Designing Public Health Surveillance for Urban Air Quality in LMICs: Community Insights, Technology Acceptance, and System Design for Low-Resource, High Vulnerability Settings

Abstract

Climate change is tightening exposure windows and widening inequalities in urban air quality, especially across low- and middle-income countries. Many cities lack dense regulatory networks, timely analytics, and trusted communication pathways, which means signals arrive after decisions are due. Grounded in Ulaanbaatar, Mongolia, this thesis begins by asking how people make sense of pollution in their daily lives, what actions are realistically available, and which institutions are expected to respond. These lived accounts specify what usable guidance must deliver in contexts where resources are limited and risks are uneven. Guidance must be fast, intelligible, transparent about uncertainty, and aligned with social roles and constraints that vary.

A second qualitative strand examines technology acceptance of digital monitoring and early warnings. It identifies what confers legitimacy, including credible data provenance, visible accountability, and delivery pathways that match capabilities such as low connectivity, limited time, and competing obligations. Together, these qualitative insights establish system requirements and the conditions under which guidance is likely to be acted upon.

Based on these insights and in partnership with UNICEF Mongolia, the thesis designs, develops, and evaluates a real-time air quality pipeline for Ulaanbaatar. Low-cost sensors feed an automated device to database workflow that stabilizes sparse and noisy inputs. A sequence modeling approach produces continuous predictions with calibrated error suitable for communication and decision support under intermittent power and limited connectivity. Evaluations suggests the system performs reliably under these constraints and can be adopted within existing civic workflows.

The integrated contribution is a pathway from qualitative insights to deployable infrastructure that supports proportional protection. The thesis advances empirical understanding of disproportionate risks in an LMIC city, delivers a validated and operational monitoring and prediction pipeline build from locally derived requirements, and offers policy and design guidance that ties technical accuracy to local relevance and shared accountability so that evidence arrives in time to reduce harm.