"Colours are my storytelling companions; I use them to bring data to life and uncover the narratives hidden within."
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Hi, I'm Avik Kumar Sam!
I am a Research Fellow at the Centre for Epidemic Research and Modelling, Saw Swee Hock School of Public Health, National University of Singapore (NUS).
I recently completed my PhD in Climate Change & Public Health at the Indian Institute of Technology Bombay, where my research focused on understanding how socioeconomic inequities, climate variability, and environmental change interact to shape infectious disease dynamics. I worked with Prof. Harish Phuleria (ESED, IITB) and Prof. Siuli Mukhopadhyay (Mathematics, IITB).
With over seven peer-reviewed presentations and awards from ISES-ISEE, MoE, SERB, IDM and ISEE, my doctoral work examined the spatiotemporal transmission of malaria and dengue across multiple scales, using a combination of statistical methods, machine learning, artificial intelligence, Bayesian modelling, and mechanistic approaches. In fact, my PhD research was shaped by continuous stakeholder engagement and collaborations with multilateral academic, research, and government institutions, including the Ministry of Family and Health Welfare, Government of India; the Government of Maharashtra; the Government of West Bengal; the Indian Council of Medical Research; and Swiss TPH.
I have developed early warning systems for climate-sensitive diseases, evaluated public health interventions using causal inference frameworks, and built scalable tools, including interactive dashboards and analytical libraries, to translate complex data into actionable insights.
More broadly, I am interested in developing integrated frameworks that connect climate science, epidemiology, and policy, with a growing focus on quantifying the health and economic impacts of climate mitigation and adaptation strategies.
Prior to my PhD, I completed my Master’s in Environmental Science and Engineering at IIT Bombay, where I conducted research on the carbon composition and toxicity of atmospheric dust.
Engaging deeply with climate and health literature during this time led me to ask a central question that continues to guide my work: how do environmental change and social inequities together shape health risks, and how can we design better, more equitable responses?
If you’d like to collaborate or exchange ideas, feel free to reach out. I’m always open to meaningful conversations.
Selected Research Highlights.
ClimAID - Climate change impact using AI on Infectious Diseases
ClimAID, is an AI-integrated, calibration-enhanced climate–disease modelling framework designed to produce reproducible, climate-informed infectious disease predictions at fine administrative scales, with a central emphasis on its deterministic reporting module.
The framework integrates a terminal-based reproducibility wizard, browser interface, and a deterministic AI-assisted reporter that generates standardized, transparent, and fully reproducible documentation across datasets and geographic contexts.
By combining epidemiological data, high-resolution meteorological variables, and CMIP6 climate projections, ClimAID ensures consistency in both analytical outputs and their interpretation.
ClimAID is available at https://pypi.org/project/climaid/
Impact of projected climate and socioeconomic scenarios on state-wise annual dengue incidence in India using ensemble models
We study the impact of climate change on dengue cases in Indian states using machine learning models. With modified socio-economic development scenarios, we projected the increase in dengue cases for each state in a near (2030) and mid-scenario future (2050).
In the immediate future, development focused on sustainability will likely have a relatively lesser increase, while a regional rivalry scenario may witness the highest increase.
In southern India, increased outbreaks are estimated in the future. In contrast, dengue is likely to decrease significantly in the densely populated states of the Gangetic Plains.
The projected spatial heterogeneity in dengue incidence suggests that targeted surveillance and early detection systems may be particularly important in states where future risk is projected to change.
Mapping malaria risk in India between 2019 and 2023: a tool for the public to track malaria
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