A Method for Reducing the Severity of Epidemics by Allocating Vaccines According to Centrality

One long-standing question in epidemiological research is how best to allocate limited amounts of vaccine or similar preventative measures in order to minimize the severity of an epidemic. Much of the literature on the problem of vaccine allocation has focused on influenza epidemics and used mathematical models of epidemic spread to determine the effectiveness of proposed methods. Our work applies computational models of epidemics to the problem of geographically allocating a limited number of vaccines within several Texas counties. We developed a graph-based, stochastic model for epidemics that is based on the SEIR model, and tested vaccine allocation methods based on multiple centrality measures. This approach provides an alternative method for addressing the vaccine allocation problem, which can be combined with more conventional approaches to yield more effective epidemic suppression strategies. We found that allocation methods based on in-degree and inverse betweenness centralities tended to be the most effective at containing epidemics.Comment: 10 pages, accepted to ACM BCB 201

First Steps: A Pilot Preparedness Program for Public Health Nurses

Public health will face major challenges in the coming decades. The 1999 West Nile outbreak in New York City and other recent incidents demonstrate how important public health is as a frontline defense against emerging infections, bioterrorism, and other unexpected emergencies. A well-prepared public health workforce is more critical than ever. The challenges are particularly great in urban areas, which traditionally serve as ports of entry, may be appealing targets to terrorists, and have large and diverse populations with complex health risk factors. To better prepare the public health workforce to carry out routine functions effectively and fulfill the additional roles required in emergencies, a national network of "Centers for Public Health Preparedness" has been established by the Centers for Disease Control and Prevention (CDC). The network currently includes seven academic Centers funded through a cooperative agreement with the Association of Schools of Public Health (ASPH). Goals include the development of competency-based public health practice courses primarily designed to utilize distance-learning technology (such as World Wide Web-based instruction) that can be implemented locally and replicated nationally. The Center for Public Health Preparedness at the Mailman School of Public Health, Columbia University, is working toward these goals in partnership with the New York City Department of Health (NYC DOH)

First Steps: A Pilot Preparedness Program for Public Health Nurses

Public health will face major challenges in the coming decades. The 1999 West Nile outbreak in New York City and other recent incidents demonstrate how important public health is as a frontline defense against emerging infections, bioterrorism, and other unexpected emergencies. A well-prepared public health workforce is more critical than ever. The challenges are particularly great in urban areas, which traditionally serve as ports of entry, may be appealing targets to terrorists, and have large and diverse populations with complex health risk factors. To better prepare the public health workforce to carry out routine functions effectively and fulfill the additional roles required in emergencies, a national network of "Centers for Public Health Preparedness" has been established by the Centers for Disease Control and Prevention (CDC). The network currently includes seven academic Centers funded through a cooperative agreement with the Association of Schools of Public Health (ASPH). Goals include the development of competency-based public health practice courses primarily designed to utilize distance-learning technology (such as World Wide Web-based instruction) that can be implemented locally and replicated nationally. The Center for Public Health Preparedness at the Mailman School of Public Health, Columbia University, is working toward these goals in partnership with the New York City Department of Health (NYC DOH)

Thin film dielectric microstrip kinetic inductance detectors

Microwave Kinetic Inductance Detectors, or MKIDs, are a type of low temperature detector that exhibit intrinsic frequency domain multiplexing at microwave frequencies. We present the first theory and measurements on a MKID based on a microstrip transmission line resonator. A complete characterization of the dielectric loss and noise properties of these resonators is performed, and agrees well with the derived theory. A competitive noise equivalent power of 5$\times10^{-17}$ W Hz$^{-1/2}$ at 1 Hz has been demonstrated. The resonators exhibit the highest quality factors known in a microstrip resonator with a deposited thin film dielectric.Comment: 10 pages, 4 figures, APL accepte