A Smartphone Enabled Approach to Manage COVID-19 Lockdown and Economic Crisis

Abstract

The emergence of novel COVID-19 causes an overload in health system and high mortality rate. The key priority is to contain the epidemic and prevent the infection rate. In this context, many countries are now in some degree of lockdown to ensure extreme social distancing of entire population and hence slowing down the epidemic spread. Furthermore, authorities use case quarantine strategy and manual second/third contact-tracing to contain the COVID-19 disease. However, manual contact-tracing is time-consuming and labor-intensive task which tremendously overload public health systems. In this paper, we developed a smartphone-based approach to automatically and widely trace the contacts for confirmed COVID-19 cases. Particularly, contact-tracing approach creates a list of individuals in the vicinity and notifying contacts or officials of confirmed COVID-19 cases. This approach is not only providing awareness to individuals they are in the proximity to the infected area, but also tracks the incidental contacts that the COVID-19 carrier might not recall. Thereafter, we developed a dashboard to provide a plan for policymakers on how lockdown/mass quarantine can be safely lifted, and hence tackling the economic crisis. The dashboard used to predict the level of lockdown area based on collected positions and distance measurements of the registered users in the vicinity. The prediction model uses k-means algorithm as an unsupervised machine learning technique for lockdown management.

COVID-19 and restaurant demand: early effects of the pandemic and stay-at-home orders

“…According to Dube et al (2020), dine-in customers dropped to an all-time low level in many countries in March 2020 due to strict lockdown policies. Second, stay-at-home orders can indirectly constrain restaurant demand through supply and labor shortages caused by the closure of nonessential businesses that are foodservice industry suppliers (Maghdid and Ghafoor, 2020) and the lack of available employees. Stay-at-home orders exerted sweeping impacts on all sectors of the economy, and restaurant supply can be adversely affected due to firm interdependence to supply chains (Luo and Tsang, 2020).…”

Systems Dynamics Approach for Modelling South Africa's Response to Covid-19: A “What If” Scenario

“…Contact tracing can be quick when the number of cases is still low, but when they increase dramatically, it becomes labour intensive and can overload public health systems. 55 A number of digital apps are available for contact tracing, although they are not widely implemented due to ethical considerations. 56 Such apps can collect real-time data such as individual location, health status and movements.…”

Real Time Viral Sub-Strains Discovery in Emerging Infectious Disease Situation – The African Perspective

“…Female isolates excavated according to country (number of sequence, state(s) extracted), include: Algeria (1, 1); Benin (4, 1); DRC (13,4); Egypt (4, 2); Gambia (4, 2); Ghana (4, 1); Kenya (4, 1); Madagascar (2, 2); Mali (4, 1); Morocco (2, 1); Nigeria (11,5); Senegal (11,3); South Africa (80, 24); Tunisia (1, 1). Hence, a total of 290 genome sequences (145 males, 145 females) with genome lengths of over 29000 nucleotides, were excavated.…”

“…Male isolates excavated according to Country (number of sequence, state(s) extracted), include: Algeria (2, 1); Benin (5, 2); Cameroon (1, 1); DRC (15,4); Egypt (5, 2); Gambia (6, 2); Ghana (4, 1); Kenya (4, 1); Mali (5, 2); Morocco (5, 3); Nigeria (13,5); Senegal (14,6); South Africa (65,20); Tunisia (1,1). Female isolates excavated according to country (number of sequence, state(s) extracted), include: Algeria (1, 1); Benin (4, 1); DRC (13,4); Egypt (4, 2); Gambia (4, 2); Ghana (4, 1); Kenya (4, 1); Madagascar (2, 2); Mali (4, 1); Morocco (2, 1); Nigeria (11,5); Senegal (11,3); South Africa (80, 24); Tunisia (1, 1). Hence, a total of 290 genome sequences (145 males, 145 females) with genome lengths of over 29000 nucleotides, were excavated.…”