  This ongoing work attempts to understand and address the requirements of
UNICEF, a leading organization working in children's welfare, where they aim to
tackle the problem of air quality for children at a global level. We are
motivated by the lack of a proper model to account for heavily fluctuating air
quality levels across the world in the wake of the COVID-19 pandemic, leading
to uncertainty among public health professionals on the exact levels of
children's exposure to air pollutants. We create an initial model as per the
agency's requirement to generate insights through a combination of virtual
meetups and online presentations. Our research team comprised of UNICEF's
researchers and a group of volunteer data scientists. The presentations were
delivered to a number of scientists and domain experts from UNICEF and
community champions working with open data. We highlight their feedback and
possible avenues to develop this research further.
