New data analytics for early disease detection in primary health care

Supporting MoHS in utilising big data nationally and in primary health, ensuring early identification and effect response to disease outbreaks.

Sarah Cundy, Health Coordinator, Concern Worldwide in Sierra Leone

Sierra Leone has a long history of health emergencies due to recurrent outbreaks and natural disasters. With a population of 7.8 million, and life expectancy of 55, health care is delivered by 1.4 healthcare workers per 10,000 population, leaving a workforce gap of approximately 32,000 to meet the Sustainable Development Goals (SDG) of 44.5 per 10,000. Although the Government of Sierra Leone has increased spending on the healthcare recently, there remains an opportunity to find innovative and efficient solutions to fill the gaps.

The West Africa Ebola outbreak (2014) infected over 14,000 people and killed almost 4,000. 221 of these deaths were health care workers (HCW), compounding the severity of the shock on an already fragile health system.

During the COVID-19 pandemic, despite less than 4,000 reported cases, the scale of risk and uncertainty of its progression, has affected the ability of the health system to maintain normal function. COVID-19 and Ebola are not the only communicable diseases requiring a coordinated response. Polio, Tuberculosis, Cholera, Lassa Fever and Yellow Fever, all pose significant risk. In addition to these diseases, the country experiences epidemic levels of malaria, child and maternal deaths, all showing seasonal variations in the number of people affected. 

The target audience for our solution is primarily staff and management of the Ministry of Health and Sanitation (MoHS) at national, district and health facility levels. It intends to help them analyse seasonal disease trends and utilise this data to effectively plan and budget logistical, programmatic, human and financial resource needs.

At the national level, our solution will strengthen Sierra Leone’s current health information system to analyse data in real time to make this data accessible and practical for MoHS.

Our secondary audience is individual users of the health service throughout Sierra Leone.  More effective system management by MoHS will contribute to achieving improved service uptake and better health outcomes for users.

Our solution will target epidemic prone/high mortality diseases, currently captured within the district health information system (DHIS) or the electronic Integrated Disease Surveillance and Response (eIDSR) project funded by the U.S. CDC. This is an approach previously utilised by Concern Worldwide in a selected number of health facilities in one of Sierra Leone’s Northern districts, with exceptionally positive results. Our solution will build on our current and previous capacity building work within the MoHS to contribute towards the global health security agenda commitments they previously made.

Lessons learnt during the Ebola epidemic demonstrated that Sierra Leone’s health system is lacking the resilience to respond to and recover from shocks, to which the country remains susceptible.

Despite continued improvement in the health system, high morbidity and mortality persist due to communicable diseases and an increasing rate of chronic health conditions. The Surge model will help enable health professionals at national, district and facility level to predict outbreaks through an early warning system in the form of a surge adaptation. The model will help MoHS intentionally plan and target health financing in advance instead of responding to unfunded large-scale outbreaks where limited resources and reactionary approaches reduce effectiveness and can ultimately increase mortality.

Concern and the MoHS in partnership with other health actors will produce a full Surge model operational plan for a nationwide roll out. This will also be available to NGO and Government partners for use in other international contexts where new approaches to disease prevention are still needed.

In Sierra Leone there are over 1,000 health facilities across the country’s 16 districts serving a population of over 8,000,000 (59% rural). Outside of headquarter towns, these facilities are the only sources of care for many communities and therefore serve the most vulnerable and marginalised of the population. It is these groups who suffer the greatest impact of infectious disease outbreaks and whilst inefficient prediction, tracking and response to health emergencies negatively impacts the whole nation, it is these communities who will take longest to recover if at all.

In January 2014, a woman died in Sierra Leone after staying with a family in Guinea who had contracted the Ebola Virus.  At the time, her death was not investigated nor reported, and the country’s vigilance was not increased until 4 months later when 2 further deaths were reported from within the same family. The West African Ebola outbreak eventually caused the deaths of more than 4,000 people in Sierra Leone many of whom came from highly vulnerable social groups.

The model will be rolled out in phases beginning with national, district and facility level (covering 2 rural districts) and this will provide the learning and adaptation needed to support the full nationwide rollout. In Kenya the roll out of CMAM surge was conducted over 2 years reaching 63% of health facilities. The Surge model complements other disease surveillance best practices and we envisage this will increase uptake to achieve nationwide use within 3 years.

Monitoring data will regularly be collected at the 3 levels of implementation to measure outcomes, process and output indicators in targeted areas. Concern will use electronic systems and mobile devices to enhance data processing and analysis and a tracking system will be implemented to communicate timely monitoring findings to the program/management in order to address any challenges. Concern will select standard indicators from the Concern SURGE approach, allowing for comparison between projects: i.e. % of target health facilities that have established thresholds based on a sound analysis of what a ‘normal’ caseload should be (national/subnational); Average number of days between the triggering of a threshold and the notification of district/national structures; % of health facilities implementing at least 75% pre-surge actions identified; % of patients at target health facilities who are satisfied with the services received during surge and non-surge periods.

‘TAP Malaria’ results showed that the establishment of evidence-based thresholds allowed health facilities to better monitor, prepare and respond to seasonal variation in malaria cases in their respective communities, notably by ensuring better management of antimalarial drug supply between health facilities and DHMT.

The bottom-up approach of Concern’s three year ‘TAP Malaria’ project to community engagement and facility level ownership has become an example of successful best practice with a strong potential to be replicated at a national and wider district level. It has demonstrated results in increased health service uptake and evidence of improved health outcomes, which has generated significant interest at national level resulting in the inclusion of its community-based approached in the National Malaria Control Programme (NMCP) five year strategic plan. 

However, a barrier faced is that the ‘Surge Model’ component has not yet been strategically embedded in the approach, beyond targeted health facilities in ‘TAP Malaria’.  This solution intends to address this deficit through investing effort at national level at the outset, with all DHMT sector leads involved from the project initiation.  This will help to ensure full ownership and sustainability. 

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This opportunity will allow a rapid growth of our solution to ensure the momentum and buy which were not possible to achieve at a small scale. Funding from Trinity Challenge will operationalise the full scope of our national roll out plan as well as providing potential technical support from SOLVE partners.  It also presents the opportunity to leverage other funding to further build on the model.

Both Johns Hopkins University and the Bill and Melinda Gates Foundation could provide valuable technical insights to our solution.

Bill and Melinda Gates Foundation have funded the Concern Innovations project globally and in Sierra Leone and their focus on learning and adaptive design fits well with this solution as well as the overall synergy in reducing burden of disease on the most vulnerable populations. 

Johns Hopkins University has interacted with our pilot project through Breakthrough Action. Their expertise in data analytics could be a support in the roll out of the model as well as in designing adaptations and ensuring learning can inform expansion and potential roll out to other countries.