Forecasting trachoma: control, elimination, or eradication?

Thomas M. Lietman

Kathryn J. Ray

Travis C. Porco

FI Proctor Foundation, UCSF

December 2012

Trachoma

• Leading infectious cause of blindness (WHO 2002)

• Causative agent Chlamydia trachomatis• Repeated infection leads to progressive

scarring of the eyelid and mechanical damage to the cornea

• Infection in children leads to blindness later in life.

Trachoma (2)

• Progression from follicular and inflammatory disease

• scarred eyelids

• inturned eyelashes

• secondary bacterial infections lead to corneal opacity

Healthy eyelid

Severe TF/TI

Scarring

Trichiasis, Corneal opacity

How much less trachoma?

• WHO: annual treatment of all inhabitants, reduce infection to level where blindness not a public health problem.

• Or, should we try to actually reduce the prevalence of infection to zero?

Important facts

• Ocular infection by C. trachomatis is easily cured with single-dose azithromycin (95% efficacy).

• Only humans are infected (there is no animal reservoir).

• No vaccine is available.• Clinical signs are unreliable in detecting

infection; laboratory tests are far too expensive and take far too long.

Trachoma now

• WHO plan to stamp it out as a public health problem

• Surgery, antibiotics, face-washing, environment

• The SAFE program• Mass distribution of azithromycin the

cornerstone Schachter J, West SK, Mabey D, et al Lancet. 1999 Aug 21;354(9179):630-5

Modeling?

So if we know what causes trachoma…

http://www.pacificu.edu/optometry/ce/courses/13036/antibacterialpg1.cfm

…and we know what stops it…

…?

Mass administration

• Why do we call this program a mass administration?

• Because no effort is made to try to find out who actually has the infection and who does not--everybody gets the treatment, regardless.

Has modeling helped?

• Lietman et al 1999: Repeat mass treatment can theoretically eliminate the infection

• Melese 2004

• Age, immunity, serotypes, households,etc.?

Good data Practical implications

Current issues

• Assess ongoing efforts

• Optimize current efforts

• Minimize collateral damage

• Consider biological questions

• Predict future trends

Assessment

• We want to eliminate infection, but what should the epidemiology of trachoma look like during elimination?

• Theoretical models suggest an approximately exponential quasistationary distribution (Nåsell; Lietman 2013 under review)

• Thus, long tails are expected

One of theseis real data from a districtin Nepal, duringelimination

…the others aresimulatedgeometricrandom variables

Chasing ghosts

• Unpredictability of trachoma at the village level

• Long tail of the distribution

• Expect transient local hot spots

• The presence of a local hot spot does NOT imply failure

When can we stop?

• Elementary models suggest as long as conditions favor transmission, disease returns unless all cases are eliminated.

• Prevalencethresholdspossible

Lietman, Epidemics, 2011

Collateral damage

• Mass administration is controversial because of macrolide resistant pneumococcus

Maher et al, PLoS1, 2012

Antibiotic minimization?

• Targeting children only leads to reductions in prevalence, even among adults

• Can treating children alone actually eliminate infection?

• Maybe

Other examples

• Does repeat treatment seem to reduce the efficacy in future years?

• Tanzania data (Kongwa region), PRET data (S. West)

Liu et al, PLoS NTD, 2013

Predict future trends

A specific model

TANA Trial

• TANA trial: Trachoma Amelioration iN Amhara

• Lietman Group U10 being conducted in Ethiopia

• Community randomized trial with four primary specific aims

Community-specific prevalence

• Analysis of pooled prevalence from randomly chosen individuals yields a prevalence estimate for the community.

• In the TANA trial, we regard whole communities as the units of the trial.

Trial

Trial

TANA

• May 2006 to March 2007

• 66,404 people in 48 subkebele

• Annual: 50 state teams; 4,437 children

• Biannual: 61 ST; 4,462 children

• Children: 49 ST; 4,150 children

• Delay: 57 ST; 5,166 children

Stochastic epidemic

• Many books now on stochastic models in epidemiology

• Standard method used here, e.g. Bailey, Elements of Stochastic Processes, 1964

State space

• Given a village of size N, let Y be the number of infected individuals; Y ranges from 0, 1, … N-1, N.

• Ignore adults for now (low prevalence)

• We examined models with age structure, partial immunity

State space (2)

0 1 2 N-1 N…

Infection

Recovery

Model

• Continuous time

• P(Y(t)=i) = pi(t)

• Assume population is fixed

• Model period between treatments first

Acknowledgments

• Tom Lietman• Teshome Gebre, Berhan Ayele• Jenafir House, Nicole Stoller• Bruce Gaynor, Jeremy Keenan• Zhaoxia Zhou, Vicky Cevallos, Kevin Hong, Kathryn

Ray, Jack Whitcher, Paul Emerson• Data and Safety Monitoring Committee (W. Barlow,

D. Everett, L. Schwab, A. Reingold, S. Resnikoff)• Study participants

Acknowledgments, cont’d

Tadege AlemayehuTesfaye BelayAzmeraw AdgoMelese TemesgenGabeyehu SibhatAbebe MekonenManalush Berihun

Temesgen DemileWosen AbebeMelkam AndwalemMitsalal AberahraneyBanchu GedamuTessema EneyewMuluken Gobezle

Trachoma Projects in EthiopiaDeb GillMelissa NeuweltNandini GandhiCyril DalmonNicolle BenitahYing PanLauren PattyVivian SchiedlerAli ZaidiDwight SilveraIsabella PhanChihori WadaDavid LeeHarsha ReddyKathryn RayRachel MayAlison SkaletSara HaugAndi HatchJesse Biebesheimer

Traci BrownLaura CieslikAnita GuptaSusie Osaki-HolmNazzy PakpourKaren ShihScott ShimotsuKristine VinupJohn WarrenYinghui MiaoMariko BirdGreg SchmidtLynn OlingerScott LeeKevin HongJaya ChidambaramAllison LohDeb GillLarry SchwabJeremy Keenan

Vicky CevallosLauren FriedlyBruce GaynorTom LietmanKevin MillerTisha PrabriputaloongMichael SaidelJohn P. WhitcherElizabeth YiMichael YoonJohn WarrenMacdara BodekerMuthiah SrinivasanMarilyn WhitcherJenafir HouseJon YangNicole StollerCharles LinTina RutarColleen Halfpenny

FundingThat Man May SeeBernard Osher FoundationBodri FoundationHarper-Inglis TrustPeierls FoundationJack and DeLoris Lange FoundationResearch to Prevent BlindnessInternational Trachoma Initiative/PfizerNIAID: RO1-AI48789NIAID: R21-AI55752NEI: U10-EY016214Bill and Melinda Gates Foundation

With grateful acknowlegment