The UC San Diego AntiViral Research Center sponsors weekly presentations by infectious disease clinicians, physicians and researchers. The goal of these presentations is to provide the most current research, clinical practices and trends in HIV, HBV, HCV, TB and other infectious diseases of global significance. The slides from the AIDS Clinical Rounds presentation that you are about to view are intended for the educational purposes of our audience. They may not be used for other purposes without the presenter’s express permission.

AIDS CLINICAL ROUNDS

!Molecular!Epidemiology!of!HIV!in!!San!Diego!and!Tijuana!

Sanjay!Mehta!MD!Assistant!Professor!February!2015!

Tracking!HIV!

How!Does!an!InternaGonal!Border!Affect!the!Spread!of!InfecGous!

Diseases!

www.globecartoon.com!

Ebola!and!Air!Travel!

•  An!esGmated!2.8!travelers!with!Ebola!board!an!internaGonal!plane!each!month!

Bogoch,!Lancet!Jan!2015!

www.darrinbell.com!

SARS:!The!Metropole!Hotel!

US!Central!Intelligence!Agency!

San!DiegoTTijuana!Border!

San!Diego!County!!pop!3.1!million!

San!Diego!City!!pop!1.3!million!

Tijuana!! !pop!1.3!million!

San!DiegoTTijuana!Border!

•  Worlds!busiest!land!border!

•  Over!50!million!border!crossings!each!year!

CityTdata.com!Inthedf.com!

San!Diego!Tijuana!Border!

•  How!likely!is!this!going!to!stop!the!spread!of!infecGous!diseases!across!the!border?!

Lest!We!Forget!

faculty.catawba.edu!

2009!H1N1!Influenza!Epidemic!

•  From!a!small!town!in!Veracruz,!Mexico!the!2009!H1N1!epidemic!spread!into!Imperial!and!San!Diego!counGes!first!in!the!US.!

Scienceblog.com!Cameron!et!al!JIDC!2009!

Dengue!

•  14!confirmed!cases!of!Dengue!in!Baja!California!

•  A.!aegypG!found!at!32nd!st!Naval!StaGon!and!in!a!home!in!Chula!Vista!

•  Transmits!Dengue,!Chikungunya!and!Yellow!Fever!

Aedes%aegyp*%has!arrived!!!

HIV!in!Mexico!

•  In!1980s,!most!HIV!cases!in!Mexico!were!in!individuals!who!previously!lived!in!the!US.!

•  By!1991,!44.3%!of!cases!were!in!previous!US!residents.!

•  In!2000!the!rate!dropped!to!~12%,!but!was!higher!in!rural!areas,!with!over!20%!of!HIV!cases!in!Michoacán!and!Zacatecas!acquired!in!the!US.!

! MagisTRodriguez!JAIDS!2004!Strathdee!et!al!!JAMA!2008!

MigraGon!to!US!

Zacatecas!

Michoacán!

QuesGons!

1)  Can!we!demonstrate!that!San!Diego!and!Tijuana!HIV!epidemics!are!connected?!

2)  Is!there!direcGonality!to!viral!migraGon!across!the!border?!

3)  What!risk!factors!are!driving!the!border!HIV!epidemic?!

!

Molecular!Epidemiology!

Using!the!relaGonships!between!viral!sequence!data!sampled!from!infected!individuals!to!characterize!the!

spread!of!HIV!!

1)  AACTGATCGC 2)  AACAGATCGC

HIV!Diversity!

Duffy,!Shackleton,!Holmes!2008!

HIV!

HSV!

HCV!

High!fidelity!Low!fidelity!

HIV!

•  Results!in!a!unique!HIV!sequence!for!each!infected!individual!

•  This!unique!sequence!signature!conGnues!to!evolve!over!Gme!(~1%/yr!for!HIVT1!pol)!

•  This!can!be!used!to!•  Study%intra1individual%viral%spread%•  Study%inter1individual%viral%spread%•  Study%epidemics%in%*me%and%space%

HIV!Diversity!

From!Tebit!and!Arts!Lancet!ID,!2011!

The!HIV!Diaspora!

Establishing!RelaGonships!

Phylogenetic Trees Network Maps

1)  AACTGATCGC 2)  AACAGATCGT Overall difference

1)  AACTGATCGC 2)  AACAGATCGT Evolutionary Difference at each site

B!

•  Clusters!can!be!represented!as!networks!!–  Data!is!resolved!into!putaGve!linked!pairs!–  Linkage!structure!emerges!

Networks!

Terminology!T!Networks!

Cluster(

Network(

A B C

D E F

A C

D F

A(Sexual(Network:!Real(World(Network(

•  Dashed!lines!indicate!sexual!contact!

Understanding(HIV(Transmission(Networks(

An(Transmission(Network:(Limita?ons(of(our(

knowledge(

•  Dates!of!infecGon!are!used!to!assign!direcGon!of!transmission!

•  New!HIV!infected!persons!already!in!care!appear!•  Other!potenGal!“sources”!of!HIV!transmission!

idenGfied!•  What!we!don’t!see!remains!missing!

G

F

A C

DH

I

An(HIV(Transmission(Network:(What(we(see(

•  Solid!lines!indicate!very!similar!viruses!•  Red!circles!indicate!HIV!infected!persons!•  Other!individuals!are!HIV!negaGve!so!don’t!appear!

J! K!

Courtesy!of!Susan!Liple!

Why!use!Network!Analysis!!•  PhylogeneGc!analysis!cannot!esGmate!the!direcGon!of!

transmission!with!certainty.!•  Similar!strains!may!be!found!in!many!more!than!two!individuals,!

especially!if!they!are!part!of!the!same!transmission!network.!•  A!network!map!beper!represents!similariGes!between!

sequences!

11/07/14!23!

A B C

ED

F

GH

??

Courtesy!of!Susan!Liple!

Terminology!–!PhylogeneGc!Trees!

(Tips)

Time!or!GeneGc!Difference!!!

Node!

Trees!allow!us!to!1)  infer!characterisGcs!

about!ancestors!!2)  Beper!understand!

the!role!of!Gme!

San!Diego!–!Tijuana!Molecular!Epidemiology!Project!

CollaboraGng!Projects!Across!the!Border!Region!

•  Tijuana!•  Persons!who!inject!drugs!(PWID)!!T!Proyecto!El!Cuete!•  Female!sex!workers!(FSW)!and!Clients!!T!Mujer!Segura,!Mujer!Mas!Segura,!Proyecto!Parejas,!Hombre!Seguro,!!Amigos!

•  Truck!Drivers!–!Crossing!Borders!–!Proyecto!Mapa!•  Community!HIV!clinic!–!CAPACITS!clinic!Tfuture!•  Prenatal!HIV!clinic!–!IMPAACT!T!future!•  MSM!in!Tijuana!Tfuture!

•  San!Diego!•  MSM!T!Primary!InfecGon!Research!ConsorGum!!•  PWID!T!STAHR!study!and!STAHR!II!study!•  MSM,!Heterosexuals!TSouth!Bay!Primary!InfecGon!Surveillance!•  MSM,!PWID,!Heterosexuals!–!CHARTER!cohort!T!future!•  MSM,!PWID,!Heterosexuals!T!CNICS!Cohort!T!future!!

San!Diego!–!Tijuana!Molecular!Epidemiology!Project!

•  Projects!used!various!sampling!methods!–  Respondent!Driven!Sampling!–  Convenience!Sampling!–  VenueTbased!Sampling!–  Targeted!Sampling!

San!Diego!–!Tijuana!Molecular!Epidemiology!Project!

•  Data!collecGon!!– HIVT1!pol!genotype!(sequence!data)!– SocioTdemographic!data!(Age,!Sex,!Race,!etc…)!– Clinical!data!(HIV!VL,!CD4,!STI!infecGon,!etc…)!–  !Risk!Factor!Data!(IDU,!sexual!RF,!etc…!!

!!!!!TT!Geographic!Data!

San!DiegoTTijuana!Molecular!Epidemiology!Study!

•  1111!HIV!sequences!were!collected!from!the!collaboraGng!studies!(including!263!background!sequences)!

•  4!sequences!were!removed!due!to!lab!contaminaGon!or!duplicaGon!

•  The!remaining!1107!sequences!included!!– 76!from!subjects!residing!in!Tijuana!– 768!from!subjects!residing!in!San!Diego!– 263!background!sequences!from!San!Diego!

Clustering!•  Using!a!network!approach,!we!inferred!the!presence!of!transmission!clusters!by!inferring!linkages!when!two!sequences!were!≤!1.5%!different!

•  We!idenGfied!164!transmission!clusters!(2T33!individuals)!

•  17!included!sequences!from!Tijuana,!and!5!included!sequences!from!both!Tijuana!and!San!Diego!

Data!VisualizaGon!

hpp://Gcino.ucsd.edu/avantgarde/dev_hua/demo2.html!

!!hpp://54.69.246.216/avant_data/circle_packing!

Clustering!•  8!Clusters!made!up!of!predominantly!PWID!

–  InteresGngly,!bisexual!individuals!were!significantly!more!common!in!these!clusters!than!others!

•  16!Clusters!were!made!up!predominantly!of!heterosexuals!–  All!of!these!that!had!3!or!more!individuals!were!predominantly!made!

up!of!females!

•  89!clusters!were!made!up!predominantly!of!MSM!

Map(of(the(Observed(San(Diego(–(Tijuana(Transmission(Network(

Tijuana!Clusters!

•  17!clusters!indenGfied!in!subjects!residing!in!Tijuana!–  Predominantly!involved!sex!workers!and!injecGon!drug!users!

–  In!6!individuals!who!seroconverted!over!the!course!of!the!study,!4!were!linked!to!another!individual!

–  In!two!idenGfied!epidemiologically!linked!pairs!who!seroconverted!over!the!course!of!!the!study,!only!one!was!geneGcally!linked!

San!DiegoTTijuana!CrossTBorder!Clusters!

CrossTBorder!Clusters!

•  5!idenGfied!clusters!including!sequences!from!San!Diego!and!Tijuana!– Significantly!higher!proporGon!of!

•  Females!(p=0.02)!•  Heterosexuals!(p=0.0003)!

– Consistent!with!our!sampling!•  Suggests!the!heterosexualTPWID!HIV!epidemic!in!Tijuana!is!linked!to!the!San!Diego!MSM!HIV!epidemic!

CrossTborder!Clusters!

–  3/5!clusters!included!PWID!and!heterosexuals!in!Tijuana,!and!MSM!in!US!(i.e.!bridging!of!risk!groups!across!the!border)!

MSM

Heterosexuals (sex workers)

PWID

Bridging!PopulaGons!

•  Very!important!in!the!Southeast!Asian!epidemic!

Is!there!direcGonality!to!viral!migraGon?!

Faria!et!al,!Science!2014!

MigraGon!Across!the!San!DiegoTTijuana!Border!Region!

Time scaled phylogenetic tree

Viral!MigraGon!

TransiGon!from! !1)San!Diego!to!Tijuana!(Blue!to!Red)!! ! ! ! !2)!Tijuana!to!San!Diego!(Red!to!Blue)!

How!Much!Viral!MigraGon!De

nsity

Viral Movement Counts

From SD toTJFrom TJ to SD Total

-10 0 10 20 30 40 50 600

5E-2

0.1

0.15

0.2

0.25

Increasing Amount !

Prob

abili

ty!

When!did!Viral!MigraGon!Occur!

Timing!of!Viral!MigraGon!between!San!Diego!and!Tijuana!

US!is!sGll!exporGng!HIV!to!Mexico!

•  What!is!the!role!of!deportaGon!–  In!Tijuana!

•  HIV!prevalence!of!deportees!esGmated!1.23%!•  77%!of!male!HIV!+!IDUs!are!deportees!•  Deportees!report!feeling!that!IDU!and!transacGonal!sex!more!acceptable!in!their!new!environment!

–  8!deportees!involved!in!transmission!clusters!•  4!likely!acquired!infecGon!in!TJ!•  Other!4!deported!with!HIV?!

Pinedo!et!al.!2014!Ojeda,!et!al!2011!

What!risk!factors!are!driving!the!border!HIV!epidemic?!!

A!Focus!of!the!nonTMSM!Epidemic!in!San!Diego!lies!just!across!the!Border!

Conclusions!based!on!our!Sample!

•  The!San!Diego!and!Tijuana!epidemics!are!connected!bridging!risk!groups!across!the!border!

•  There!is!evidence!of!biTdirecGonal!viral!migraGon!across!the!border!–  1990s!–!More!migraGon!from!SD!to!TJ!–  2000s!–!More!migraGon!from!TJ!to!SD!

•  The!demographics!of!the!border!epidemic!likely!differs!from!that!of!the!overall!San!Diego!epidemic!

Does the disparity in resources between Mexico and the US affect HIV prevention

efforts in the border region?!

Treatment!as!PrevenGon!

•  Test!and!Treat!strategies!rely!on!frequent!tesGng!of!high!risk!individuals!and!early!treatment!!

Viral!IntroducGons!can!Help!Sustain!an!Epidemic!

Rakai Cohort, Uganda

Grabowski,!PloSMed!2015!

69% of non-household transmissions were from outside the community

One!Epidemic!

Which!country!has!universal!access!to!HIV!

For!prevenGon!of!new!infecGons,!we!need!aggressive!screening!for!HIV!infecGon!on!both!sides!of!the!border,!followed!by!linkage!to!care.!!

Acknowledgements!UCSD SDPIRC and CFAR

Susan Little Doug Richman Davey Smith Christy Anderson Gina Osorio Karole Ignacio Millenka Vargas

Lorri Freitas Bioinformatics Team

Antoine Chaillon Ben Murrell Sergei L Kosakovsky Pond Konrad Scheffler Joel Wertheim Jason Young

Funding(Sources(

Lab!

UCSD GPH Steffanie Strathdee Tom Patterson Kimberly Brouwer Rich Garfein Maria Rangel Karla Wagner Alicia Vera Deyna Arellano Daniela Abramovitz GIS

Hayden Lowenstein