A Launch Met with Enthusiasm

The WHO event was the ideal platform to unveil Epiverse in Africa, bringing together a diverse audience of global health leaders, innovators, and policymakers.

One of the most inspiring outcomes of the official launch was the level of interest from strategic partners eager to join the journey. Representatives from countries across Africa expressed their interest in adopting Epiverse and integrating it into their national health strategies. There was a shared recognition of the need for initiatives like Epiverse to address diverse health challenges like epidemic preparedness and healthcare optimization by reimagining solutions and methods.

Collaborative Opportunities

Beyond the launch, the event highlighted exciting opportunities for collaboration, including:

• Local Data Solutions: Tailoring Epiverse tools for specific regional needs. This can only be done by working closely with local experts and communities to adapt our interventions. And this echoes our data.org approach of thinking globally, but working locally.
• Capacity Building: Empowering regional hubs to ensure local ownership and equipping local professionals and communities with skills to facilitate the Epiverse adoption and maximize its impact.
• One Health Approach: Aligning efforts with other social impact organizations (SIOs) working in animal and environmental health.

These discussions laid the groundwork for transformative partnerships and innovations.

Looking Ahead

Our plan for Epiverse’s next phase of broader adoption is ambitious yet focused: “Roll out the suite of tools in 10 African countries as part of the initial implementation”. To ensure success, we will prioritize local engagement, working closely with government bodies, local data practitioners, and key stakeholders to understand each country’s needs and/or challenges.

We are also committed to localizing training and fellowship programs to build the capacity of professionals on the ground, empowering them to champion Epiverse’s adoption. By equipping local leaders with the knowledge and tools they need, we aim to create a sustainable model for long-term impact, led by those closest to the issues at hand.
As part of this effort, we are excited to announce the launch of the Epiverse Fellowship Program in Q1 2025. This program provides an opportunity for professionals to develop their expertise, collaborate with global peers, and drive the adoption of Epiverse in their respective countries and communities.

Together, we can harness the power of data and technology to address past and present challenges while anticipating tomorrow’s needs. Our shared goal is to create a healthier, more equitable world and foster a resilient, inclusive approach to global health security.

The post Catalysts for Change: Building the Future of Public Health Intelligence appeared first on data.org.

How will we respond when the next crisis hits? 

To ensure that we are better prepared when that time comes to collect, share, and take action informed by data, we launched Epiverse, a collaborative to develop a trustworthy data analysis ecosystem. This system of standardized, easily accessible epidemiological software tools, is making exciting progress toward strengthening our resilience and response in the global fight for public health. 

Using GitHub—a collaborative development platform for creating, storing, and managing code—we have more than 15 packages available. The design of these free-to-use, open-source tools was informed by methods and analysis used successfully in epidemic response to infections including cholera, COVID-19, dengue, diphtheria, Ebola, influenza, and Zika. Three of the packages are available on the Comprehensive R Archive Network, or CRAN, making them more easily accessible and proving their high quality, and have been downloaded more than 21,000 times, and three are certified as digital public goods by the Digital Public Goods Alliance.

In other words, the Epiverse ecosystem is growing by the day, and we are committed to making it accessible and actionable for our likewise growing network of partners. The Epiverse community launched ​​training materials to support the adoption of computational tools in epidemiology and hosted an in-person training event in Colombia.

To further expand our reach, we are excited to announce a new partnership with RECON and rOpenSci. RECON delivers a collection of epidemiological tools that provide key building blocks and methods for the Epiverse ecosystem. rOpenSci brings over a decade of expertise in creating software standards and managing code and community through its unique software peer-review process.  As part of this partnership, rOpenSci will work with Epiverse developers to produce sustainability strategies for the software suite, including growing the user and contributor base, training skilled maintainers, producing developer documentation, and planning for governance and knowledge transfer. rOpenSci will also use its expertise in multilingual software development to help make Epiverse more accessible to non-English users and contributors. 

At data.org, we think a lot about the best ways in which we can contribute to an ecosystem of digital public goods and build purpose-driven data capacity for the social impact sector. Through our training, resources, webinars, and cross-sector partnerships, we aim to advance the growing community of people and organizations doing good work to harness the power of data and deploy it for social impact. With RECON and rOpenSci in our corner, we are in an even better position to do just that. 

The post Forging Partnerships and Accelerating the Field: New Epiverse Partnerships with RECON and rOpenSci appeared first on data.org.

The development of digital tools for social impact and specifically for scientific research and technically driven decision-making requires a new approach to professional development and team building. In Scientific Software Development (SSD), particular challenges must be faced, for “social impact products demand a more complex design process than commercial products do because of the complicated ecosystem of data providers, partnerships, and revenue streams required to bring them to life.” That complex design process depends upon a diverse team and one in which roles and skills are defined differently from those existing in the industry.

To face these demands, we should move away from conventional understandings of the social division of labor and consider SSD—and Open Source Software (OSS) at large—as an emergent field, with specific needs and changing dynamics. 

For instance, we know that collaborative networks are important for the sustainability of OSS projects. In other words, OSS projects rely on community participation for progress. This community-based growth of OSS highlights how people sustaining OSS collaborate, for interaction functions primarily occur through indirect communication (via platforms such as GitHub), even questioning traditional division of labor structures in this type of work.

How does the division of work operate in OSS and particularly in SSD initiatives when facing their challenges? 

This is not a simple question, but there are key themes worth exploring. 

During the Collaborative Software Development Ecosystem for Public Health – Epiverse-TRACE Summit, which was held in Bogotá from June 26 to July 7, 2023, members of the Epiverse-TRACE initiative met to discuss topics such as collaborative software development, team building, and community engagement. In these conversations, we posed three new questions:

1. What roles are necessary for SSD enterprises and what does this word (role) mean in context? 
2. What are the structures for collaborative work between different roles? and
3. What kind of growth opportunities do these roles bring?

Context is Everything

When discussing the intricate design process involved in this type of software development, one could compile an exhaustive list. Indeed, in the summit discussions we identified a list of 20 different roles that can be tailored to the needs of the SSD and involves many more fields than software engineering for research and data science. However, it is worth highlighting that beyond Research Software Engineering and Data Science roles, those focused on the localized and contextualized engagement, design, testing, and direction of technological tools are equally critical to produce tools that could be globally connected and, at the same time, locally situated and significant.

For instance, domain expertise—such as epidemiology in the case of Epiverse—is crucial for orienting and defining SSD’s purposes. Domain experts represent the community of practice for which a software solution is produced, offering knowledge from a highly specialized user perspective. Social scientists, communicators, UX/IX designers, and training experts bring to SSD a user-centered and context-sensitive perspective to SSD, thus minimizing the risks of being lost in the translation between different styles of thinking and communities.

Simultaneously, traditional and new research coordination roles are necessary for sustaining the SSD initiatives, by mobilizing funding and promoting collaboration within and beyond projects. These roles play a crucial part in establishing new alliances with stakeholders and managing the human talent, financial, and bureaucratic resources required for the successful development and implementation of scientific software solutions.

In SSD, roles should not imply a strict division of labor but rather delineate collaborative spaces that facilitate the achievement of shared goals. 

Viewed from this perspective, we can understand how developers engage in translation activities throughout the development process by putting development outputs in tune with users’ definitions of priority, concerns, and needs. Similarly, social scientists and domain experts also do data science when reflecting on, and challenging different understandings of data and its uses, utility, and consequences.

Cultivating Collaboration Across Roles

As a relatively new field, we are encouraged to build new and open forms of work. If we understand roles in SSD as spaces for collaboration, what should this collaboration look like? SSD calls for a movement from rigid disciplinary efforts to forms of transdisciplinary cooperation.

On one hand, producing valuable SSD outputs requires different knowledge and communities. On the other hand, this knowledge is not limited to specialized professionals involved in a project. It is distributed among different types of users, including diverse external domain experts, other developers and collaborators who can interact with and improve SSD outputs, organizational stakeholders, and decision makers.

New Field, New Opportunities

Let us think of SSD as an opportunity. Placed at the interaction of the worlds of research and decision-making, SSD has the potential to avoid the traditional misunderstandings and uncontrolled mistakes that have fueled distrust and unease on both sides of this interface. SSD as transdisciplinary collaboration offers an opportunity to value the standpoint of different actors, to engage them in more open and humble conversations on decisive topics and translate this into durable technological outcomes.

Getting on the same page will help, but improved communication is not the only opportunity created by SSD.

As a transdisciplinary effort, SSD projects constitute an ideal environment for the career development of those involved. Building on Epiverse’s vision to place people at the center of software development, we can say that “the most important determinants of a successful OSS project are first and foremost about humans, and how they interact.” Cross-fertilization between different expertise, standpoints, and global connections open doors for personal and professional growth by providing the interchange of a wide range of skills.

As with skills, so with perspectives. Diversity in the broad sense is central to SSD enterprises. The engagement of different voices and experiences strengthen development outputs by improving their relevance and usability and fostering a sense of ownership within the user community. At the same time, it promotes an enabling environment for horizontal learning. This is not a minor thing if we consider how important it is for overcoming important barriers that are the business as usual in STEM fields, like the gender gap. By doing so, SSD shares the potential of different data science initiatives to contribute to a more equitable world.

The process of building diverse Scientific Software Development (SSD) teams highlights that SSD is more than simply writing code to develop innovative solutions. It emphasizes how the innovative nature and solution-oriented quality of technological advancements depend on a robust and diverse network of interactions among various roles, expertise, and collaboration mechanisms.

Stakeholders and funders should recognize this complexity when implementing and supporting SSD projects. Doing so will not only produce more responsible development outputs but also foster more diverse and inclusive development environments. Furthermore, it will enhance the professional growth of the individuals involved, who are tasked with transforming global and local infectious disease responses, while contributing to a more generous and sustainable world.

The post Building the Bench: Assembling an Interdisciplinary Team for Scientific Software Development appeared first on data.org.

El desarrollo de herramientas digitales para el impacto social y, en concreto, para la investigación científica y la toma de decisiones técnicas requiere de diversas prácticas de formación de equipos y una definición de roles y competencias distinta a la de la industria. En el desarrollo de software científico (SSD, por sus siglas en inglés) deben afrontarse retos particulares, ya que “los productos de impacto social exigen un proceso de diseño más complejo que los productos comerciales debido al complicado ecosistema de proveedores de datos, asociaciones y flujos de ingresos necesarios para darles vida”.

Para hacer frente a estas exigencias, debemos alejarnos de las concepciones convencionales de la división social del trabajo y considerar el SSD -y el Software de Código Abierto (OSS) en general- como un campo emergente, con necesidades específicas y dinámicas cambiantes. Por ejemplo, sabemos que las redes de colaboración son importantes para la sostenibilidad y crecimiento de los proyectos de OSS.  Este desarrollo basado en la comunidad llama la atención sobre cómo las personas que sostienen los proyectos de OSS colaboran, ya que su interacción se lleva a cabo principalmente a través de comunicación indirecta (en plataformas como GitHub), cuestionando estructuras rígidas de división del trabajo en este tipo de tareas.

Entonces, uno de los retos para las iniciativas de desarrollo de software para el impacto social es enfrentarse a la pregunta por la formación de equipos de trabajo y por sus formas de colaboración: ¿cómo opera la división del trabajo en el OSS y particularmente en iniciativas de desarrollo de software científico? La respuesta a este interrogante está lejos de ser simple, pero hay asuntos clave que llaman nuestra atención y que quisiéramos compartir con diferentes comunidades de OSS.

Las reflexiones que presentamos hicieron parte de las discusiones del evento Collaborative Software Development Ecosystem for Public Health – Epiverse-TRACE Summit, llevado a cabo en Bogotá del 26 de junio al 7 de julio de 2023. En este espacio, diferentes miembros de la iniciativa Epiverse-TRACE se reunieron para discutir temas como el desarrollo de software colaborativo, la formación de comunidades de usuarios y el ensamblaje de equipos interdisciplinares para el SSD. Para explorar este último asunto, nos planteamos tres preguntas:

1. ¿Qué roles son necesarios para las iniciativas de SSD y qué significa esta palabra (rol) en contexto?
2. ¿Cuáles son las estructuras para el trabajo colaborativo entre diferentes roles? 
3. ¿Qué tipo de oportunidades de crecimiento ofrecen estos roles?

Aunque una elaboración más compleja de la respuesta a estas cuestiones se encuentran en el reporte del evento, y harán parte de un artículo en desarrollo, a continuación queremos esbozar algunas líneas que -creemos- merecen ser tenidas en cuenta al momento de formar equipos robustos para el SSD:

El contexto lo es todo

Al discutir el intrincado proceso de diseño involucrado en este tipo de desarrollo de software, se podría recopilar una lista exhaustiva de roles necesarios. De hecho, en las discusiones del Summit identificamos una lista de 20 roles que pueden ser adaptados a las necesidades del SSD y que involucra muchos más campos que la Ingeniería de Software para la investigación y la ciencia de datos. Además de estos, los roles centrados en la contextualización y localización del diseño, las pruebas y la orientación de las herramientas de software abierto son igualmente importantes para producir tecnologías globalmente conectadas y, al mismo tiempo, localmente situadas y significativas.

Por ejemplo, el conocimiento especializado en el SSD es crucial para orientar y definir los propósitos de los resultados del desarrollo. En este proceso, aquellos roles orientados a brindar conocimiento especializado en un área particular representan a la comunidad de práctica para la cual se produce una solución de software determinada. Ofreciendo conocimientos desde una perspectiva de un usuario altamente especializado, profesionales en epidemiología, salud pública, demografía, clima y geografía, entre otras áreas dotan de sentido el SSD.

De igual manera, especialistas en las ciencias sociales comunicación, en diseño de experiencia de usuario y de interfaz, y especialistas en entrenamiento aportan a SSD una perspectiva centrada en el usuario y sensible al contexto, minimizando así los riesgos de perderse en la traducción entre diferentes estilos de pensamiento y comunidades.

Simultáneamente, los roles de coordinación de investigación tradicionales y nuevos son necesarios para sostener las iniciativas de SSD, movilizando financiamiento y promoviendo la colaboración dentro y más allá de los proyectos. Estos roles desempeñan un papel crucial en el establecimiento de nuevas alianzas con partes interesadas y en la gestión del talento humano, los recursos financieros y burocráticos requeridos para el desarrollo e implementación exitosa de soluciones de software científico.

A pesar de marcar áreas específicas de acción, en el desarrollo de software científico, los roles no deben implicar una división estricta del trabajo, sino delinear espacios colaborativos que faciliten el logro de objetivos compartidos.

Desde esta perspectiva, podemos entender cómo aquellas personas dedicadas al desarrollo de software como tal participan en actividades de traducción a lo largo del proceso de desarrollo. Es importante considerar cómo expertos en la ingeniería de software y la ciencia de datos alinean activamente las salidas de desarrollo con las definiciones de prioridad, preocupaciones y necesidades de los usuarios. De manera similar, los y las científicas sociales y especialistas en un área particular del conocimiento también realizan ciencia de datos al reflexionar y desafiar diferentes entendimientos sobre los datos y sus usos, utilidad y consecuencias.

Cultivando la Colaboración entre Roles

Como un campo relativamente nuevo, el SSD e iniciativas de desarrollo de software de código abierto nos alientan a construir formas de trabajo nuevas en las que los diversos roles constituyen espacios para la colaboración. Entendiendo esto, la pregunta que procede es ¿cómo debería lucir esta colaboración? El SSD requiere un movimiento de esfuerzos disciplinarios rígidos hacia formas de cooperación transdisciplinarias.

Por un lado, la producción de resultados valiosos de SSD requiere de diferentes conocimientos y comunidades. Por otro lado, este conocimiento no se limita a profesionales y especialistas involucrados en un proyecto: está distribuido entre diferentes tipos de usuarios y usuarias, así como en diversos perfiles especializados en conocimientos que pueden asesorar el proceso de desarrollo de software. Y, por supuesto, este conocimiento procede también de otros desarrolladores y desarrolladoras y de organizaciones y personas interesadas en colaborar que pueden interactuar y mejorar los resultados de un desarrollo de software.

Nuevo Campo, Nuevas Oportunidades

Pensemos en el desarrollo de software científico como una oportunidad. Situándonos en la interfaz de los mundos de la investigación y la toma de decisiones, el SSD tiene el potencial de evitar los malentendidos tradicionales y los errores no controlados que han alimentado la desconfianza y la incomodidad en ambos lados de esta interacción. El SSD como colaboración transdisciplinaria ofrece la oportunidad de valorar el punto de vista de diferentes participantes, de involucrarse en conversaciones más abiertas y humildes sobre temas decisivos y de traducir esto en resultados tecnológicos duraderos.

Colaborar y llegar a acuerdos entre distintos sectores y áreas del conocimiento es importante, sin embargo no es la única oportunidad que ofrece el SSD.

Como esfuerzo transdisciplinario, los proyectos de SSD constituyen un ambiente ideal para el desarrollo profesional de quienes están involucrados. Basándonos en la visión del Epiverse de colocar a las personas en el centro del desarrollo de software, podemos decir que “los determinantes más importantes de un proyecto OSS exitoso son, en primer lugar, sobre humanos, y cómo interactúan.” La interacción cruzada entre diferentes habilidades, puntos de vista y conexiones globales abre puertas para el crecimiento personal y profesional al proporcionar el intercambio de una amplia gama de habilidades.

Al igual que con las habilidades, también con las perspectivas. La diversidad en el sentido más amplio es central para las iniciativas de SSD. La participación de diferentes voces y experiencias fortalece los resultados del desarrollo al mejorar su relevancia y usabilidad y fomentar un sentido de propiedad dentro de la comunidad de usuarios. Al mismo tiempo, promueve un ambiente propicio para el aprendizaje horizontal. Esto no es algo menor si consideramos lo importante que es esto para superar barreras importantes en los campos STEM, como las brechas de género. Al hacerlo, el SSD comparte el potencial de diferentes iniciativas de ciencia de datos para contribuir a un mundo más equitativo.

El proceso de construcción de equipos diversos de Desarrollo de Software Científico hace notar que este tipo de desarrollo involucra mucho más que simplemente escribir código para producir soluciones innovadoras. Nos llama la atención sobre cómo la naturaleza innovadora y la calidad orientada a la solución de los avances tecnológicos dependen de una red robusta y diversa de interacciones entre varios roles, habilidades y mecanismos de colaboración.

Las personas interesadas y organizaciones dedicadas al financiamiento de proyectos OSS deben reconocer esta complejidad al implementar y apoyar proyectos de SSD. Hacerlo no solo producirá resultados de desarrollo más responsables, sino que también puede fomentar entornos de desarrollo más diversos e inclusivos. Además, mejorará el crecimiento profesional de las personas involucradas, que tienen la tarea de transformar escenarios críticos como las respuestas a las enfermedades infecciosas globales y locales, al tiempo que contribuyen a un mundo más generoso y sostenible.

The post Construir un Banco de Trabajo: Ensamblar Equipos Interdisciplinarios para el Desarrollo de Software Científico appeared first on data.org.

“During the COVID-19 crisis, experts worldwide developed numerous software tools to enhance outbreak modeling and analytics. Yet, many of these solutions remain isolated, leading to duplicated effort, lack of interoperability, and poor documentation, support, and maintenance” said Dr. Danil Mikhailov, executive director of data.org. “The opportunity for global collaboration and resource-sharing remains largely unrealized. Through generous support from The Rockefeller Foundation, our partnership with the WHO Pandemic Hub reinforces our commitment to leveraging data for social good and brings us closer to our long-standing vision of a safer, healthier global community.”

“Climate change’s rising temperatures and extreme weather are fueling outbreaks of malaria, cholera, and other deadly diseases. Health leaders can outsmart infectious threats like these by combining climate and health information to predict where pathogens will spread – and digital tools can put that data at their fingertips,” said Dr. Naveen Rao, senior vice president of health, The Rockefeller Foundation. “We’re proud to support the sharing of world-class pandemic preparedness technology so people can stay healthy in a warmer world.”

The WHO Pandemic Hub fosters a collaborative environment for innovators, scientists, and experts from across a wide spectrum of disciplines, leveraging and sharing cutting-edge technology and anchoring our work in the needs of stakeholders around the world. Building on expertise across disciplines, sectors, and regions, the Hub leverages WHO’s convening power to foster global solutions built on an architecture of global collaboration and trust. By leveraging Epiverse’s existing collaborative network—including academic partners—data.org will support the WHO Pandemic Hub in crafting the “Pandemic and Epidemic Intelligence (PEI) Collaboratory.” Tailored for pandemic intelligence professionals, the PEI Collaboratory will make digital public goods more accessible for WHO country members and partners engaging on the platform. There, they will find a space that fosters collaboration, the sharing of ideas and best practices, and joint problem-solving for better public health results. 

Across both the PEI Collaboratory and Epiverse networks, data.org also aims to increase the uptake of Epiverse digital public goods in low- to middle-income nations to streamline the global public health tech arena, granting open access to best-in-class epidemic intelligence resources for health institutions globally. This builds on data.org’s ongoing work with The London School of Hygiene & Tropical Medicine, The Medical Research Council Unit The Gambia, Universidad de los Andes, and Pontificia Universidad Javeriana, where locally-developed tools and human-centered design are leading to more effective, more equitable public health solutions. As part of this process, community-based champions will be identified and mobilized to build trust locally and lead change management efforts in a way that increases in-country adoption. Outreach to other existing communities of practice will likewise help identify a diverse group of stakeholders and bring them into the fold to use Epiverse tools and engage with the growing community.

“Collaborative efforts in the realm of global health data are not just strategic, but essential,” said Dr. Julia Fitzner, unit head of insights and analytics at the World Health Organization. “As we’ve witnessed, isolated solutions can only go so far. By uniting our expertise and resources with data.org through the PEI Collaboratory, we’re not just aiming to respond to global health threats but to anticipate them. Our shared vision is to empower nations, especially those most vulnerable, with the tools and insights they need for a healthier tomorrow.”

About data.org

data.org is accelerating the power of data to solve some of our greatest global challenges. Launched in 2020 by the Mastercard Center for Inclusive Growth and The Rockefeller Foundation, data.org serves as a platform for partnerships to build the field of data for social impact by widening access to the tools, resources, and talent needed to make sustainable and equitable change.    

A global organization, data.org convenes and coordinates across sectors and is committed to supporting and amplifying visionary — but also practical — solutions to drive greater impact, through data.

About WHO Hub for Pandemic and Epidemic Intelligence

The WHO Hub for Pandemic and Epidemic Intelligence is working towards a world where collaborative surveillance empowers countries and communities to minimise the impact of pandemic and epidemic threats. Collaborative surveillance, a key concept within WHO’s framework to strengthen the global architecture for health emergency prevention, preparedness, response and resilience (HEPR), facilitates the systematic strengthening of capacity and collaboration among diverse stakeholders globally, both within and beyond the health sector, to enhance public health intelligence and improve evidence for decision-making.

With the support of the Government of the Federal Republic of Germany, the WHO Pandemic Hub was established in September 2021 in Berlin, as part of the WHO’s Health Emergencies Programme. More info here.

About The Rockefeller Foundation

The Rockefeller Foundation is a pioneering philanthropy built on collaborative partnerships at the frontiers of science, technology, and innovation that enable individuals, families, and communities to flourish. We make big bets to promote the well-being of humanity and make opportunity universal and sustainable by advancing the global climate transition and ensuring everyone can participate in it. Our focus is on mobilizing collective action that transforms four systems that are essential to the well-being of people and planet: energy, agriculture, health, and finance systems. For more information, sign up for our newsletter at rockefellerfoundation.org and follow us on X @RockefellerFdn.

Media Contact 

data.org: Emma Marty | emma@data.org

The post data.org Partners with the World Health Organization on Global Health Response appeared first on data.org.

Ha pasado un año desde que la colaboración global Epiverse-TRACE se expandió a América Latina y el Caribe (LAC).

Con el apoyo del International Development Research Centre (IDRC) de Canadá, en TRACE-LAC, nuestro objetivo ha sido construir un conjunto de herramientas de datos de alta calidad, de código abierto e interoperable para el análisis de datos epidemiológicos. Además, buscamos crear una comunidad de usuarios que ayude a informar a los tomadores de decisiones en la respuesta a epidemias en la región.

El proyecto inició con la asociación entre la Universidad Javeriana y la Universidad de los Andes para ingresar a la iniciativa TRACE liderada por el LSHTM y el MRC The Gambia. En ese proceso Zulma M. Cucunubá, Catalina González-Uribe y Juan Manuel Cordovez establecieron  un modelo de trabajo colaborativo a través de la integración de  un equipo multidisciplinario conformado por personas expertas en ciencia de datos, modelamiento matemático, ciencias sociales y toma de decisiones en salud pública.

A partir de esto, se trazaron tres líneas de acción para fortalecer el ecosistema en ciencia de datos y salud en LAC.

Caracterización del contexto sociotécnico para el análisis de datos en Colombia

Esta línea de acción, dirigida por Natalia Niño, cuenta con un grupo de expertos en ciencias sociales que exploran el ecosistema de actores en ciencias de datos y salud mediante la creación de un mapa de actores en Colombia, incluyendo la identificación de actores en áreas STEAM y barreras de acceso a herramientas de análisis y entrenamiento. El grupo ha identificado al menos 250 actores de organizaciones relevantes para la respuesta a epidemias, así como actores clave en el entrenamiento formal en ciencia de datos y organizaciones que promueven acciones con enfoque de género y ciencia de datos, uno de los temas transversales de TRACE-LAC.

Para identificar algunas de las barreras, el grupo adoptó un enfoque cualitativo con el cual se han realizado entrevistas a personas que trabajan en ciencia de datos en salud para comprender las razones por las que eligen trabajar en esta área, a pesar de los persistentes desafíos para captar y retener talento humano en el sector de ciencia datos para el impacto social.  

En este proceso, se han identificado varias similitudes entre los entrevistados. Algunas de estas incluyen incentivos percibidos no financieros como trabajar con colegas profesionales, los constantes desafíos intelectuales, pertenecer a una comunidad y el empoderamiento para las mujeres. Además, el grupo de ciencias sociales está construyendo un inventario de bases de datos de código abierto en Colombia para poner este recurso a disposición de los diferentes paquetes de R que el grupo de desarrollo de software de TRACE-LAC está creando.

Fortalecimiento de la capacidad regional para el análisis de datos en América Latina

Esta línea, liderada por Zulma Cucunubá, está compuesta por un grupo de expertos en educación que tiene como objetivo fortalecer las capacidades regionales para análisis de datos mediante el diseño de estrategias de entrenamiento presencial y de e-learning. Lo anterior con el fin de captar, atraer y retener a trabajadores de salud pública, estudiantes e investigadores de áreas STEAM. Estas estrategias están adaptadas para satisfacer las necesidades de los tomadores de decisiones e investigadores y se enfocan en la inclusión, la diversidad, la equidad y la accesibilidad.

El componente de e-learning incluye el desarrollo de un kit de entrenamiento en epidemiología, análisis y respuesta a brotes en América Latina y el Caribe, que estará disponible en una plataforma virtual. Durante el primer año, el equipo exploró conocimientos, necesidades y desafíos de la potencial comunidad de usuarios y su entorno de aprendizaje en Colombia. Además, probó algunos de los materiales de capacitación con usuarios en áreas que son relativamente fáciles de acceder geográficamente.

Para esto, se organizaron varios talleres y conferencias donde los participantes aprendieron sobre programación básica en R, el uso de sivirep (paquete de R desarrollado por el equipo de desarrollo de software en la Javeriana), modelamiento de enfermedades infecciosas, análisis de brotes y vigilancia de salud pública.

Los talleres fueron bien recibidos por 274 participantes que incluyeron epidemiólogos de campo, profesionales de entidades gubernamentales en salud y grupos académicos. Además, tuvieron una respuesta inesperada de futuras generaciones de científicos de datos para quienes la usabilidad y la practicidad de las herramientas fueron un factor clave en el aprendizaje sobre el análisis y el control de enfermedades infecciosas. Las personas demostraron su interés en ampliar el conocimiento en herramientas que les permitan responder adecuadamente a la próxima pandemia.

En el segundo año, el equipo de entrenamiento llegará a comunidades más remotas para probar los materiales y comprender los desafíos de la formación tanto online como offline en el desarrollo de la plataforma de e-learning.

Desarrollo de software para análisis de datos:

Usando información de los hallazgos iniciales de los equipos de caracterización sociotécnica y de capacitación, coordinados por Geraldine Gómez en Javeriana y Mauricio Santos en Uniandes, los equipos de desarrollo de software están construyendo seis paquetes en R. Estos tienen como objetivo proporcionar herramientas esenciales para mejorar el análisis, la vigilancia y el reporte de brotes en América Latina y el Caribe.

El proceso de desarrollo de software es iterativo y se basa en una estrecha relación de trabajo con entidades locales, como las secretarías de salud, para garantizar que las herramientas estén de acuerdo con sus necesidades.

Una de las herramientas, sivirep, ya tuvo sus primeras pruebas de usuario con trabajadores en el campo de salud pública en Bogotá. Estas pruebas validan la usabilidad y relevancia, y permitirán que los paquetes lleguen a comunidades más grandes. Durante el segundo año, el equipo continuará codesarrollando paquetes en R que llegarán a otras comunidades de la región. Tres de las herramientas (sivirep, serofoi y epiCo) formaron parte de la exhibición en el LSHTM en abril de 2023.

Explorar el potencial del ecosistema de ciencia de datos y su relación con la salud pública a través de tres líneas de acción nos ha enseñado que involucrar a nuestra comunidad de usuarios es vital para el éxito. Este compromiso continuo, y las prácticas de desarrollo iterativo, nos ayudan a comprender la interacción de los usuarios con el sistema y sus necesidades de capacitación, lo que es crítico para la adopción de las herramientas que diseñamos.

Nuestro primer año de TRACE-LAC ha demostrado que desarrollar herramientas de alta calidad, de código abierto y centradas en el usuario al incorporar mejores prácticas mientras nos adherimos a los valores de la comunidad Epiverse-TRACE, es crucial para construir un ecosistema de datos confiable y próspero.

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It has been one year since the global collaboration Epiverse TRACE expanded to Latin America and the Caribbean.

With support from International Development Research Centre (IDRC), our goal was to build a high-quality, open-source, and interoperable data toolkit for epidemics analytics – and grow an engaged user community – to inform decision-makers in the response to epidemics in Latin America and the Caribbean (TRACE-LAC).

To be part of the TRACE initiative integrated by the LSTHM and the MRC Unit in the Gambia, Zulma M. Cucunubá, Catalina González-Uribe and Juan Manual Cordovez from Universidad Javeriana (Javeriana) and Universidad de los Andes (Uniandes) started by building a strong organizational connection and established a multidisciplinary team of experts in mathematical modelling, social sciences, and decision making. They set up three lines of action, providing the team with the opportunity to assess barriers hindering the transformation of the software ecosystem for data science and health in Latin America and the Caribbean. With this assessment, the team would then be able to put forward solutions to enhance epidemic response in the region through capacity building and software development.

Characterizing the socio-technical context for data analytics in Colombia

Led by Natalia Niño, the social science team started by exploring the ecosystem of actors in data science and epidemics through mapping of stakeholders in Colombia and identifying barriers to access to tools and training. They identified at least 250 actors among organizations relevant to epidemic response, key actors in formal data science training as well as organizations promoting action on gender and data science, one of the cross-cutting themes of TRACE-LAC. To identify some of the barriers, the team adopted a qualitative approach seeking to understand why people choose to work on data science with a focus on health, given the persisting challenges of shortage of talent and lack of proper data ecosystems. They have already identified several commonalities among interviewees including working with peers, professional and intellectual challenge, community building, and empowerment (for women). Additionally, the social science team is building an inventory of open-source databases in Colombia and making this resource available for use within the different R libraries the TRACE-LAC software development team is developing.

Strengthening regional capacity for data analysis in Latin America

Led by Zulma, the training team aims to strengthen the regional capacities for data analytics by designing in-person and e-learning strategies to reach, attract, and retain public health workers, students, and researchers from STEAM areas into data analytics for health. These data analytics are adapted to meet the needs of decision-makers and of researchers focusing on inclusivity, diversity, equity, and accessibility. 

The e-learning component includes the development of an epidemic e-training kit, an online platform for inclusive training on outbreak analytics and response in Latin America. During the first year, the team explored the current knowledge, needs, and challenges of the potential community of users and learning environment in Colombia, and also tested some of the training materials with end-users in areas that are relatively easy to access geographically. They organized various workshops, conferences, and practicals where participants learned about basic programming in R, using sivirep (R library developed by the software development team at Javeriana), infectious disease modeling, outbreak analytics, and public health surveillance.

The workshops were well received among 274 participants which included field epidemiologists, national health agencies, and academic groups; they had an overwhelming response from future data scientist generations, for whom the usability and practicality of the tools was a key factor in learning about analysis and control of infectious diseases. Individuals demonstrated an interest for broadening knowledge in tools that allows them to respond adequately to the next pandemic.

In the second year, the training team will reach more remote communities to test materials and comprehend the challenges of online and offline training to be included in the development of the e-learning platform.

Developing Software for data analytics:

Using information from the initial findings of the socio-technical characterization and training teams, coordinated by Geraldine Gómez at Javeriana and Mauricio Santos at Uniandes, the software development teams are building the first six R libraries. These aim at providing essential tools for improving basic outbreak analytics, surveillance, and reporting in Latin America and the Caribbean. The software development process is iterative and builds from a close working relationship with local agencies, such as secretaries of health, to ensure the tools are in line with their needs. 

One of the tools, sivirep, already had its first end users test with public health workers in Bogota. These end-user tests validate usability and relevance and will allow the packages to reach larger communities. During the second year, the team will continue co-developing R packages reaching other communities in the region. Three of the tools (sivirep, serofoi and epiCo) were part of the showcase at the LSHTM in April 2023.

Exploring the potential of the data science ecosystem with three different lines of action has taught us that engaging our community of users is vital for success. This ongoing engagement and iterative development practices help us understand users’ interaction with the system, and their training needs are critical for adoption. Our first year of TRACE-LAC has underscored that developing high-quality, open-source, human-centered tools for outbreak analytics by using best practices and adhering to the Epiverse-TRACE community values, is crucial to build a trustworthy and thriving data ecosystem.

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In June 2022, the Epiverse TRACE community established blueprints for software development, considering not only technical elements (such as coding conventions) but also crucially, human interactions and the experience of participating in an open-source community. Incentivizing Collaborative and Open Research (ICOR)—a nonprofit initiative that seeks to facilitate and reward open science and collaboration—is working with us on tracking and measuring our goals toward this vision.

Metrics will become targets: make sure they mean something

An inspiration for our discussion were the metrics and analytics being developed for open-source community health by our colleagues at Community Health Analytics in Open Source Software (CHAOSS). They believe that metrics selected for one’s community will inevitably become targets, which means that the values underpinning the chosen metrics are critical. This was the impetus to begin formally defining the values we wished to inform the metrics for gauging the initiative’s collective success.

Securing collective buy-in of core values

The selection of Epiverse TRACE core values involved the following stepwise actions, which took place over four months:

• Team audit of project documentation and discussions to date, plus a review of CHAOSS focus areas as a potential library of metrics to employ
• Draft documentation of values derived from the audit, indicating for each the purpose and potential metrics and data collection measures
• Circulation of draft document to the full Epiverse TRACE staff: 40 individuals with diverse backgrounds across four academic institutions and our funding partner, data.org
• In-depth interrogation of potential values, taking place over several weeks, with additional values proposed
  For example, an exploration of  the concepts of usability versus utility led to the determination that both were distinctive and crucial
• Clarification and selection session, attended virtually by Epiverse TRACE staff across all partner sites, narrowed core values to 13 possibilities with the aim of selecting 7 to 8
• Final vote by team members resulting in a list of 8 core values selected and adopted

Epiverse TRACE community core values

The following list of values will represent the Epiverse-TRACE community, with metrics built out accordingly:

1. Inclusion – ensuring that our community spaces are inclusive and welcoming to all.
2. Sustainability of the ecosystem beyond the project’s grand-funded lifetime.
3. Reciprocity – operating from a stance of give and take.
4. Practicality of Epiverse TRACE tools and materials for end users – both in terms of usefulness and usability.
5. Quality within the code development process.
6. Timeliness of the tools developed (e.g., on a regular basis).
7. Accountability to our community, our funders and each other.
8. Environmentally conscious – taking steps as a project to minimise the negative consequences of our actions on the climate.

Next steps: metrics, communication, and ongoing assessment

We must now define appropriate metrics for capturing these values, taking care to incorporate both ‘hard’ and ‘soft’ measures. For example, when considering inclusion, in addition to recording the identity of those in attendance at virtual events and seminars, taking into account those who do or don’t feel empowered to speak.

Each of the core values will be embedded in our discussions, communications, and documentation. Embodying them will require accountability – i.e., admitting errors and making unpopular or difficult decisions. However, we anticipate that our systematic community approach will ameliorate these difficulties.

And as our community grows, there will be periodic reviews to capture new insights and wider perspectives, as well as to question the continuing relevance of each value. We see this as an ongoing conversation, one which we hope will be as engaging as the discussions to date.

To get involved with the community, please complete this short form.

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