Leveraging Open-Source and Low-Resource Tools to Strengthen National Public Health Institutes in LMICs for Effective Mpox Outbreak Response

Introduction

The re-emergence of Mpox, a zoonotic viral disease, has underscored the vulnerability of global health systems, particularly in low- and middle-income countries (LMICs). With limited resources, LMICs often face an uphill battle when dealing with infectious disease outbreaks. At the frontline of these challenges are National Public Health Institutes (NPHIs), which shoulder the responsibility of detecting, monitoring, and responding to epidemics like Mpox. Yet, many NPHIs in LMICs are constrained by inadequate technology, underfunding, and insufficient trained personnel, making effective outbreak management difficult.

But where challenges exist, so too do solutions. Open-source and low-resource tools, many of which have been tested in previous global health crises, can provide critical support. These tools—including social media monitoring, event-based surveillance, mobile data collection platforms like Open Data Kit (ODK) and CommCare, clinical decision support algorithms, artificial intelligence (AI), and real-time data dashboards—are not only cost-effective but adaptable. With these innovations, NPHIs can enhance their surveillance capacities, streamline data management, and make more informed decisions. It’s a simple truth: Public health outcomes improve by using technology that scales to local contexts.

Background on Mpox and the Role of NPHIs

Mpox Overview

Mpox, caused by the mpox virus, is part of the Orthopoxvirus genus. The disease manifests with symptoms like fever, rash, and swollen lymph nodes, which, in severe cases, can lead to respiratory or neurological complications. The virus spreads through direct contact with infected individuals or animals, as well as through respiratory droplets in prolonged close interactions. While Mpox may not make headlines like other viruses, its outbreaks can stretch healthcare systems—especially in LMICs that are already operating with limited resources (World Health Organization, 2022).

Role of NPHIs

NPHIs are the unsung heroes of public health—often working behind the scenes to keep disease outbreaks from spiraling out of control. Their primary tasks include:

• Surveillance: Monitoring disease trends and identifying emerging threats.
• Case Detection and Diagnostics: Identifying and confirming cases through laboratory testing.
• Data Management and Analytics: Collecting, storing, and analyzing health data to inform responses.
• Resource Mobilization and Coordination: Ensuring that resources, whether personnel or medical supplies are deployed effectively.
• Public Health Communication: Informing the public with accurate, timely information while countering the ever-present risk of misinformation.

In LMICs, however, the obstacles NPHIs face can seem almost insurmountable.

Challenges Faced by NPHIs in LMICs During Mpox Outbreaks

Managing a public health crisis like Mpox is tough even in well-resourced countries, but for NPHIs in LMICs, it can feel like walking a tightrope. These institutes must balance immediate responses with long-term sustainability, often while under-resourced and under-supported.

Some of the most pressing challenges include:

• Limited Technology Access: Many NPHIs are working with outdated or insufficient technological infrastructure, making real-time disease surveillance and data management nearly impossible (Kruk et al., 2018).
• Lack of Interoperability: With various health information systems that don't “talk” to one another, data sharing becomes a nightmare.
• Data Collection Bottlenecks: Gathering timely, accurate data is essential during an outbreak, but delays in data collection can hobble response efforts.
• Coordination Difficulties: Managing diverse stakeholders, from local communities to international health bodies, is a complicated and often time-consuming process.

Yet, the tools that can address many of these issues are not as far out of reach as one might think.

The Promise of Open-Source and Low-Resource Solutions

Open-Source Solutions

Open-source tools are the democratizers of technology. These platforms, which are free to use and adapt, provide much-needed flexibility for NPHIs working with limited budgets. Because they come without the hefty price tags of proprietary software, open-source solutions allow public health institutes to direct their resources where they’re needed most: saving lives. These tools are also customizable, meaning they can be adapted to local contexts and specific public health needs (Open Source Initiative, 2023).

Low-Resource Tools

For regions where technology infrastructure is sparse, low-resource tools like social media and event-based surveillance systems offer an ingenious way to extend the reach of public health monitoring. By tapping into already widespread platforms like WhatsApp or Twitter, NPHIs can gather data quickly and inexpensively—allowing for faster, more targeted responses in places where traditional healthcare infrastructure might not exist.

AI and Dashboards

In a world flooded with data, the challenge often lies in making sense of it all. This is where AI and dashboards come into play. Tools like PowerBI, Tableau, and Zoho Analytics allow NPHIs to visualize complex data sets in a digestible way, helping decision-makers identify trends and allocate resources swiftly. In short, these dashboards transform numbers into actionable insights (Mazzoli et al., 2021; Yuan et al., 2021).

Some Tools to Support Mpox Response in LMICs

Here are a few open-source, and low-cost tools, I have interacted with over the last decade that can be useful to support the Mpox response;

1. Event-Based Surveillance and Social Media Monitoring - As everyday tools for millions, social media platforms are powerful channels for public health surveillance. By monitoring public discussions, health authorities can pick up early signs of an outbreak and address misinformation quickly. It's not just about detecting symptoms—it's about understanding how people are responding to public health risks and interventions (Boulianne, 2019). Similar to this, in resource-limited environments, mobile data collection tools like ODK and CommCare are invaluable. These platforms allow NPHIs to gather real-time data from even the most remote regions, and their offline functionality ensures continuous operation, even when internet access is spotty (Pfeiffer et al., 2018).

2. Clinical Decision Support Tools and Algorithm Libraries- Open-source CDSS tools can guide healthcare workers through diagnosis and case management, ensuring a standardized approach to Mpox treatment. With consistent algorithms, these systems reduce diagnostic errors, allowing for more accurate and efficient care (Gordon et al., 2020). AI doesn’t just crunch numbers—it can also predict disease outbreaks. By analyzing clinical data and factoring in variables like population density and mobility, AI algorithms help health authorities predict where Mpox might spread next, allowing for proactive interventions (Vermunt et al., 2021).

3. Data Analytics and Visualization Dashboards - Dashboards using tools like PowerBI, Tableau, and Zoho Analytics bring data to life. In the hands of NPHIs, these tools can display real-time case numbers, testing rates, and resource availability on easy-to-understand dashboards, turning raw data into a clear and actionable picture (Yuan et al., 2021).

4. Surveillance and Data Collection Tool - DHIS2 is a cornerstone for health data management in LMICs. It’s open-source, customizable, and widely used. This platform makes it easier to track and analyze Mpox-related data in real time, enhancing both reporting and monitoring capabilities (Harris et al., 2019). Similarly, SORMAS - a comprehensive outbreak management tool helps track cases, manage contact tracing, and collect epidemiological data, making it a critical ally for NPHIs managing Mpox outbreaks (Müssigbrodt et al., 2018).

5. Geographic Information Systems (GIS) - Creating context for data unlocks a much deeper level of insight. Mapping an outbreak’s spread is key to understanding and containing it. QGIS, an open-source GIS tool, helps visualize the geographic distribution of Mpox cases, identifying hot spots where containment measures might be most effective (Bivand et al., 2013).

6. Communication and Community Engagement - SMS may seem old-school, but they are a winner when it comes to ease of use and adoption in low-resource settings. Platforms such as RapidPro are invaluable for reaching out to communities. It can disseminate health information via SMS or messaging apps, engage people in surveys, and build two-way communication with the public—all of which are crucial during an outbreak (White et al., 2020).

Leveraging AI and Machine Learning for Real-Time Decision Support

AI might sound futuristic, but it’s already reshaping public health responses. By analyzing massive data sets, AI can predict the future course of an outbreak, allowing NPHIs to plan rather than simply react. Imagine knowing the trajectory of a disease before it happens—AI turns this into a reality.

The Value of Open-Source and Low-Resource Tools

What makes open-source and low-resource tools so compelling is their accessibility and adaptability. They break down barriers, making advanced technologies available to even the most resource-constrained regions. Whether through their cost-effectiveness, scalability, or ability to function in low-connectivity environments, these tools provide real-world solutions to complex challenges (Open Source Initiative, 2023).

Overcoming Barriers to Adoption

While the benefits of open-source and low-resource tools are undeniable, barriers remain. Lack of technical expertise can prevent these tools from reaching their full potential, which is why capacity-building initiatives and international partnerships are so important. Initial setup costs can also be a hurdle, but the long-term savings and increased efficiency justify the investment.

Case Studies: Learning from the Past

The use of open-source or low-cost technology solutions is not new within the LMICs. There is documented evidence of remarkable successes recorded with their deployment. Epidemics such as Ebola and COVID-19 are recent examples in Africa.

Ebola Outbreak in West Africa

During the 2014-2016 Ebola outbreak, open-source tools like DHIS2 and SORMAS helped track cases in real time and improved coordination across multiple agencies. The lessons learned from Ebola underscore the importance of digital tools in managing fast-moving epidemics (Müssigbrodt et al., 2018).

COVID-19 Pandemic

The COVID-19 pandemic reinforced the power of digital platforms like RapidPro and DHIS2. These tools were essential in community engagement and data management, enabling countries to respond quickly and effectively even in the most challenging circumstances (White et al., 2020).

Conclusion

The future of public health in LMICs lies in embracing open-source and low-resource tools. These technologies offer scalable, adaptable, and affordable solutions that enable NPHIs to act swiftly in the face of outbreaks like Mpox. By investing in these tools—and in the training and infrastructure needed to support them—countries can build more resilient health systems capable of responding to future health threats.

The solutions are here. It’s time to put them to work.

References

• Bivand, R., Keitt, T., & Rowlingson, B. (2013). Spatial Data Analysis: An Introduction. Springer.
• Boulianne, S. (2019). Social Media Use and Participation: A Meta-Analysis of Current Research. Social Media + Society, 5(1), 1-19.
• Gordon, W., et al. (2020). Clinical Decision Support Systems: Current Status and Future Directions. Journal of Clinical Informatics, 6(2), 73-82.
• Harris, B., et al. (2019). Implementing and Scaling DHIS2 in Low-Resource Settings. Health Information Systems Journal, 25(4), 145-159.
• Kass-Hout, T., & Alhinnawi, H. (2020). Artificial Intelligence for Health and Healthcare: A Review. Journal of Health Informatics Research, 4(3), 261-279.
• Kruk, M. E., et al. (2018). Building Stronger Health Systems: The Role of NPHIs in Global Health Security. Global Health Action, 11(1), 1-12.
• Mazzoli, S., et al. (2021). Real-Time Decision Support Systems for Epidemic Outbreaks. Journal of Public Health Informatics, 13(1), 65-79.
• Müssigbrodt, S., et al. (2018). The Role of SORMAS in Managing Epidemic Outbreaks. Epidemiology and Infection, 146(11), 1234-1243.
• Open Source Initiative. (2023). Open Source Software: A Comprehensive Guide. Retrieved from https://opensource.org/
• Pfeiffer, J., et al. (2018). Mobile Data Collection Tools in Low-Resource Settings: A Review. Journal of Global Health, 8(2), 1-10.
• Vermunt, J. K., et al. (2021). Machine Learning for Predictive Analytics in Public Health. Public Health Reviews, 42(1), 12-29.
• White, R., et al. (2020). Community Engagement in Health Crises Using RapidPro. Journal of Communication in Healthcare, 13(3), 245-258.
• World Health Organization (WHO). (2022). Mpox: Information and Guidance. Retrieved from https://www.who.int/
• Yuan, Y., et al. (2021). Data Visualization and Analytics in Public Health. International Journal of Health Data Science, 7(4), 198-210.