Quantifying potentially infectious sharing patterns among people who inject drugs in Baltimore, USA.

Mixing matrices quantify how people with similar or different characteristics make contact with each other, creating potential for disease transmission. Little empirical data on mixing patterns among persons who inject drugs (PWID) are available to inform models of blood-borne disease such as HIV and hepatitis C virus. Egocentric drug network data provided by PWID in Baltimore, Maryland between 2005 and 2007 were used to characterise drug equipment-sharing patterns according to age, race and gender. Black PWID and PWID who were single (i.e. no stable sexual partner) self-reported larger equipment-sharing networks than their white and non-single counterparts. We also found evidence of assortative mixing according to age, gender and race, though to a slightly lesser degree in the case of gender. Highly assortative mixing according to race and gender highlights the existence of demographically isolated clusters, for whom generalised treatment interventions may have limited benefits unless targeted directly. These findings provide novel insights into mixing patterns of PWID for which little empirical data are available. The age-specific assortativity we observed is also significant in light of its role as a key driver of transmission for other pathogens such as influenza and tuberculosis.