HIV/AIDS STATISTICS S.E MICHIAGAN (ABR) #Southeast Michigan includes Lapeer, Macomb, Monroe, Oakland, St. Clair, and Wayne Counties COMPLETE AND DETAILED INFORMATION CAN BE FOUND

Prevalence Estimate Calculations  HIV prevalence estimates include all persons living in SOUTHEAST MICHIGAN at HIV diagnosis (any stage) who:  were diagnosed by January 1, 2014, and incorporates an approximation of those not yet diagnosed. All estimates  are rounded to the nearest ten, and the minimum estimate given is 10. Prevalence estimates were most recently revised by MDHHS in July 2014.

RACE/ ETHNICITY TABLE 1. Demographic Information on Prevalent HIV Infection Cases Living in SOUTHEAST MICHIGAN at Diagnosis [MDHHS] REPORTED PREVALENCE EST PREV* HIV Infection Non-Stage 3 Num Percent HIV Infection Stage 3 (AIDS) Total Rates per 100,000 CENSUS 2014 ESTIMATES White 3,1701,32827%1,38425%2,71226%95 2,850,398 67% Black 8,2903,36767%3,72468%7,09168% ,956 23% Hispanic %1873%3593% ,872 4% Asian/PI 70301%27<1%571%34 166,786 4% Am Indian/AN 2012<1%4**16<1%12512,768<1% Multi/Other/Un k %1523%2412%N/A85,0592%

SEX TABLE 1. Demographic Information on Prevalent HIV Infection Cases Living in SOUTHEAST MICHIGAN at Diagnosis [MDHHS] REPORTED PREVALENCE EST PREV* HIV Infection Non-Stage 3 Num Percent HIV Infection Stage 3 (AIDS) Total Rates per 100,000 CENSUS 2014 ESTIMATES Male9,4803,87978%4,23477%8,11377%393 2,066,604 49% Female2,7601,119 22%1,24423%2,36323%108 2,194,235 51%

Risk* TABLE 1. Demographic Information on Prevalent HIV Infection Cases Living in SOUTHEAST MICHIGAN at Diagnosis [MDHHS] REPORTED PREVALENCE Male-Male sex 1,86369%3,40048%19253%16352%5,61854% Injection Drug Use 140 5%6219%329%248%8178% MSM/IDU1174%1823%3 ** 175%3193% Blood Products 301%7<1%2**140<1% Heterosexual Contact (HC) 27010%1,52822%6919%4615%1,91318% Perinatal 10<1%951%5 93%1191% Undetermined 28210%1,25818%5616%5417%1,65016% *See front matter page i for descriptions of prevalence estimate calculations and risk category groupings. Risk categories used in Michigan are redefined as of January NOTE: Heterosexual contact for males includes only males whose sexual partners are known to be HIV infected or at high risk for HIV (HCFR). Heterosexual contact for females includes all females who have had sex with a male regardless of what is known about the male’s HIV status or behaviors (HCM). (this can be found via the first link on the title slide) WhiteBlackHispanicOtherRisk all

Diagnosis By County State of Michigan

HIV/AIDS TRENDS  The number and rate of new HIV diagnoses in Michigan remained stable between 2009 and 2013 for the 5th  consecutive trend report, with an average of 801 new cases per year and an average rate of 8.1.  The highest rates of new HIV diagnoses occurred among:  and year olds  Black males and females  Men who have sex with men (MSM)*  SE MI residents  INCREASES in rates occurred among:  White females  DECREASES in rates occurred among:  Black females SOUTH EAST MICHIGAN

HIV/AIDS TRENDS  Almost three quarters of Michigan’s new cases among year olds were residents of SE MI at diagnosis. Of these SE MI young adults, 61% lived in the City of Detroit.  82% of new year old cases are black (of whom 74% are MSM), whereas 59% of those aged 20 and older are black  This finding suggests that black teens and young adults in general, and young black MSM in particular, should continue to be the focus of aggressive prevention activities.  Race and sex disparities in rates of new HIV diagnoses remain. Comparing the diagnosis rates of black persons and white persons in 2013:  Overall: The rate for black persons was over 13 times higher  Males: The rate for black males was over 13 times higher  Females: The rate for black females was over 14 times higher Increases in concurrent diagnoses occurred overall as well as among males overall, black males, and blacks overall. This is the first report to ever show increases in concurrent diagnoses in any race/sex group suggesting a need for increased efforts toward improving early case detection. SOUTH EAST MICHIGAN