COVID-19 outbreak and the role of digital twin.

COVID-19 has transformed the life of human beings and digital twin infrastructure can facilitates working remotely during COVID-19 outbreak by reducing burden on services and infrastructure. Currently, many organizations are installing and developing devices such as thermal cameras, sensors aiming to minimize human contact and so forth, in addition to enforcing social distancing resulting in reducing the risk of transmission. Due to economic reasons, lockdown restrictions are being relaxed/lifted in many countries and Pakistan which is one of the most densely populated countries in the world with a population of 220 + million is no exception. Though, Pakistan contained the first two waves of coronavirus infections reasonably well but the country is struggling to contain the third wave of the spread due to violations of social distancing norms. While our predictions may deviate from official statistics due to lack of mass testing and existence of asymptomatic infections, the described approach predicts the possible actual burden of infection over times. In view of the unique demographics, our data quantify the efficacy of social distancing as an effective measure to forestall the infection. We highlight few areas where digital twins can be created/deployed to provide services and essential facilities to citizens as COVID-19 is expected to have permanent impact on the way we work.

A survey of COVID-19 contact-tracing apps.

Recently, the sudden outbreak of the COVID-19 virus caused a major health crisis by affecting masses around the world. The virus, which is known to be highly contagious, has forced the research community and governments to fight the disease and take prompt actions by applying various strategies to keep the numbers under control. These strategies range from imposing strict social distancing measures, isolating infected cases, and enforcing either a partial or a full lockdown, to mathematical modeling and contact-tracing applications. In this work, we survey the current contact-tracing apps and organize them based on underlying technologies such as Bluetooth, Wi-Fi, GPS, geofencing, and Quick Response (QR) codes. We compare the main features of 22 existing applications and highlight each of the pros and cons associated with these different technologies.

Impact of lockdowns on the spread of COVID-19 in Saudi Arabia.

Epidemiological models have been used extensively to predict disease spread in large populations. Among these models, Susceptible Infectious Exposed Recovered (SEIR) is considered to be a suitable model for COVID-19 spread predictions. However, SEIR in its classical form is unable to quantify the impact of lockdowns. In this work, we introduce a variable in the SEIR system of equations to study the impact of various degrees of social distancing on the spread of the disease. As a case study, we apply our modified SEIR model on the initial spread data available (till April 9, 2020) for the Kingdom of Saudi Arabia (KSA). Our analysis shows that with no lockdown around 2.1 million people might get infected during the peak of spread around 2 months from the date the lockdown was first enforced in KSA (March 25th). On the other hand, with the Kingdom's current strategy of partial lockdowns, the predicted number of infections can be lowered to 0.4 million by September 2020. We further demonstrate that with a stricter level of lockdowns, the COVID-19 curve can be effectively flattened in KSA.