Health information system strengthening and malaria elimination in Papua New Guinea

Abstract

BackgroundThe objective of the study was to describe an m-health initiative to strengthen malaria surveillance in a 184-health facility, multi-province, project aimed at strengthening the National Health Information System (NHIS) in a country with fragmented malaria surveillance, striving towards enhanced control, pre-elimination.MethodsA remote-loading mobile application and secure online platform for health professionals was created to interface with the new system (eNHIS). A case-based malaria testing register was developed and integrated geo-coded households, villages and health facilities. A malaria programme management dashboard was created, with village-level malaria mapping tools, and statistical algorithms to identify malaria outbreaks.ResultsSince its inception in 2015, 160,750 malaria testing records, including village of residence, have been reported to the eNHIS. These case-based, geo-coded malaria data are 100% complete, with a median data entry delay of 9 days from the date of testing. The system maps malaria to the village level in near real-time as well as the availability of treatment and diagnostics to health facility level. Data aggregation, analysis, outbreak detection, and reporting are automated.ConclusionsThe study demonstrates that using mobile technologies and GIS in the capture and reporting of NHIS data in Papua New Guinea provides timely, high quality, geo-coded, case-based malaria data required for malaria elimination. The health systems strengthening approach of integrating malaria information management into the eNHIS optimizes sustainability and provides enormous flexibility to cater for future malaria programme needs.

Plasmodium falciparum Histidine-Rich Protein 2 Gene Variation in a Malaria-Endemic Area of Papua New Guinea

“…Such infections, if undetectable by the current generation of RDTs, may compromise the current focus on malaria elimination in PNG. 30 Recently, funding agencies, manufacturers, and researchers have been working toward developing ultra-sensitive RDTs (uRDT) with limits of detection similar to those nucleic acid amplification-based methods. As a step in this direction, uRDT (Alere ™ Malaria Ag P.f (05FK140), Standard Diagnostics/Alere, San Diego, CA) has been commercialized with claims of an analytical sensitivity approximately 10 times the detection limit of the best conventional RDTs.…”

Mapping a Plasmodium transmission spatial suitability index in Solomon Islands: a malaria monitoring and control tool

“…Previous malaria surveillance models have been developed, including for the Pacific region (e.g. [ 5 , 29 ]). The GIS-based spatial decision support system of Kelly et al was applied to three Pacific provinces including two for the Solomon Islands, Temotu and Isabel.…”

“…In their system, Kelly et al [ 5 ] mapped confirmed malaria cases and used this to classify active transmission foci for use in guiding targeted responses in eliminations zones. Rosewell et al [ 29 ] also developed a case-based malaria surveillance system based on mobile technologies and GIS for Papua New Guinea. Statistical algorithms were used to generate outbreak detection data down to the village level, with the results being automatically displayed within a mapping platform.…”

“…In the Solomon Islands, not all cases of malaria are currently reported within the central government’s Health Information System, reasons including illegible writing, lack of understanding of the clinical definition of malaria and insufficient resources and training [ 30 ] and this can impact on the usefulness of malaria surveillance models such as those discussed here. In addition, both systems of Kelly et al and Rosewell et al [ 5 , 29 ] support the rapid detection of malaria cases but, unlike the TSI developed here, neither has any predictive capacity or considers the environmental preferences of the mosquitos and malaria parasite transmission. This includes the reported cases of malaria.…”

Towards effective outbreak detection: a qualitative study to identify factors affecting nurses’ early warning surveillance practice in Solomon Islands

“…Mobile technology has been successfully used as part of early warning surveillance in several developing settings [ 27 – 30 ]. Owing to the similarities Solomon Islands shares with neighbouring Papua New Guinea (PNG), attention should be paid to the work of Rosewell et al [ 30 ] who report PNG’s experience using mobile devices and Global Information Systems for malaria surveillance. Emerging evidence from PNG and other comparable settings should be explored.…”