Real-time forecasts and risk assessment of novel coronavirus (COVID-19) cases: A data-driven analysis

The coronavirus disease 2019 (COVID-19) has become a public health emergency of international concern affecting 201 countries and territories around the globe. As of April 4, 2020, it has caused a pandemic outbreak with more than 11,16,643 confirmed infections and more than 59,170 reported deaths worldwide. The main focus of this paper is two-fold: (a) generating short term (real-time) forecasts of the future COVID-19 cases for multiple countries; (b) risk assessment (in terms of case fatality rate) of the novel COVID-19 for some profoundly affected countries by finding various important demographic characteristics of the countries along with some disease characteristics. To solve the first problem, we presented a hybrid approach based on autoregressive integrated moving average model and Wavelet-based forecasting model that can generate short-term (ten days ahead) forecasts of the number of daily confirmed cases for Canada, France, India, South Korea, and the UK. The predictions of the future outbreak for different countries will be useful for the effective allocation of health care resources and will act as an early-warning system for government policymakers. In the second problem, we applied an optimal regression tree algorithm to find essential causal variables that significantly affect the case fatality rates for different countries. This data-driven analysis will necessarily provide deep insights into the study of early risk assessments for 50 immensely affected countries

Examination Of Factors Affecting The Frequency, Response Time, And Clearance Time Of Incidents On Freeways

Traffic incidents are the primary cause of non-recurrent congestion in urban areas, resulting in reductions in roadway capacity and significant safety hazards to other motorists, as well as first responders. Many communities have initiated incident management programs that detect and respond to incidents and restore freeways to full capacity by clearing the incident scene as soon as possible. In the Detroit metro area, the Michigan Department of Transportation (MDOT) operates a Freeway Courtesy Patrol (FCP) program as part of its larger freeway incident management program from the Michigan Intelligent Transportation Systems (MITS) Center in downtown Detroit. The MITS Center maintains a series of databases that detail freeway operations, as well as the activities of the FCP. However, these databases are independent of one another and no research has concurrently examined the interrelationships between freeway operations and the services provided by the MITS Center. This study aims at analyzing operations on the Detroit freeway network. This study assesses the data maintained by the MITS Center and involves the development of a software interface that was used to combine data from these various sources. These data include traffic flow information obtained from side-fire sensors, as well as data related to FCP operations in the Detroit freeway network. In addition to linking these independent data sources, preliminary data analyses are conducted in order to identify important factors influencing the incident clearance time. A comprehensive database along with traffic flow characteristics is prepared and statistical analyses are conducted to identify important factors that impact the frequency and duration of incidents on various freeway sections in Detroit metro area. It allows the consideration of the effect of various site-specific variables across different locations as well as the transferability of developed models. Consequently, this assessment highlights different areas of opportunity, uncovers the underlying strong and weak areas of existing MDOT freeway incident management program and offers important directions for the possible improvement that can collectively result in the development of better freeway traffic operations in Detroit metro area

Group-Key Management Model for Worldwide Wireless Mesh Networks

Wireless Mesh Network (WMN) is an upcoming wireless network technology and is mainly used to provide broadband internet in remote locations. It is characterized by minimum fixed infrastructure requirement and is operated in an open medium, such that any user within the range covered by mesh routers may access the network. So a critical requirement for the security in WMN is the authentication of users. However, WMN is far from mature for large-scale deployment in some applications due to the lack of the satisfactory guarantees on security. A wellperformed security framework for WMN will contribute to network survivability and strongly support the network growth or reduction. A key management model to overcome the scalability issue on security aspect for large-scale deployment of WMN i.e. Worldwide WMN is proposed in this work, which aims to guarantee wellperformed key management services and protection from potential attacks. Here, we use a combination of techniques, such as zonebased topology structure, off-line CA, virtual certification authority ) etc

Zoonotic MERS-CoV transmission: modeling, backward bifurcation and optimal control analysis

Middle East Respiratory Syndrome Coronavirus (MERS-CoV) can cause mild to severe acute respiratory illness with a high mortality rate. As of January 2020, more than 2500 cases of MERS-CoV resulting in around 860 deaths were reported globally. In the absence of neither effective treatment nor a ready-to-use vaccine, control measures can be derived from mathematical models of disease epidemiology. In this manuscript, we propose and analyze a compartmental model of zoonotic MERS-CoV transmission with two co-circulating strains. The human population is considered with eight compartments while the zoonotic camel population consist of two compartments. The expression of basic reproduction numbers are obtained for both single strain and two strain version of the proposed model. We show that the disease-free equilibrium of the system with single stain is globally asymptotically stable under some parametric conditions. We also demonstrate that both models undergo backward bifurcation phenomenon, which in turn indicates that only keeping R0 below unity may not ensure eradication. To the best of the authors knowledge, backward bifurcation was not shown in a MERS-CoV transmission model previously. Further, we perform normalized sensitivity analysis of important model parameters with respect to basic reproduction number of the proposed model. Furthermore, we perform optimal control analysis on different combination interventions with four components namely preventive measures such as use of masks, isolation of strain-1 infected people, strain-2 infected people and infected camels. Optimal control analysis suggests that combination of preventive measures and isolation of infected camels will eventually eradicate the disease from the community

Short-term predictions and prevention strategies for COVID-19: A model based study

An outbreak of respiratory disease caused by a novel coronavirus is ongoing from December 2019. As of July 22, 2020, it has caused an epidemic outbreak with more than 15 million confirmed infections and above 6 hundred thousand reported deaths worldwide. During this period of an epidemic when human-to-human transmission is established and reported cases of coronavirus disease 2019 (COVID-19) are rising worldwide, investigation of control strategies and forecasting are necessary for health care planning. In this study, we propose and analyze a compartmental epidemic model of COVID-19 to predict and control the outbreak. The basic reproduction number and control reproduction number are calculated analytically. A detailed stability analysis of the model is performed to observe the dynamics of the system. We calibrated the proposed model to fit daily data from the United Kingdom (UK) where the situation is still alarming. Our findings suggest that independent self-sustaining human-to-human spread ($R_0>1$, $R_c>1$) is already present. Short-term predictions show that the decreasing trend of new COVID-19 cases is well captured by the model. Further, we found that effective management of quarantined individuals is more effective than management of isolated individuals to reduce the disease burden. Thus, if limited resources are available, then investing on the quarantined individuals will be more fruitful in terms of reduction of cases.Comment: N

Photochemical Functionalization of Helicenes

Herein, a visible-light photochemical approach for practical helicene functionalization at very mild reaction conditions is described. The photochemical reactions allow for the regiospecific and innate late-stage functionalization of helicenes and are easily executed either through the activation of C(sp(2))-Br bonds in helicenes using K2CO3 as inorganic base or direct C(sp(2))-H helicene bond functionalization under oxidative photoredox reaction conditions. Overall, using these transformations six different functional groups are introduced to the helicene scaffold through C-C and four different C-heteroatom bond-forming reactions