Steven A. Cohen, MPH¹, Jyotsna S. Jagai, MS¹, Karrie-Ann Toews, MPH¹, Bela T. Matyas, MD, MPH², Alfred DeMaria, Jr, MD³, Jeffrey Griffiths, MD, MPH, TM⁴, and Elena N. Naumova, PhD⁵. (1) School of Medicine, Tufts University, 136 Harrison Ave, Boston, MA 02111, 617-636-3852, jyotsna.jagai@tufts.edu, (2) Immunization Program, Massachusetts Department of Public Health, 305 South Street, Boston, MA 02130, (3) Bureau of Communicable Disease Control, Massachusetts Department of Public Health, 305 South Street, Jamaica Plain, MA 02130, (4) Family Medicine and Community Health, Tufts University School of Medicine, 136 Harrison Avenue, Boston, MA 02111, (5) School of Medicine, Department of Family Medicine and Community Health, Tufts University, 136 Harrison Avenue, Boston, MA 02111

It is known that socioeconomic, environmental, and demographic (SED) conditions may affect the incidence of enteric infections (EI) caused by Cryptosporidium, Salmonella, Shigella, hepatitis A virus, Giardia, and Camplylobacter. We assessed these relationships using over 50,000 cases reported to the state surveillance system. A set of 24 community-based proxies for SED conditions were derived based on the 2000 Census for Population and Housing database. We analyzed these relationships at three levels of spatial aggregation: town/city, zip-code, and county using regression modeling. A set of SED indicators, which were significantly associated, was selected for each EI. Our preliminary analysis showed that eight SED indicators were consistently significant at all three levels of spatial aggregation for giardiasis: median per capita income, median value of houses, percentage of residents age 25 and older with at least 4 years of college education, population density, an estimate of the average number of people per room in a given area, percentage of households in an area with a private water supply, percentage of households with a septic tank as the primary means of sewerage, and the median age of houses in an area. All these SED indicators were also significant for cryptosporidiosis contributing from 2% to 35% percent change in the EI incidence. Complete analysis was carried out for all EI. We offer explanations for the findings and outline directions for future studies. We also discuss potential differential underreporting in the surveillance data and suggest approaches to improve reporting.

Learning Objectives:

• Identify disparities in reporting patterns in various communities in Massachusetts for six enteric infections and discuss differential underreporting and improvements for surveillance data.

Presenting author's disclosure statement:
I do not have any significant financial interest/arrangement or affiliation with any organization/institution whose products or services are being discussed in this session.