A simple and fast spectroscopy-based technique for Covid-19 diagnosis.

The coronavirus pandemic, which appeared in Wuhan, China, in December 2019, rapidly spread all over the world in only a few weeks. Faster testing techniques requiring less resources are key in managing the pandemic, either to enable larger scale testing or even just provide developing countries with limited resources, particularly in Africa, means to perform tests to manage the crisis. Here, we report an unprecedented, rapid, reagent-free and easy-to-use screening spectroscopic method for the detection of SARS-CoV-2 on RNA extracts. This method, validated on clinical samples collected from 280 patients with quantitative predictive scores on both positive and negative samples, is based on a multivariate analysis of FTIR spectra of RNA extracts. This technique, in agreement with RT-PCR, achieves 97.8% accuracy, 97% sensitivity and 98.3% specificity while reducing the testing time post RNA extraction from hours to minutes. Furthermore, this technique can be used in several laboratories with limited resources.

From predictions to prescriptions: A data-driven response to COVID-19.

The COVID-19 pandemic has created unprecedented challenges worldwide. Strained healthcare providers make difficult decisions on patient triage, treatment and care management on a daily basis. Policy makers have imposed social distancing measures to slow the disease, at a steep economic price. We design analytical tools to support these decisions and combat the pandemic. Specifically, we propose a comprehensive data-driven approach to understand the clinical characteristics of COVID-19, predict its mortality, forecast its evolution, and ultimately alleviate its impact. By leveraging cohort-level clinical data, patient-level hospital data, and census-level epidemiological data, we develop an integrated four-step approach, combining descriptive, predictive and prescriptive analytics. First, we aggregate hundreds of clinical studies into the most comprehensive database on COVID-19 to paint a new macroscopic picture of the disease. Second, we build personalized calculators to predict the risk of infection and mortality as a function of demographics, symptoms, comorbidities, and lab values. Third, we develop a novel epidemiological model to project the pandemic's spread and inform social distancing policies. Fourth, we propose an optimization model to re-allocate ventilators and alleviate shortages. Our results have been used at the clinical level by several hospitals to triage patients, guide care management, plan ICU capacity, and re-distribute ventilators. At the policy level, they are currently supporting safe back-to-work policies at a major institution and vaccine trial location planning at Janssen Pharmaceuticals, and have been integrated into the US Center for Disease Control's pandemic forecast.