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Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 1 Tuberculosis epidemiology: Using data to inform TB control approaches and priorities Lisa Pascopella, PhD, MPH Senior Epidemiologist Tuberculosis Control Branch California Department of Public Health November 18, 2019 Objectives Describe the epidemiology of tuberculosis in the U.S. Describe how epidemiologic and population data can be used to inform TB prevention and control activities
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  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 1

    Tuberculosis epidemiology: Using data to inform TB control approaches and priorities

    Lisa Pascopella, PhD, MPHSenior EpidemiologistTuberculosis Control BranchCalifornia Department of Public HealthNovember 18, 2019

    Objectives

    • Describe the epidemiology of tuberculosis in the U.S. • Describe how epidemiologic and population data can

    be used to inform TB prevention and control activities

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 2

    Topics• Epidemiology of TB in the United States• Death with TB• Epidemiology of TB in California• TB prevention cascades in

    Contacts to infectious TB cases

    New arrivers with abnormal chest radiographs

    National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention

    Tuberculosis in the United States1993–2018*

    National Tuberculosis Surveillance System

    Division of Tuberculosis Elimination

    *Updated as of June 6, 2019

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 3

    Reported Tuberculosis (TB) Cases and Rates United States, 1993–2018

    Percentage of TB Cases by State, United States, 2018

    DC, District of Columbia

    DC

    12.56.5

    23.2

    8.3

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 4

    Tuberculosis Case Rates by Reporting Area United States, 2018

    3.9

    5.3

    8.5

    TB Incidence Rate (per 100,000 persons)8.4

    5.3

    8.5

    3.9

    NYC (6.7)

    D.C. (5.1)

    TB Incidence Rate (per 100,000 persons)

    8.5

    5.3

    TB Cases and Rates Among U.S.-Born versus Non-U.S.–Born Persons, United States, 1993–2018

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  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 5

    Countries of Birth Among Non-U.S.–Born Persons Reported with TB, United States, 2018*

    *Percentages are rounded.

    Percentage of Non-U.S.–Born TB Casesby Time in the United States at Diagnosis, 2018

    Pe

    rce

    nta

    ge o

    f TB

    Cas

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    Time in the United States

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 6

    TB Case Rates by Race/Ethnicity,* United States, 2010–2018

    * All races are non-Hispanic; multiple race indicates two or more races reported for a person, but does not include persons of Hispanic/Latino origin.† Asian race category reporting includes Pacific Islander from 1993–2002; Native Hawaiian/Other Pacific Islander race first reported separately in 2003.§ Multiple race rates first reported in 2003..

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    Reported TB Cases by Origin and Race/Ethnicity*, United States, 2018†

    Non-U.S.–born persons § U.S.-born persons

    * All races are non-Hispanic; multiple race indicates two or more races reported for a person, but does not include persons of Hispanic/Latino origin.† Percentages are rounded.§ American Indian/Alaska Native accounted for

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 7

    TB Case Rates by Age Group, United States, 1993–2018

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    Year

    Distribution of Sex by Age Group, United States, 2018

    Males Females

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 8

    U.S. TB Cases by Site of Disease, 2018

    *Any pulmonary involvement which includes cases that are pulmonary only and both pulmonary and extrapulmonary.Patients may have more than one disease site but are counted in mutually exclusive categories for surveillance purposes.

    Note: Percentages are rounded.

    National guidance: Assess pulmonary involvement for any form of TB

    For diagnostic purposes, all persons suspected of having TB disease at any site should have sputum specimens collected for an AFB smear and culture, even those without respiratory symptomsfrom CDC’s Core Curriculum on TB Chapter 4

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 9

    Isoniazid Resistance Among U.S.-Born versus Non-U.S.–Born Persons, United States, 1993–2018

    Cases of MDR TB by History of TB, United States, 1993–2018*

    * Based on initial isolates from persons with no prior history of TB; multidrug-resistant TB (MDR TB) is defined as resistance to at least isoniazid and rifampin.

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 10

    HIV Coinfection by Age Among Persons Reported with TB, United States, 2011–2018

    Reported TB Cases by Risk Factor, United States, 2018

    Non-HIV immunosuppression

    Contact to Infectious TB

    Diabetes Mellitus

    Contact to Infectious TB Diabetes Mellitus

    Comparison of Selected Risk Factors by Origin of BirthMost Common Risk Factors Reported Among TB Patients

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 11

    *Correctional facilities include federal prisons, state prisons, local jails, juvenile correctional facilities, other correctional facilities, or unknown type of

    correctional facility.

    TB Cases among Residents of Correctional Facilities Ages ≥15, 1993–2018*

    TB Cases Ages ≥15 with Other Selected Risk Factors, 2018

    Risk Factor

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 12

    Substance Misuse Among TB Patients ≥15 years, United States, 2018

    Risk factors for TB

    Born in a non-US country where TB is endemicLiving with HIV, diabetes, other immunosuppressionExperiencing homelessnessUsing substances (e.g. injection drugs)Living in certain institutional settings

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 13

    TB treatment outcomes

    The majority of TB patients complete their treatment within 12 monthsFew TB patients are lost to followupTB patients who move may be provided with continuity of careAlmost 10% of TB patients die while on treatment

    TB Cases by Reason Therapy Stopped, 2016*

    *Data available through 2016 only.

    Outcomes for patients that did not complete treatment

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 14

    Death with TB

    Reported Tuberculosis (TB) Deaths* and Rates United States, 1993–2017

    *National Vital Statistics System Multiple Causes of Death (accessed from CDC Wonder)

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 15

    TB Surveillance data is more accurate than Vital Statistics data for TB patients who die

    We have reviewed the characteristics of the population who has TBNow let’s review what we know about persons who die with TB

    Although TB is a preventable and curable disease, approximately 10% of persons with TB die with TBWhy?Can we prevent death with TB?

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 16

    Published in Annals ATS, Vol 15 June 2018

    TB Epidemiologic Studies Consortium Mortality Study Objectives

    Assess the frequency of TB-related deathsIdentify risk factors for TB-related death

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 17

    Methods

    • Reviewed deaths of TB cases reported 2005-2006

    • Inpatient and outpatient medical records

    • Laboratory records

    • Used standardized and piloted algorithm to determine TB-relatedness

    • Trained data abstractors

    • 2 reviewers per case (at least 1 TB clinician)

    • 3rd reviewer to resolve disagreements

    • Classification

    • Definitely or probably TB-related

    • Definitely not or unlikely TB-related

    • Unclassifiable

    TB relatedness and timing of deaths

    1,304 adults who died

    942 (72%)TB-related deaths

    272 (21%) TB-unrelated

    deaths

    90 (7%) could not be classified

    705 (75%) TB-related deaths during

    treatment

    237 (25%) TB-related deaths before

    treatment

    329 (47%) TB-related deaths

    within 30 days of diagnosis

    371 (53%) TB-related deaths >31

    days after diagnosis

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 18

    Time to deathTB related vs TB-unrelated

    TB unrelated

    TB related

    Days to death

    Study algorithm/Death cert TB was not an immediate,

    underlying, or contributing

    cause of death

    TB was an immediate,

    underlying, or

    contributing cause of

    death

    Totala

    Not TB-related death 185 (75) 61 (25) 246 (23)

    TB-related death 378 (45) 469 (55) 847 (77)

    Totala 563 (52) 540 (48) 1093 (100)

    Study algorithm vs. Death certificate

    aDeath certificates were not available for 10% of decedents

    Kappa = 0.21 (0.16, 0.26)

    Sensitivity of death certificate=55.4% (51.9,58.7)Specificity of death certificate=75.2% (69.3, 80.5)

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 19

    Risk factors for TB-related death

    Delayed diagnosis

    Extensive TB disease

    Immune suppression

    Comorbidities

    Started anti-TB treatment as inpatient

    TBESC study conclusions

    • 72% TB deaths were TB-related• Death certificates were not reliable

    • and underestimate TB-related death• Need information from medical/hospitalization charts• Increased death risk when TB was diagnosed in hospital

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 20

    What do we know about TB deaths in CA?

    Reviewed recent surveillance data for 2 types

    • Dead at diagnosis

    • Died during treatment

    Report of Verified Case of TuberculosisWas TB a cause of death?

    1. Dead at diagnosis

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 21

    CA TB surveillance data 2010-2016Dead at diagnosis

    2% (n=304) TB cases dead at diagnosis

    • 30% TB-related

    • 40% not TB-related

    • 30% unknown relatedness

    Report of Verified Case of Tuberculosis Was death related to TB disease or TB therapy?

    2. Died during treatment

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 22

    CA TB surveillance data 2010-2016Died during treatment

    8.4% (n= 1267) TB cases died on treatment

    • 36% related to TB disease

    • 1.6% related to TB therapy

    • 41% not TB-related

    • 21% unknown

    Deaths on treatment for select local TB programsCA TB surveillance data 2010-2016

    LHJ Unrelated to TB disease

    Related to TB disease

    Related to TB therapy

    Unknown

    a 40% 21% 0.5% 39%

    b 43% 47% 2.8% 7%

    c 24% 56% 1.9% 19%

    d 55% 16% 0 29%

    e 19% 70% 0 12%

    Large range of responses across CA

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 23

    Why the difference in TB-related deathTBESC study (72%) vs.CA surveillance (38%)?

    • Diversity of responses to RVCT questions in CA• Variability in methods to ascertain TB-relatedness?• Role for independent review?

    TB programs should review every death using a standardized approach that includes medical and hospital records

    • To identify potential missed prevention opportunities• To monitor trends• To identify areas for working with partners

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 24

    Consider using algorithm developed in CA for review of deaths

    https://www.cdph.ca.gov/Programs/CID/DCDC/CDPH%20Document%20Library/TBCB-RVCT-Death-Algorithm-v1.0.pdf

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 25

    TB epidemiology in California

    How do TB Cases Occur in California?

    TB in new arrivers TB within 6 months of arrival in US 2015-2017

    Recent TransmissionRT recipient 2014-2016

    Reactivation of remote infection. Cases not from importation or recent transmission

    2,000 TB cases/yr

    12%

    82%

    6%

    50

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 26

    The Long View: Dramatic ProgressCalifornia Tuberculosis Epidemic 1930–2018

    0

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    The Medium View: Dramatic ProgressCalifornia Tuberculosis Epidemic 1991–2018

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    1991 1996 2001 2006 2011 2016

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  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 27

    The Medium View: Slowing ProgressCalifornia Tuberculosis Epidemic 1991–2018

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    -4.3%

    53

    -6.2%

    -1.2%

    Progress StalledCalifornia Tuberculosis Epidemic 2014–2018

    0

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  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 28

    Progress StalledCalifornia Tuberculosis Epidemic 2014–2018

    2091

    5.3

    0

    1

    2

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    4

    5

    6

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    55

    Progress StalledCalifornia Tuberculosis Epidemic 2014–2018

    2133 2131 2058 2059 2091

    5.3

    0

    1

    2

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    4

    5

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  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 29

    Photograph by Jodie JoOx http://yourshot.nationalgeographic.com/photos/6232126/ 57

    Match the TB program strategy to the TB mechanism

    58

    TB in recent arrivers

    Recent transmission

    Reactivation of LTBI

    • Overseas screening and treatment• Domestic evaluation and treatment

    • Outbreak investigation• Contact investigation

    • Risk assessment• LTBI testing• LTBI treatment

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 30

    83% of cases in people born outside U.S.TB Cases by country of birth California, 2018

    0% 20% 40% 60% 80% 100%

    60

    Other Countries

    Mexico PhilippinesVietnam

    China

    India

    83%

    CentralAmerica

    17%

    U.S.

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 31

    Cases from >120 countriesCountry of origin of TB cases 2014-2018, California

    61

    62

    60

    40

    20

    0

    TB Incidence by Country of Birth,California, 2001−2016

    Cas

    es p

    er

    10

    0,0

    00

    Philippines

    Vietnam

    IndiaChina

    Mexico

    U.S.

    2004 2008 2012 2016

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 32

    Large disparity by place of birthTB case rate by nativity California 2009–2018

    2.21.2

    18.9

    16.1

    0

    2

    4

    6

    8

    10

    12

    14

    16

    18

    20

    2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

    63

    Non-U.S.-born

    U.S.-born

    Disparity by place of birth increasingTB case rate by nativity California 2009–2018

    2.21.2

    18.9

    16.1

    9

    13

    0

    2

    4

    6

    8

    10

    12

    14

    16

    18

    20

    2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

    FB:USB Ratio

    64

    U.S.-born

    Non-U.S.-born

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 33

    20x-60x higher rates among non-U.S.-born

    minorities compared with U.S.-born whitesTB rate by race/ethnicity and nativity, 2018

    0.5

    1.7

    2.7

    2

    4

    11

    19

    29

    0 10 20 30 40

    White

    Hispanic

    Black

    Asian

    Rate per 100,000

    Non-U.S.-born

    U.S.-born

    65

    Most People with TB have been U.S. residents for many yearsYears in U.S. at TB diagnosis California, 2014-2018

    0

    200

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    -61

    62

    +

    TB C

    ase

    s

    Years in U.S.

    66

    >50% in US >18 yrs

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 34

    Half of TB cases are older than 55Age at Report of TB, 2018

    0

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    1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 79 82 85 88 91 94 97 100

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    Age

    Median

    Median age continues to increase: 53 (2014) 55 (2018)2018: Born outside US=57 years US-born=36 years 67

    More TB Cases are Older% of TB Cases Aged 65+, 1993-2018

    18%

    23%

    34%

    0

    5

    10

    15

    20

    25

    30

    35

    40

    1993 2008 2018

    % o

    f C

    ases

    68

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 35

    More TB Cases are Older% of TB Cases Aged 65+, 1993-2018

    5%9%

    12%

    0

    5

    10

    15

    20

    25

    30

    35

    40

    1993 2009 2018

    % o

    f C

    ases

    80+

    69

    Decreasing TB in youngest kidsPediatric Cases

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 36

    Correctional cases increased in 2018Cases Diagnosed in a Correctional Facility, 2009-2018

    38 (1.8%)

    67 (3.2%)

    0

    0.5

    1

    1.5

    2

    2.5

    3

    3.5

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    Correctional case Percent correctional71

    Cases increased most in local jails and others*Type of Correctional Facility, 2017-2018

    10

    3

    11

    1412

    4

    28

    22

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    72

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 37

    Low education associated with high TB rateTB rate by % of adults in census tract with HS education

    United States, 4.5

    China, 3.3

    India, 1.4

    Mexico, 1.5

    Philippines, 1.7

    Vietnam, 2.7

    0

    10

    20

    30

    40

    50

    60

    94%

    Inci

    de

    nce

    rat

    e p

    er

    10

    0,0

    00

    Percent of adults with HS education

    Country, Rate Ratio

    73

    Lower SES associated with higher TB rate.TB Rate by SES Level and Country of Birth

    0

    10

    20

    30

    40

    50

    60

    Un

    ited

    Sta

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    Me

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    Ind

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    Low SES High SES

    74

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 38

    2018 CA TB Epi Highlights Summary

    Stall in decline confirmedSimilar epi patterns continue: disparitiesHigh TB rate in older age groupsFalling number of peds cases reason for optimismCases in local jails and other facilities bears monitoringTB is associated with lower socioeconomic status!(even in California and after accounting for country of birth)

    75

    Contacts Care Cascade: EvaluationARPE Data California, 2016‒2017

    23,589 19,2040

    5,000

    10,000

    15,000

    20,000

    25,000

    Contactsto Smr +

    Evaluated

    Nu

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    con

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    s

    81%

    76NTIP data for California based on ARPE reporting for cohorts reported in 2016 and 2017

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 39

    TB prevention cascade amongContacts to infectious TB, California, 2016-2017

    3,117 2,125 1,5100

    500

    1000

    1500

    2000

    2500

    3000

    3500

    With LTBI Started treatment Completedtreatment

    Started treatment Completed treatment

    68%

    71%

    77

    NTIP data based on ARPE California data, 2016-2017

    Contacts with LTBI

    Improving treatment completionContacts Completing LTBI Treatment (of those who start)

    62% 62% 73% 69% 72% 70%0%

    10%

    20%

    30%

    40%

    50%

    60%

    70%

    80%

    2012 2013 2014 2015 2016 2017

    78ARPE data reported to California 2012-2017

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 40

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 41

    81

    Class B1 arriver care cascade2014-2018

    32215

    1994562%

    711936%

    310444% 1574

    51%

    0

    5000

    10000

    15000

    20000

    25000

    30000

    35000

    ClassB arrivers

    Evaluated& reported

    LTBI*

    Started Tx Completed Tx

    *Excludes B1 arrivers who reported a history of treatment for active TB

    Potential room for program improvement?

    • Only 42% of contacts with LTBI completed treatment

    • Only 22% of B1 arrivers with LTBI completed treatment

    82

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 42

    TB programs are responsible for at least 2 populations at risk of TB: Contacts and New arrivers with B-notifications

    Improved evaluation and treatment to prevent TB

    83

    Contacts for California TB programs

    • CDPH TB Branch 510-620-3865• Program Liaisons

    – Lisa True– Stephanie Spencer– Leslie Henry– Anne Cass– Michael Joseph

    • Epi Liaisons– Lisa Pascopella– Melissa Ehman– Adam Readhead– Phil Lowenthal– Varsha Hampole

    • TB Registry Chief– Janice Westenhouse

    • Surveillance and Epidemiology Section Chief

    – Pennan Barry

    • Program Development Section Chief– Kristen Wendorf

    • You can reach me at lisa.pascopella@cdph.ca.gov

  • Tuberculosis epidemiology: using data to inform tuberculosis control approaches and priorities 43

    National and California resourcesDivision of Tuberculosis Elimination National Center for HIV/AIDS, Viral Hepatitis,

    STD, and TB PreventionCenters for Disease Control and Preventionhttp://www.cdc.gov/tb/

    • National data slidesethttps://www.cdc.gov/tb/statistics/surv/surv2018/default.htm

    • Core curriculum on TB https://www.cdc.gov/tb/publications/slidesets/corecurr/default.htm

    Tuberculosis Control Branch

    Division of Communicable Disease Control

    Center for Infectious Diseases

    California Department of Public Health• https://www.cdph.ca.gov/Programs/CID/DCDC

    /Pages/TBCB.aspx

    • https://www.cdph.ca.gov/Programs/CID/DCDC/CDPH%20Document%20Library/TBCB-Program-Liaison-Epi-Assignments.pdf

    • https://www.cdph.ca.gov/Programs/CID/DCDC/CDPH%20Document%20Library/TBCB-RVCT-Death-Algorithm-v1.0.pdf

    Acknowledgements

    CDC DTBE slidesetCDPH TBCB:• Pennan Barry• Phil Lowenthal• Melissa Ehman