Introduction

Our project, Dots of Despair, focuses on a critical intersection between water infrastructure and mosquito-borne diseases. Together, we, Team Ripple, explored how insufficient water infrastructure can accelerate the spread of diseases such as Dengue, Malaria, and Kala Azar. By examining the relationships between water access, sanitation, electricity, and health insurance, we sought to uncover patterns that reveal the often overlooked human cost of these systemic failures. With a nature-based, mosquito-focused approach, we asked: How does inadequate water infrastructure contribute to the spread of mosquito-borne diseases? Through causal mapping, data analysis, and iterative design, we were able to make several key discoveries that could inform future interventions.

Research Methods

Our research initially focused on healthcare and water, examining personal, public, and community health perspectives. We sought to understand how healthcare, water, and various socio-economic factors interacted. However, we realized that continuing in this direction would not be productive without relevant datasets. Shifting to a data-first approach was a significant and challenging change. We explored different datasets and the variables they captured, starting with WASH (Water, Sanitation, and Hygiene) data across multiple countries. We examined stagnant water and found a correlation between groundwater levels and diarrhea. By combining two datasets, we tried to explore this connection but struggled to define the narrative we wanted to tell. The association between water levels over time and disease outcomes was not clear. With frequent references to the John Snow map in class and the persistently high rates of waterborne diseases, we decided to concentrate on water-related diseases in India, which have a high prevalence. From there, we focused on understanding water-related factors that contribute to disease outcomes. Further, with a system map and causal loops that broke down the factors we hypothesized might contribute to water-related diseases. We identified four critical components of water infrastructure: clean water, sanitation, electricity, and health insurance. These elements form the foundation of public health, yet in many regions of India, they are insufficiently addressed or poorly maintained. The diseases we focused on — Dengue, Malaria, and Kala Azar — are intimately connected to these infrastructure deficits, particularly in rural and under-resourced areas.

Data Sources

We drew on publicly available datasets, specifically the Health Management Information System (HMIS) and the National Family Health Survey (NFHS). These resources provided us with a wealth of data on infrastructure access, health outcomes, and mosquito-borne disease trends in India. We focused on these datasets to explore the direct and indirect effects of infrastructure on health.

Causal Mapping

To better understand the relationship between water infrastructure and mosquito-borne diseases, we created a causal map. This process helped us visualize the key factors — such as stagnant water, inadequate sanitation, and lack of electricity — that contribute to mosquito breeding.

Data Analysis

Using the datasets, we analyzed the connections between infrastructure and disease, focusing on seasonal trends. For example, we found that access to clean water — while generally beneficial — could also lead to increased mosquito bites in some regions, likely due to stagnant water accumulation. By contrast, improved sanitation and consistent electricity access had clear positive impacts, reducing disease transmission significantly.

Visualizing Seasonal Trends

Mapping seasonal trends allowed us to understand how the timing of infrastructure failure exacerbates disease outbreaks. For instance, during the monsoon season, insufficient drainage systems lead to higher mosquito breeding rates, creating peaks in Dengue and Malaria cases.

Graph Interfaces

To make our findings accessible, we created visual representations of the data. These graphs illustrate the relationships between water infrastructure, disease spread, and other factors. For instance, the correlation between sanitation and disease reduction was striking, showing a direct link that could be critical for policymakers to address.

Value Systems

Our project is deeply rooted in the values of public health, environmental justice, and equity. The systems we analyzed disproportionately affect rural and impoverished communities, where access to clean water and sanitation is often unreliable. This imbalance creates a public health crisis that is both preventable and urgent. By focusing on infrastructure improvements, our aim was to spotlight the human cost of systemic neglect and the moral imperative to address these gaps.

We also sought to emphasize the importance of sustainable development, recognizing that the impacts of climate change and urbanization are making these problems more severe. Our project reflects a commitment to rethinking how infrastructure investment can lead to better health outcomes and stronger, more resilient communities.

Solution Concept and Realization

Our hypothesis was that weak water infrastructure directly contributes to the spread of mosquito-borne diseases. The ambition behind Dots of Despair was to uncover these relationships in a way that could inspire real-world change, whether through infrastructure investment or public health policy.

We used Python for data analysis and visualization software to create our final graphs and maps. The design process was highly iterative; we continually refined our methods based on new insights from the data. For example, when we discovered that clean water access had a complex relationship with mosquito breeding, we revisited our data and revised our visualizations to more accurately reflect these findings.

Next Steps

Our research highlighted several gaps, particularly in terms of data availability and granularity. For future work, we would like to expand the scope of our datasets to include climate projections and economic models, which would provide a more comprehensive view of the factors influencing mosquito-borne diseases. Additionally, there is a need to better understand the differences between public and private sector roles in water management, as these distinctions could influence policy decisions and infrastructure improvements.

Conclusion

In conclusion, Dots of Despair offers a window into the significant yet often overlooked impact of weak water infrastructure on mosquito-borne diseases. Our findings emphasize the need for targeted investments in infrastructure to protect vulnerable communities from preventable diseases. We hope this project contributes to a broader conversation about the critical role of infrastructure in public health and inspires actionable solutions.

Reflection

Working on Dots of Despair was both challenging and rewarding. I am proud of how my team handled the complex dataset and stayed persistent despite the learning curve. One area I could have improved is simplifying the data to focus on a clearer narrative. As my instructor noted, refining the graph-based format, particularly by adding a key for the clean water, sanitation, and electricity diagram, would have made the data easier to understand. Additionally, exploring different forms of visualization and focusing on comparative cases would have strengthened our story. The idea of using the data to identify anomalies for further qualitative study was a valuable takeaway, and I hope to apply this approach in future projects. Overall, this module has taught me a lot about how to effectively communicate complex data in a meaningful way.

References

Health Management Information System (HMIS) Dataset. Ministry of Health & Family Welfare, National Health Portal. Available at India Data Portal.
National Family Health Survey (NFHS). Ministry of Health & Family Welfare, International Institute for Population Sciences (IIPS). Available at India Data Portal.

🙌 Developed in the Design Engineering program at Harvard, alongside Siddhi Patil

Dots Of Despair