Session goals | Session outputs | Action points |
---|---|---|
Session 1: building capacity through research | ||
Discuss, identify and prioritize what research is needed to support malaria elimination in the Asia–Pacific region | - List of research questions submitted by NMCPs in different sub-regions and APMEN partner institutions (Additional File 1) - Priority research in order of votes: 1. Strategies to address malaria transmission amongst mobile and migrant populations (MMPs) 2. Cost effective surveillance strategies to maximize in low resource setting 3. Integration of malaria surveillance with the broader health system 4. Minimal surveillance package for monitoring and evaluation for sustaining malaria free status | - Build capacity for elimination through research by: 1. Openly and widely disseminating identified research priorities 2. Providing linkage with APMEN research institutions to conduct the research needed in specific countries 3. Advocating to potential donors to fund the identified research priorities |
Session 2 & 3: building capacity through data quality, integration and technology | ||
Identify key challenges to, and solutions for, improving data quality Identify key challenges to, and solutions for, integrating epidemiology and entomology data for malaria surveillance Review technical solutions for malaria elimination | - Data quality challenges: 1. Limited human resources and technological capacity for data collection and entry processes 2. Difficulty in tracing mobile and migrant populations 3. Poor or lack of Standard Operating Procedures (SOP) and monitoring and evaluation of both data collection teams and data quality 4. Competing priorities for data collectors 5. Complex reporting and poor data management systems - Data quality solutions: 1. Clear SOPs for case investigation 2. Simplified reporting systems and digitization of data collection tools 3. Improved monitoring and supervision of data collection units 4. Establishment of a national quality assurance system for malaria diagnosis 5. Routine data cleaning and review 6. Integration of private sector data and supplementing with geospatial information - Data integration challenges: 1. Divergence in spatial resolution, coverage and frequency of data collected 2. Costliness and lack of capacity to collect entomological data 3. Extrapolating vector surveillance data geographically 4. Lack of data management systems supporting integration of both types of data - Data integration solutions: 1. Correlating data collected at the same geographical location and time 2. Coordinating data collection between epidemiological and entomological data collection teams 3. Unifying data collection and management systems - Technical solutions: 1. WHO’s Digital Solutions for Malaria Elimination initiative supports the use of digital tools to strengthen an integrated surveillance information system on the DHIS2 platform 2. Utilization of malaria packages under DHIS2 metadata tools to leverage the health management information system 3. Google data studio as complementary digital dashboard for malaria case-based and drug stock surveillance in Sri Lanka 4. Nationally designed and tailored web-based Malaria Information System in Cambodia supports real-time reporting through mobile applications | - Build capacity for elimination through improved data quality and integration by: 1. Reviewing key challenges and barriers raised across national programs to target topics for implementing informative webinars and training workshops for the wider APMEN audience 2. Providing linkage with APMEN implementing partners to establish technical support initiatives |
Session 4: moving from data to elimination | ||
Identify ways to strengthen capacity to utilize data for action | - Inter-regional partnerships with the Roll Back Malaria Surveillance, Monitoring and Evaluation Reference Group’s Surveillance Practice and Data Quality (SMERG SP&DQ) Committee - Training topics identified from training needs assessment and breakout group discussions: 1. Malaria vector surveillance 2. Case and foci investigation 3. GIS and mapping 4. Data quality assurance in the surveillance data pipeline | - Build capacity for elimination through training by: 1. Developing cross-regional training workshops 2. Designing and delivering training workshops for data quality dimensions and GIS and mapping 3. Establishing technical support initiatives to improve the quality of case and foci investigation in specific countries that have expressed interest |