Coordinating uncertainty in the political economy of cyber threat intelligence.

Cyber threat intelligence firms play a powerful role in producing knowledge, uncertainty, and ignorance about threats to organizations and governments globally. Drawing on historical and ethnographic methods, we show how cyber threat intelligence analysts navigate distinctive types of uncertainty as they transform digital traces into marketable products and services. We make two related contributions and arguments.

A framework for monitoring RSV prevention product effectiveness in the United States.

During 2023, the Centers for Disease Control and Prevention (CDC) recommended the first respiratory syncytial virus (RSV) immunizations intended for widespread use in the United States to prevent severe RSV illness in infants and older adults. CDC, in collaboration with federal, public health, and academic partners, is conducting evaluations of real-world effectiveness of recommended RSV immunization products in the United States. Similar frameworks for evaluation are being applied to RSV vaccines and nirsevimab, a long-acting preventative monoclonal antibody, to estimate product effectiveness.

Expanding the use of mathematical modeling in healthcare epidemiology and infection prevention and control.

During the coronavirus disease 2019 pandemic, mathematical modeling has been widely used to understand epidemiological burden, trends, and transmission dynamics, to facilitate policy decisions, and, to a lesser extent, to evaluate infection prevention and control (IPC) measures. This review highlights the added value of using conventional epidemiology and modeling approaches to address the complexity of healthcare-associated infections (HAI) and antimicrobial resistance. It demonstrates how epidemiological surveillance data and modeling can be used to infer transmission dynamics in healthcare settings and to forecast healthcare impact, how modeling can be used to improve the validity of interpretation of epidemiological surveillance data, how modeling can be used to estimate the impact of IPC interventions, and how modeling can be used to guide IPC and antimicrobial treatment and stewardship decision-making.

Infectious disease surveillance needs for the United States: lessons from Covid-19.

The COVID-19 pandemic has highlighted the need to upgrade systems for infectious disease surveillance and forecasting and modeling of the spread of infection, both of which inform evidence-based public health guidance and policies. Here, we discuss requirements for an effective surveillance system to support decision making during a pandemic, drawing on the lessons of COVID-19 in the U.S.

Challenges of COVID-19 Case Forecasting in the US, 2020-2021.

During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and government entities led by the Centers for Disease Control and Prevention and the US COVID-19 Forecast Hub (https://covid19forecasthub.org).