A systematic review of spatial decision support systems in public health informatics supporting the identification of high risk areas for zoonotic disease outbreaks

Beard, R. Suzanne; Wentz, Elizabeth A.; Scotch, Matthew

doi:10.1186/s12942-018-0157-5

Cited by 36 publications

(29 citation statements)

References 129 publications

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“…The distinction is important because it helps determine the most appropriate level for clinical and policy intervention. Spatial epidemiology can fill the gaps in traditional surveillance and equip healthcare professional with the data analytics to effectively make decisions and policy recommendations to improve patient and population-level outcomes 22 .…”

Section: Discussionmentioning

confidence: 99%

Geospatial epidemiology of Staphylococcus aureus in a tropical setting: an enabling digital surveillance platform

Wozniak

Cuningham

Buchanan

et al. 2020

Sci Rep

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Delivery of information to clinicians on evolving antimicrobial susceptibility needs to be accurate for the local needs, up-to-date and readily available at point of care. In northern Australia, bacterial infection rates are high but resistance to first-and second-line antibiotics is poorly described and currently-available datasets exclude primary healthcare data. We aimed to develop an online geospatial and interactive platform for aggregating, analysing and disseminating data on regional bacterial pathogen susceptibility. We report the epidemiology of Staphylococcus aureus as an example of the power of digital platforms to tackle the growing spread of antimicrobial resistance in a high-burden, geographically-sparse region and beyond. We developed an online geospatial platform called Hotspots that visualises antimicrobial susceptibility patterns and temporal trends. Data on clinically-important bacteria and their antibiotic susceptibility profiles were sought from retrospectively identified clinical specimens submitted to three participating pathology providers (96 unique tertiary and primary healthcare centres, n = 1,006,238 tests) between January 2008 and December 2017. Here we present data on S. aureus only. Data were available on specimen type, date and location of collection. Regions from the Australian Bureau of Statistics were used to provide spatial localisation. the online platform provides an engaging visual representation of spatial heterogeneity, demonstrating striking geographical variation in S. aureus susceptibility across northern Australia. Methicillin resistance rates vary from 46% in the west to 26% in the east. Plots generated by the platform show temporal trends in proportions of S. aureus resistant to methicillin and other antimicrobials across the three jurisdictions of northern Australia. A quarter of all, and up to 35% of methicillin-resistant S. aureus (MRSA) blood isolates in parts of the northern Australia were resistant to inducible-clindamycin. Clindamycin resistance rates in MRSA are worryingly high in regions of northern Australia and are a local impediment to empirical use of this agent for community MRSA. Visualising routinely collected laboratory data with digital platforms, allows clinicians, public health physicians and guideline developers to monitor and respond to antimicrobial resistance in a timely manner. Deployment of this platform into clinical practice supports national and global efforts to innovate traditional disease surveillance systems with the use of digital technology and to provide practical solutions to reducing the threat of antimicrobial resistance.

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Section: Discussionmentioning

confidence: 99%

Geospatial epidemiology of Staphylococcus aureus in a tropical setting: an enabling digital surveillance platform

Wozniak

Cuningham

Buchanan

et al. 2020

Sci Rep

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“…Plans however do remain to further progress SDSS-based targeted support in high priority locations pending future external support and resource allocation to enable this. Extension of data entry to health centres is now possible with the DHIS2 enhanced system [69,70] because DHIS2 has developed an android app which allows for an offline data entry [71]. More work needs to be done to explore this and other technological solutions for improving DHIS2 applications for malaria and other infectious diseases.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of the malaria reporting system supported by the District Health Information System 2 in Solomon Islands

Wangdi

Sarma

Leaburi³

et al. 2020

Malar J

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Background District Health Information Systems 2 (DHIS2) is used for supporting health information management in 67 countries, including Solomon Islands. However, there have been few published evaluations of the performance of DHIS2-enhanced disease reporting systems, in particular for monitoring infectious diseases such as malaria. The aim of this study was to evaluate DHIS2 supported malaria reporting in Solomon Islands and to develop recommendations for improving the system. Methods The evaluation was conducted in three administrative areas of Solomon Islands: Honoria City Council, and Malaita and Guadalcanal Provinces. Records of nine malaria indicators including report submission date, total malaria cases, Plasmodium falciparum case record, Plasmodium vivax case record, clinical malaria, malaria diagnosed with microscopy, malaria diagnosed with (rapid diagnostic test) (RDT), record of drug stocks and records of RDT stocks from 1st January to 31st December 2016 were extracted from the DHIS2 database. The indicators permitted assessment in four core areas: availability, completeness, timeliness and reliability. To explore perceptions and point of view of the stakeholders on the performance of the malaria case reporting system, focus group discussions were conducted with health centre nurses, whilst in-depth interviews were conducted with stakeholder representatives from government (province and national) staff and World Health Organization officials who were users of DHIS2. Results Data were extracted from nine health centres in Honoria City Council and 64 health centres in Malaita Province. The completeness and timeliness from the two provinces of all nine indicators were 28.2% and 5.1%, respectively. The most reliable indicator in DHIS2 was ‘clinical malaria’ (i.e. numbers of clinically diagnosed malaria cases) with 62.4% reliability. Challenges to completeness were a lack of supervision, limited feedback, high workload, and a lack of training and refresher courses. Health centres located in geographically remote areas, a lack of regular transport, high workload and too many variables in the reporting forms led to delays in timely reporting. Reliability of reports was impacted by a lack of technical professionals such as statisticians and unavailability of tally sheets and reporting forms. Conclusion The availability, completeness, timeliness and reliability of nine malaria indicators collected in DHIS2 were variable within the study area, but generally low. Continued onsite support, supervision, feedback and additional enhancements, such as electronic reporting will be required to further improve the malaria reporting system.

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“…However, the SDSS could not be sustained because it was not integrated into the national surveillance system. Extension of data entry to health centres is now possible with the DHIS2 enhanced system [70,71] because DHIS2 has developed an android app which allows for an o ine data entry [72]. More work needs to be done to explore this and other technological solutions for improving DHIS2 applications for malaria and other infectious diseases.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of the District Health Information System 2 supported malaria reporting system in Solomon Islands

Wangdi

Sarma

Leaburi³

et al. 2020

Preprint

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BackgroundDistrict Health Information Systems 2 (DHIS2) is used for supporting health information management in 67 countries, including Solomon Islands. However, there have been few published evaluations of the performance of DHIS2-enhanced disease reporting systems, in particular for monitoring infectious diseases such as malaria. The aim of this study was to evaluate DHIS2 supported malaria reporting in Solomon Islands and to develop recommendations for improving the system.MethodsThe evaluation was conducted in three administrative areas of Solomon Islands: Honoria City Council, and Malaita and Guadalcanal Provinces. Records of nine malaria indicators from 1st January to 31st December 2016 were extracted from the DHIS2 database. The indicators permitted assessment in four core areas: availability, completeness, timeliness and reliability. To obtain more detailed information on the performance of the malaria case reporting system, focus group discussions were conducted with health centre nurses, whilst in-depth interviews were conducted with stakeholder representatives from government (province and national) staff and WHO officials who were users of DHIS2. ResultsData were extracted from nine health centres in Honoria City Council and 64 health centres in Malaita Province. The completeness and timeliness from the two provinces of all nine indicators were 28.2% and 5.1% respectively. The most reliable indicator in DHIS2 was ‘clinical malaria’ (i.e. numbers of clinically diagnosed malaria cases) with 62.4% reliability. Challenges to completeness were a lack of supervision, limited feedback, high workload, and a lack of training and refresher courses. Health centres located in geographically remote areas, a lack of regular transport, high workload and too many variables in the reporting forms led to delays in timely reporting. Reliability of reports was impacted by a lack of technical professionals such as statisticians and unavailability of tally sheets and reporting forms. ConclusionThe availability, completeness, timeliness and reliability of nine malaria indicators collected in DHIS2 were variable within the study area, but generally low. Continued onsite support, supervision, feedback and additional enhancements such as electronic reporting will be required to further improve the malaria reporting system.

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A systematic review of spatial decision support systems in public health informatics supporting the identification of high risk areas for zoonotic disease outbreaks

Cited by 36 publications

References 129 publications

Geospatial epidemiology of Staphylococcus aureus in a tropical setting: an enabling digital surveillance platform

Geospatial epidemiology of Staphylococcus aureus in a tropical setting: an enabling digital surveillance platform

Evaluation of the malaria reporting system supported by the District Health Information System 2 in Solomon Islands

Evaluation of the District Health Information System 2 supported malaria reporting system in Solomon Islands

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