malaria monitoring and evaluation plan...

Monitoring and Evaluation Plan 2016-2020

National Malaria Contol Programme

Department of Public HealthMinistry of Health and Sports

The Republic of the Union of Myanmar

Department of Public HealthMinistry of Health and Sports

The Republic of the Union of Myanmar

National Malaria Control Programme

Monitoring & Evaluation Plan 2016-2020

Table of contents................................................................................................................... iList of acronyms................................................................................................................... ii 1. Introduction...................................................................................................................... 1 2. Goal and Objectives of National Strategic Plan (2016-2020)............................................... 1 3. Monitoring and Evaluation................................................................................................ 2

3.1 Indicator definitions and measurement....................................................................... 23.2 Routine data collection, analysis and reporting........................................................... 23.2.1 Data collection and reporting tools............................................................................. 23.2.2 Information flow and feedback mechanisms............................................................... 33.2.3 Infrastructures available for data capturing and reporting (paper-based system, computers, internet connections, etc.)......................................................................... 63.2.4 Information products, timeline, and target audience.................................................... 63.2.5 Information dissemination strategy............................................................................. 73.3 Evaluation, reviews, periodic surveys, surveillance and special studies......................... 73.3.1 Annual programme evaluation (internal).................................................................... 73.3.2 Periodic Malaria Programme Review (joint)............................................................... 73.3.3 Periodic surveys......................................................................................................... 83.3.4 Special studies........................................................................................................... 83.4 Data quality assurance mechanisms and related supportive supervision....................... 93.5 M&E coordination.................................................................................................... 113.6 Capacity building...................................................................................................... 133.7 Data Use for Decision-making and Communication................................................... 143.8 Reporting for M&E................................................................................................... 14

Annex 1. Programme indicator framework (PIF)................................................................... 15Annex 2. Performance Framework of M&E........................................................................... 41Annex 3. Tools for M&E....................................................................................................... 43

LIST OF TABLES and FIGURES

Table 1a. Tools for data collection (Transmission Reduction Phase)........................................ 2 Table 1b. Tools for data collection (Elimination Phase)........................................................... 3Table 2. Different tasks related to data at different levels.......................................................... 5

Figure 1. Routine data collection, recording, reporting, analysis and feedback.......................... 6

Table of contents

i

ACT Artemisinin-based Combination TherapyAIDS Acquired Immune Deficiency SyndromeBHS Basic Health StaffCD compact discDQA Data Quality Audit/AssuranceDOPH Department of Public HealthDHIS2 District Health Information System 2HA Health AssistantHIS Health Information SystemIRS Indoor Residual SprayingIP Implementing PartnerIR Insecticide ResistanceITN Insecticide Treated NetLLIN Long-Lasting Insecticidal NetMIS Malaria Information SystemMNMEC Myanmar National Malaria Elimination CommitteeMPR Malaria Programme ReviewM&E Monitoring and Evaluation M-HSCC Myanmar-Health Sector Coordinating CommitteeMoHS Ministry of Health and SportsNIMEMC National Independent Malaria Elimination Monitoring CommitteeNMCP National Malaria Control ProgrammeNSP National Strategic Plan NGO non-governmental organizationP. PlasmodiumPR Principal RecipientPIF Programme Indicator FrameworkQA Quality AssuranceRDT Rapid Diagnostic TestRAI Regional Artemisinin InitiativeRHC Rural Health CentreSOP Standard Operating ProcedureTSG Technical and Strategy GroupTB TuberculosisTMO Township Medical OfficerTPHD Township Public Health DepartmentTWG Technical Working GroupUNOPS United Nations Office for Project ServicesVBDC Vector Borne Disease ControlVHV Village Health VolunteerWHO World Health Organization

Acronyms and abbreviations

ii

1

1. Introduction

Monitoring and Evaluation (M&E) is a fundamental component of the National Strategic Plan for Intensifying Malaria Control and Accelerating Progress towards Malaria Elimination 2016-2020 (NSP). Through M&E, the programme’s results at impact, outcome, output and input levels can be measured to provide the basis for accountability and informed decision-making at both programme and policy level.

M&E is an essential feature of performance-based funding, and external funding partners such as the Global Fund to Fight AIDS, TB and Malaria (Global Fund) make a significant contribution to the national budget for malaria control and elimination in Myanmar. This document will help the country not only to track the progress of the programme’s interventions, but also to identify any deviation and take corrective actions. The M&E system ensures that data can be collected, processed and transformed into strategic information to allow informed decision-making at local, country, regional and global levels.

This M&E Plan should be read together with the NSP, which provides contextual information relating to Myanmar’s Health System (including its malaria information system), an analysis of the epidemiology of malaria, an assessment of the current malaria situation and a review of likely future trends for key indicators. It also describes all planned programme activities, including a detailed description of the strengthening measures planned to improve the current M&E system.

This Plan describes how the M&E system is run and provides a detailed description of each of the programme’s impact and outcome indicators. Information flow, feedback mechanisms and associated infrastructure are discussed and an overview of the evaluations, reviews, periodic surveys, surveillance and special studies that go together to support routine data collection is provided. Data quality assurance mechanisms, related supportive supervision, coordination and capacity building are presented.

This document has been developed by the National Malaria Control Programme (NMCP) in partnership with the World Health Organization (WHO), stakeholders and implementing partners. Key representatives of the broader Ministry of Health and Sports (MoHS) have provided strategic inputs where appropriate. The plan has been designed to support the critical need for a unified countrywide approach to malaria related M&E. All partners implementing malaria control and elimination activities will be required to comply with the guidelines herein in a timely and comprehensive manner.

2. Goal and Objectives of the National Strategic Plan (2016-2020)

The goal of the five-year strategy is to reduce malaria morbidity and mortality by 85% and 75% respectively by 2020 relative to 2015 baseline figures. In States/Regions where malaria transmission has been interrupted, the goal is to maintain malaria-free status and prevent re-establishment of local transmission.

Achieving these goals will put Myanmar on the path to eliminate Plasmodium falciparum malaria by 2025 (in-line with the urgent action required against multidrug resistance) and to eliminate all malaria from Myanmar by 2030.

The objectives of the national strategic plan are:

1. To reduce reported incidence of malaria to less than 1 case per 1,000 population in all States/Regions by 2020.

2. To interrupt transmission of falciparum malaria in at least 5 States/Regions by 2020 (i.e. Bago, Magway, Yangon, Mon, Mandalay).

3. To prevent the emergence of multi-ACT resistant P. falciparum in Myanmar.4. To prevent the re-establishment of malaria in areas where transmission has been interrupted.

2

3. Monitoring and Evaluation

3.1 Indicator definitions and measurementIndicators have been developed taking into account the current situation in Myanmar as well as Global and Regional malaria indicator frameworks developed by WHO and partners. A complete list of indicators at the impact and outcome levels, for both malaria control and malaria elimination, is presented in the Programme Indicator Framework (PIF) (Annex 1). The PIF provides the following details for each indicator:

Indicator type and numberIndicator nameDefinition (with Numerator, Denominator, Multiplier and Equation)Rationale/purposeBaseline valuesTarget valuesInterpretationData source – numerator and denominator (including method of measurement and measurement tool)Frequency of data collection/reportingEntity responsible for data collection

The PIF thus provides a detailed and unambiguous description of each programme indicator. This framework is to act as the sole source of indicator descriptions. The Global Fund ‘Modular Template’ for example should therefore refer its readers to the PIF for detailed indicator descriptions rather than repeating them in the performance framework itself. This ‘single source approach’ should avoid the type of confusion that commonly arises when changes are made to an indicator in one document, but these changes are not copied to the same indicator in all corresponding documents.

The performance framework (Annex 2) presents periodic targets for indicators at the impact and outcome levels for the period 2016 to 2020.

Indicators at the process level (inputs and outputs) are managed at the implementation level through measurement of progress against the targets presented in annual workplans.

3.2 Routine data collection, analysis and reportingThis section describes existing systems in place as well as plans to develop systems to collect data for measuring programmatic indicators. It includes a mapping of relevant data flow with feedback and provides details of planned dissemination and use of information products.

3.2.1 Data collection and reporting toolsThe data collection and reporting tools for the Transmission Reduction Phase and the Elimination Phase are summarized in tables 1a and 1b respectively. The data collection tools are presented in Annex 3.

Activity Tools

Early diagnosis and treatment (EDAT)

Malaria Case Register Monthly Report on Morbidity and MortalityMonthly Report on Laboratory Diagnosis and RDTsMonthly Report on Morbidity and Mortality of <5 and pregnant womenDeath investigation form

Malaria prevention Reporting formats for LLIN distributionReporting formats for ITN impregnationReporting formats for IRS

Entomological data Entomological monitoring records

Malaria epidemic Reporting formats for epidemics

Table 1a. Tools for data collection (Transmission Reduction Phase)

3

3.2.2 Information flow and feedback mechanisms

The information flow and feedback mechanisms for each indicator are described in detail in the PIF (annex 1). In Transmission Reduction Phase areas, hospitals, health facilities, reporting units and laboratories send their reports related to case finding and management to higher level on a monthly basis. These reports are based on the carbonless recording forms appropriate to each level in the health system, which include details of patient’s name, age, sex, address, type of population (migrant, resident), test results, and parasite species (annex 3). An annual compilation of the data generated is sent to higher levels at the end of each year. Epidemic reports are submitted immediately by phone, followed by paper report.

In Elimination Phase Areas, hospitals, health facilities, reporting units and laboratories are required to immediately notify to all higher levels of any confirmed malaria cases by phone, email or fax, followed by paper report. These reports include patient’s name, age, sex, address, type of population (migrant, resident), test results and species. The Township Health Assistant or focal point, together with Vector Borne Disease Control (VBDC) staff are required to go to the site of the reported case and conduct a case investigation, and if appropriate a focus investigation within 3 days of notification. Investigation findings are sent to State/Regional VBDC and copied to Central VBDC. State/Regional VBDC are responsible for reviewing investigation forms and sanctioning a response where appropriate within 7 days of notification. If new cases are identified during investigation and response, these cases are investigated and entered into the case investigation database. All investigations strictly follow standard operating procedures (SOPs).

Routine reporting against health facility/community indicators is generally based on Malaria Health Management Information System (HMIS) reports, which will be developed as follows:

Malaria case reporting

In the public sector, health staff at every level is responsible for recording details of all patients tested for malaria in carbonless registers at the time of testing. BHS and Implementing Partners (IP) staff are responsible for reviewing the registers of volunteers during monthly or quarterly volunteer meetings and providing feedback. They are also responsible for compiling data from their own registers and from volunteer registers, and for completing and submitting Health Management Information System (HMIS) reports to the TPHD.

Table 1b. Tools for data collection (Elimination Phase)

Type of facilities Tools

Central Level (State/Regional level for the period aiming for Subnational elimination)

National malaria case register: single database of all individual case and death information for detailed analysis and synthesis of epidemiological information and trends.

Public/private health facilities/hospitals

Malaria patient register: all malaria patient records which will reflect the case classification. Case investigation records. Death investigation records.Laboratory register.

State/Regional VBDC and Central VBDC

Foci investigation, classification, response register and records.

Entomological monitoring/ vector control records.

Tentative activity timeline

2016/2017 – in selected States/Regions and after 2020 for the whole country.

4

At the community level

In transmission reduction areas village level volunteers of NMCP and implementing partners use the NMCP Malaria Case Register (carbonless register) to capture their data. They submit two copies to their local Sub-centre every month (last week of the current month). In elimination areas every case will be reported within 24 hrs to the concerned Basic Health Staff (BHS). Routine reporting will continue at the end of the month as for transmission reduction areas. The concerned BHS will immediately inform the Township Public Health Officer if a case investigation is required.

In transmission reduction areas General Practitioners working at community level and other informal health care providers will use NMCP carbonless registers (under development) to capture their data and they will submit two copies to their local Sub-centre every month. In elimination areas every case will be reported within 24 hours to the concerned BHS and routine reporting will be at the end of the month.

It is important that feedback is provided at every level starting from community level. Feedback for VHVs for example, will be given during the monthly supervision meetings, which form an integral part of the community based case management intervention.

At the Sub-centre level

Data received from different sources will be entered into the malaria register by the BHS staff. Sub-centres will submit a copy to Rural Health Centre (RHC) level every month during monthly meetings at RHC.

At Rural Health Centre level

Health Assistants (HA) at RHC level will enter the report into the register and will send a copy to the Township (during monthly meetings of the Township Public Health Department - TPHD). Data verification and feedback will be done by HAs during monthly meetings with Sub-centre staffs at the RHC.

At Township level

The focal person at the TPHD is responsible for compiling data from RHCs, Sub-centres (including data from their volunteers) and from the Township Hospital. Data received from all sources (public, implementing partners and private sector) will be compiled and submitted to the State/Region within 15 days of the end of each month. Data will be entered into the VBDC’s access databases and uploaded to ‘Cloud Storage’ to be readily available at the State/Regional and Central level.

DHIS2

It has been planned to roll out the ‘District Health Information System 2’ (DHIS2) for HIV, TB and Malaria over the course of the next several years.

DHIS2 is a tool for collection, validation, analysis, and presentation of aggregate and patient-based statistical data, tailored to integrated health information management activities. DHIS2 was developed by the ‘Health Information Systems Programme’ (established by the University of Oslo) as an open and globally distributed process. The DHIS2 software is now used in more than 40 countries in Africa, Asia, and Latin America, and countries that have already adopted DHIS2 as their nationwide HIS software include Kenya, Tanzania, Uganda, Rwanda, Ghana, Liberia, and Bangladesh. The existing malaria access database will be linked to DHIS2 at central level first and then at State/Region and Township levels.

5

At Township level, data verification and feedback should be done by the focal person/ VBDC staff during monthly meeting to respective health staffs. Feedback for private sector providers will be given by the IP and/or public health department concerned.

At State/Regional level

The VBDC focal point at the State/Region level is responsible for compiling data from all Townships within the State/Region and for sending it to VBDC at Central Level. The compilation will be done online in access database and uploaded to Cloud Storage.

State/Regional Malaria M&E focal points are responsible for visiting health facilities and reconciling details recorded in facility registers with those reported, for providing feedback as appropriate, and for assisting with the transfer of reports to State/Region level where necessary.

At Central Level

VBDC at Central Level is responsible for reviewing data received from the States/Regions and providing feedback, and for sending monthly HMIS malaria datasets to the Health Information Section of the Department of Public Health (DOPH).

VBDC at Central Level compiles the relevant data for health facility indicators for monitoring and reporting purposes.

LLIN and IRS reporting

Reporting of non-health facility indicators (e.g. those relating to LLINs and IRS) is generally based on implementation reports. In these cases, data flows up from implementation teams to VBDC at Central Level, via the VBDC focal point at the State/Region and Township level with respective reporting formats.

VBDC at Central level compiles the relevant data for non-health facility indicators for monitoring and reporting purposes.

Details regarding the frequency of reporting and entities responsible at each stage are presented against individual indicators in the PIF (annex 1).

Table 2. Different tasks related to data at different levels

Level of Health Interventions Tasks of Data

Community level Monthly Reporting of routine data in malaria case register (both in transmission reduction and elimination phase) as mentioned under 3.2.2. Reporting within 24 hours of case based data in elimination areas as mentioned under 3.2.2.Reporting of non-routine data such as LLIN distribution

Township Public Health Department

Reporting of non-routine data such as training of BHS Monthly aggregation and computerization of routine data as described under 3.2.2 Aggregation of other non-routine data

State/Regional VBDC office

Aggregation & computerization of routine data from malaria registers from reporting units as described under 3.2.2Aggregation of non-routine data reported from townships

Central VBDC Aggregation & computerization of routine data sent from State/RegionAggregation of non-routine data sent from State/Region

6

3.2.3 Infrastructures available for data capturing and reporting (paper-based system, computers, internet connections, etc.)

Most data collection is paper-based at health facility level. Internet and computers are available at State/Region level and also in some Townships. HIS data is generally entered into a computerized system at State/Region level (and sometimes Township level) into an Access database (in the process of converting from Excel to Access) and thereafter it is transferred up to the reporting chain electronically. At State/Region and Central level data is stored on compact discs (CDs) and in Cloud Storage. All programmatic and financial data are maintained for eight years for review and audit purposes. The data management SOP provides clear instructions on data management including storage.

3.2.4 Information products, timeline, and target audience

Results for indicators that are dependent on surveys for data collection will be reported in the annual report following each survey. Both three monthly and annual reports will be shared with implementing partners and with WHO and other implementing partners.

Additional information products based on the data collected above may be developed on an ad hoc basis according to findings and according to programmatic needs.

Figure 1. Routine data collection, recording, reporting, analysis and feedback

Implementing partners and Private sector

Implementing partners (field)

National DHIS2

Township focal person Data Assistant

State/Region focal person Data Assistant

Central NMCP/ WHO Data section

NMCP - VHW

Health facilities (sub-centre level)

Google Drive

7

The resulting products may take the form of publications for dissemination amongst the scientific community, concept notes and components within funding applications targeting donor agencies, briefing documents for political advocacy, and glossy brochures, banners, press releases or items for radio and television for changing public behaviour in relation to malaria.

3.2.5 Information dissemination strategy

Information will be disseminated in a number of ways according to needs. NMCP will take overall responsibility for ensuring that data is analysed and interpreted appropriately and that the resulting information is used effectively to ensure that any necessary action is taken promptly thereby maximizing programme performance and impact. Data will be analysed and used at the local level (Sub-centre, RHC and Township level). WHO, UNOPS and other partners will provide assistance as required.

3.3 Evaluation, reviews, periodic surveys, surveillance and special studies

Regular evaluation is important to ensure the effectiveness and efficiency of the programme. Important considerations include how much the program costs per beneficiary, how the program could be improved, whether the program’s strategies/approaches are appropriate, whether there are better alternative strategies/approaches, if there are unintended outcomes, and whether the program goals are appropriate and useful. The main forum for evaluation activities is the annual evaluation meeting conducted at Central, and State/Regional levels. These internal evaluations are supplemented by external reviews carried out every 3 years. In addition, periodic surveys and special studies are carried out to answer specific questions as required.

3.3.1 Annual programme evaluation (internal).

Internal evaluation meetings covering all aspects of the Programme will be held annually. An assessment of M&E (based on established tools) will form an important component of these meetings.

Annual evaluation and planning meeting at Central level: the annual evaluation and planning meeting at central level will be organized by VBDC. The participants will include: Central VBDC Programme staffs, State/Regional VBDC Team Leaders and Malaria Assistants, Township Medical officers and representatives from partner organizations. The key purpose of the meeting will be to:

present and discuss data from all partnerspresent and discuss activities done by all partnersidentify gaps and strengthening measuresstrengthen coordination and information sharing share best practicesplan for the coming year

Annual evaluation and planning meeting at State/Divisional level: The annual evaluation and planning meetings at State/ Regional level are organized by the State/Regional Officer/ Team Leader of VBDC. The participants will include: VBDC staff from State/Regional and Township levels, Township Medical Officers (TMOs) and partner organizations. The purpose is similar to that for the central level but the discussion will be more focused on the situation in the Townships and guidance will be given from the central VBDC as needed.

3.3.2 Periodic Malaria Programme Review (joint).

A joint review conducted by a team made up of external evaluators and programme stakeholders covering all aspects of the national malaria control and elimination effort (covering a representative range of implementing partners) will be conducted every 3 years. As with the internal reviews, an assessment of M&E will form an important component of these evaluations and this will be highlighted in the evaluation team’s terms of reference.

8

Joint Malaria Programme Reviews (MPR) are important for accountability purposes. The Global Fund for example places increasing emphasis on health outcomes and impact, demonstrated through program reviews and evaluations, as a condition for renewing grant funding. Joint MPRs meet external demands for demonstrating quality, quality assurance and quality enhancement. They can also enhance the reputation of the programme and thus act as an important tool to support national resource mobilization and applications to funding partners. This will be conducted by WHO with support of NMCP and other IPs.

3.3.3 Periodic surveys.

Surveys are useful tools for gathering primarily quantitative information about target populations of interest, which are not otherwise accessed through routine reporting or surveillance. A survey may focus on opinions or factual information depending on its purpose, and many surveys involve questioning individuals. They can be resource intensive if a large sample size is needed to ensure wide representation. Smaller surveys that are qualitative in nature are useful for obtaining answers to specific inquiries.

Population-based surveys are a key part of collecting some of the necessary data for constructing many of the important indicators for a project. These community and health facility-based surveys are designed by experts in the NMCP in consultation with WHO and technical partners. Where possible the surveys, and associated data entry and analysis, are carried out by teams formed from health staff from various levels in the Public Health network but where appropriate they are contracted out to technical partners.

Periodic surveys carried-out include target population, health facility and drug outlet surveys:

Target population surveys include household surveys and surveys targeting specific risk groups such as seasonal agricultural labourers and cross-border migrants. In each community a representative random sample of households/individuals will be interviewed using group specific questionnaire forms. Indicators measured by means of data collected during household surveys for example include: ‘VHV utilization rate’, ‘Bednet utilization’ (overall and amongst forest goers), ‘ ITN coverage rate’ (survey required for indicators mentioned in PIF)’.

Health facility surveys are usually conducted periodically. A representative sample of health facilities in target areas will be selected. Data collection forms and checklists have been developed in order to obtain accurate information on various indicators including the core indicator ‘Stock-out rate’ (for diagnostics and for antimalarials).

Drug outlet surveys are carried out periodically to monitor levels and trends in the availability, price and volumes of antimalarials, and providers’ perceptions and knowledge of antimalarial medicines at different outlets. Price and availability data on diagnostic testing services is also collected. The surveys are based on a standard protocol developed by the ‘ACTwatch’ project. A nationally representative sample of all private outlets with the potential to sell or provide antimalarials to a consumer is taken covering both urban and rural domains and both project intervention and control areas.

3.3.4 Special studies.

Insecticide resistance monitoring studies. Existing information on the resistance status of the main malaria vectors in Myanmar is patchy and country-wide comparable resistance data are required to make informed decisions on the correct use of insecticides in malaria vector control. Close monitoring of insecticide resistance will continue to be carried out at sentinel sites. Every year the programme will conduct regular entomological surveillance and insecticide resistance (IR) monitoring surveys in 7 of 14 sentinel sites (7 sites/year) and ad hoc surveys in additional sites in outbreak areas where IR may be responsible for the outbreak and in areas at high risk of IR (e.g. areas with high agricultural pyrethroid use). Resulting data will be shared with WHO and technical partners. If insecticide resistance is found its operational significance will be assessed and a suitable response will be developed as required.

In addition to routine IR monitoring, the residual efficacy of insecticide on LLIN and the durability of the nets themselves will be monitored. Bioassays will be conducted checking mortality amongst various target mosquito vectors exposed to insecticide-treated nets and sprayed surfaces.

9

The programme will conduct regular drug resistance monitoring for P. falciparum at 6 of 11 sentinel sites each year as well as regular in vitro assessments of parasite sensitivity to range of antimalarials. The programme will also support drug resistance surveillance based on genetic epidemiology. Monitoring drug resistance in P. vivax will be carried out in parallel where feasible.

There are currently 11 sentinel sites in Tanintharyi Region, Mon States, Eastern Shan State, Northern Shan State, Chin State, Kachin State, Kayin State, Rakhine State, Sagaing Region, Mandalay Region and in Bago Region. They are being monitored every other year by expert teams from the Department of Medical Research (including Pyin Oo Lwin branch) and the Defense Services Medical Research Unit.

The programme will also carry out special clinical fieldwork in outbreak areas and in areas where treatment failure is suspected.

The data from these routine and ad hoc monitoring sites provide essential information that feeds into decision-making for both the national programmes and the Regional approach to the elimination of multi-drug resistance (including ACT resistance). The information generated will be used to update national treatment guidelines as appropriate.

Other special studies that are planned include drug outlet surveys, drug quality surveillance, surveys in support of village-wise malaria risk stratification and an assessment of patient compliance to the 14-day course of primaquine for vivax malaria.

3.4 Data quality assurance mechanisms and related supportive supervision

The role of a data quality assurance (DQA) system is to validate the quality of data and thereby provide information on possible needs to improve the reporting system and help inform decision makers on the extent to which data can be relied on to plan future interventions. DQA is different both in methodology and purpose from programmatic quality assurance. It is not the role of DQA to look at whether the programme implementation is according to the plan or if the target is reached. Instead, DQA focuses only on the quality of the recorded, reported and aggregated data and seeks to quantify any errors.

There are different dimension of data quality. To ensure appropriate targeting and planning it is crucial that data is precise, complete, timely, reliable and accurate. Furthermore, it is important that the data has integrity to be considered credible.

Reports will be thoroughly checked at every level of the reporting chain to ensure accuracy and completeness. Necessary clarifications will be sought and corrections made as required and within the strict timeframes set out for reporting in the relevant standard operating procedures. The DQA system consists of five different components:

Logical cross-check of data Re-aggregation at the State/Regional and Central level dataField visit to Townships and reporting units for DQAEnsuring adequate storage of dataIdentification of training needs

a) Logical cross-check of data The data recorded and computerized will be checked monthly for inconsistencies, such as an unlikely number of drugs used compared to the number of patients, and feedback will be given to the Townships. A standard list of logical tests will be developed to ensure consistency and easy reporting.

b) Re-aggregation at the State/Regional and Central levelQuality checks of the aggregation and computerization of routine data at the State/Regional level will be done quarterly either by visiting central level VBDC staff or by the State/Regional VBDC staff.

10

The check will be done by randomly choosing one or two Townships1 in the State/Division and re-aggregating all reported data from the reporting units in these Townships. The results will be reported to the central level as:

The number of reporting units where the aggregation for a given recorded data item was wrong compared to the total number of reporting units checked.The total accumulated error for a Township for the selected dataset

Quality check of the aggregation of non-routine data will be done at the same time as the quality check for the routine data if applicable (i.e. if activities such as training, LLIN distribution or ITN impregnation have occurred in the past quarter). The results will be reported as:

The total number of recorded trainees trained/LLINs distributed/ITN impregnated versus the number reported.

Standard forms will be developed together with detailed guidelines to enable easy and consistent reporting of the findings.

c) Field visits for DQAField visits will be conducted in order to get information on the quality of the data recorded and reported. Field visits aimed at assessing the data quality should be random, meaning that all Townships/ reporting units should have equal likelihood of being visited. However, as resources for DQA are limited, the majority of the DQAs will be done as part of the regular supervision visits to the Townships and reporting units.

At the Township level the following checks will be done:

Appropriate storage of dataRoutine data from one month will be chosen and checked to see if the required data items are recorded or not.Reported stock will be checked against the stock-book and actual stock in store. If training has occurred then staff on the training list will be asked if they have received the reported training.

At the reporting unit/Community level the following test will be done:

A selection of malaria patients listed will be tracked-down and interviewed and the information recorded for them will be verified.Reported stock will be checked against the stock-book and actual stock in store. If for instance LLIN distribution has happened, a random sample of beneficiaries will be asked if they have received LLINs as reported

d) Ensuring adequate data storageAdequate storage of data at all levels is important to ensure that data are available for validation. Ensuring that data are stored correctly is done through provision of clear instructions and supervision visits.

e) Identification of training needsThe components listed above will inform the programme of any problems and help identify any training required to resolve issues.

For areas entering the elimination phase, new indicators and associated norms and requirements will be described clearly in SOPs and supervisors will be thoroughly trained to conduct elimination specific DQAs. The principles of DQA will be the same but the methods may differ somewhat.

Development and utilization of tools, guidelines and checklists for data quality assurance, assessments and for supervision: Standardized tools, guidelines and checklists have been developed for Control Phase operations and are being used. These are based on established formats but have been simplified where possible to

1 Number of Townships checked depends on the number of reporting units in the Township. The aim is to check the aggregation of 30-40 Service Delivery Points (SDPs).

11

minimize workload for peripheral staff without compromising the value of the data gathered. Tools, guidelines and checklists specific to Elimination Phase operations will be developed as part of the process to upgrade the HIS in-line with the requirements for malaria elimination.

Supportive supervision for M&E and data quality: M&E activities are part of a broader supportive supervision approach, which uses a series of short checklists to foster improvements in service delivery. Supportive supervision is a process of helping staff to improve their own work performance continuously. It is carried out in a respectful and non-authoritarian way with a focus on using supervisory visits as an opportunity to improve knowledge and skills of health staff. Supportive supervision encourages open, two-way communication, and building team approaches that facilitate problem-solving. It focuses on monitoring performance towards goals, and using data for decision-making, and depends upon regular follow-up with staff to ensure that new tasks are being implemented correctly. The checklists help supervisors to organize their work and provide effective technical guidance. Recipients of this supervision find the process motivating, because it helps them to prioritize their problem solving activities.

The programme will implement supportive supervision at every level of the network. Central level staff (Programme Manager, Assistant Director and Assistant Malariologist) will visit each State/Region annually in the Transmission Reduction Phase and quarterly in the Elimination Phase; State/Regional level supervisors will supervise and monitor all targeted Townships at quarterly in the Transmission Reduction Phase and monthly in the Elimination Phase; Township level supervisors will supervise lower level health facilities on a quarterly basis; and peripheral health staff, sometimes supported by Township level staff, will monitor field level activities and community-based volunteers through a mixture of monthly health facility meetings and ad hoc field visits. Priority will be given to weak volunteers and those failing to report for 2 consecutive months.

3.5 M&E coordination

This section describes the M&E coordination mechanisms in place and includes a brief overview of management structures and roles.

M&E coordination mechanisms

Although malaria control is primarily the responsibility of VBDC, several Implementing Partners (26 recently) complement national efforts. The structures and roles within VBDC are defined so as to strengthen M&E coordination within VBDC and among the partners to ensure standardized tracking and gauging of the national response to malaria control. However, the structures and roles are dynamic and are adjusted/ modified from time to time according to needs. In 2013 Myanmar transformed the ‘Myanmar-Country Coordinating Mechanism’ into the ‘Myanmar Health Sector Coordinating Committee (M-HSCC)’ to govern health matters with broader and more transparent consultations and discussions both within the government sector and with development partners. The M-HSCC takes a leading role in coordination of both governmental and non-governmental sectors.

The Myanmar National Malaria Elimination Committee (MNMEC) was formed in November 2015 to oversee elimination activities. Its roles and responsibilities are described in detail in section 4 of the National Strategic Plan (NSP) for Intensifying Malaria Control and Accelerating Progress towards Malaria Elimination, 2016-2020. Key responsibilities include monitoring progress and coordination. Within the MNMEC there is a ‘Working Group’ and an ‘Executive Working Group’. Again, their roles and responsibilities are described in detail in section 4 of the NSP.

Technical and Strategy Groups

Technical and Strategy Groups (TSGs) are bodies that have been established for each of the diseases (HIV, TB and Malaria) and thematic areas and given a mandate by the M-HSCC to provide technical guidance in the development of the specific national strategies, to provide coordination among partners, and to provide clarity on major technical and policy issues.

12

The TSGs are also in the position to meet to discuss, review and endorse certain proposals, reports and other documents and carry out the assignments given to them and provide broad oversight of the implementation of grants and projects as required, such as Global Fund grants. All formal activities/meetings are documented and reported to the M-HSCC Secretariat.

A Malaria TSG comprising the NMCP and various implementing partners is responsible for overall technical review and coordination across organizations. The member secretary of the TSG is WHO (Malaria Unit). The TSG will support the development of an enabling environment for executing malaria M&E activities in-line with the elimination strategy. Activities will include: Establishment of a ‘National Independent Malaria Elimination Monitoring Committee’2 (NIMEMC), updating legislation in support of malaria elimination and introducing mandatory notification of all malaria cases in elimination States/Regions.

This NIMEMC will be formed in 2017. It will include members with expertise in epidemiology, malariology, entomology and malaria research, a Technical Officer from WHO, one or two representatives from NGOs/INGOs with malaria elimination expertise, persons working in other public health fields, representative from the Epidemiology Unit (Department of Public Health) and a senior physician from the University of Public Health. The committee will be responsible for organization, management and maintenance of the malaria elimination database and for quarterly monitoring of performance relating to malaria elimination. It will provide technical guidance to DOPH, NMCP and if necessary to MoHS. Periodic data audits will be performed to ensure completeness and accuracy of records.

Updating legislation and introducing mandatory notification are essential for the implementation of malaria elimination activities.

The M&E Technical Working Group (TWG) is formed under TSG to provide specific guidance on M&E and ensure coordinated M&E action across partners. The M&E TWG will meet quarterly and on an ad hoc basis as required and will be responsible for:

Updating and harmonizing data collection forms to be used at all service delivery points (health facilities, laboratory service points, private sector outlets, community settings etc.).

Strengthening the health information system to capture data from all sources (the public, non-governmental organization (NGO) and private sector), in order to have comprehensive information on the malaria situation. Partner organizations will be required to submit data at the Sub-centre/Township level on a monthly basis in transmission reduction areas. This data will be transmitted by the Township to the higher levels for consolidation.

Organization of quarterly review meetings and annual review and planning meetings together with other partners at Township level. These meetings will discuss progress and performance, programmatic and coordination bottlenecks and gaps, data quality and capacity building issues and identify corrective measures where appropriate. The annual planning meetings will discuss the annual plan and joint actions, as appropriate. These meetings will serve as important platforms for strengthening linkages and networking across public and non-public sectors. Selected peripheral level staff (Sub-centre/rural health centre staff), nurses/midwives and the NGO representatives will participate in these meetings. Participants will be selected on a rotational basis and efforts will be made to ensure that they provide a representative mixture in terms of performance.

Organization of annual review and planning meetings at central level. The participants will include: State/Region, Township officers and representatives from partner organizations.

Biennial monitoring missions for programme review to be undertaken jointly with partners and external technical agencies.

M&E procedures will also be reviewed as necessary during routine monthly meetings in the periphery. Monthly meetings in the periphery will have a broad focus covering a range of issues and challenges relating to malaria control/elimination and other health related activities.

2 WHO-2007- Malaria Elimination: A Field Manual

13

An assessment of M&E will form an important component of all planned internal and external programme evaluations.

Global Fund may conduct an external data quality audit (DQA) at any stage during the term of any Global Fund grant.

Alignment and harmonization on indicators, information/report flows, reporting timeline etc.

The indicators presented in this document have been developed in close collaboration with MoHS. They are fully in-line with the requirements of the HIS.

Reporting flows and timelines are presented for each indicator in the PIF (Annex 1).

3.6 Capacity building

Capacity development of staff on programmatic areas is an ongoing activity under VBDC. The country strategic plan includes training/ capacity building of Township level staff using a comprehensive curriculum including M&E.

For strengthening M&E, review of existing capacity of the staff and infrastructure and a rapid capacity needs assessment will be carried out across Townships, State/ Region and central levels of the programme and will be translated into a M&E training plan for the target group. The purpose is to institutionalize M&E capacity within the VBDC. Subsequently, capacity building plans including learning objectives based on needs assessment, agenda, modules, facilitator guides, pre- and post-tests, checklists for overall assessment of trainees and trainers will be developed centrally and disseminated at State/Region and Township levels for use. Necessary technical support will be sought from the partner organizations.

The M&E training sessions will be tailor made for specific target groups. Overall, the learning areas will focus on the following:

M&E fundamentals, the need for M&E for optimal performance Designing M&E planM&E framework Routine data recording, reporting, aggregation, analysisData dissemination and use (generation and use of information products, organization of cross learning workshops, etc.) for planning, decision making and resource allocationEvaluation, Studies, Research Data sources and data collection/ reporting tools for various interventions and health system strengthening (training, etc.)—registers/ forms/ records/ reports for routine and non-routine data; checklists/ questionnaire for supervision, evaluations, studies, surveys Data flow (vertical, lateral) within and across public sector, other partnersData quality assurance, auditNational District Health Information System 2 (DHIS2) and its linkages with the VBDC Computer assisted data entry, analysisImplementation challenges of M&E

All training related documents (e.g., attendance sheets, course outline with learning objectives, reports, etc.) will be kept safely and securely and made available for review and auditing purposes, as needed.

Further to trainings on M&E, during the stakeholder workshops and meetings that are held periodically, feedback from the trainees as well as supervisors/ observers will be shared. These platforms will also be utilized for brainstorming to improve ongoing programmatic and M&E training programmes. Coordination mechanisms within VBDC and between partners will ensure that activities are not duplicated.

14

3.7 Data Use for Decision-making and Communication

Communicating results (Reporting, Dissemination and Provision of feedback): VBDC will document and disseminate to relevant partners (National, State and local) the lessons learned from malaria control programme activities. In collaboration with partners, it will use standardized and participatory methodology to monitor, assess and improve performance in both public and private sectors.

3.8 Reporting for M&E

The Malaria control/elimination results will be reported in Annual NMCP Reports, Global Fund reports and other donor reports. The results will also be included in the WHO’s annual World Malaria Report.

15

ANNEXESAnnex 1. Programme indicator framework (PIF)

Impact Indicators1. Annual Parasite Incidence (API)

Indicator name: Annual Parasite Incidence

Definition: Number of confirmed malaria cases per 1,000 mid-year population (per year). Reported from all sources (disaggregated by parasite species and by source - State/Region, Township).

Numerator (N): Number of parasitologically confirmed malaria cases reported from all sources during the reporting period.

Denominator (D): National mid-year population at risk.

Multiplier (M): 1,000

Equation: =(N/D)xM

Rationale/Purpose: API is the most important criterion to assess the progress of a malaria programme. API is the most broadly applied measure of risk of infection. It is a core measure of risk of infection. It is used as the basis for comparing risk between communities, districts, provinces, and nations.

Baseline value: 4.16/1000 pop at risk in 2015.

Target value: <1/1000 pop at risk in 2020 and 0 by 2030. By State/Region: API <1/1000 pop at risk by 2018 in 5 States/Regions; API 0/1000 pop at risk by 2018 in 5 States/Regions.

Interpretation: Falling API suggests that control/elimination efforts are effective.

Data source (numerator): Patient registers for each group of service providers (health facilities, community level and private sector).

Data source (denominator): National mid-year population at risk estimate.

Method of Measurement: Review of patient registers.

Measurement Tool: Routine HIS.

Data collection frequency: a) Data collection by health facilities, VHVs and private sector providers is continuous.

b) Data is collected from VHVs during monthly meetings at health facility level.

c) Data collection from private sector providers occurs on site once per month according to a routine supervision schedule.

d) Transfer of all of this data to national level occurs once per month within 2 weeks of the end of the reporting period.

e) Results are published by NMCP annually. Preliminary results for any given year are available within 1 month of the end of that year. Final results are available (once any late reports have been received) within 3 months of the end of that year.

Reporting frequency: -

Table continues on the next page.

16

Entity responsible for data collection: 1. VHVs are responsible for:a) Recording details of all patients tested for malaria in

VHV registers at the time of testing. b) Submitting VHV registers to the nearest Health Centre

(HC) every month.

2. Private providers are responsible for: a) Recording details of all patients tested for malaria in

registers at the time of testing. Data collection from the private sector.

3. Public sector staff at Township level is responsible for: a) Reviewing private sector registers during routine monthly

supervision visits and providing feedback. b) Collecting and compiling private sector data.c) Completing and submitting reports to the State/Region

Health Department.

4. Health Centre staff at every level is responsible for: a) Recording details of all patients tested for malaria in

registers at the time of testing.

5. HC staff is responsible for:a) Reviewing VHV registers during monthly VHV meetings

and providing feedback.b) Compiling data from registers and VHV registers.c) Completing and submitting HIS reports to the Township

Hospital.

6. The focal person at the Township Hospital is responsible for compiling data from all health facilities in the Township.

7. The focal point within the Statistics Unit of the State/Region

is responsible for compiling data (from Township level) and for sending it to NMCP.

8. NMCP is responsible for: a) Reviewing data received from the Regions/States and

providing feedback. b) Sending monthly HIS malaria datasets to the MoHS.

17

2. Number of Severe Malaria Cases

Indicator name: Severe malaria case number

Definition: Number of confirmed severe malaria cases (per year).

Numerator (N): Number of parasitologically confirmed malaria cases admitted as in-patients in public sector health facilities.

Denominator (D): -

Multiplier (M): -

Equation: Absolute number.

Rationale/Purpose: Number of severe malaria case is key to assessing the effectiveness of efforts to improve access to quality healthcare services and promote early treatment seeking.

Baseline value: 660 in 2015.

Target value: 165 in 2020 and 0 by 2025.

Interpretation: Falling severe malaria case suggests that efforts to improve access to quality healthcare services and/or promote early treatment seeking are effective.

Data source (numerator): Hospital inpatient registers.

Data source (denominator): -

Method of Measurement: Review of hospital inpatient registers.

Measurement Tool: Hospital inpatient registers.

Data collection frequency: a) Data collection at hospitals will be continuous. b) Transfer of data to national level occurs once per

month within 2 weeks of the end of the reporting period.

c) Results are published by NMCP annually. d) Preliminary results for any given year are available

within 1 month of the end of that year.e) Final results are available (once any late reports have

been received) within 3 months of the end of that year.

Reporting frequency: Monthly

Entity responsible for data collection: Health workers at hospitals are responsible for:a) Recording details of all malaria admissions at the time

of admission in the inpatient register. b) The focal person at the Township Hospital is

responsible for collecting data. c) The focal point at the Statistics Unit of the State/

Region is responsible for compiling data (from Township and State/Region Hospitals) and for sending it to NMCP.

NMCP is responsible for:a) Reviewing data received from the States/Regions and

providing feedback. b) Sending monthly HIS malaria datasets to MoHS.

18

Indicator name: Malaria Mortality Rate

Definition: Number of deaths due to confirmed malaria per 100,000 mid-year population at risk (per year).

Numerator (N): Number of parasitologically confirmed malaria cases admitted as in-patients in public sector health facilities dying before discharge.

Denominator (D): National mid-year at risk population.

Multiplier (M): 100,000

Equation: =(N/D)xM

Rationale/Purpose: Mortality is a major component of the burden caused by malaria, and reducing malaria related mortality is a key aspect of the overall goal of malaria control efforts globally.

Baseline value: 0.08 in 2015.

Target value: 0.02/100,000 pop at risk in 2020 and 0 by 2025.

Interpretation: Falling malaria specific mortality rate suggests that control efforts are effective and, depending on changes in API, may suggest better access to early diagnosis and treatment and/or more effective treatment of severe malaria.

Data source (numerator): Hospital inpatient registers.

Data source (denominator): National at risk mid-year population estimate.

Method of Measurement: Review of hospital inpatient registers.

Measurement Tool: Hospital inpatient registers.

Data collection frequency: a) Data collection at hospitals will be continuous.b) Transfer of data to national level occurs once per

month within 2 weeks of the end of the reporting period.

c) Results are published by NMCP annually. d) Preliminary results for any given year are available

within 1 month of the end of that year. e) Final results are available (once any late reports have

been received) within 3 months of the end of that year.

Reporting frequency: Monthly

Entity responsible for data collection: Health workers at hospitals are responsible for:a) Recording details of all malaria admissions at the time

of admission in the inpatient register and for recording any malaria deaths (verified by audit).

b) The focal person at the Township Health Centre is responsible for collecting the data.

c) The focal point within the Statistics Unit of the State/Region is responsible for compiling data (from Township Hospitals) and for sending it to NMCP.

NMCP is responsible for:a) Reviewing data received from the States/Regions and

providing feedback.

3. Malaria Mortality Rate

19

Indicator name: Parasite composition

Definition: Percentage of malaria cases by species among parasitologically confirmed malaria cases treated in public, private and community health facilities.

Numerator (N): Number of cases for each species among parasitologically confirmed malaria cases reported from all sources

Denominator (D): Number of parasitologically confirmed malaria cases reported from all sources.

Multiplier (M): 100

Equation: =(N/D)xM

Rationale/Purpose: This is the standard indicator for measuring changes in species composition, which can support interpretation of other epidemiological trends.

Baseline value: Pf 64% in 2015.

Target value: Pf: 25% by 2020, 0% by 2025.

Interpretation: A falling percentage of cases due to P. falciparum provides a relatively robust indication of progress towards elimination of falciparum malaria.


Data source (denominator): Patient registers for each group of service providers (health facilities, community level and private sector).



Data collection frequency: Data is collected as described for API.


Entity responsible for data collection: Entity responsible for data collection is as described for API.

4. Percentage of cases disaggregated by Species

20

Indicator name: Annual Blood Examination Rate (ABER)

Definition: Number of parasitological tests carried out per 100 mid-year population at risk (per year).

Numerator (N): Number of parasitological tests carried out (data from all sources - health facilities, community level services and private sector providers).

Denominator (D): National mid-year at risk population.

Multiplier (M): 100

Equation: =(N/D)xM

Rationale/Purpose: This is a proxy for the standard indicator for assessing the adequacy of case detection (the standard indicator is based on the number of people subjected to parasitalogical testing).

Baseline value: 6% in 2015.

Target value: 8% in 2020.

Interpretation: This indicator provides information on overall diagnostic activity (coverage) and can be useful in interpreting trends in malaria cases.


Data source (denominator): National at risk mid-year population estimate.





Entity responsible for data collection: Entity responsible for data collection is as described for API.

5. Annual Blood Examination Rate

21

Indicator name: Case classification - Target States/Regions

Definition: Percentage of cases by classification [by species and month]. Classified as indigenous, introduced, imported, relapse, recrudescence or induced.

Numerator (N): Number of cases investigated by classification [by species and month]. Classified as indigenous, introduced, imported, relapse, recrudescence or induced.

Denominator (D): Number of cases investigated [by species and month].

Multiplier (M): 100

Equation: =(N/D)xM

Rationale/Purpose: This is the standard indicator for measuring progress towards elimination at the impact level.


Target value: 80%, 40% and 10% (indigenous cases) in 2016, 2017 and 2018 respectively; and 80% and 40% (indigenous cases) in 2019 and 2020 respectively in elimination States/Region.

Interpretation: A falling percentage of indigenous cases indicates progress towards elimination.

Data source (numerator): Case investigation reports.

Data source (denominator): Case investigation reports.

Method of Measurement: Review of case investigation reports.

Measurement Tool: Case investigation database.

Data collection frequency: a) Case investigation is carried out by community and Township level health staff on a continuous basis.

b) Community level data is sent monthly to Township level and then on with Township data to State/Region level to arrive within two weeks of the end of the reporting period.

c) It is analysed at State/Region level and then a summary is sent to NMCP before the end of the month.


Entity responsible for data collection: a) Case investigation reports will be completed by trained health staff at peripheral and Township levels.

b) Data is compiled and analysed at State/Region level by the focal point at the Statistics Unit of the State/Region.

c) A summary report is submitted to NMCP.

6. Case classification rate (Elimination)

22

Indicator name: Foci classification - Target States/Regions

Definition: Percentage of foci by classification: active, non-active residual and cleared up [by species and month].

Numerator (N): Number of foci investigated by classification: active, non-active residual and cleared up [by species and month].

Denominator (D): Number of foci investigated [by species and month].

Multiplier (M): 100

Equation: =(N/D)xM

Rationale/Purpose: This is the standard indicator for measuring progress towards elimination at the impact level.

Baseline value: NA in 2015.

Target value: 80% in elimination States/Regions by 2020. 80%, 40% and 10% (active foci) in 2016, 2017 and 2018 respectively; and 80% and 40% (active foci) in 2019 and 2020 respectively in elimination States/Region.

Interpretation: A falling percentage of active foci indicates progress towards elimination.

Data source (numerator): Focus investigation reports.

Data source (denominator): Focus investigation reports.

Method of Measurement: Review of focus investigation reports.

Measurement Tool: Focus investigation database.

Data collection frequency: Focus investigation reports will be submitted to national level on a monthly basis within 2 weeks of the end of each reporting period. Data will be compiled by NMCP within 28 days of the end of each year.


Entity responsible for data collection: Focus investigation reports will be submitted to national level on a monthly basis within 2 weeks of the end of each reporting period. Data will be compiled by NMCP within 28 days of the end of each year.

7. Foci classification - Target States/Regions (Elimination)

23

Outcome Indicators1. Quality Microscopy Coverage rate

Indicator name: Quality microscopy coverage rate

Definition: Percentage of designated microscopy points participating in QA/QC management system as per the WHO QA/QC manual V2 2016.

Numerator (N): Number of designated microscopy points participating in QA/QC management system.

Denominator (D): Number of designated microscopy points.

Multiplier (M): 100

Equation: =(N/D)xM

Rationale/Purpose: Quality of microscopy can only be ensured if microscopy points participate in an effective QA/QC management system. This is particularly crucial in an elimination setting where positive blood films from patients become increasingly rare.


Target value: 80% by 2020.

Interpretation: Complete coverage with an effective QA/QC management system will maximize the quality of microscopy services.

Data source (numerator): Microscopy QA database (to be established).

Data source (denominator): Microscopy QA database (to be established).

Method of Measurement: Review of microscopy QA database (to be established).

Measurement Tool: Microscopy QA database (to be established).

Data collection frequency: Data collection will be continuous according to the QA supervision schedule.


Entity responsible for data collection: Microscopy QA teams will maintain an online database which will be updated following each QA session. Records of QA visits to each designated microscopy point will be included.

24

2. Malaria Test Positivity Rate

Indicator name: Malaria test positivity rate.

Definition: Percentage of parasitological tests for malaria that are positive (includes both microscopy and rapid diagnostic tests).

Numerator (N): Number of parasitologically confirmed malaria cases.

Denominator (D): Number of patients parasitologically tested for malaria.

Multiplier (M): 100

Equation: =(N/D)xM

Rationale/Purpose: Malaria test positivity rate assesses the proportion of tests positive for malaria among tests on suspected malaria patients. In areas with unstable malaria, an increasing test positivity rate among symptomatic patients is one of the warning signs of a possible outbreak.


Target value: 0.7% by 2020.

Interpretation: An increasing test positivity rate among symptomatic patients is one of the warning signs of a possible epidemic. Unusually low test-positivity rates for individual healthcare providers may indicate poor clinical diagnostic skills.







Entity responsible for data collection: Data is collected as described for API.

25

3. Diagnosis rate

Indicator name: Diagnosis rate

Definition: Percentage of people in target areas with fever in the last 3 months that accessed parasite-based diagnosis [disaggregated by population category: static/mobile/migrant]

Numerator (N): Number of people in target areas with fever in the last 3 months that accessed parasite-based diagnosis [disaggregated by population category: static/mobile/migrant]

Denominator (D): Number of people in target areas interviewed [disaggregated by population category: static/mobile/migrant]

Multiplier (M): 100

Equation: =(N/D)xM

Rationale/Purpose: It is essential that all groups access rational treatment with appropriate antimalarials. Mobile and migrant populations in particular are key risk groups for malaria in Myanmar and they are thought to have had a significant role in driving the development of multi-drug resistance, including ACT resistance in the Region.

Baseline value: 44% in 2014 (for mobile and migrant population).

Target value: 80% (for mobile and migrant population) by 2020.

Interpretation: A rising diagnosis rate indicates that programmatic efforts to promote rational treatment are becoming increasingly effective.

Data source (numerator): Survey subjects.

Data source (denominator): Survey subjects.

Method of Measurement: Household survey in a representative random sample of households in a representative random sample of villages plus special survey in a representative random sample of people from mobile and migrant populations in high risk areas.

Measurement Tool: Survey questionnaire.

Data collection frequency: Annual.


Entity responsible for data collection: Implementation of the surveys will be carried out by NMCP.

26

4. ACT treatment rate

Indicator name: ACT treatment rate

Definition: Percentage of confirmed malaria cases that received first-line antimalarial treatment according to national policy (disaggregated by source: health facilities, community level services and private sector providers [private sector to be introduced once reporting system in place]).

Numerator (N): Number of parasitologically confirmed uncomplicated malaria cases receiving anti-malarial treatment as per national guidelines.

Denominator (D): Number of parasitologically confirmed uncomplicated malaria cases.

Multiplier (M): 100

Equation: =(N/D)xM

Rationale/Purpose: Adherence to national treatment guidelines is the basis of ensuring appropriate treatment for malaria and reduced mortality.



Interpretation: This indicator provides a measure of adherence to national treatment guidelines.

Data source (numerator): Patient registers.

Data source (denominator): Patient registers.





Entity responsible for data collection: Supervisors of healthcare providers at each level will be responsible for collecting the necessary information.

27

5. Active VHV coverage Rate

Indicator name: Active VHV coverage Rate

Definition: Percentage of target villages with VHV providing malaria case management services.

Numerator (N): Number of target villages with VHV providing malaria case management services.

Denominator (D): Number of target villages.

Multiplier (M): 100

Equation: =(N/D)xM

Rationale/Purpose: Community-based case management services delivered through the VHV network is a key component of the programme. Achieving and maintaining high coverage in target areas is crucial both to burden reduction and to elimination efforts.


Target value: 95% by 2020 (in targeted village).

Interpretation: A high VHV coverage rate in target areas indicates that the programme is on track to achieving its burden reduction and elimination goals.

Data source (numerator): State/Region records.

Data source (denominator): State/Region records.

Method of Measurement: Review of State/Region records.

Measurement Tool: State/Region records.

Data collection frequency: Figures will be based on data from periodic VHV planning exercises (denominator) and a combination of periodic training records and monthly VHV supervision reports (numerator). This data will be entered into the VHV data-base as it becomes available.


Entity responsible for data collection: a) NMCP will update the list of target villages in the VHV database as necessary following any VHV planning exercise.

b) VHV training teams will update the number of target villages with trained VHVs in the VHV database as necessary following any training sessions.

c) Health Facility level VHV coordinators will conduct regular monthly VHV meetings and keep a record of any VHV attrition by village.

d) This information will be passed to the focal point within the Statistics Unit of the State/Region as part of routine monthly reporting.

e) NMCP will update the VHV database on which target villages still have a VHV present every month.

28

6. VHV utilization rate

Indicator name: VHV utilization rate

Definition: Percentage of respondents in VHV villages reporting VHV as first point of consultation for fever (stratified by endemicity and range of services provided).

Numerator (N): Number of respondents in VHV villages reporting VHV as first point of consultation for fever (stratified by endemicity and range of services provided).

Denominator (D): Number of respondents in VHV villages.

Multiplier (M): 100

Equation: =(N/D)xM

Rationale/Purpose: Community-based case management services delivered through the VHV network is a key component of the programme. For the approach to be cost effective utilization rates must be high.


Target value: >80% by 2020 (in targeted village).

Interpretation: A rising VHV utilization rate indicates that the VHV component of the programme is becoming increasingly cost effective.



Method of Measurement: Household Survey in a representative random sample of households in a representative random sample of villages targeted by the VHV approach.


Data collection frequency: Every year.



29

7. Private practitioner functionality rate

Indicator name: Private practitioner functionality rate

Definition: Percentage of target private practitioners with adequate case management practices and supply of quality-assured diagnostics and medicines (based on a private sector QA assessment tool).

Numerator (N): Number of target private practitioners with adequate case management practices and supply of quality-assured diagnostics and medicines.

Denominator (D): Number of target private practitioners surveyed using private sector QA assessment tool.

Multiplier (M): 100

Equation: =(N/D)xM

Rationale/Purpose: Private sector providers must be adequately skilled and supplied with appropriate diagnostic tools and antimalarials to provide quality malaria case management services.



Interpretation: A rising functionality rate amongst private practitioners is indicative of improving private sector case management services.

Data source (numerator): Private sector database.

Data source (denominator): Private sector database.

Method of Measurement: Review of private sector database.

Measurement Tool: Private sector QA assessment tool and private sector database.

Data collection frequency: Data collection will occur annually according to the private sector QA assessment schedule.


Entity responsible for data collection: Region/State private sector support teams will conduct regular QA assessments at all participating private sector outlets. Data generated will be entered into a private sector database following each QA session.

30

8. Bednet utilization rate

Indicator name: Bednet utilization rate

Definition: Percentage of people in target villages who slept under an insecticide-treated net (ITN) during the previous night. (disaggregated by age and sex and disaggregated to reveal habits in the village [for all] and habits in the forest for forest goers)

Numerator (N): Number of people in survey who slept under an ITN the previous night.

Denominator (D): Number of people in survey.

Multiplier (M): 100

Equation: =(N/D)xM

Rationale/Purpose: Provision of ITNs is the programme’s key strategy for vector control and personal protection. For the strategy to effectively provide a ‘community effect’ utilization in excess of 80% is required.



Interpretation: This indicator provides a direct measure of the use of ITNs by people in villages targeted for ITN delivery.



Method of Measurement: Household Survey in a representative random sample of households in a representative random sample of villages targeted by the vector control programme.





31

9. Bednet utilization - MMPs

Indicator name: Bednet utilization - MMPs

Definition: Percentage of mobile/migrant population in targeted areas who slept under an insecticide-treated net the last time they slept in a transmission area.

Numerator (N): Number of people from the mobile and migrant population in the survey who slept under an ITN the previous night.

Denominator (D): Number of people from the mobile and migrant population in the survey.

Multiplier (M): 100

Equation: =(N/D)xM

Rationale/Purpose: Provision of ITNs is the programme’s key strategy for vector control and personal protection. For the strategy to effectively provide a ‘community effect’ utilization in excess of 80% is required.



Interpretation: This indicator provides a direct measure of the use of ITNs by people from the mobile and migrant population in areas targeted for ITN delivery.



Method of Measurement: Special MMP survey in a representative random sample of people from mobile and migrant populations in high risk areas.





32

10. ITN coverage rate

Indicator name: ITN coverage rate

Definition: Percentage of households in target areas with at least one insecticide-treated net (ITN)

Numerator (N): Number of households surveyed in target areas with at least 1 ITN.

Denominator (D): Number of households surveyed in target areas.

Multiplier (M): 100

Equation: =(N/D)xM

Rationale/Purpose: Households in communities at risk of malaria should benefit from having at least one ITN as a vector control interventions.


Target value: >95% by 2020.

Interpretation: This indicator provides a measure of household coverage by ITN in the target areas under National Malaria Control Programme’s malaria prevention measures.

Data source (numerator): Household representatives.

Data source (denominator): Household representatives.

Method of Measurement: Household Survey in a representative random sample of households in a representative random sample of villages targeted by the vector control programme.





33

11. Timely reporting rate - control

Indicator name: Timely reporting rate - control

Definition: Percentage of reporting units (public, private and community) submitting timely reports at all levels according to national guidelines.

Numerator (N): Number of routine HIS reports submitted on time by reporting units during reporting period.

Denominator (D): Number of HIS reporting units.

Multiplier (M): 100

Equation: =(N/D)xM

Rationale/Purpose: Ensuring timely reporting is key to effective M&E and therefore to effective program management. It is also critical to ensuring timely disbursement under performance based funding.



Interpretation: This indicator measures the timeliness of routine reporting by reporting unit.

Data source (numerator): Records of the timeliness of reporting by reporting unit (part of the routine HIS).

Data source (denominator): Records of the total reporting units (derived from the routine HIS).

Method of Measurement: Review of routine HIS.


Data collection frequency: a) Data on timeliness of HIS reporting is generated at each level during the routine reporting process described under indicator API.

b) Timeliness thresholds: on day 25/26 of each month from community to Sub-centre/RHC level; on day 30/31 of each month from Sub-centre/RHC to Township level; on day 15 of next month from Township to State/Region level.

c) NMCP is responsible for compiling a summary of HIS reporting timeliness.


Entity responsible for data collection: Supervisors at each level are responsible for recording data on the timeliness of data submission during the routine reporting processes described under Impact Indicator API.

34

12. Timely reporting rate - elimination

Indicator name: Timely reporting rate - elimination

Definition: Percentage of confirmed malaria cases detected at health facilities and at community level in target Townships notified through SMS-based real-time reporting [to be introduced once reporting system in place].

Numerator (N): Number of confirmed malaria cases detected at health facilities and at community level in target Townships notified through real-time reporting.

Denominator (D): Number of confirmed malaria cases detected at health facilities and at community level in target States/Regions.

Multiplier (M): 100

Equation: =(N/D)xM

Rationale/Purpose: Timely notification/reporting of all cases in target States/Regions is crucial to ensure a rapid response and thereby minimize the risk of onward transmission. This is a key component of the elimination effort.


Target value: >90% by 2020 in targeted areas.

Interpretation: An increasing timely notification/reporting rate indicates that the programme is making progress towards developing the level of surveillance required for elimination.

Data source (numerator): Real time reporting records for each group of service providers (health facilities, community level and private sector) in the HIS.


Method of Measurement: Review of updated routine HIS.

Measurement Tool: Updated routine HIS.

Data collection frequency: Numerator: Data on real time reporting (within 24 hours) is compiled automatically as each report is received. Denominator: Data is collected as described for API.


Entity responsible for data collection: Numerator: All service providers in target Region/States are responsible for real time reporting by SMS (or similar technology). Denominator: As described for API.

35

13. Case investigation rate

Indicator name: Case investigation rate

Definition: Percentage of confirmed cases fully investigated within 3 days (including case investigation form).

Numerator (N): Number of confirmed cases fully investigated and classified within 3 days of detection.

Denominator (D): Total confirmed cases.

Multiplier (M): 100

Equation: =(N/D)xM

Rationale/Purpose: Case investigation is a key strategy for the elimination of malaria.

Baseline value: 9% in 2015 in RAI areas.

Target value: 30%, 60% and >95% in 2016, 2017 and 2018 respectively; and 40% and >70% in 2019 and 2020 respectively.

Interpretation: An increasing case investigation rate indicates that the programme is making progress towards developing the level of surveillance required for elimination.

Data source (numerator): Case Investigation Form.

Data source (denominator): Case Investigation Form.



Data collection frequency: Data from case investigation forms is entered into the Health Information System continuously as it is received.


Entity responsible for data collection: Township level malaria officers are responsible for uploading data from case investigation forms to the Health Information System.

36

14. Focus investigation rate

Indicator name: Focus investigation rate

Definition: Percentage of foci fully investigated and registered within 3 days of detection (including malaria focus investigation form, entomological investigation form and focus geo-referencing and mapping).

Numerator (N): Number of foci fully investigated and registered within 3 days of detection.

Denominator (D): Number of foci detected.

Multiplier (M): 100

Equation: =(N/D)xM

Rationale/Purpose: Focus investigation is a key strategy for the elimination of malaria.


Target value: 40%, 70% and >95% in 2016, 2017 and 2018 respectively; and 50% and >80% in 2019 and 2020 respectively

Interpretation: An increasing focus investigation rate indicates that the programme is making progress towards developing the level of surveillance required for elimination.

Data source (numerator): Focus Investigation Form.

Data source (denominator): Focus Investigation Form.



Data collection frequency: Data from focus investigation forms is entered into the Health Information System continuously as it is received.


Entity responsible for data collection: Township level malaria officers are responsible for uploading data from focus investigation forms to the Health Information System.

37

15. Active focus response rate

Indicator name: Active focus response rate

Definition: Percentage of confirmed active foci investigated in which an appropriate response was initiated within 7 days.

Numerator (N): Number of confirmed active foci investigated in which an appropriate response was initiated within 7 days.

Denominator (D): Number of confirmed active foci.

Multiplier (M): 100

Equation: =(N/D)xM

Rationale/Purpose: A timely response to confirmed active foci is key to preventing continued transmission in elimination settings.

Baseline value: 7% in 2015 (in RAI areas).

Target value: 50%, 80% and >95% in 2016, 2017 and 2018 respectively; and 60% and >90% in 2019 and 2010 respectively.

Interpretation: An increasing active focus response rate indicates that the programme is making progress towards developing the level of responsiveness required to achieve elimination.

Data source (numerator): Focus Response Form.

Data source (denominator): Focus Response Form.



Data collection frequency: Data from active focus response forms is entered into the Health Information System continuously as it is received.


Entity responsible for data collection: Township level malaria officers are responsible for uploading data from active focus response forms to the Health Information System.

38

16. Stock-out rate (diagnostics)

Indicator name: Stock-out rate (diagnostics)

Definition: Percentage of outlets with no stock-out of diagnostics (RDTs/ microscopy supplies) lasting more than 1 week at any time during the past 3 months. [This indicator will be disaggregated according to type of outlet - health facility, VHV etc.].

Numerator (N): Number of outlets with no stock-out of diagnostics lasting more than 1 week at any time during the past 3 months.

Denominator (D): Total number of outlets.

Multiplier (M): 100

Equation: =(N/D)xM

Rationale/Purpose: Ensuring adequate and continued supply of the recommended diagnostics is key to the delivery of prompt and effective treatment and key to success in preventing and controlling malaria.



Interpretation: This indicator measures the effectiveness of supply management.

Data source (numerator): Stock control cards and VHV reports.

Data source (denominator): Survey reports.

Method of Measurement: Public sector heath outlet survey in a representative random sample of sites.

Measurement Tool: Survey reports.




39

17. Stock-out rate (Antimalarials)

Indicator name: Stock-out rate (Antimalarials)

Definition: Percentage of outlets with no stock-out of first-line antimalarials lasting more than 1 week at any time during the past 3 months. [This indicator will be disaggregated according to type of outlet - health facility, VHV etc.].

Numerator (N): Number of outlets with no stock-out of first-line antimalarials lasting more than 1 week at any time during the past 3 months.

Denominator (D): Total number of outlets.

Multiplier (M): 100

Equation: =(N/D)xM

Rationale/Purpose: Ensuring adequate and continued supply of the recommended first-line antimalarials is key to the delivery of prompt and effective treatment at health facilities and key to success in preventing and controlling malaria.



Interpretation: This indicator measures the effectiveness of supply management.

Data source (numerator): Stock control cards and VHV reports.

Data source (denominator): Survey reports.

Method of Measurement: Public sector heath outlet survey in a representative random sample of sites.





40

18. Monotherapy rate

Indicator name: Monotherapy rate

Definition: Percentage of private sector outlets in endemic Region/States stocking oral artemisinin monotherapy.

Numerator (N): Number of private sector outlets in endemic Region/States stocking oral artemisinin monotherapy.

Denominator (D): Number of private sector outlets in endemic Region/States sampled.

Multiplier (M): 100

Equation: =(N/D)xM

Rationale/Purpose: The use of oral artemisinin-based monotherapies has been one of the root causes of multi-drug resistance, including ACT resistance in falciparum malaria.

Baseline value: 27% in 2015 (PSI ACT Watch Survey).


Interpretation: A falling percentage of private sector outlets in endemic Region/States stocking oral artemisinin monotherapy indicates that regulation and enforcement efforts are successfully progressing.

Data source (numerator): Surveyed outlets.

Data source (denominator): Surveyed outlets.

Method of Measurement: Outlet Survey in a representative random sample of outlets.





41

19. Inappropriate antimalarial rate

Indicator name: Inappropriate antimalarial rate

Definition: Percentage of sampled antimalarials that are unregistered, fake, substandard or degraded.

Numerator (N): Number of sampled antimalarials that are unregistered, fake, substandard or degraded.

Denominator (D): Number of antimalarials sampled.

Multiplier (M): 100

Equation: =(N/D)xM

Rationale/Purpose: Testing of malaria products at point of use is essential to ensure that they meet required quality standards.



Interpretation: A 100% pass rate indicates that healthcare providers are dispensing quality products.

Data source (numerator): Minilab test results.

Data source (denominator): Minilab test results.

Method of Measurement: Review of Minilab test results database.

Measurement Tool: Minilab test results database.

Data collection frequency: On-going surveys.


Entity responsible for data collection: Implementation of Minilab surveys will be carried out by FDA/NMCP.

42

Annex 2. Performance Framework of M&E

44

Annex 3. Tools for M&E

a) Malaria Case Register/ Monthly Report (BHS)

Vill

age,

Tow

nshi

p,

Sta

te/R

egio

n

malaria monitoring and evaluation plan...

Documents