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BACKGROUND DOCUMENT 1

Strengthening national notification systems for direct

measurement of TB cases: an overview of progress

Prepared by:

Laura Anderson, Katherine Floyd, Babis Sismanidis

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This document provides a global overview of progress with activities related to the first strategic area of work of the WHO Global Task Force on TB Impact Measurement: Strengthening national notification systems for the direct measurement of TB cases, including drug-resistant TB and HIV-associated TB specifically.

In the April 2016 meeting of the Task Force, four topics were specifically identified for this strategic area of work:

1. National TB epidemiological reviews, including standardised assessment of national surveillance systems using the WHO checklist of standard and benchmarks.

2. Regional analysis workshops. 3. Transitioning from paper to electronic case-based surveillance. 4. TB inventory studies to measure underreporting of detected TB cases.

The document covers progress related to 1, 3 and 4. The second topic is covered in background document 5a. As part of topic 4, progress in the implementation of mandatory notification of detected TB cases is discussed; this is both one of the benchmarks used to assess underreporting in the WHO surveillance checklist, and one of the major solutions recommended to address the problem of underreporting.

1. Epidemiological Reviews and Standards and Benchmarks assessments

Epidemiological Reviews

Between early 2013, when the first TB epidemiological review using new and standardized terms of reference was undertaken, and April 2018, 69 countries have completed a national TB epidemiological review. Of these, 64 included an assessment of the performance of TB surveillance using the WHO checklist of standards and benchmarks (published in January 2013). Of the 69 reviews, 42 were implemented in 2016 and 2017 (Figure 1).

Figure 1: National TB epidemiological reviews conducted since 2012 and planned in the next year

*Two reviews have been completed in 23 countries : Angola, Bangladesh, Botswana, DRC, Egypt, Ethiopia, Fiji, Ghana, Indonesia,

Kenya, Lesotho, Madagascar, Mozambique, Myanmar, Nigeria, Pakistan, Papua New Guinea, Philippines, Swaziland, Thailand, United

Republic of Tanzania, Zambia and Zimbabwe

A national TB epidemiological review is planned in 17 countries in 2018. This is either because a review has not previously been done, or because it has been more than 3 years since the last

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review and an update is required as part of Global Fund-related concept note development or reprogramming of grant funds. Please also see background document C.

Standards and Benchmarks assessments

A major goal of tuberculosis (TB) surveillance is to provide an accurate measure of the number of new TB cases and TB deaths that occur each year, and to be able to assess these trends over time. In some countries, TB surveillance already meets the standards necessary to do this, but in others, there are important gaps in the TB surveillance system that make this impossible. The Checklist of standards and benchmarks for TB surveillance and vital registration systems1 was developed with the following objectives: to assess a national surveillance system’s ability to accurately measure TB cases and deaths and to identify gaps in national surveillance systems that must be addressed in order to improve TB surveillance. There are two parts to the checklist, Part A comprises 18 questions that characterize the national TB surveillance system and sets the background for Part B, the main part of the assessment, which consists of 13 standards and their associated benchmarks. The standards are general statements about the criteria for a high-performance TB surveillance system. Benchmarks define (in quantitative terms wherever possible) the level of performance considered sufficient to meet respective standards. For a full list of standards please see Table 1. For a full list of standards and their associated benchmarks please see Appendix 1.

Table 1: Checklist of standards and benchmarks for TB surveillance; full list of standards

GROUPING STANDARDS

CO

RE

Data quality

B1.1 Case definitions are consistent with WHO guidelines

B1.2 TB surveillance system is designed to capture a minimum set of variables for all reported TB cases

B1.3 All scheduled periodic data submissions, e.g. electronic data files or quarterly paper reports, have been received and processed at the national level

B1.4 Data in quarterly reports (or equivalent) are accurate, complete and internally consistent (For paper-based systems only)

B1.5 Data in national database are accurate, complete, internally consistent and free of duplicates (For electronic case-based or patient-based systems only)

B1.6 TB surveillance data are externally consistent

B1.7 Number of reported TB cases is internally consistent (within country)

System coverage

B1.8 All diagnosed cases of TB are reported

B1.9 Population has good access to health care

Vital registration

B1.10 Vital registration system has high national coverage and quality

SU

PP

LE

ME

NT

AR

Y

Special sub populations

B2.1 Surveillance data provide a direct measure of drug resistant TB in new cases

B2.2 Surveillance data provide a direct measure of the prevalence of HIV infection in TB cases

B2.3 Surveillance data for children reported with TB (defined as ages 0-14 years) are reliable and accurate or all diagnosed childhood TB cases are reported

1 http://www.who.int/tb/publications/standardsandbenchmarks/en/

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Since July 2012, 66 Standards and Benchmarks assessments have been completed (in Saudi Arabia and South Africa, the assessment was done separately from an epidemiological review) (Figure 2). Two further assessments are planned in 2018, in the United Republic of Tanzania and Cambodia, as well as the 17 planned as part of national epidemiological TB reviews. Most countries (n=40) that have completed an assessment met 4-6 of the 13 standards.

Figure 2: Countries in which a checklist of standards and benchmarks has been

completed since 2012*

*An additional 6 countries completely self-assessments as part of the DHIS2 workshops on data analysis and use

A Standards and Benchmarks assessment has been carried out in 24/30 high TB burden countries (Figure 3) and an assessment is planned for three further countries in 2018; Brazil, Cambodia and Central African Republic. It is possible that an assessment could be undertaken in India.

To date, most high burden countries have met 4-6 standards (out of 13). There were 3 countries that met only 1 standard: Angola, Liberia and Papua New Guinea. Most countries met standards for case definitions (B1.1) and the minimal dataset being in line with the 2013 WHO recording and reporting framework (B1.2). Half of the countries met the standards for completeness of reporting from all districts (B1.3), external consistency (B1.6) and coverage of TB-HIV testing (80% of cases with a known HIV status) (B2.2). A third of countries met the standard on surveillance of drug resistant TB (B2.1). The standards for data quality (B1.4) and internal consistency (B1.7) were partially met or not met in many countries, indicating that data validation and associated monitoring and evaluation processes could be strengthened.

Almost all countries failed to meet standards on reporting of all cases (mandatory notification and at least 90% cases reported as measured with a national TB inventory study) (B1.8), access to health care (B1.9), vital registration systems (B1.10) and detection and/or reporting of children under 5 years old (B2.3).

- - -

n=19

n=40

n=4

n=1 -

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Figure 3: Results from Standards and Benchmarks assessments in 30 High TB Burden

Countries (status April 2018)

Key

Met

Partially met

Not met

Not applicable

Not assessed

Planned 2018

Sixteen countries have completed repeat standards and benchmarks assessments. This allows progress to be assessed, in terms of the implementation of recommendations from the first assessment to correct partially and unmet standards and the outcomes of those recommendations.

Results from these 16 repeat assessments are summarised in Figure 4 and Appendix 2. The main findings are:

Overall, there was an improvement in surveillance in half of the countries (in terms of the number of standards being met).

Only Kenya and Madagascar improved on standards whilst maintaining all those that were previously met.

For most countries, the picture was mixed. Some standards improved over time while others worsened or stayed the same. When a standard was met in the first assessment but not the repeat assessment there was usually a good explanation (see below for further details).

Country B1.1 B1.2 B1.3 B1.4 B1.5 B1.6 B1.7 B1.8 B1.9 B1.10 B2.1 B2.2 B2.3 Met

Angola 1

Bangladesh 5

Brazil

Cambodia

Central African Republic

China

Congo

Democratic People's Republic of Korea 4

Democratic Republic of the Congo 6Ethiopia 4

India

Indonesia 4

Kenya 6

Lesotho 5

Liberia 1

Mozambique 5

Myanmar 5

Namibia 4

Nigeria 5

Pakistan 4

Papua New Guinea 1

Philippines 4

Russian Federation 8

Sierra Leone 2

South Africa 5

Thailand 5

United Republic of Tanzania 5

Viet Nam 3

Zambia 4

Zimbabwe 6

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Most of the improvements were in recording and reporting (data collected and reporting rates), the internal consistency of data, coverage of HIV testing and drug resistance surveillance (in terms of the coverage of routine diagnostic testing for drug susceptibility).

In countries where the situation appeared to have worsened, some reasons were country-specific. However, a major reason across all countries was a deterioration in data accuracy, timeliness and completeness, associated with the implementation and national roll-out of electronic systems for recording and reporting of data. It is expected that during the transition period from paper to electronic data collection, data quality may initially worsen until adequate training and supervision has been provided. During this transition period it is particularly important to ensure that staff with the correct skill-sets are employed to manage this process at the national level who can also deliver training to sub-national level staff.

There were very few improvements in reporting of all cases, VR systems, or detection/reporting of TB in children under 5 years old.

There were no improvements in access to health care and in two countries the situation worsened.

Figure 4: Summary results from sixteen countries with repeat standards and benchmarks

assessments (for further details, see Appendix 2).

While easy to understand, summarising progress based on whether standards were met in a repeat assessment does not provide the full picture and can conceal important progress that is being made. This is illustrated by three case-studies from Kenya, Indonesia and Pakistan, shown in Appendices 3–5, which show the more detailed results from repeat Standards and Benchmarks assessments conducted 3–4 years apart. Particular attention is given to progress made in implementing the recommendations from each assessment.

It is clear that if a recommendation is not implemented, or partially implemented, then there is no improvement. However, the implementation of recommendations does not necessarily lead to an immediate improvement or to a standard being met. This is because some standards are not within the remit of a national TB programme (NTP), such as vital registration and universal access to health care. Nonetheless, in Kenya the NTP has made efforts to actively engage with the system for civil and vital registration statistics (CVRS) to set up a routine mechanism for data sharing and record linkage. These standards also require a longer term implementation

0 1 2 3 4 5 6 7 8 9 10 11 12 13

GhanaEgypt

IndonesiaPhilippines

EthiopiaKenya

MadagascarMyanmar

LesothoNigeriaZambia

BotswanaSwazilandZimbabwe

PakistanRwanda

Number of standards

Worse No Change in those not previously met Better Met

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plan over several years, such as the expansion of health insurance in Indonesia, and the development or strengthening of CRVS.

Some standards under the direct control of the TB programme at the national level have shown clear improvement when recommendations are implemented. Good examples are recommendations related to recording and reporting, drug resistant TB, childhood TB and mandatory notification. These standards are linked to normative guidance that outlines clear activities that can be easily identified, funded and implemented within a relatively short time period i.e. drug resistance surveillance, an inventory study, updating of recording and reporting tools and a ministerial decree for TB notification.

Standards that are within the control of the NTP but involve all levels of the programme are more difficult to tackle and take longer. Examples include those related to improving data quality and the coverage of TB-HIV testing. To strengthen these standards, multiple activities are required, including the development of guidance and processes, training, routine monitoring and supervision, and hiring staff with the appropriate skills to deliver the work.

A particular challenge has been the introduction of unique identifiers, de-duplication and monitoring the timeliness of reports in electronic systems. Furthermore, as noted above, the transition from paper based to electronic systems has been associated with a deterioration in data quality. Standards B1.3 - B1.7 have not been met in all three countries for exactly this reason – the transition from paper based to electronic surveillance, despite substantial progress having already been made merely by the implementation of an electronic surveillance system. These standards can all be achieved over time with good IT support, training and routine analysis of data.

Finally, even though a standard has been met, this does not mean that it cannot be improved upon. For example, in Kenya where the standard is already met for TB-HIV, the country now plans to tackle the problem of the last TB-HIV cases who do not start on treatment for ART or CPT through operational research.

Capacity building for Epidemiological Reviews and Standards and Benchmarks assessments

Since April 2016, 12 consultant epidemiologists have been trained to conduct epidemiological reviews (including standards and benchmarks assessments). This training was provided during a workshop held in Crete, Greece in May 2016. These 12 consultants are now part of the TB expert roster for epidemiological reviews maintained by WHO (GTB/TME), which in April 2018 has a total of 35 people. The roster includes staff and consultants working for WHO, US-CDC, KNCV, Public Health England and the London School of Hygiene and Tropical Medicine, as well as independent consultants. Four of the people on the expert roster were trained by WHO (GTB/TME) in the field through “shadowing”, while nine NTP staff from the roster who come from West African countries were trained in the field by WHO-TDR as part of research network that brings together the NTPs of 16 countries in west Africa, the West Africa Research Network-TB (WARN-TB).2

To further increase capacity for carrying out epidemiological reviews in the African region, a training workshop will be held in September 2018 in Kigali, Rwanda. This will focus on training consultant epidemiologists who can work in francophone Africa, and others living in the region. This workshop will be carried out in collaboration with the WHO Regional Office for Africa (AFRO), US-CDC and Challenge TB.

In terms of guidance, the implementation document for national epidemiological TB reviews was finalised in 2017 and translated into French. The standardised terms of reference for national epidemiological TB reviews are being updated based on recent experience; a draft is

2 The NTPs of the following countries are part of WARN-TB: Benin, Burkina Faso, Cape Verde, Gambia, Ghana, Guinea Conakry, Guinea Bissau, Ivory Coast, Liberia, Mali, Mauritania, Niger, Nigeria, Senegal, Sierra Leone, Togo.

https://bit.ly/2qPTss7https://bit.ly/2HIBAcb

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available and has been reviewed by a small working group of the Task Force. The draft will be further discussed during Day 3 of the May 2018 Task Force meeting.

2. Transitioning from paper to electronic surveillance systems

Of the 181 countries with data available on the type of national TB surveillance system that has been established in the country, the majority have now implemented an electronic case-based data base for reporting all TB cases (n=127) (Figure 5). A further 22 countries have established an electronic case-based data base for MDR-TB cases only. These countries, mainly in the WHO African and South-East Asia regions, are in a transition phase between aggregate and case-based surveillance systems and have initiated this transition by first establishing a case-based system for MDR-TB cases only. These systems have been prioritised since case-based data on MDR-TB are crucial to ensure patients are started on appropriate treatment and actively followed up throughout, in addition to the practical reason that usually these systems only need to be established at a few specialist centres or laboratories around the country. About half of countries in the WHO African Region still have paper-based systems (Figure 6).

Figure 5: Global status of electronic surveillance systems in 2016 (source : Global TB

database 2017, epidemiological reviews and DHIS2 workshops)

Figure 6: Proportion of countries with different types of surveillance systems by WHO

region

0

10

20

30

40

50

60

70

80

90

100

AFR AMR EMR EUR SEA WPR

Co

un

trie

s (%

)

Paper Aggregate electronic

Case-based (MDR-TB patients) Case-based (All TB patients)

https://bit.ly/2HIBAcb

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Over the last four years, a key finding from national TB epidemiological reviews is that although TB data may be available, they are often underused, or not used at all at both national and sub-national levels. This is partly because data, from paper-based systems in particular, are not maintained in an appropriate database, making it extremely difficult to carry out timely analysis or disseminate results from the national to sub-national levels.

In response to this finding and the WHO recommendation to transition from paper based to electronic surveillance systems, a TB module in DHIS2 (https://www.dhis2.org/overview), based on the WHO 2013 recording and reporting framework, 3 has been developed jointly by GTB/TME and the University of Oslo. This is designed to capture sub-national level aggregate data (https://tbhistoric.org), and consists of standardised data entry forms and the ability to generate graphics and reports at sub-national level in addition to a set of standardised dashboards which display graphs, tables and maps to enable the monitoring of key surveillance and data quality indicators; notifications (numbers and rates), ratios and percentages (representing the internal consistency indicators from the S & B surveillance assessment), TB-HIV, DR-TB and treatment outcomes.

The reason DHIS2 was chosen as the software to implement this work was because many countries have already implemented this system for the capture of data for many different diseases, it is open-source software with no license fees, and there is a global movement of technical and funding partners that also support it. The WHO DHIS2 TB module for aggregate data can be integrated into any country’s existing DHIS2 module and is configurable to allow the country to tailor it according to its needs.

In 2017, GTB/TME actively started to collaborate with other WHO departments (Department of Information, Evidence and Research (IER), Global HIV and Hepatitis Programme, Global Malaria Programme, Department of Immunisation) and the University of Oslo, under the umbrella of the Health Data Collaborative (https://www.healthdatacollaborative.org/), to promote an integrated approach for implementation of DHIS2 health apps for strengthening facility-based data quality, analysis and use (Figure 7). A collaborative joint work-plan 2017-2020 has been developed, with funding from the Global Fund, with the goal of implementing the WHO DHIS2 TB module for aggregate data in 15 priority countries and a fully integrated DHIS2 system across TB, HIV and malaria by 2020 in 6 priority countries ; Malawi, Myanmar, Pakistan, Tanzania, Uganda and Zimbabwe (Table 2).

Table 2: Countries supported for implementation of the DHIS2 TB module for aggregate

TB data under the WHO HTM Joint Data Collaborative

3 World Health Organization. Definitions and reporting framework for tuberculosis – 2013 revision (updated December 2014) (WHO/HTM/TB/2013.2). Geneva: WHO; 2013 (www.who.int/iris/ bitstream/10665/79199/1/9789241505345_eng.pdf, accessed 2 August 2017)

2. Implementation phase of the WHO

DHIS2 TB module

Country

R&R forms aligned with

2013 WHO case

definitions

R&R forms aligned with

WHO DHIS2 module

(level of disaggregation)

HMIS & NTP

cooperating

SOPs for R & R and

supervision which includes

DHIS2 -> shared with TME

Status (interest/recommended,

planned, ongoing, completed)

DHIS2 general

training for the

HMIS/NTP

responsible

TB data analyses and

use workshop (planned

or date completed)

Detailed follow up

plan including funding

(roll out, cascade

training, etc) -> shared

with TME

Implementation of

the key outputs

from the workshop

Clear roles and

responsabilities

between the NTP

and HMIS

including funding

Bangladesh interest

Benin ongoing planned Q3 2018

Burkina Faso planned

Cote d'Ivoire planned planned Q3 2018

DRCongo planned planned Q3 2018

Ghana planned

Guinea ongoing done Q4 2017

Indonesia ongoing planned Q3 2018

Liberia planned planned Q3 2018

Malawi planned

Mozambique planned

Myanmar planned

Pakistan ongoing done Q2 2017

Senegal

Sierra Leone ongoing

Sudan ongoing?

Tanzania planned

Uganda planned

Zambia

Zimbabwe planned

Priority

Substitute

1. Pre - implementation phase (TA from WHO) 3. Training / Workshop 4. Post - implementation phase

https://www.dhis2.org/overviewhttps://tbhistoric.org/https://www.healthdatacollaborative.org/http://www.who.int/iris/

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Figure 7: WHO DHIS2 Health Apps; standards for measurement, cross-cutting and

programme specific modules

Four countries have already implemented their own TB module in DHIS2 and support is also being given to optimise the functionality and use of these modules; Ghana, Guinea-Bissau, Liberia and Tanzania. Furthermore, GTB/TME are working with an additional 24 countries who have requested support for implementation of the DHIS2 TB module for aggregate data. So far the WHO DHIS2 TB module for aggregate data (tbhistoric.org) holds and safeguards historical data at regional or district level in a total of 38 countries (Figure 8). These data can be easily transferred into national DHIS2 databases once these are adopted and implemented.

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Figure 8: Subnational data stored in the DHIS2 platform developed by WHO (status March

2018)

A DHIS2 TB module for case-based data has now also been developed by GTB/TME and University of Oslo, to capture data on both drug susceptible and drug resistant TB cases. Data can be entered at the clinic or also by the laboratory allowing the capture of multiple lab records linked to one patient. This module is in user testing phase and will be piloted in Laos (all TB cases) and Benin (DR-TB cases).

3. Coverage of national notification system of TB cases

In countries with state-of-the-art national surveillance systems, where most, if not all, new TB cases are diagnosed and registered, the number of notified TB cases provides a good proxy for TB incidence. In many countries, however, under-reporting of detected cases as well as under-diagnosis mean that there are gaps between the number of notified TB cases and TB incidence.

National TB inventory studies can be used to quantify at least one of these gaps – the level of under-reporting – and in turn can inform better estimates of TB incidence as well as the actions needed to minimize levels of under-reporting. If certain assumptions are met, results can also be used to estimate TB incidence using capture–recapture methods.4

Countries in which a national inventory study has been implemented since 2000 are shown in Figure 9. Progress in 2016–2018 includes the completion of a study focused on the underreporting of TB cases in children in Pakistan, and completion of fieldwork for the first-ever such studies (covering adults and children) in Indonesia and Viet Nam, Final results from these three studies are now available and will be presented on Day 1 of the meeting. National studies in Denmark, the Netherlands and Portugal are also under way as part of a project funded by the European Centre for Disease Prevention and Control, and a study protocol is being developed for a study in South Africa, while discussions are under way in Mongolia.

Another important step in addressing under-reporting of cases into national TB surveillance systems is the legal framework to make the notification of all TB cases mandatory for all health

4 World Health Organization. Assessing tuberculosis underreporting through inventory studies. Geneva: WHO; 2012 (http://www.who.int/tb/publications/inventory_studies/en/, accessed 20 April 2018).

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care providers who diagnose and treat TB. Three country examples from Indonesia, Myanmar and Pakistan where such a framework is currently being implemented will be presented on Day 1 of the meeting.

Figure 9: Countries in which national inventory studies of the under-reporting of

detected TB cases have been implemented since 2000 (status March 2018)

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Appendix 1: Checklist for TB surveillance and vital registration systems; full list of standards and associated benchmarks

STANDARD BENCHMARKS

TB surveillance system data quality

B1.1. Case definitions are consistent with WHO guidelines

All benchmarks should be satisfied to meet this standard: • Laboratory-confirmed cases are distinguished from clinically diagnosed cases • New cases are distinguished from previously treated cases • Pulmonary cases are distinguished from extrapulmonary cases.

B1.2. TB surveillance system is designed to capture a minimum set of variables for all reported TB cases

Data are routinely collected for at least each of the following variables for all TB cases: • Age or age group • Sex • Year of registration • Bacteriological results • History of previous treatment • Anatomical site of disease • For case-based systems,

B1.3. All scheduled periodic data submissions have been received and processed at the national level

For paper-based systems: • 100% of expected reports from each TB BMU have been received and data aggregated at the national level For national patient-based or case-based electronic systems that import data files from sub-national (e.g. provincial or regional) electronic systems: • 100% of expected data files have been imported.

B1.4. Data in quarterly reports (or equivalent) are accurate, complete, and internally consistent (For paper-based systems only)

All benchmarks should be satisfied to meet this standard: • Sub-totals of the number of TB cases by age group, sex and case type matches the total number of reported TB cases in ≥95% of quarterly reports (or equivalent) from BMUs

• The number of TB cases in ≥95% of quarterly reports (or equivalent) matches the number of cases recorded in BMU TB registers and source documents (patient treatment cards and laboratory register) • Data for a minimum set of variables are available for ≥95% of the total number of reported TB cases in BMU TB registers.

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TB surveillance system data quality

B1.5. Data in the national database are accurate, complete, internally consistent, and free of duplicates (For electronic case-based or patient-based systems only)

All benchmarks should be met to reach this standard: • Data validation checks are in place at the national level to identify and correct invalid, inconsistent and/ or missing data in the minimum set (Standard B1.2) • For each variable in the minimum set (Standard B1.2), ≥90% of case records are complete, valid and

internally consistent for the year being assessed •

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TB surveillance system coverage

B1.8. All diagnosed cases of TB are reported

Both benchmarks should be satisfied to meet this standard: • TB reporting is a legal requirement • ≥90% of TB cases are reported to national health authorities, as determined by a national-level

investigation (e.g. inventory study, conducted in past 10 years). B1.9. Population has good access to health care

Both benchmarks should be satisfied to meet this standard: • Under-five mortality rate (probability of dying by age 5 per 1000 live births) is

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Appendix 2: Detailed results from sixteen countries with repeat standards and benchmarks assessments of national TB surveillance

systems of TB cases and TB deaths

Country B1_1 B1_2 B1_3 B1_4 B1_5 B1_6 B1_7 B1_8 B1_9 B1_10 B2_1 B2_2 B2_3

Case

definitions Minimal dataset Reporting rate

Accuracy and

consistency

Electronic data

validation

Externally

consistent

Internally

consistent

All cases

reported

Access to health

care

Vital

registration Drug res TB-HIV Childhood TB

Botswana Met Met Met Partially met Partially met Met Partially met Partially met Partially met Not met Partially met Met Not met

Egypt Partially met Partially met Met Partially met Not applicable Met Met Partially met Not met Partially met Met Not met Not met

Ethiopia Met Met Partially met Not met Not applicable Met Partially met Not met Not met Not met Not met Met Not met

Ghana Partially met Partially met Not met Not met Not applicable Met Partially met Partially met Not met Not met Met Met Not met

Indonesia Met Met Not met Not applicable Not met Met Partially met Not met Not met Not met Not met Not met Met

Kenya Met Met Not met Partially met Partially met Met Partially met Met Not met Not met Met Met Not met

Lesotho Met Met Met Partially met Not applicable Not met Not met Not met Not met Not met Met Met Not met

Madagascar Met Met Partially met Not assessed Not applicable Met Partially met Partially met Not met Not met Met Not met Not met

Myanmar Met Met Partially met Not assessable Not applicable Not met Met Not met Not met Not met Met Met Not met

Nigeria Met Met Met Partially met Not assessed Met Not met Not met Not met Not met Partially met Met Not met

Pakistan Met Met Partially met Not met Not met Met Not met Not met Not met Not met Met Not met Not met

Philippines Met Met Partially met Not met Partially met Met Not met Not met Not met Partially met Met Not met Not met

Rwanda Met Met Met Not met Not met Met Partially met Partially met Partially met Not met Met Met Not met

Swaziland Met Met Partially met Partially met Not applicable Met Partially met Not met Not met Not met Met Met Not met

Zambia Met Met Partilally met Partially met Not applicable Met Partially met Not met Not met Partially met Partially met Met Not met

Zimbabwe Met Met Met Not Met Not applicable Met Met Partially met Not met Not met Not met Met Not met

Previously met Improved Got worse No change

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Appendix 3: Monitoring progress with strengthening surveillance in Kenya through implementation of recommendations from repeat Standard and Benchmark assessments

*Colour coding for standards and recommendations columns: red = not met/implemented, orange = partially met/implemented, green = met/implemented

2013 Recommendations Implemented (Yes/No/Other) 2017 Recommendations

Recording and reporting B1.1 B1.1

B1.2 B1.2 Introduce a unique identifier

B1.3Develop automated report in TIBU

(unreported vs zero cases)

Other-Team actively follow up with

facilities that have zero cases B1.3Develop automated report/dashboard graphic in TIBU

(unreported vs zero cases)

Data quality B1.4National DQA and develop SOPs for data

quality checks for paper tools Yes B1.4

Refresher training on R & R; finalize data management

manual; develop data quality indicators that can be

monitored over time in TIBU; data entry staff required

at large facilities (hospitals)

Yes for IT suport and data validations

No for deduplicationB1.6 B1.6

B1.7

Routinely analyze data to monitor trends

for consistency over time (e.g quarterly

reports) and investigate unusual findings

Yes but paper aggregate reports are used

for management meetings and no

analysis at facility level B1.7

Quarterly reports should be produced by TIBU in a

standardised template for the facility level and shared

with facilities

Mandatory notification B1.8 Conduct an inventory studyYes; mandatory notification AND an

inventory study was conducted B1.8

Access to health care B1.9

Identify, map and assess barriers to

health care for high risk groups; identify

% undiagnosed in prevalence survey

Prevalence survey was completed after

2017 and current exercise of identifying

barriers is ongoing using the new

intergrated approach

B1.9 Conduct catastrophic cost survey

Vital registration B1.10

Actively engage with development of

routine VR system using ICD-10 coding

which includes commuity and hospital

deaths

Yes but VR system has 45% coverage and

no data sharing yetB1.10

CVRS and the NTP should compare data routinely in

quarterly review meetings and carry out a matching

study between case based datasets using probablistic

matching

Drug resistance B2.1 Conduct a DRS Yes B2.1

Increase GeneXpert and DST coverage to cover 100% of

retreatment cases with long term expansion to all

cases

TB-HIV B2.2 B2.2

Conduct operational research to understand reasons

why some TB-HIV cases do not start on treatment with

ART or CPT

Childhood TB (under 5 yrs) B2.3Conduct an inventory study including

pediatric, private and NTP clinicsNo B2.3

Conduct an inventory study including pediatric, private

and NTP clinics, ensure R & R tools are in pediatric

wards and review guidance on diagnosis and treatment

of children under 5 years old

B1.5

Routine de-duplication and matching with LIMS,

GenXAlert, DR-TB and CVRS should be carried out

ideally using a unique identifier (B1.2)

Hire IT support for TIBU; resolve

duplicates in the system; add date

validations in TIBU

B1.5

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Appendix 4: Monitoring progress with strengthening surveillance in Indonesia through implementation of recommendations from repeat S&B assessments

*Colour coding for standards and recommendations columns: red = not met/implemented, orange = partially met/implemented, green = met/implemented

2013 Recommendations Implemented (Yes/No/Other) 2017 Recommendations

Recording and reporting B1.1 B1.1

B1.2

Introduce a unique identifier for patient

tracking, de-duplication and linkage with

other systems e.g HIV

Yes but completeness is poor B1.2

Change ID to mandatory field with option of ticking "not

available"; training of staff on how to complete this field;

introduce a common identifier to link TB and lab records

in the meantime

B1.3Focus on Papua and introduce continuous

training to address high turn over of staff

No-6 districts in Papua do not report,

25% of puskesmas do not reportB1.3

Automatically monitor timeliness and completeness of

quarterly reports received in SITT. Differentiate “0 TB

case” to “no report received”.

Data quality B1.4 National DQA

Other-Routine monitoring of

completeness and accuracy by district

wasors; supervisory checklist

B1.4No paper quarterly report forms now exist, electronic

system in place

B1.5Electronic system was in pilot phase and had

not gone live yetB1.5

Review and fix bugs; implement data validation rules;

recruit a dedicated project manager, IT/developer and

data manager for SITT; carry out routine de-duplication

(see B1.2); run data validation and completeness checks

at the national level and to produce outputs that can be

used by district TB wasors for data validation in the fieldB1.6 B1.6

B1.7Analyse SRS (VR) data, expand SRS to VR

systemYes-ongoing B1.7

Develop SOPs for data quality and verification including

data quality indicators (in SITT) that should be monitored

over time; assess workload of district wasors/dedicated

TB wasor required; build capacity at HMIS for data

validation and the NTP for routine data analysis

(workshop on data analysis and use)

Mandatory notification B1.8

Conduct an inventory study; advocate for

mandatory notification; expand models for

PPM

Yes; introduced mandatory notification

AND an inventory study was conducted

(after 2017)

B1.8

Access to health care Yes for expansion of health insurance

No for other recommendations

Vital registration B1.10 See B1.7 Yes-ongoing B1.10Expand SRS to VR system; additional analysis on TB-HIV

and TB-diabetes; probablistic matching of NTP data to Drug resistance B2.1 Conduct a DRS No but DRS is planned B2.1 Conduct a DRS

TB-HIV B2.2 Expand routine testing with high coverage Other-Some improvement B2.2Collabrate with HIV to link HIV and SITT data; actively

monitor completeness of this indicator in SITT

Childhood TB (under 5 yrs) B2.3Conduct an inventory study and link with

pediatric hospitals and clinics for reporting of Yes B2.3

Ensure R & R tools are in pediatric wards and improve

reporting to SITT

B1.9

BPJS MoH plan for expansion of health insurance

coverage; identify/map risk groups;assess barriers to

health insurance

BPJS MoH plan for expansion of health

insurance coverage; identify/map risk

groups;assess barriers to health insurance

B1.9

19

Appendix 5: Monitoring progress with strengthening surveillance in Pakistan through implementation of recommendations from repeat

S&B assessments

*Colour coding for standards and recommendations columns: red = not met/implemented, orange = partially met/implemented, green = met/implemented

2013 Recommendations Implemented 2016 Recommendations

Recording and reporting B1.1Planning to introduce the 2013 revisions

to the definitions and reporting

YesB1.1

B1.2Introduction of case-based data using an

electronic system is being planned.

YesB1.2

B1.3 Recommendation from 2016 already implemented

in 2017B1.3 Enter/import all historical district (even BMU) level TB data in DHIS2

Data quality B1.4 Not assessed B1.4

Put together a plan of activities to promote cross-fertilization and

communication. Consider bringing all “data” people under one

roof. Develop a routine analysis plan, informal monthly meeting to

review simplified data

B1.5Introduction of case-based data using an

electronic system is being planned.

High level meeting on DHIS2 implementation

occurred in 2017 and in 2018 work has started on

imlementation

B1.5

Under the coordination of HPSSIU bring all of TB, malaria, and HIV

departments together to discuss options (federal and provincial

levels); Implementation of DHIS2

B1.6

Large differences by province should be

exploredYes-ongoing

B1.6

Other- Good data management and TB data analysis

and use practices (workshops, courses, on-the-job

training)

Workshop on data analysis and use was carried out in

2017

Mandatory notification B1.8Federal legislation to mandate the

compulsory notification of TB; expand

No- Ongoing efforts to make TB notifcation

mandatoryB1.8

Mandatory notification of TB (legal requirements) and

recommendations for its successful implementation at all levels

Access to health care B1.9

Significant improvements in access to

primary and secondary health care which

are free at the point of care for TB

patients

Yes-ongoing B1.9

Conduct catastrophic cost survey; NTP vans with CXR and GX for

contact tracing, prisons (staff + prisoners), urban slums; Screening

of TB at maternal and child health sites (e.g. Greenstar’s 7,000

family planning providers); “PPM5” – data linkages within public

tertiary and secondary hospitals

Vital registration B1.10Vital registration of deaths by cause

would be desirableNo B1.10

Sample system in 1-2 districts; Pilot hospital TB minimally invasive

autopsy study

Drug resistance B2.1 DRS in 2013 (still valid) B2.1

TB-HIV B2.2

More extensive HIV testing of TB patients

with collection of data on HIV status is

needed; carry out a survey of HIV

seroprevalence among TB patients

Yes-ongoing B2.2 Yes-ongoing

Childhood TB (under 5 yrs) B2.3Improved diagnosis and reporting of TB in

childhood in both public and private Other- inventory study on childhood TB B2.3 Use childhood TB inventory study results (analysis ongoing)

B1.7

Vital registration of deaths by cause

would be desirable but long term

investment required

B1.7

TB surveillance data analysis and use workshop; mini provincial epi

reviews, with provinces and select districts (one of the data cross-

fertilization activities, will promote buy-in from provinces)