# DeepSOCIAL: Social Distancing Monitoring and Infection Risk Assessment in COVID-19 Pandemic
## 2 Related Works
### Medical Research  
Many researchers in the medical and pharmaceutical fields are aiming at treatment of COVID-19 infectious disease; however, no definite solution has yet been found. One the other hand, controlling the spread of the virus in public places is another issue, where the AI, computer vision, and technology can step-in to help.  
A variety of studies with different implementation strategies [5; 6; 20] have proven that controlling the prevalence is a contributing factor, and social distancing is an effective way to reduce the transmission and prevent the spread of the virus in society. Several researchers such as [20; 21] use Susceptible, Infectious, or Recovered (SIR) model. SIR is an epidemiological modelling system to compute the theoretical number of people infected with a contagious disease in a given population, over time. One of the oldest yet common SIR models is Kermack and McKendrick models introduced in 1927 [22]. [PERSON] et al. [21], have recently introduced a modified model of SIR by including a social distancing parameter, which can be used to determine the number of infected and recovered individuals.  
Effectiveness of social distancing practices can be evaluated based on several standard approaches. One of the main criteria is based on the reproduction ratio, \(R_{o}\), which indicates the average number of people who may be infected from an infectious person during the entire period of the infection [23]. Any \(R_{o}>1\) indicates an increasing rate of infection within the society and \(R_{o}<1\) indicates that every case will infect less than 1 person, hence, the disease rate is considered to be declining in the target population.  
Since the \(R_{o}\) value indicates the disease outspread, it is one of the most important indicators for selecting social distancing criteria. In the current COVID-19 pandemic, the World Health Organisation estimated the \(R_{o}\) rate would be in the range of 2-2.5 [14], which is significantly higher than other similar diseases such as seasonal flu with \(R_{o}=1.4\). In [11], a clear conclusion is drawn about the importance of applying social distancing for cases with a high amount of \(R_{o}\).  
In another research based on the game theory on the classic SIR model, an assessment of the benefits and economic costs of social distancing has been examined [24]. The results also show that in the case of \(R_{o}<1\), social distancing would cause unnecessary costs, while \(R_{o}\approx 2\) implies that social distancing measures have the highest economic benefits. In another similar research, [PERSON] et al. [25] investigated the relationship between the stringency of social distancing and the region's economic status. This study suggests although preventing the widespread outbreak of the virus is necessary, a moderate level of social activities could be allowed.  
[PERSON] et al. [26] use location-specific contact patterns to investigate the effect of social distancing measures on the prevalence of COVID-19 pandemic in order to remove the persistent path of disease outbreak using susceptible-exposed-infected-removed models (SEIR).