No lab is an island: universal coding of laboratory test names.

The local laboratory with a local client-base, that never needs to exchange information with any outside entity, is a dying breed. As marketing channels, animal movement, and reporting requirements become increasingly national and international, the need to communicate about laboratory tests and results grows. Local and proprietary names of laboratory tests often fail to communicate enough detail to distinguish between similar tests.

Challenges and Opportunities Developing Mathematical Models of Shared Pathogens of Domestic and Wild Animals.

Diseases that affect both wild and domestic animals can be particularly difficult to prevent, predict, mitigate, and control. Such multi-host diseases can have devastating economic impacts on domestic animal producers and can present significant challenges to wildlife populations, particularly for populations of conservation concern. Few mathematical models exist that capture the complexities of these multi-host pathogens, yet the development of such models would allow us to estimate and compare the potential effectiveness of management actions for mitigating or suppressing disease in wildlife and/or livestock host populations.

An approach for de-identification of point locations of livestock premises for further use in disease spread modeling.

We describe a method for de-identifying point location data used for disease spread modeling to allow data custodians to share data with modeling experts without disclosing individual farm identities. The approach is implemented in an open-source software program that is described and evaluated here. The program allows a data custodian to select a level of de-identification based on the K-anonymity statistic.

An epidemiologic simulation model of the spread and control of highly pathogenic avian influenza (H5N1) among commercial and backyard poultry flocks in South Carolina, United States.

Epidemiologic simulation modeling of highly pathogenic avian influenza (HPAI) outbreaks provides a useful conceptual framework with which to estimate the consequences of HPAI outbreaks and to evaluate disease control strategies. The purposes of this study were to establish detailed and informed input parameters for an epidemiologic simulation model of the H5N1 strain of HPAI among commercial and backyard poultry in the state of South Carolina in the United States using a highly realistic representation of this poultry population; to estimate the consequences of an outbreak of HPAI in this population with a model constructed from these parameters; and to briefly evaluate the sensitivity of model outcomes to several parameters. Parameters describing disease state durations; disease transmission via direct contact, indirect contact, and local-area spread; and disease detection, surveillance, and control were established through consultation with subject matter experts, a review of the current literature, and the use of several computational tools.

The etiology of social change.

A fundamental aspect of human beings is that they learn. The process of learning and what is learned are impacted by a number of factors, both cognitive and social; that is, humans are boundedly rational. Cognitive and social limitations interact, making it difficult to reason about how to provide information to impact what humans know, believe, and do.

Sending data to a central repository.

The Veterinary Medical DataBases (VMDB) has been collecting data from participating institutions for 40 years. We have recently started a program to collect clinical case data from not only veterinary schools but from veterinary practitioners as well. In so doing, we are using commonly accepted means of data representation and transmission.

Connecticut RxData project.

The Connecticut Hospital Association has developed a data resource for inpatient pharmacy information. The RxData project collects drug dispensing information from member hospitals and joins it to administrative discharge data in the Chime database. The resulting dataset is useful for descriptive epidemiology of drug use patterns as well as surveillance, quality improvement, and some hypothesis testing.