Abstract
The current situation of COVID-19 highlights the paramount importance of infectious disease surveillance, which necessitates early monitoring for effective response. Policymakers are interested in data insights identifying high-risk areas as well as individuals to be quarantined, especially as the public gets back to their normal routine. We investigate both requirements by the implementation of disease outbreak modeling and exploring its induced dynamic spatial risk in form of risk assessment, along with its real-time integration back into the disease model. This paper implements a contact tracing-based stochastic compartment model as a baseline, to further modify the existing setup to include the spatial risk. This modification of each individual-level contact’s intensity to be dependent on its spatial location has been termed as Contextual Contact Tracing. The results highlight that the inclusion of spatial context tends to send more individuals into quarantine which reduces the overall spread of infection. With a simulated example of an induced spatial high-risk, it is highlighted that the new spatio-SIR model can act as a tool to empower the analyst with a capability to explore disease dynamics from a spatial perspective. We conclude that the proposed spatio-SIR tool can be of great help for policymakers to know the consequences of their decision prior to their implementation.
Highlights
Detection and control of COVID-19 in particular, and infectious diseases in general, have irrupted as a major societal challenge
As the inclusion of spatial risk tends to affect the rates of events related to Susceptible individuals and getting infected is subject to an infectious contact, in the spatio-SIR model, there are more events of the population moving into Quarantine Susceptible
Though the trends of Quarantine Susceptible in both models are similar till day 15th, the mentioned phenomenon is evident afterwards where the peak of individuals in Quarantine Susceptible is 59 on the 29th day, whereas there are less than 50 individuals in Quarantine Susceptible by the same day
Summary
Detection and control of COVID-19 in particular, and infectious diseases in general, have irrupted as a major societal challenge. As of 31st January 2021, the COVID-19 pandemic has over 101 million confirmed cases with above 2.1 million deaths worldwide (WHO 2021). This explosive dissemination is a universal threat to public health organizations, but it jeopardizes social functioning, industry, economy and international relations (Zhou et al.2020). Countries such as Israel and South Korea which took prompt actions towards testing and identification of previous contacts in case of an identified individual were able to restrict the disease spread. In a situation like this, detection of an infectious disease requires non-pharmaceutical interventions (NPI) and is to be supported by methods outside of the medical system, which sets the basis of the term Digital Epidemiology (DE) (Salathe 2018)
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