Study objective-Administrative databases from the City of Philadelphia that track public shelter utilisation (n=44 337) and AIDS case reporting (n=7749) were merged to identify rates and risk factors for co-occurring homelessness and AIDS. Design-Multiple decrement life tables analyses were conducted, and logistic regression analyses used to identify risk factors associated with AIDS among the homeless, and homelessness among people with AIDS. Setting-City of Philadelphia, Pennsylvania, USA. Main results-People admitted to public shelters had a three year rate of subsequent AIDS diagnosis of 1.8 per 100 person years; nine times the rate for the general population of Philadelphia. Logistic regression results show that substance abuse history (OR = 3.14), male gender (OR = 2.05), and a history of serious mental disorder (OR = 1.62) were significantly related to the risk for AIDS diagnosis among shelter users. Among people with AIDS, results show a three year rate of subsequent shelter admission of 6.9 per 100 person years, and a three year rate of prior shelter admission of 9%, three times the three year rate of shelter admission for the general population. Logistic regression results show that intravenous drug user history (OR = 3.14); no private insurance (OR = 2.93); black race (OR = 2.82); pulmonary or extrapulmonary TB (OR = 1.43); and pneumocystis pneumonia (OR = 0.56) were all related to the risk for shelter admission. Conclusions-Homelessness prevention programmes should target people with HIV risk factors, and HIV prevention programmes should be targeted to homeless persons, as these populations have significant intersection. Reasons and implications for this intersection are discussed. (J Epidemiol Community Health 2001;55:515-520)

The aim of the study was to assess the median time between HIV diagnosis and entry into primary HIV medical care in a large urban area and to assess the potential individual, diagnosing facility, and community level factors influencing entry into care. One thousand two hundred and sixty-six individuals diagnosed with HIV in Philadelphia between 1 July 2005 and 30 June 2006 were followed until entry into care through 15 June 2007. Time to entry into care was calculated as a survival time variable and was defined as the time in months between the date of HIV diagnosis and the date more than 3 weeks after diagnosis when a CD4 cell count or percentage and/or HIV viral load were obtained. The median time to entry into care for all individuals was 8 months, with a range of 1-26 months. Factors associated with delayed entry into care included age more than 40 years [hazard ratio (HR) = 0.85; 95% confidence interval (CI) = 0.75-0.97] and diagnosis as an inpatient in the hospital (HR = 0.37; 95% CI = 0.37-0.57). Factors associated with earlier entry into care included Hispanic ethnicity (HR = 1.39; 95% CI = 1.05-1.84), male sex with men as HIV transmission risk factor (HR = 1.27; 95% CI = 1.03-1.56), and residence in a census tract with a high poverty rate (HR = 1.68; 95% CI = 1.22-2.30). Individuals newly diagnosed with HIV in Philadelphia demonstrated marked delays in accessing care highlighting the tremendous need for interventions to improve overall linkage. These interventions should especially be targeted at those aged more than 40 years and those diagnosed in the hospital.

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Travel distance to medical care has been assessed using a variety of geographic methods. Network analyses are less common, but may generate more accurate estimates of travel costs. We compared straight-line distances and driving distance, as well as average drive time and travel time on a public transit network for 1789 persons diagnosed with HIV between 2010 and 2012 to identify differences overall, and by distinct geographic areas of Philadelphia. Paired t-tests were used to assess differences across methods, and analysis of variance was used to assess between-group differences. Driving distances were significantly longer than straight-line distances (p<0.001) and transit times were significantly longer than driving times (p<0.001). Persons living in the northeast section of the city traveled greater distances, and at greater cost of time and effort, than persons in all other areas of the city (p<0.001). Persons living in the northwest section of the city traveled farther and longer than all other areas except the northeast (p<0.0001). Network analyses that include public transit will likely produce a more realistic estimate of the travel costs, and may improve models to predict medical care outcomes.

Purpose Investigate whether characteristics of geographic areas are associated with condomless sex and injection-related risk behavior among racial/ethnic groups of people who inject drugs (PWID) in the United States. Methods PWID were recruited from 19 metropolitan statistical areas (MSAs) for 2009 National HIV Behavioral Surveillance. Administrative data described ZIP codes, counties, and MSAs where PWID lived. Multilevel models, stratified by racial/ethnic group, were used to assess relationships of place-based characteristics to condomless sex and injection-related risk behavior (sharing injection equipment). Results Among black PWID, living in the South (vs. Northeast) was associated with injection-related risk behavior [Adjusted Odds Ratio (AOR)=2.24, 95% Confidence Interval (CI)=1.37,4.34;p-value=0.011] and living in counties with higher percentages of unaffordable rental housing was associated with condomless sex [AOR=1.02, 95% CI=1.00,1.04; p-value=0.046]. Among white PWID, living in ZIP codes with greater access to drug treatment was negatively associated with condomless sex [AOR=0.93, 95% CI=0.88,1.00;p-value=0.038). Discussion Policies that increase access to affordable housing and drug treatment may make environments more conducive to safe sexual behaviors among black and white PWID. Future research designed to longitudinally explore the association between residence in the south and injection-related risk behavior might identify specific place-based features that sustain patterns of injection-related risk behavior.