WHO Global Tuberculosis Report 2023

Code and data used to develop the WHO Global Tuberculosis Report for 2023. The report was published on 7 November 2023 at https://www.who.int/teams/global-tuberculosis-programme/tb-reports/global-tuberculosis-report-2023/

Folders

• data: External datasets:

  • bcg: BCG coverage indicator from the WHO Global Health Observatory

  • gtb: R binary datasets extracted from the WHO gobal TB database:

    • other: Country lists, population estimates, reference lists, survey results and external indicators

    • snapshot_yyyy-mm-dd: Snapshot of country-reported data

  • ihme: VR data from IHME

  • mortality: VR data from the WHO Mortality database

  • unaids: HIV estimates from UNAIDS

• disaggregation: Pete Dodd's R scripts to estimate incidence and mortality disaggregated by age group and sex.

• doc: A PDF version of the web-based data collection form used by countries to report data to WHO. The PDF also shows database variable names.

• drtb: Pete Dodd's R and Stan scripts to estimate drug-resistant TB burden.

• dynamic: Nim Arinaminpathy's Matlab code for dynamic modelling of TB incidence and mortality for the period 2020-2022 in selected countries.

• finance: Andrew Siroka and Peter Nguhiu's R and Stata code for analysing TB financing data.

• import: R scripts to load saved data files from the WHO gobal TB database and the Global Health Observatory.

• inc_mort: Mathieu Bastard and Philippe Glaziou's R scripts to produce estimates of TB incidence and mortality

• lives_saved: Takuya Yamanaka and Philippe Glaziou's R scripts to produce estimates of the number of death averted by TB treatment and ART since 2005.

• report: R Markdown scripts by Mathieu Bastard/Philippe Glaziou, Irwin Law, Peter Nguhiu, Hazim Timimi and Takuya Yamanaka to generate tables, static figures, interactive Kendo UI charts and text for the 2023 edition of the WHO Global Tuberculosis Report web pages and the report PDF.

Global tuberculosis database data sets

The following sections show the data object names chosen in previous years. If you use the load_gtb() function you don't need to know if a data object is part of a snapshot or other, not does your code have to use the same object name.

For example, the following line loads the most recently saved snapshot of notifications into a dataframe / data table called notifs:

notifs <- load_gtb("tb")

Snapshot data

• agg: TB/HIV indicators with rules to be used to calculate aggregates from view_TME_master_TBHIV_for_aggregates

• covid: Impact of COVID on services and response to the UNHLM commitments from view_TME_master_covid_unhlm

• drfq: DRS records used to estimate fluoroquinolone resistance among RR-TB patients from view_DRS_for_estimation_sldst

• drhnew: DRS records used to estimate HR-TB among new TB patients from view_DRS_for_estimation_new_INH

• drhret: DRS records used to estimate HR-TB among previously treated TB patients from view_DRS_for_estimation_ret_INH

• drnew: DRS records used to estimate RR-TB among new TB patients from view_DRS_for_estimation_new

• drret: DRS records used to estimate RR-TB among previously treated TB patients from view_DRS_for_estimation_ret

• drroutine: Routine drug resistance surveillance records from view_TME_master_dr_surveillance

• ltbi: Estimates of TPT coverage among children (numbers derived from reported data) from view_TME_estimates_ltbi

• monthly: Provisional monthly or quarterly notifications from dcf.latest_provisional_c_newinc

• sty: Services, PPM, community engagement, M&E systems from view_TME_master_strategy

• tb: TB notifications from view_TME_master_notifications

• tpt: TB preventive treatment from view_TME_master_contacts_tpt

• tx: Treatment outcomes from view_TME_master_outcomes

• vrgtb: VR data reported by countries in the European Region from dcf.latest_vr

Other data

Explanatory

• dic: Data dictionary from view_TME_data_dictionary

• codes: Meaning of codes used for categorical variables from view_TME_data_codes

Reference: countries, country groups, population and SDG indicators

• cty: Country and area names in 4 languages, their codes and WHO region and status from view_TME_master_report_country

• datacoll: Options set for the data collection form for each country-data collection year combinations from view_TME_master_data_collection

• grptypes: Themes by which to group countries from view_country_group_types

• grp: Country groups within each grouping theme (e.g. the 4 income groups of High, Upper Middle, Lower Middle and Low in the World Bank income classification) from view_country_groups

• grpmbr: Countries belonging to each country group from view_country_group_membership

• pop: UN Population Division population estimates from view_TME_estimates_population

• sdg: SDG indicator data and codes relevant to TB incidence from external_indicators.view_indicator_data

• sdgdef: Full names of SDG indicators and their sources from "external_indicators.view_indicator_definition

Surveys and survey results

• svy.cc: Results of catastrophic costs surveys from survey.view_catastrophic_costs_survey

• svy.prev: Prevalence estimates resulting from prevalence surveys from survey.view_prevalence_survey_estimates

• svy.prevcases: Numbers of TB cases found in prevalence surveys from survey.view_prevalence_survey_cases

• svy.prevchar: Characteristics of prevalence surveys from survey.view_prevalence_survey

Codes used in survey records:

• svy.agegr: Codes for age groups from survey.age_group

• svy.areatype: Codes for area types from survey.area_type

• svy.casetype: Codes for case types from survey.case_type

• svy.patientgr: Codes for patient groups from survey.patient_group

• svy.screen: Codes for screening methods from survey.screen_group

• svy.sex: Codes for sex from survey.sex