For an overview of the BDI pathogens group's work on sustainable containment of covid-19 please see our website. For the details, this repository contains two preprints:
Quantifying dynamics of SARS-CoV-2 transmission suggests that epidemic control and avoidance is feasible through instantaneous digital contact tracing
Luca Ferretti1*, Chris Wymant1*, Michelle Kendall1, Lele Zhao1, Anel Nurtay1, David Bonsall1,2 and Christophe Fraser1,3†
*contributed equally; † To whom correspondence should be addressed: christophe.fraser@bdi.ox.ac.uk
1 Big Data Institute, University of Oxford, UK, 2 Oxford University NHS Trust, University of Oxford, UK, 3 Wellcome Centre for Human Genetics, University of Oxford, UK
Mobile phone apps implementing algorithmic contact tracing can speed up the process of tracing newly diagnosed individuals, spreading information instantaneously back through a past contact network to inform them that they are at risk of being infected, and thus allow them to take appropriate social distancing and testing measures. The aim of non-pharmaceutical infection prevention is to move a population towards herd protection, a state where a population maintains R0 < 1, thus making it impossible for a pathogen to cause an epidemic. Here, we address epidemiological issues that affect the feasibility of an algorithmic approach to instantaneous contact tracing; ethical and implementation issues are addressed separately. First we quantify the parameters of COVID-19 in a framework that is consistent with the renewal equation formulation of epidemic spread. Second, we use an analytical solution to application of first-degree contact tracing in the renewal equation model to explore combinations of efficacy that can induce herd protection (R0 < 1). With the emergence of the novel viral pathogen SARS-CoV-2, of clear potential for a global pandemic with high fatality rates and incapacitated health systems, the question of prevention has critical priority. We come to the conclusion that isolating symptomatic cases and tracing their contacts in a classical manner is not sufficiently fast to stop the spread of the epidemic and needs to be accompanied by measures of social distancing that are disruptive to a wide number of people. We show that first-degree instantaneous contact tracing, informing users when they can move safely or when to seek medical help and avoid vulnerable individuals, has the potential to stop the spread of the epidemic if used by a sufficiently large number of people with reasonable fidelity.
Sustainable containment of COVID-19 using smartphones in China: Scientific and ethical underpinnings for implementation of similar approaches in other settings
David Bonsall1,2 Michael Parker3 and Christophe Fraser1,4
1 Big Data Institute, University of Oxford, UK, 2 Oxford University NHS Trust, University of Oxford, UK, 3 Wellcome Centre for Ethics and the Humanities and Ethox Centre, University of Oxford, UK 4 Wellcome Centre for Human Genetics, University of Oxford, UK
COVID-19 is a rapidly spreading infectious disease with pandemic potential, caused by the novel virus, SARS-COV-2. With intensive care support, the case fatality rate is approximately 2%, and around half of infections become cases [1]. More concerning is that the fraction of cases requiring intensive care support is 5%, and patient management is complicated by requirements to use personal protective equipment (PPE) and engage in complex decontamination procedures [2]. Fatality rates are likely to be higher in populations older than in Hubei province (such as in Europe), and in low-income settings where critical care facilities are lacking [3]. Even modest outbreaks will see fatality rates climb as hospital capacity is overwhelmed, and the indirect effects caused by compromised health care services have yet to be enumerated. Effective containment must be achieved.