More than 2 billion people live on less than 2 US dollars per day. People in these conditions often have inadequate access to basic sanitation, safe water, and medical services. These individuals, households and communities may be at high risk for a wide range of preventable and treatable infectious diseases. The aims of this study were to: 1) describe the prevalence of endemic helminth, protozoal, bacterial and viral infections of people in a small-holder farming community in western Kenya; 2) explore the spatial distribution of infection risk; 3) quantify associations between social and environmental conditions and individual- and household-level infection; 4) identify shared risk factors operating on multiple pathogens. All data were collected between July 2010 and July 2012 as part of a cross-sectional survey of 416 households and 2113 people. This sample was considered representative of a population of 1.4 million people living in an area of western Kenya characterised by high levels of poverty. Sampled individuals were tested for exposure to, or infection with, 21 infectious agents using a range of faecal, blood and serological tests. Extensive questionnaire-based data were also collected. Individual- and household-level risk factors for infection with prevalent pathogens were explored using multilevel logistic regression, with a particular focus on examining the impact of socioeconomic position (SEP). Hierarchical zero-inflated binomial (ZIB) regression was used to derive an estimate of household pathogen ‘species richness’ with correction for imperfect detection. This modelling framework allowed assessment of the relationship between household-level infection with each parasite and a range of social and environmental conditions and, uniquely for a single study setting, the average response of the ‘group’ of parasites to these conditions. This study found very high levels of parasitism in the community, particularly with hookworm (36.3% (95% CI 32.8 – 39.9)), Entamoeba histolytica/dispar (30.1% (27.5 – 32.8)), Plasmodium falciparum (29.4% (26.8 – 32.0)), and Taenia spp. (19.7% (16.7 – 22.7)). Some degree of within-household clustering was found for all pathogens, and this was particularly large for the helminth species and HIV. Most pathogens also showed spatial heterogeneity in infection risk, with evidence of spatial clustering in household-level infection, most notably for HIV, Schistosoma mansoni, P. falciparum and the soiltransmitted helminths. A socioeconomic gradient was identified, even in this predominantly poor community. Increasing socioeconomic position (SEP) resulted in significantly reduced risk of individual infection for E. histolytica/dispar, P. falciparum, and hookworm. By contrast, individuals living in the richest households were at significantly elevated risk of infection with Mycobacterium spp. Individuals living in the poorest households were least likely to report the recent use of medical treatments. The average pathogen species richness (out of 21 species) per household was 4.7 (range: 0 to 13). Following correction for detection error, the predicted average helminth species count (out of 6 species) was 3 (range: 0.94 to 5.96). While socioeconomic position had little effect on the probability that a household was infected with any of the helminth species of interest, domestic (within-household) transmission appeared to be greatest in the poorest households for hookworm, S. mansoni, Ascaris lumbricoides and Strongyloides stercoralis. Household size had a consistent effect on probably of household infection with each helminth species, so that the largest households were also the most pathogen diverse. Household-level helminth species richness was identified as a significant positive predictor of individual risk of HIV infection, raising potentially important questions about helminth-HIV interactions in the study area. This study integrates approaches from epidemiology and ecology to explore infectious disease risk and its determinants at a range of social and geographic scales in a small-holder farming community in western Kenya. Considering risk at both the individual and household level within the same community can contribute to better understanding of the factors that influence disease transmission in both domestic and public domains.