Summary of results from using digital data application tools for implementing SMC
| Country choice | Strengths | Weaknesses | |
| Rationale | Benin, Nigeria, Ghana, and the Gambia To improve data quality, reduce workload on workers, and ease the management of and accessibility to data (facilitate storing, retrieving and comparing data). DDC tools also improve data quality as errors are reduced. | As explained in column to the left on country choices | All countries mentioned that DDC tools have high initial outlay for implementation and a steep learning curve to train staff, especially those with low literacy levels |
| Application deployed | Benin: Red Rose | See table 2 | See table 2 |
| The Gambia: Initially Apple-iFormBuilder; Currently CommCare. | |||
| Ghana: In-house designed SiCapp application | |||
| Nigeria: Had initially piloted Reveal and introduced the Red Rose app in 2021 | |||
| Registration and eligibility determination | Benin: Children were registered and determined eligible for SMC based on data from recently collected census data, or registered anew based on information provided during household visits | Census data can be useful across several other programme areas | |
| The Gambia, Ghana and Nigeria: Caregivers gave information during house visits, which helps to determine a child’s eligibility, which is then registered on the app | If caregivers are the parents/ primary caregivers, then the information they provide could be the most up-to-date and relevant for use in other campaigns as well | Recall data may be prone to errors as it is not based on documented evidence. Recall data from caregivers may also be inaccurate if they are not the parents /primary caregivers of the children | |
| Dose compliance | Benin and The Gambia: Child’s barcode used to track dose compliance; SMS used to remind parents/caregivers to promote compliance | In the event of loss or errors, barcodes can be rescanned and checked with synced data in the cloud | There is an additional cost to produce and distribute barcoded cards |
| Ghana: First dose data entered in app and recalled for entering information on the second and third doses. Caregivers also reminded by SMS | Entering the data directly into the app without the use of barcoded cards is cheaper - no cost for cards | It will be difficult to cross-check in case there is doubt on data entry or errors. | |
| Nigeria: Use of colour coding in app to mark SMC administration | Colour coding is cheaper—no cost for cards | Colour coding can be difficult to double-check in case of doubt or errors, in the absence of barcoded cards | |
| Coverage monitoring | Benin and Nigeria: App can identify structures/households within a specific distance of the device—this helps enumeration | Data from identifying structures/households can be used for other heath programmes | Specifically for Nigeria, not all structures could be identified as the app had not been geographically programmed |
| Benin (additional): Data from the application was linked with ArcGIS to develop near real-time dose coverage maps | |||
| The Gambia: CommCare has visualisation features which support coverage monitoring | The visualisation features on CommCare can be used to present strategic and programmatic data | ||
| Ghana: A feature on the application was used to monitor coverage of SMC using the application | The monitoring feature on SiCapp can be used to present strategic and programmatic data | ||
| Health worker performance assessment | Benin: Staff were paid in 3 weeks when DDC tools were used, compared with 8 weeks when using paper-based tools | The app was useful for speeding up the payment for volunteers and avoiding potential delays in administering SMC cycles; staff remain motivated | |
| Ghana and Nigeria: App provides details of the work done by volunteers and proof of attendance at training sessions | Using the app helped prevent fraud and ensured that volunteers and staff were paid for actual work completed | ||
| The Gambia: Assessment not based on the app due to poor internet connectivity | Not being able to assess the work completed by staff makes it difficult to assess the work done to enable performance-based payment. This also reduces the motivation of volunteers. | ||
| Combining SMC with other interventions | Benin: Currently, DDC is implemented on its own—exploring to combine with malnutrition screening /systematic deworming programmes | Not combining SMC with other interventions helps to maintain focus and resources on SMC. It also helps to maintain data integrity | |
| Ghana: Separation of SiCapp for yearly SMC campaigns and NetApp for ITN campaigns every 3 years to ensure data integrity | |||
| Nigeria: Reveal App has been used for ITNs campaigns, but for this pilot, only SMC was implemented | |||
| The Gambia: Partial malaria campaign integration by sharing mobile devices across SMC and ITN campaigns | Using mobile devices across multiple campaigns helps to spread limited resources across several programmes General population and health data can be used across several programmes | Staff can get exhausted due to additional workload arising from working on multiple campaigns There was also the risk of not achieving high coverage rates and compromising data integrity | |
| Digital infrastructure management and cost benefit | Benin and Nigeria: App downloaded on personal smartphones of volunteers and health staff | Downloading app on mobile devices of personnel is cheaper, as smartphones and tablets then do not need to be bought by the NMCP | Data security could be compromised as app is on personal devices |
| The Gambia and Ghana: NMCP of The Gambia purchased smartphones while Ghana purchased tablets for volunteers | Buying smartphones and tablets is more expensive for NMCPs and devices need to be maintained | ||
| Cost of digital vs paper-based | Benin: Paper-based version was 1.5 times more expensive than digital system | ||
| The Gambia, Ghana, and Nigeria: Initially high capital outlay for the rollout of DDC tools, but eventually cheaper than paper-based tools in the long-run No cost-effectiveness analysis conducted by these three countries | A cost-effectiveness analysis would have helped to understand whether using DDC systems was cheaper for the NMCP | ||
| Challenges | All four countries: Electricity and internet connectivity challenges | ||
| Nigeria (additional): Need to train health volunteers with low literacy. This led to an increase in number of days to implement SMC on the first roll out of app | |||
| Future plans | Benin and Ghana: Not stated | ||
| The Gambia: DHIS2 training is being given with plans to move to this application and use the tracker to collect SMC data as a replacement for CommCare | Combining data from DDC tools with DHIS2 and other digital data tools would help to analyse health data more broadly and compare across data and indicators from other health interventions for programmatic planning | Combining data from DDC tools with other digital data tools will require higher financial investments | |
| Nigeria: Plans to address challenges confronted in first rollout; test Red Rose application to determine which app is most appropriate; and link the app with the National Malaria Data Repository | Testing the Red Rose vs Reveal app will help identify which tool is most cost-effective, efficient, and appropriate | Studies to compare Red Rose with the Reveal app as well as potential rollout of a new app may require additional staff training |
DDC, digital data collection; DHIS2, District Health Information Software 2; NMCP, National Malaria Control Programme; SMC, seasonal malaria chemoprevention.