Using EPP 2007 in Concentrated Epidemics The basics of making a run - - PowerPoint PPT Presentation

Using EPP 2007 in Concentrated Epidemics

UNAIDS/WHO Working Group

• n Global HIV/AIDS & STI Surveillance

The basics of making a run The basics of making a run

Building a concentrated national epidemic in EPP 2007

A brief introduction and overview

Steps in constructing a national epidemic Steps in constructing a national epidemic

Choose your country and name this attempt at national

projections (the workset in EPP)

Decide the key groups in the epidemic and its

geographic breakdown

Define population characteristics

– Demographics

Steps in constructing a national epidemic Steps in constructing a national epidemic

Enter HIV prevalence data and sample sizes for each

sub-population or regional sub-epidemic

Fit the Reference Group model to each of them Adjust your prevalence up or down to match any large

scale survey data that may be available

Display and review the results of your work

EPP 2007 EPP 2007 – – steps you through the process steps you through the process

Each step on a different Each step on a different “ “page page” ” or

• r “

“tab tab” ” – – starts w/ starts w/ Worksets Worksets

The The Worksets Worksets page page

What is a workset?

– A national epidemic composed of smaller epidemics in different sub-populations and/or geographic areas

What can I do on this page?

– Load an existing workset – Create a new workset, choose the country, enter notes – Create a new template

Epidemics are generalized or concentrated

– The one you select changes the pages you’ll see

Digression Digression – – creating a new template creating a new template

What is a template?

– A predefined form for a national epidemic

How do I create a template?

– By pushing the create button on the Worksets page

What options exist when I create a template?

– Choose its name and epidemic type – May now associate a country with a template – Each sub-population can have its own characteristics

Creating a new template pop Creating a new template pop-

• up

up

Define Define Epi Epi page page – – Defining your epidemic Defining your epidemic

The Define The Define Epi Epi page page

What are sub-populations and sub-epidemics?

– A sub-population is an epidemic in a specific group of people

• Has a population size and HIV data associated with it

– A sub-epidemic is an epidemic made up from multiple epidemics in sub-populations and/or other sub-epidemics

What can I do on this page?

– Define whatever structure you wish for the epidemic – Select special characteristics for a given sub-population

Can build complex epidemics Can build complex epidemics

Can build complex epidemics Can build complex epidemics

The Define Pops page The Define Pops page

Different pages for Generalized and Concentrated

epidemics, so be sure you create Generalized workset

What can I do on this page?

– Set the overall national population & population base year – Define population sizes – Define demographic parameters – Display populations without an HIV epidemic

The Define Pops page The Define Pops page – – Generalized Generalized

The Define Pops page The Define Pops page -

• Concentrated

Concentrated

The Define Pops Page The Define Pops Page – – Concentrated Concentrated IDUs IDUs

The Enter Data page The Enter Data page

What to enter here – HIV prevalence and sample sizes Why do I need the samples sizes in EPP 2007?

– Uses maximum likelihood and sample sizes serve as weights

The significance of sites – use ‘em if you have ‘em What can I do here?

– Changing the display options – Adding/deleting sites – Cutting and pasting

The Enter Data page The Enter Data page

The Enter Data page The Enter Data page – – % HIV Only % HIV Only

Useful if you want to cut & paste from Excel or old EPP file Useful if you want to cut & paste from Excel or old EPP file

The Project page The Project page

A bewildering set of options

– What to fit to? – How to fit – what to fix and what to leave free

New feature – level fits (if have multiple sites) How do I know if my fit is better than yours?

– LL = log likelihood

The Project page The Project page

The Project page The Project page – – a non a non-

• level fit

level fit

Using the Project page Using the Project page

Click on “Make initial guesses” Examine the outputs of these initial guesses –

– Either accept the best fit it finds by clicking “Use best fit in EPP” or… – Enter the r, f0, t0 and phi values you like on the Projection Page

Using this initial guess, do a fit to further refine it If you hit stop the current values from the fitting

process are loaded

The Calibrate page The Calibrate page

Forms the link between the surveillance data and the

actual national epidemic results

– Allows adjusting prevalence up or down to match large scale survey data or upward/downward biases in the data

Two personalities – generalized and concentrated

The Calibrate page The Calibrate page – – Generalized Generalized

The Calibrate Page The Calibrate Page -

• Concentrated

Concentrated

The Results page The Results page

What can I see here?

– Prevalence (percent and number of infections) & population – Choosing what to display

The hidden gold – the “Output results” button

– Creating a Spectrum file – Saving the details for future examination (*.csv’s)

The Results page The Results page – – Prevalence (%) Prevalence (%)

The Results page The Results page – – Prevalence (#) Prevalence (#)

The Results page The Results page – – Populations Populations

The The Prefs Prefs page page

What are the User Preferences and why do I care? What can I change on this page?

– Language – HIV parameters – Default population parameters – Default sample sizes

What’s the difference in changing pop parameters here

and on the Project page? Here it applies to the workset and ALL sub-populations

The The Prefs Prefs page page

Features relevant to concentrated epidemics with turnover

• ut

in 200 in

EPP 2007 includes turnover in populations EPP 2007 includes turnover in populations

Clients of sex workers (1000 men with 5 yr duration) 200 out Death General pop males

The Define Pops page The Define Pops page -

• Concentrated

Concentrated

The Calibrate page The Calibrate page -

• Concentrated

Concentrated

Why is assign prevalence here? Why is assign prevalence here?

The model in EPP 2007 includes population turnover

– Many HIV+ ex-members of at-risk populations, e.g., HIV+ ex- sex workers or HIV+ ex-IDUs

These HIV+s are sometimes captured in other

surveillance populations

– e.g., ex-sex workers showing up in antenatal clinic data

But other times, they’re missed

– e.g., ex-IDUs may be missed because of limited male surveillance

Fits to Thai Central Region IDU Data Fits to Thai Central Region IDU Data

Changes to the fit Changes to the fit

5 10 15 20 25 30 35 40 45 1 9 8 1 9 8 3 1 9 8 6 1 9 8 9 1 9 9 2 1 9 9 5 1 9 9 8 2 1 2 4 2 7 No turnover Dur 10 yrs Data

Living ex Living ex-

• IDUs

IDUs with 10 year duration with 10 year duration

Thailand Thailand IDUs IDUs

5000 10000 15000 20000 25000 30000 1 9 8 1 9 8 3 1 9 8 6 1 9 8 9 1 9 9 2 1 9 9 5 1 9 9 8 2 1 2 4 2 7 10 yr duration

At peak this is 5.4% of adult male prevalence

How is assignment of HIV+ ex How is assignment of HIV+ ex’ ’s done? s done?

One selects the population from which the HIV+s are

coming

– Only populations with turnover show up here

One selects where they are to go after they leave the

group

– Only populations without turnover (closed pops) here

One decides to add or replace prevalence

What do What do “ “add add” ” and and “ “replace replace” ” prevalence prevalence mean? mean?

Add prevalence

– The HIV+ former at-risk group members are added to the HIV+ members of the target population – This means they have NOT been captured in surveillance there

Replace prevalence

– Some of the HIV+’s in the target population are assumed to come from the former at-risk group members – The remaining infections that occurred “within group” are calculated

Where do you see the effects? Where do you see the effects?

In the graphs on the Results page By pushing the “Reassigns” button on the Results page Example

– Sex workers and general population women in Mumbai

The Results page The Results page – – Concentrated form Concentrated form

The Reassignment table The Reassignment table

The Audit Check page The Audit Check page

Concentrated epidemics only What gets checked?

– The size of at-risk populations: MSM, IDU, FSW, Clients – The ratio of infection in lo-risk and high-risk populations – The AIDS case ratio over time

• Additional user input of data required

The Audit Check page The Audit Check page

Closing remarks and caveats Closing remarks and caveats

In no cases should projections be run beyond 5 years

and even there caution is advised

Fancier interface and model is no substitute for data

– Still GIGO, just prettier garbage – Still a very limited number of countries that can use this for full national projections

Always watch for internal consistency, especially with

concentrated epidemics using turnover

Appendix – level fits

Why levels? Addition of new surveillance sites Why levels? Addition of new surveillance sites can drive the curve downward can drive the curve downward

1% 2% 3% 4% 5% 6% 7% 8% 9% 1984 1989 1994 1999 2004

Year HIV Prevalence

The Project page The Project page – – A fit with levels A fit with levels

Two approaches to address site additions Two approaches to address site additions

Fit all sites independently

– Can enter each site with appropriate proportion of the national population

Assume a single “trajectory” for all

sites, i.e., the shape of the curve is the same

– pit = λi pt – n-1 extra level parameters for n sites – Fit the λi along with the model parameters

0% 5% 10% 15% 20% 25% 30% 35% 1985 1990 1995 2000 2005 2010

Result of using level parameters Result of using level parameters

0% 1% 2% 3% 4% 5% 6% 7% 8% 9% 10% 1984 1989 1994 1999 2004

Year HIV Prevalence

Alternative approach Current approach