Epidemiologic Modeling of HIV/AIDS: Use of Computational Models to Study the Population Dynamics of the Disease to Assess Effective Intervention Strategies for Decision-making.

Computational models and simulations are becoming central research tools in epidemiology, biology, and other fields. Epidemiologic research involves the study of a complex set of host, environment and causative agent factors as these interact to impact health and diseases in any population. The most advanced of these efforts have focused on micro (cellular) or macro (human) population levels. The dynamic interplay of HIV with a focus in its hosts at the cellular level provides the micro-epidemiologic basis, while the dynamic interplay of multifactorial determinants: biomedical, behavioral, and socioeconomic factors provide the macro-epidemiologic basis at the human population level. We have developed the computational tools and mathematical approaches to study the population-level effects of various drugs on HIV to integrate models from micro to macro- levels in a seamless fashion. The critical variables that facilitate transmission of HIV and intracellular interactions and molecular kinetics were considered. Such multilevel models are essential if we are to develop quantitative, predictive models of complex biological systems such as HIV/AIDS.

A Conceptual Multivariate Modelling Approach for Integrating Epidemiologic and Psychosocial Determinants to Examine the Epidemiology of Diseases in Under-served Populations.

Epidemiologic research involves the study of a complex set of host, environment and causative agent factors as these interact to impact health and diseases in any population. A conceptual multivariate modelling approach for integrating epidemiologic and psychosocial determinants to examine the epidemiology of chronic and infectious diseases in under-served populations in the USA was developed. Our approach relies upon systems analysis, i.e. integrating concepts and methods in epidemiology with mathematics and statistics along with computational methods and tools to rigorously examine the dynamics of diseases such as the Human Immunodeficiency Virus/Acquired Immunodeficiency Syndrome (HIV/AIDS) in a community. We used a multifactorial and quantitative epidemiologic (static) model that interrelates multiple determinants including biomedical, behavioral, and socioeconomic factors to analyze morbidity and mortality due to HIV/AIDS. The research involved participation of the community in the collection of socioeconomic, demographic, environmental, epidemiologic and biomedical data. In collaboration with Montgomery AIDS Outreach (MAO), a community based Organization in Montgomery, Alabama; blood samples were collected and tested using Orasure HIV testing kits to establish infection status with HIV/AIDS. Using these models, evaluations of various intervention scenarios with the objective of recommending effective strategies to minimize the risk of new HIV infections and/or manage existing diseases in a community can be generated.

Investigation of Salmonella infection in goats fed corn silage grown on land fertilized with sewage sludge.

A total of 36 goats were fed for 17 months with corn silage grown on land fertilized with human sewage sludge. These animals were investigated for salmonella infections. Salmonellae were not detected in cultures of fecal or silage samples. No significant agglutination titers were detected in goat sera examined. Salmonella newport C2 was isolated from the sludge used as fertilizer on the cornfields. The public health aspects of the findings are discussed as they relate to the increasing use of sewage sludge for agricultural fertilizers, as well as to the resultant effects on human food and livestock feed.