solutions, stability analysis, epidemic equilibrium point, basic reproduction number and local stability of the disease free equilibrium. We introduced a self-protection parameter, m to analyze the impact of physical distancing, staying at home, using masks, washing hands and so on. The impact of isolation and quarantine has been analyzed and their effects on the number of Exposed, infected and dead people were clearly discussed. In addition to these, the effects of symptomatic and asymptomatic individuals on the value of basic reproduction number have been examined. The numerical simulations of this study indicate that the government should increase isolation, quarantine and self-protection rates. Additionally to minimize the contact rate between susceptible and asymptotic individuals, self-protection at all cost and everywhere has to be done, so that both symptomatic and importantly asymptomatic individuals stop transmitting the virus.

The significantly increasing mobile capacity demand, the use of advanced techniques like enhanced multiple input multiple output to boost throughput, very high data rate, reliability, very low latency, long battery life, mobility, and to enable internet of things in 4G and 5G technologies, aggravate extreme backhaul requirements with respect to capacity, latency, availability, energy, and on the top of this, cost efficiency. However, it is challenging to get a complete one backhaul technology that can solve all problems of backhaul especially massive introduction of small cells in mind. To overcome various backhaul problems there are many backhaul solutions i.e. the use of diversified backhaul under different use cases provides cost efficient backhaul solution. This paper presents benefits, implementation challenges, and use cases of mobile backhaul in release 8 and beyond. It also presents coverage and capacity analysis using excel based dimensioning tool for a given sample area. Lastly the paper shows economic benefits of diversified backhaul for small and macro cells and high-level implementation strategy for the considered area.