Estimating the COVID-19 infection rate: anatomy of an inference problem

As a consequence of missing data on tests for infection and imperfect accuracy of tests, reported rates of population infection by the SARS CoV-2 virus are lower than actual rates of infection. Hence, reported rates of severe illness conditional on infection are higher than actual rates. Understanding the time path of the COVID-19 pandemic has been hampered by the absence of bounds on infection rates that are credible and informative. This paper explains the logical problem of bounding these rates and reports illustrative findings, using data from Illinois, New York, and Italy. We combine the data with assumptions on the infection rate in the untested population and on the accuracy of the tests that appear credible in the current context. We find that the infection rate might be substantially higher than reported. We also find that the infection fatality rate in Italy is substantially lower than reported.

Innovation in Data Visualisation for Public Policy Making

In this contribution, we propose a reflection on the potential of data visualisation technologies for (informed) public policy making in a growingly complex and fast changing landscape—epitomized by the situation created after the outbreak of the Covid-19 pandemic. Based on the results of an online survey of more than 50 data scientists from all over the world, we highlight five application areas seeing the biggest needs for innovation according to the domain specialists. Our main argument is that we are facing a transformation of the business cases supporting the adoption and implementation of data visualisation methods and tools in government, which the conventional view of the value of Business Intelligence does not capture in full. Such evolution can drive a new wave of innovations that preserve (or restore) the human brain’s centrality in a decision making environment that is increasingly dominated—for good and bad—by artificial intelligence. Citizen science, design thinking, and accountability are mentioned as triggers of civic engagement and participation that can bring a community of “knowledge intermediaries” into the daily discussion on data supported policy making. © 2021, The Author(s).

Safety of urologic elective surgery in a covid-hospital

Introduction: To demonstrate safety of a new internal protocol for patients and health workers adopted for elective urologic surgical activity during COVID-19 pandemic. Materials and methods: We have retrospectively evaluated 86 patients who underwent elective surgery in the urology department of IRCCS Policlinico San Donato, from March 9th to May 8th, 2020. Our institution became a first line hospital for COVID-19 patients since March 2020. We identified non-deferrable patients that needed to be treated within one month. All patients included have followed a dedicated pathway from the day-hospital till the discharge. Clinical data, as nasopharyngeal swabs, chest X-ray, type of anesthesia, type of surgical procedure and days of hospitalization were collected. Moreover, individual risk factors for COVID-19 pneumonia, as advanced age, ongoing malignancy, high blood pressure and coronary artery disease, were analyzed. All patients were interviewed after a minimum post discharge time of 14 days to find out if any of them had developed general and Covid-related complications. Results: The study population included 66 (76.75%) men and 20 (23.25%) women, aged between 17 and 90 years old. We have performed eighty-eight (88) preoperative screenings and two (2) patients were excluded, due to exclusion criteria. Overall, 63 (71.60%) patients underwent oncological procedures while only 23 (28.40%) patients underwent non-oncological surgery. The average number of hospitalization days was 2.39 ± 2.21. After at least 14 days after discharge (25.00 ± 10.35 days), we phone interviewed all patients to check their conditions. No patients included in the study showed symptoms related to COVID-19, except for 2 (2.32%) who manifested coryza, 28 and 35 days after discharge respectively. We also analyzed clinical characteristics of the study participants in relation to develop SARS CoV-2. None of patient developed Covid-19 postoperatively and in addition, none of hospital workers that were part of this pathway got the Covid-19 infection. Conclusions: The duration of pandemic period is undefined;therefore, our protocol could be considered a good model for every type of surgery and its application could ensure a continuous treatment for non-deferrable conditions, even during healthcare emergencies in a safe way for both the patients and health workers.