Using the Newcomb-Benford law to study the association between a country's COVID-19 reporting accuracy and its development.

The COVID-19 pandemic has spurred controversies related to whether countries manipulate reported data for political gains. We study the association between accuracy of reported COVID-19 data and developmental indicators. We use the Newcomb-Benford law (NBL) to gauge data accuracy. We run an OLS regression of an index constructed from developmental indicators (democracy level, gross domestic product per capita, healthcare expenditures, and universal healthcare coverage) on goodness-of-fit measures to the NBL. We find that countries with higher values of the developmental index are less likely to deviate from the Newcomb-Benford law. The relationship holds for the cumulative number of reported deaths and total cases but is more pronounced for the death toll. The findings are robust for second-digit tests and for a sub-sample of countries with regional data. The NBL provides a first screening for potential data manipulation during pandemics. Our study indicates that data from autocratic regimes and less developed countries should be treated with more caution. The paper further highlights the importance of independent surveillance data verification projects.

Discovering New Trends & Connections: Current Applications of Biomedical Text Mining.

The explosive growth of digital information in recent years has amplified the information overload experienced by today's health-care professionals. In particular, the wide variety of unstructured text makes it difficult for researchers to find meaningful data without spending a considerable amount of time reading. Text mining can be used to facilitate better discoverability and analysis, and aid researchers in identifying critical trends and connections. This column will introduce key text-mining terms, recent use cases of biomedical text mining, and current applications for this technology in medical libraries.

Adapting to a Pandemic - Conducting Oncology Trials during the SARS-CoV-2 Pandemic.

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic has necessitated changes in cancer care delivery as resources are reallocated. Clinical trials and other research activities are inevitably impacted. Start-up activities for new trials may be deferred and recruitment suspended. For patients already enrolled however, there are challenges in continuing treatment on trial. Regulatory bodies have issued guidance on managing clinical trials during the pandemic, including contingency measures for remote study visits, delivery of investigational product, and site monitoring visits. New cancer clinical trial practices during the SARS-CoV-2 pandemic include new risk assessment strategies, decentralized and remote trial coordination, data collection, and delegation of specific therapeutic activities. This experience could provide evidence of more feasible and cost-effective methods for future clinical trial conduct.