When it comes to the timeline of outbreak response, every minute and every day counts. The World Health Organisation uses the The 7-1-7 framework, developed by Resolve to Save Lives, to benchmark outbreak response worldwide, with targets of 7 days to detect a suspected outbreak, 1 day to notify authorities, and 7 days to complete early response actions. The Framework represents an innovative and significant improvement on outbreak response globally – but in the Pacific, fundamental problems remain.

What’s not working in the Pacific? Detection is largely manual, usually relying on a surveillance officer doing weekly reviews of data from sentinel sites. Syndromic surveillance occurs only from a limited number of ‘sentinel sites’ which misses many outbreaks and does not provide the statistical output to generate data signals. Notifiable diseases occur only irregularly and facilities often lack pathways for reporting. The consequences can be devastating.

As an example, Samoa’s 2019 measles outbreak was declared 16 days after its index case, already more than double the 7-day target. The outbreak went on to infect over 5,700 people and 83 people died in just four months, mostly children under five, in a population of just over 200,000. In Australia that would translate to roughly 10,375 deaths: more than our entire road toll for over eight years combined (Australia sees around 1,200 road deaths a year). In Samoa’s case, the slow start to detection left less time for effective early response that can limit outbreaks and save lives (though to be fair, measles outbreaks are notoriously difficult to respond to and local authorities did an incredible job under the circumstances and with the tools available at the time.

More often though, deadly disease outbreaks in the Pacific are of much less high-profile diseases, they’re often geographically limited to a single island or village and consequently go completely undetected. The biggest killers of children remain community-acquired pneumonia and diarrhoea.

That’s where AI can help. 

Overlaying an AI data layer to existing disease detection data sources

An increasing number of countries in the Pacific are using EMRs/EHRs to record and manage every single clinical encounter in the public sector, in real-time. Samoa and Nauru are already there and other countries are catching up. Our idea is to build an AI layer on top of existing EHR tools, matched to what each country’s digitisation already looks like. The tool will support earlier outbreak detection by leveraging existing patient data, which is already being passively collected. In most cases, clinical staff will not be required to manually report anything else than information they are already collecting. The AI layer would alert authorities to disease threats in near real-time (minutes/hours, not days), enabling earlier detection, and thereby, notification, and response. In regards to infrastructure, the data pipeline, encounter records and visualisation layer already exist; the work is the AI layer, scoped specifically to detection. 

Health authorities using data visualisation tool Tupaia to support decision making.

The difference BES would bring – infrastructure and relationships

BES’s involvement will leverage our existing relationships and data infrastructure deployed in Pacific Island Countries. The infrastructure includes two of BES’s flagship products, The Tamanu Electronic Medical Record (EMR), and the Tupaia data visualisation platform. By way of introduction:

• Tamanu is the national EMR in six Pacific Island Countries
• 15 million clinical encounters have been tracked in Tamanu
• Almost 5000 healthcare workers are using Tamanu across the Pacific
• 2 million patients from Pacific Island Countries have a patient record in Tamanu

What’s the relevance of these data platforms to an AI layer? Every patient visit recorded in Tamanu is tracked live. When a cluster of patients turns up at the same clinic in a short window with the same set of symptoms – for example, fever, cough and a rash – it can be an early sign that an outbreak is underway. The AI layer watches for this: it checks incoming data against a set of pre-built thresholds and indicators, and the moment a cluster looks abnormal, it sends an automatic alert to the relevant health authorities, giving them the chance to respond before the outbreak spreads.

It still relies on local doctors and nurses capturing clinical details correctly – but the AI layer can also be trained to detect where this is not happening, enabling us to direct improved training and support.

Who would benefit the most from the AI layer?

Findings from a recent review of 84 outbreaks in Uganda found that faster detection is associated with fewer cases, fewer deaths, and shorter outbreaks. Surveillance timeliness is a determinant of outbreak impact. 

With this AI layer, surveillance teams would become aware of potential outbreak risks much earlier, gaining precious time to mobilize an effective, systematic response through actions like awareness raising campaigns, contact tracing and case finding, positioning of commodities and surge staffing.

Healthcare workers would be able to react more quickly and in the best cases, reduce the impact of disease outbreaks, improving quality care, reducing the spread of transmission and saving lives.

As the response actions reached communities, people could take action to reduce their own risk,  as well as seek care earlier and more easily. Patients and their communities could be diagnosed and treated more quickly and with better care, before an illness has the chance to spread widely. From there, the benefit reaches neighbouring countries and the wider region, since containing an outbreak locally reduces the risk of it crossing borders.

Nothing in the AI removes the human factor required to properly respond to disease outbreaks. Highly trained field epidemiologists, ‘surge’ staff providing clinical care, and public health communication campaigns also need support and strengthening, playing the critical role of using data in their decision making.

But AI can help a lot.

A laboratory technician adding a solution to a sample. Credit: Rawpixel.com

Next steps

Next steps could include:

• Potential partnerships to explore linkages in the Pacific, with donors and Governments
• Conducting feasibility study in a single Pacific Island Country to generate evidence for the initiative
• Conducting a pilot of the AI layer for disease surveillance in one of the countries.
• Seeking grant funding from philanthropists, Governments etc for distinct phases of the initiative, leveraging the results of the feasibility study
• Developing the AI layer with BES’s software developers and data engineers
• Seeking additional funding from Governments, philanthropy and corporations
• Scaling the initiative across nine Pacific Island Countries.

Not forgetting the bigger picture  

Now that we’ve made early disease detection sound straightforward, it’s worth being upfront about the real challenges that apply to any health initiative, even more so in a low-resource setting. This isn’t a simple problem to solve. It starts with the data itself: the consistency and quality of what’s being collected in the first place. Then the build – securing the system, and the genuine complexity of programming AI to detect disease patterns reliably, whilst ensuring data integrity and sovereignty remain paramount. And then implementation – making sure the workforce has the capacity and technical skill to run it, and that the authorities receiving the alerts have the resourcing to act on them with a comprehensive, coordinated response.

Realistically, delivering this sustainably and at scale might take two to three years, and it needs real commitment from funders and partners. But the payoff – automating early outbreak detection to speed up outbreak response and contribute to minimizing preventable deaths- is worth that investment.

When a mother in a rural clinic in the Pacific goes into labour, the difference between life and death can come down to whether there is electricity in the room. Too often, that electricity is missing. Babies have been delivered by the glow of mobile phone torchlights whilst critical procedures have been interrupted by failing generators or small solar systems that can’t keep up.

For those health workers, this is an obvious, everyday struggle. Behind the scenes though, another challenge exists: how do you even know where every clinic is, what services they provide, and what their power situation looks like in the first place? For Superfly Solomon Islands, this was the challenge facing them setting out on a recent project to bring solar power to clinics across Solomon Islands.

That’s where Tupaia, BES’ flagship data platform, has been transformative.

Tupaia can be used to track infrastructure, equipment, disease surveillance, biomedical assets, environmental health programs or supply chain.

A Map That Goes Beyond Medicine

Tupaia was originally designed to track the availability of medicines and health services across the Pacific. In Solomon Islands, in 2017, Tupaia was used to map out hundreds of facilities, capturing GPS coordinates, service levels, and vital infrastructure details — including whether or not the clinic had electricity. This program of data collection was overseen by the National Medical Stores and the data was subsequently used by the Ministry of Health and Medical Services to populate local MHMS systems such as DHIS2.

For doctors, nurses, and policymakers, that data has been useful – DHIS2 now has accurate coordinates for all health facilities across the country. But its ripple effects reach much further and have been sustained. Companies like Superfly Limited, which designs and installs solar energy systems, have relied on Tupaia for years as a foundation for their work.

A Tool for Second-Tier Stakeholders

Superfly Solomon Islands is the country’s only high quality-focused solar power provider, sourcing best-in-class solar components and supplying them for government, private sector, and retail customers. In the health sector, for Superfly, Tupaia has become a first step in scoping new solar deployment projects.

Roughly 80% of health facilities in the country are off-grid, located in some of the most remote corners of the archipelago. By starting with Tupaia, the team can:

• Identify priority clinics — those without reliable power or medical services that would benefit most from solarisation.
• Estimate energy needs — inferring power requirements based on the level of care and services provided.
• Plan logistics — triangulating GPS coordinates with Google Maps to assess roof space, access routes, and the feasibility of installation.
• View clinics in advance, understanding the services they provide, opening hours, and even viewing images to get a sense of the local situation.

In this way, a tool designed for health sector planners has also become a quiet enabler of energy infrastructure, bridging the worlds of medicine, technology, and logistics. The data (and the software) are available free to Superfly and any other stakeholders, as well as members of the public.

Superfly’s work in Solomon Islands incudes the installation of a solar power system at Good Samaritan Hospital on Guadalcanal

Data as the Foundation of Resilient Systems

Superfly’s work has shown how investments in data and mapping can bolster more than just health outcomes. They help coordinate efforts across sectors: energy providers, logistics companies, donors, and government agencies. The result is stronger, more resilient systems. When facilities are mapped and understood, it becomes easier to bring in electricity, refrigeration for vaccines, internet connectivity, and ultimately, better healthcare.

Lighting the Way Forward

The story of Tupaia in Solomon Islands is not just about databases or maps. It’s about turning data into action. It’s about ensuring that when a baby is born in a rural clinic, the light shining on them comes from a reliable solar system — not a flickering torch.

For non-medical stakeholders like Superfly, tools like Tupaia have been vital. For communities across the islands, they are life-changing.

High quality solar projects can be transformative for health facilities across the Pacific

Health facility assessments in Papua New Guinea have been successfully digitised in Tupaia – a GIS and data intelligence platform built by BES – in June 2025. The project, co-funded by the World Bank Group and the Australian Government’s Department of Foreign Affairs and Trade (DFAT) was implemented by partners, the United Nations Office for Project Services (UNOPS) and BES.

In Papua New Guinea, routine health facility assessments allow the national Department of Health to identify gaps in areas like health service provision, staffing levels, infrastructure and biomedical equipment.  In the past, the process for conducting these assessments was made particularly time consuming thanks partly to the use of PDF forms for data collection and spreadsheets for analysis and reporting. 

In June 2025, the health assessments were fully digitised in Tupaia which means that data reporting is now integrated with data collection with the aim of improving the efficiency, quality and accessibility of health assessments. The digitised tool provides health administrators with valuable information to make decisions about where to allocate resources to improve health services for the people of Papua New Guinea. Improved resource allocation should in turn result in better health outcomes.

Gau Baru, Chief Technical Officer, Health Engineering Services, National Department of Health, piloting Tupaia at 6 Mile Polyclinic, 4 June 2025

The key changes made through digitisation of the health facility assessment tool are the speed with which reports are generated and the quality and accessibility of data contained in the reports. Auditors can now collect data through Tupaia’s offline app, MediTrak, while customised reports built in Tupaia.org update as soon as new data syncs. The reports contain a vast array of data, including comparisons with national standards, which is summarised into dashboards and maps that use colour to visually identify areas of concern. 

The system also includes an inventory management module that uses Tupaia’s QR Code capabilities for maintaining records on biomedical and static equipment.

Infrastructure & Engineering dashboard in Tupaia.org

“The tool is one important element that we have been longing for, and having the condition and status (of a facility) known to us has always been challenging. The tool will provide us with the evidence and data we really need to help with evidence based decision making.”

Ambrose Kwaramb, Head of National Health Services Standards

Between April and June 2025 and in collaboration with UNOPS and NDOH, BES imported into Tupaia NDOH’s six assessment surveys and data for 31 health facilities, built reporting dashboards containing over 200 separate data visuals, and piloted the tool with the National Health Services Standards team at 6 Mile Polyclinic health facility in Port Moresby.

“I find the tool very easy, very reliable and user friendly. Previously we used paper which took a lot of time and some data went missing. With Tupaia we just enter data and the information is straight there on the dashboard”

Roy Matthew, Nursing Officer at 6 mile Polyclinic

BES is proud to have contributed to the digitisation of health facility assessments in PNG.

Every day, digital health systems built by BES help visualise thousands of data points across the Pacific and beyond. But data isn’t useful just because it exists. It has to be structured, validated, and presented in a way that helps people make real-world decisions. That’s the job of our data team.

In this post, we share a bit about how that happens – the people behind it, the processes that keep it running, and the work we do to turn raw data into something that matters. Our data team spans Melbourne, Sydney and Canberra, and brings together a mix of backgrounds across analytics, software engineering, and biomedical research.

From point of care to point of impact

Data in Tupaia comes from many sources. Our own data collection tools — MediTrak on Android and DataTrak in the browser — are widely used, especially for surveys and field reporting. But we also pull data from other systems including Tamanu, DHIS2, mSupply, Kobo, and Google Drive, among others. These integrations are designed to be flexible: we can ingest data through APIs, database exports, backups, or spreadsheets, depending on the context.

But just ingesting data isn’t enough. Once we have it, we need to make sure it’s clean, consistent, and safe to report on. That’s where our processing pipelines come in.

Built-in checks and balances

Our data pipelines process over 30 million data points every single day. For that to work reliably, we use automated checks to detect issues in real time, before they impact reports.

When new data arrives, it goes through a series of steps that automatically:

• Remove any deleted, outdated, or otherwise unneeded records
• Check for issues like missing values, data integrity failures, etc.
• Flag inconsistencies for our team to review

If something looks off, it doesn’t just sit there quietly. A validation error is raised and the team is notified. These early alerts are often what allow us to catch issues before they make it into a report or dashboard. It also means we can go back to the original data source, and make sure it doesn’t happen again – whether that’s through user training, or requesting a bug fix in the source system.

Making it easy to report on what matters

As data is ingested, validated, and cleaned, we simultaneously structure it into reporting-friendly database views. We also apply standard calculations at this database view layer, so that metrics are consistent from one visualisation to another. This helps ensure dashboards are fast and reliable, while also keeping the reporting logic clear and easy to follow. Tamanu reports use straightforward queries on these views, and the data from them flows through the rest of our data pipelines. Once in Tupaia’s Viz Builder, they can be combined, filtered, and visualised however needed.

A real-world example: forecasting medication shortages

In September 2023, the Samoan Ministry of Health carried out a mass drug administration for lymphatic filariasis and scabies. Doses were weight-based, and recorded each evening in Tamanu. These were visualised immediately in Tupaia.

After a few days, the dashboards showed something unexpected: stock levels were dropping faster than anticipated. Because of how we model and visualise data, the Ministry was able to quickly spot the trend and take action — placing an emergency order for more medication to ensure the campaign could continue.

That’s the kind of impact we want our data systems to have: helping people see the issue early, and act on it.

To read more about this case study and others like it, visit Data for decision making case studies from the Pacific.

Why it matters

Whether it’s a national outbreak dashboard, a forecasting tool, or a facility-level report, our goal is always the same: to make health data useful. Only then can it be used to improve patient safety, make better policy decisions, or strengthen public health programming.

It takes a solid system, a clear process, and a good team to get there. Fortunately, we have all three.

What happens to all the data collected in Tupaia MediTrak about basic health facility infrastructure? Information on areas including water availability, electricity, and and hygiene services? With the support of Australia’s Department of Foreign Affairs and Trade, and TetraTech International, BES has been working with the Fiji MHMS on a novel, data-based approach to implement infrastructure repairs at the 20 highest-need health facilities in the country.

How were these facilities identified? The work is part of the national health supply chain reform project, which started with a national Tupaia survey. BES are working with MHMS and the Fiji Pharmaceutical and Biomedical Service (FPBS) to improve the supply chain for the national health system and as part of that work, identifying, locating, and gaining baseline data from all facilities was identified as an early priority.

Vunivutu door locks: before and after

MHMS staff, with the support of BES Project Managers, fanned out across the country in 2022, touring to nearly every health facility in the country to collect invaluable information in a structured, standardised way using Tupaia MediTrak. MediTrak is a free, open-source health data collection app designed specifically for remote settings in the Indo-Pacific region. Data can be collected offline against any entity – fridges, clinics, houses, communities, water sources etc – and aggregated using Tupaia’s powerful data platform. During the initial data collection round, staff built a snapshot of medicines availability across all facilities but in addition looked at issues such as basic medical equipment, staff training needs, shelving and storage infrastructure, water supply, physical access and WASH facilities.

With every facility in Fiji comprehensively assessed, BES and MHMS used Tupaia to identify the twenty lowest performing facilities across the country. These 20 facilities were then targeted for low-cost but high-impact repairs, maintenance, and training activities to help improve the average performance of all facilities in the country. BES staff coordinate the follow-up maintenance visits to these 20 facilities, whilst MHMS staff lead on the ground and help guide the activities most important to improving patient experiences. The work has also been delivered through a gender and disability lens, highlighting gaps in areas such as wheelchair accessibility, menstrual care facilities, and safe working environments for female staff at night.

This follow-up mechanism ensures that data collected in surveys is actioned, resulting in tangible improvements to Fiji’s basic health facility infrastructure. The data-led approach ensures efficiency – with a limited bucket of resources, focusing on the facilities in most need is imperative, as well as knowing exactly what is required in each of those facilities, rather than trying to implement a one-size-fits-all approach.

Lomaivuna water tanks: before and after

At Moce Nursing Station, a remote facility in Fiji’s Eastern Division, the program has recently enabled:

• Installation of solar panels, meaning the facility can now provide patient care at night, which was not previously possible. They can now also use electronic equipment, including the concentrator and nebuliser machine, and charge their mSupply tablet to place orders for essential medicines and medical supplies to FPBS.
• Water pipe repair, resulting in restoration of water supply to the facility, and repair of two toilets for patients.
• Repair of the facility door and lock replacement, improving security.

“Now I don’t have to worry about trespassers entering the station after hours,” said the nurse at Moce Nursing Station. “I’m very thankful to [the] Tupaia project for all that’s being done for Moce Nursing Station. It has made my work easier and enabled me to carry out my nursing duties. Also, the people of Moce are very happy with the maintenance done as they have also benefit[ed] from it… I have 2 patients admitted at the moment, and it’s good to see them using the toilets in the station instead of walking to my quarters to use the washroom.”

Moce toilets: before and after

Other facilities that have benefited from the project include Kabara Health Centre, Naduri Health Centre, Navakaka Nursing Station Savusavu Health Centre, Vunivutu Nursing Station, Rakiraki Health Centre, and more.

BES is currently working with the Fiji MHMS to plan the next round of national surveys this year, when staff will visit every health facility in the country with MHMS staff to assess infrastructure, supply chain, and basic clinic services – and begin the cycle of data for action again!

BES are set to enhance digital product ownership and leadership in the Pacific with the doors of a new Support Centre, based in Suva, Fiji, opening this week. 

Two full-time, Fijian staff will provide service desk support to BES platform users across the Pacific region – covering Tamanu, Tupaia and SENAITE.. Participating countries can directly access the Support Centre through the Tamanu platform or explore the revamped support website on mobile or desktop.

“The goal is to continue to localise tech-support, to create jobs and to add to the overall sustainability of the digital health ecosystem in the Pacific,” said Michael, Chief Executive Officer of BES.

“We know the Pacific is leading in implementing digital health technology. A local Support Centre just adds to this,” said Michael. 

“The best support is Pacific-based. The local team appreciates the Pacific context; such as internet outages, power interruptions and often a lack of local IT support. They know the culture, communication styles and for the health sector – the work landscape,” said Michael.

The support team will also be in the same timezone as its users. A benefit that cannot be understated. 

“It’s a simple thing, but when you’re having a tech-issue you don’t want help in ten hours or the next-day. Having a local support team will improve response times,” says Rahul Prasad who will help lead the support desk. 

Backed by Zendesk, a popular service desk system in the tech-industry, requests for help to the Support Centre can be raised in multiple ways. Email, online forms, and LiveChat can be used, with Viber being piloted later this year as another way to ask for assistance. 

Photo: Zendesk software will help the team manage requests coming from multiple sources across the Pacific

The LiveChat is powered by an intelligent ChatBot named Waka – who is programmed to respond to common questions with answers. While Zendesk keeps track of all the queries, the support team can work more efficiently with greater oversight of regional trends or issues. 

“Waka is a Polynesian word for ‘canoe’ and a Melanesian Pijin word for ‘work’”, explains Michael. “Our staff liked the idea of using Waka to go and get help, as you might do in a canoe throughout the islands – and to support their work” 

Equipped with dashboards and visual workflows, the support team can gain data-based insights for proactive monitoring, training, and ultimately, the optimised use of BES-supported platforms; Tamanu, Tupaia, SENAITE and DHIS2.’‘ 

A comprehensive Knowledge Centre with a search function is also at users’ finger tips. This helps users by providing easy to find training articles with step-by-step guides and lots of screenshots. 

The Support Centre’s initial roll-out serves BES customers based in Nauru. BES were fortunate to be able to provide face-to-face training for 61 dedicated health professionals from the Republic of Nauru Hospital and Public Health Clinics on the new BES Support Centre.

Photo: Clinical staff from the Nauru Ministry of Health receive training in accessing the new support centre and ‘Waka’

“A heartfelt thank-you to all our Nauru users for embracing this new platform. Your open-mindedness and willingness to adapt will undoubtedly enhance the benefit you’re getting from the systems and help you serve your communities even better in the long run.” – A message from BES staff member Alex to training participants in Nauru.

The full roll-out of BES Support Centre services will expand to include other Pacific countries in early 2024, where BES products are used. Palau is next onboard in mid-February, 2024. 

Any country that has Tamanu v1.36.0 (or above) and ‘accidently or curiously’ clicks the ‘Support Centre’ button at the bottom left of Tamanu (when logged in) can raise a ticket as well!

The future is digital, and it’s in the Pacific!

#BeyondEssentialSystems #SupportCentreLaunch #HealthcareInnovation #EmpoweringCommunities #Sustainability #Tamanu #Tupaia

Jessica believes that ‘continued ‘South to South’ cooperation in the region can foster stronger relationships and increase the potential for healthcare workforce mobilisation in the Pacific’.   

Everyone in the Pacific benefits when Pacific islands can request staff support with broader experience and knowledge during staff shortages, emergencies, and crises and to support health campaign rollouts. Exchanging skills and staff within the Pacific has the added benefit of cultural understanding and nuance. This knowledge shortens the learning curve in a new setting for staff with greater familiarity with similar healthcare challenges. 

The regional skill exchanges work towards cultural and contextual understanding. They focus on respect for national sovereignty and shared responsibility, strengthening the region’s healthcare systems. 

Knowing how to communicate culturally and speak with a regional voice is more likely to lead to real and effective change, even in the diverse language and cultural systems of the Pacific region. 

‘Knowing the software is one thing, but looking around and seeing what can be improved diplomatically so that real change happens is important too’, says Elizabeth Bryson, who visited Niue on the DTAC program skills exchange from the Cook Islands. In April, DTAC invited Elizabeth to visit Niue to support the move from paper to digitisation of their pharmacy systems by implementing mSupply. 

 Elizabeth arrived in Niue with the public health team and got straight into the stocktake of one of their three locations. She met with the pharmacy team and had many suggestions to help to create a safer and more efficient workplace, skills she had already learned from her work in the Cook Islands.

As a champion of change, Elizabeth believes that ‘’Building relationships is so important across the Pacific.’ She never imagined that she would ever visit Niue to support their health system, but now she can see that it is a practical solution with so much to gain from both sides. She takes with her skills and knowledge that will impact a project she is working on in the outer islands of her country, where the medicine supply can be difficult to manage. 

Elizabeth hopes that regional collaboration can continue between countries in the Pacific and that she can take the lessons learned from her experience to continue to strengthen health systems in the Cook Islands. She can see that the much more isolated Niue and outer Cook Islands have some similarities – and she now has some insight into possible problems and solutions because of her experience with skills exchange in Niue. 

BES and the mSupply Foundation support the Pacific skills exchange through peer-to-peer networks between PICTs with the support of DFAT and MFAT.

Elizabeth Bryson (The Cook Islands Ministry of Health) and Jessica Jago (DTAC) enjoy beautiful Niue in between stocktakes. The Pharmacy Dispensary Team: Ebony Feleti and Seddon Paka with Elizabeth Bryson from the Cook Islands Ministry of Health. The Public Health and Nursing Team, organising a stocktake of their medical consumables: Andy Manu, Reuben Siataga with nurse, Fonokalafi Moleni, and Jessica Jago (DTAC Project Manager). Ebony Feleti, organising the pharmacy. Team photo celebrating the launch of mSupply for the Public Health Department in Niue. Jessica Jago and Elizabeth Bryson after a long day of stocktake. Nurse, Fonokalafi Moleni in the pharmacy.