HealthLight

According to the WHO (2020), approximately 6 billion of the world’s population today is at risk of one or more vector-borne diseases. Though preventable, these diseases still cause an average of at least 700,000 deaths annually as governments struggle to develop timely responses. During 2020, Impulso developed the most popular early warning system for governments to assess the coronavirus situation in Brazil on a daily basis, receiving +140,000 visits from government officials alone. We are now expanding this existing platform to provide governments with information on vector-borne diseases, starting with dengue and chikungunya. Through quick, sustainable actions incited by our early warning system, such as identifying imminent surges and isolating areas in vulnerable communities, governments will be able to prevent outbreaks, epidemics and pandemics, saving up to 40,000 lives annually in Brazil alone; when scaled globally, it can help save up to 200,000 lives. 

As per the WHO (2020), approximately 6 billion of the world’s population today is at risk of one or more vector-borne diseases. Even though they are mostly preventable, they cause an average of over 700,000 deaths annually. They also disproportionately affect poor populations, being responsible for a gap in life expectancy, between the rich and poor, of almost 40 years. This is most notable in tropical regions where the poor tend to live in unplanned and/or informal communities with lack of sanitation and high population density, settings in which viruses thrive. The situation remains unchanged mostly because governments have been unable to develop efficient, timely responses: since 2014, we have seen major outbreaks of dengue, malaria, chikungunya, yellow fever and Zika affect different populations, claim lives, and overwhelm unprepared health systems in several countries - in Brazil, 2019 alone saw over 1,5 million dengue cases; in 2020, the Coronavirus pandemic hid the fact that there were more than 1 million cases registered again. If we do not provide government officials with tools to monitor and structure quick and sustainable actions to stop these preventable surges, they may end up turning into new epidemics and pandemics.

During 2020, Impulso developed CovidLight, a daily updated early warning system for governments to assess the Coronavirus situation in Brazil. It is the country's most popular tool for this purpose, with +280.000 visits, 50% of which being of government officials. Through an intelligent analysis of open data, it evaluates Disease status, Disease control and System responsiveness to issue alert levels for each of Brazil's 5570 municipalities, ranging from Very High (red - growing number of cases) to New Normal (green - cases are rare). Given its success and the proven recurrence of preventable communicable diseases' surges due to delayed responses, we are expanding the system to include diseases such as dengue and chikungunya, using the same open data technology and alert level methodology. Entitled HealthLight, it is adaptable to each communicable disease's context and data, issuing alerts in accordance. The health official or interested party selects his/her municipality and the disease, and gets a summary of its status to understand if there are imminent outbreaks in specific areas with suggestions on how to prevent them; they also receive e-mails with warnings in case of relevant changes. Metrics include houses infested, water-holding containers infested and hospital admissions per region.  

Our solution serves four different groups:

• Local and state government officials: our system directly serves them with the required data intelligence to improve their decision making responses to communicable diseases by measuring the alert level of possible surges. We have been working with +40 different-size Brazilian governments (from small towns to states) for the past two years, developing close relationships with different health departments. This allows us to do constant UX research (monthly interviews and observation sessions to understand how the platform is being used) and to design iterations in accordance with the UX findings. We also have monthly online surveys done through the platform to have a more general overview of the product's acceptance and daily use. This ensures that our system is constantly being upgraded in response to our main users' needs over time, as both high and entry-level officials get access to and understanding of information that might have been missed otherwise, fomenting sustainable health public policies.

• Citizens: the people the governments that use the system serve become indirectly impacted by their informed actions. This is especially true for vulnerable communities and settlements that have no sanitation and high population density, as our platform's monitoring helps prevent them from becoming hotspots for new cases of dengue or chikungunya, for example. An estimated 1 billion people of the world's urban population live in such regions (UN-Habitat, 2015), and in Brazil, 5,2 million people live in slums (IBGE, 2020).

• Civil society: different civil society groups (such as NGOs, research institutes, think tanks and academia) can use our early warning system for advocacy purposes, monitoring data in order to pressure adverse political settings to ensure rapid responses in situations that may become dangerous if any delays occur. We have a few of such groups as partners today (Brazilian institutes such as Umane, Vital Strategies and IEPS) and work alongside them in developing studies to foment important policy making decisions; the most notable case so far has been the campaign April For Life, a campaign to implement a national lockdown due to Coronavirus in Brazil, with over +100.000 signatures.

• Private sector: we will offer private hospitals, institutions and organizations paid reports presenting them with the evolution of vector-borne diseases in their areas, enabling them to be prepared in case of possible surges. We currently have contracts for COVID-19 weekly reports with different industries based on the data provided by CovidLight, and per our market research we believe that there is space for semestrial reports for our expanded database as well.

Approximately 6 billion of the world’s population today is at risk of one or more vector-borne diseases. Though mostly preventable, they still cause an estimated 700,000 deaths annually (WHO, 2O2O). HealthLight is an early warning system that addresses governments' struggle to respond timely to these constant health threats by issuing alert levels that detect imminent surges - for instance, to help prioritize areas and seasons for vector control, the % of houses infested and the % of water-holding containers infested per region are monitored. By inciting informed actions we can help save an estimated 40,000 lives annually in Brazil alone. 

We have successfully tested our early warning system throughout the Coronavirus pandemic by providing data and alert warnings on the status of the disease for the entire Brazilian territory. It has had +280.000 visits, 50% of which being public officers. We are currently poised to expand this well-established product to include information on other communicable diseases, such as dengue and chikungunya. It is a vertical scale plan that will add more value to the service provided, ensuring its sustainability. 

Our early warning system is a government-centric digital technology: it is built and powered by user experience (UX), developed alongside government officials to ensure its usability and effectiveness. This method alone is already an innovation in developing countries. The platform uses available, official health factors to develop alerts, something that does not currently exist in any Brazilian state or municipality, or in most of the world. This provides governments with automated, high frequency data analysis that usually would not have been done in time in order to act effectively in case of surges. It also gives them a big-picture overview for the development of more sustainable policies. The main change these solutions bring is that they enable government officials to be more pro-active in their health policy actions. Historically, Brazil, like most of the world, has been handling vector-borne diseases by responding to them; through HealthLight, the public health systems will have the required data analysis and support to disrupt this decades-long logic, using resources more efficiently to prevent and not cure. The main positive outcome of this work is a better quality of life for vulnerable communities due to these improved policies. 

Currently, as an open-source early warning tool, CovidLight has provided required data on Coronavirus for the entire Brazilian territory (211 million people); 50% of the platform's visits are confirmed to be of government officials. Our plan to expand the system to include vector-borne diseases will start with data from 05 Brazilian State governments in year one through an established partnership with the Brazilian National Council of State Health Departments (Conass). This direct work with local health departments will reach an average of 72 million people (the populations of the states of São Paulo, Rio Grande do Sul, Goiás, Maranhão and Distrito Federal). In 5 years, our goal is to be serving all 27 Brazilian states, reaching all 211 million Brazilians. To do this, we will be rolling out a phased scale plan that will add 5-6 states per year. By year four, we will also start to expand the platform to other tropical global regions that suffer from vector-borne diseases. 

In the short-term our impact will be measured through established metrics such as: (1) the number of governments with access to the platform, and its yearly growth; (2) the number of accesses to the platform per active government per month and its monthly growth; (3) the number of alerts issued per active government in the platform per month and per disease, and their monthly growth and (4) monthly surveys regarding user experience for iterations. In the long-term, the impact will be measured by the evolution of different factors in the communities, such as mortality rates,  life expectancy rates and hospital admission rates, comparing periods before and after the use of HealthLight as well as regions that did not use the system at all (differences-in-differences).    

Full-time staff: 18

Part-time staff: 4

We have a team of 22 people. 18 work full time, while 4 are part-time / interns. We also have a rolling number of volunteers, exceptional talents who have come together around our mission. Our team is motivated, competent and multidisciplinary - we have data scientists, developers and specialists in public health management. They gave up opportunities at the best companies in Brazil, from for-profit technology startups to investment banks, for believing in making an impact in Brazil. Many of them have field experience, having worked in local and state health departments, and channel that to help us solve government officials' daily challenges and difficulties, providing our organization with important insights on how to develop solutions that are truly government-centric.

To ensure diversity, equity and inclusion in our team, Impulso has written Hiring Practices & Workplace Policies. These policies include efforts to prioritize hiring minorities by placing job vacancies on Black and POC-centered job boards and outreach to Black and POC candidates, and a clear salary philosophy that provides every team member with information on how total compensation is developed. We have an ethics code that instates our employees' expected conduct, sharing the organization's core values of empathy, shared knowledge, diversity, integrity and transparency. We do bimestrial workplace surveys with all employees to assess if Impulso is sensed to be a space for collaboration, a learning environment and a diverse environment. 72% of the current team, ⅖ of our board members and one of the two co-founders are women; 22% of the current team identifies as black and 33% as LGBTQ+. 

We are applying to Solve because we value the network it offers: the nine months of personalized support will enable us to validate our platform and our business model with world-leading specialists, ensuring the sustainability of our venture and the impact we intend to achieve. We also understand that this award is the type of recognition that can open a lot of doors for new partnerships and investments, both of which are essential for our strategy of scale to happen. 

We seek support in developing a sustainable business model that will ensure the organisation's sustainability for the next 5-10 years. Up to now, our main resources have been grants and partnerships with foundations; by developing scalable products such as HealthLight that may be sold through the B2G model, we are starting to diversify our funding and having support while doing it is essential to guaranteeing that we are making the right choices without losing focus on our mission to ensure a healthy life for all. As we expand our early warning system to include more data on vector-borne diseases, we will also need support in structuring a platform that continues to be not only user-friendly but also really useful in its purpose for the main final users (government officials). Lastly, we would also like help in measuring the impact of our work, through experiments and/or other methods, as it is an important part of verifying our theory of change.

We are interested in partnering with and learning from other Solve Members who are developing similar health initiatives, such as  Moskeet, a real-time, integrated vector and disease management platform for prevention and control of mosquito-borne diseases, and MapSight, a spatial and temporal predictive analytics Decision Support System (DSS) for public health and governance. It would be great to understand their challenges, how they converse with ours and how we can work together to get past them. We would also like to have access to MIT health specialists and Solve partner organizations that focus on data solutions, such as the Patrick J McGovern Foundation.