UGS 302 Lecture 5: 9/12

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8 Nov 2016
School
Course
Professor
HIV Surveillance- Epidemiologist for State of Texas- TB/HIV/STD
HIV 101- fing t-cell, dock with it, inject it, uncodes, uses hosts DNA w its RNA to create -RNA to
DNA to Rna, normal is opposite, mutates quickly, hard to treat, replicates, buds out, looks for
other cells
2 types- HIV 2- mainly in Africa
HIV 1- 4 subgroips & 9 subtypes
US- Subtype 1B
HIV infection>Lower T Helper Cells>CD$ down T lymphocyte expression>immune system
deterioration>Infections & malignancies development
Quick n dirty test- HIV specific Antibodies
Difficult to know right away, used to have to wait a month or two, window period is down to a
week or two
Also have tests targeting RNA
No symptoms during latency
Difficult to track due to epidemiology
Surveillance-
Event Occurs > Reporting to Public Health Authority > Data > Analysis and Interpretation >
Information > Decision ( Feedback) > Intervention > Real World changes > Effect future Events
Every time one person reports HIV + must report every case
TB, Syphillis, Gonnorea, chlamydia,
Go out and find people that the + person slept with or they can inform them on their own
Find out how the person became exposed
Core (case) surveillance- gathers bsic info, gender, age, race, mode of exposure
Provides info on # of cases& trends
Incidence= # new infections/Specific time
New Diagnosis= # reactive confirmatory diagnostic tests/ specific time period (could be increase
in testing)
Prevalence= # of people who already have infection/ Specified time period (still many people
who have not been tested
In 1998- only AIDS was reported, took 10 years to make the govt get names
People with aids before 1999 did not have to be reported
Epidemiologists-
HIV incidence- number of new infections, not diagnosis, way to estimate
Core HIV surveillance Data + Testing & treatment history form + regency assay on diagnostic
specimen = estimates of new hiv infections in texas
New HIV DIagnosis
In texas, more men and more blacks then hispanic & whites
Black gay men- more likely to report using condoms & less partners than other men
Research on sexual networks- mainly homogenous- small sexual networks, transmitted just a
few times and it spreads within small network. Morbidity drives higher numbers
Social networks- high poverty, lower education, higher crime and prison rates
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