An evaluation of the impact of social and structural determinants of health on forgone care during the COVID-19 pandemic in Baltimore, Maryland.

Evidence suggests that reductions in healthcare utilization, including forgone care, during the COVID-19 pandemic may be contributing towards excess morbidity and mortality. The objective of this study was to describe individual and community-level correlates of forgone care during the COVID-19 pandemic. We conducted a cross-sectional, secondary data analysis of participants (n = 2,003) who reported needing healthcare in two population-representative surveys conducted in Baltimore, MD in 2021 and 2021-2022. Abstracted data included the experience of forgone care, socio-demographic data, comorbidities, financial strain, and community of residence. Participant's community of residence were linked with data acquired from the Baltimore Neighborhood Indicators Alliance relevant to healthcare access and utilization, including walkability and internet access, among others. The data were analyzed using weighted random effects logistic regression. Individual-level factors found to be associated with increased odds for forgone care included individuals age 35-49 (compared to 18-34), female sex, experiencing housing insecurity during the pandemic, and the presence of functional limitations and mental illness. Black/African American individuals were found to have reduced odds of forgone care, compared to any other race. No community-level factors were significant in the multilevel analyses. Moving forward, it will be critical that health systems identify ways to address any barriers to care that populations might be experiencing, such as the use of mobile health services or telemedicine platforms. Additionally, public health emergency preparedness planning efforts must account for the unique needs of communities during future crises, to ensure that their health needs can continue to be met. Finally, additional research is needed to better understand how healthcare access and utilization practices have changed during versus before the pandemic.

The biosecurity benefits of genetic engineering attribution.

Biology can be misused, and the risk of this causing widespread harm increases in step with the rapid march of technological progress. A key security challenge involves attribution: determining, in the wake of a human-caused biological event, who was responsible. Recent scientific developments have demonstrated a capability for detecting whether an organism involved in such an event has been genetically modified and, if modified, to infer from its genetic sequence its likely lab of origin. We believe this technique could be developed into powerful forensic tools to aid the attribution of outbreaks caused by genetically engineered pathogens, and thus protect against the potential misuse of synthetic biology.

Proposed Changes to U.S. Policy on Potential Pandemic Pathogen Oversight and Implementation.

We propose here changes to the U.S. government policy on potential pandemic pathogen (PPP) oversight and implementation, emphasizing transparency of the review process and the content of the review, publication of the review in advance, responsible publication of enhanced PPP research, high-level signoff on approvals of enhanced PPP experiments, and the need for a significant effort to establish a common international approach to enhanced PPP work. We advocate that the U.S. government recommend, and non-U.S. government funders and journals adopt, a set of best practices that would extend important considerations of biosafety and biosecurity to all work on enhanced potential pandemic pathogens regardless of funding source.

Characteristics of Microbes Most Likely to Cause Pandemics and Global Catastrophes.

Predicting which pathogen will confer the highest global catastrophic biological risk (GCBR) of a pandemic is a difficult task. Many approaches are retrospective and premised on prior pandemics; however, such an approach may fail to appreciate novel threats that do not have exact historical precedent. In this paper, based on a study and project we undertook, a new paradigm for pandemic preparedness is presented. This paradigm seeks to root pandemic risk in actual attributes possessed by specific classes of microbial organisms and leads to specific recommendations to augment preparedness activities.

COPEWELL: A Conceptual Framework and System Dynamics Model for Predicting Community Functioning and Resilience After Disasters.

OBJECTIVE: Policy-makers and practitioners have a need to assess community resilience in disasters. Prior efforts conflated resilience with community functioning, combined resistance and recovery (the components of resilience), and relied on a static model for what is inherently a dynamic process. We sought to develop linked conceptual and computational models of community functioning and resilience after a disaster. METHODS: We developed a system dynamics computational model that predicts community functioning after a disaster. The computational model outputted the time course of community functioning before, during, and after a disaster, which was used to calculate resistance, recovery, and resilience for all US counties. RESULTS: The conceptual model explicitly separated resilience from community functioning and identified all key components for each, which were translated into a system dynamics computational model with connections and feedbacks. The components were represented by publicly available measures at the county level. Baseline community functioning, resistance, recovery, and resilience evidenced a range of values and geographic clustering, consistent with hypotheses based on the disaster literature. CONCLUSIONS: The work is transparent, motivates ongoing refinements, and identifies areas for improved measurements. After validation, such a model can be used to identify effective investments to enhance community resilience. (Disaster Med Public Health Preparedness. 2018;12:127-137).

Challenges and Opportunities of Nontraditional Approaches to Treating Bacterial Infections.

Due to increasing rates of antimicrobial-resistant infections and the current inadequacy of the antibiotic pipeline, there is increasing interest in nontraditional approaches to antibacterial therapies. We define "traditional" agents as small-molecule agents that directly target bacterial components to exert a bacteriostatic or bactericidal effect, and "nontraditional approaches" as antimicrobial therapeutics that work through other means (ie, not a small molecule and/or utilizes a nontraditional target). Due to their atypical features, such therapies may be less susceptible to the emergence of resistance than traditional antibiotics. They include approaches such as monoclonal antibodies, virulence disruptors, immunomodulators, phage therapies, microbiome-based therapies, antibiotic potentiators, and antisense approaches. This article discusses both the developmental and regulatory advantages and challenges associated with each of these technologies. By identifying existing regulatory and developmental gaps, we hope to provide a sense of where focusing resources may provide the greatest impact on successful product development.

Clinical management of potential bioterrorism-related conditions.

The agents most likely to be used in bioterrorism attacks are reviewed, along with the clinical syndromes they produce and their treatment.