Health System Resilience for Climate Change Adaptation: An Empirical Evaluation of Access and Utilization in Western Province, Zambia

Abstract

Background Achieving Universal Health Coverage (UHC) in low- and lower-middle-income countries (LMICs) is jeopardized by the convergence of climate-related shocks and chronic health systems stressors. In Western Province (WP), Zambia, a vast, rural, and remote area characterized by the Barotse Floodplain, progress toward UHC is hindered by the interplay between seasonal flooding variations and pre-existing challenges such as low health facility density and geographic barriers to accessing and utilizing essential primary health care services. A significant gap exists in the empirical evidence necessary to quantify these adverse synergistic interactions, improve routine surveillance systems that currently lack reliable population denominators, and develop dynamic models to assess the impact of shocks and stressors on health service utilization.

Objectives This dissertation develops and applies a comprehensive methodological framework to empirically evaluate access to and utilization of essential health services in WP, Zambia. It endeavors to (1) define and measure the dimensions of access, encompassing supply- and demand-side conditions within the context of spatial and temporal parameters; (2) establish an innovative methodology for generating population denominators to enhance disease surveillance and epidemiological metrics; (3) quantify the synergistic impacts of environmental and systemic challenges on service utilization through a novel econosyndemic framework; and (4) model health system resilience dynamically by forecasting utilization patterns and evaluating the effects of various shocks and stressors over time. Furthermore, this dissertation concludes with a policy brief, representing a preliminary policy assessment (Phase I) that employs a location-allocation model to optimize the current health facility network for geographical efficiency, thereby identifying existing access gaps and redundancies within the system. This initial optimization serves as a foundation for a proposed multi-stage framework designed to generate actionable investment strategies by integrating health system capacity, cost considerations, and evolving population needs into future analyses (Phase II). Ultimately, this work offers an integrated, evidence-based framework aimed at strengthening health system resilience as a vital climate change adaptation strategy, thereby advancing the overarching objective of ensuring equitable access to healthcare for vulnerable populations.

Methods This dissertation, grounded in comprehensive research, comprises four empirical studies in addition to a policy analysis. Study no. 1 employed a cross-sectional design utilizing geospatial analysis of 220 health facilities (centres and posts) to assess access through metrics such as facility density, population growth, travel durations, and personnel distribution. Study no. 2 introduced and applied an innovative Spatially Defined Catchment Area and Population Under Rooftop (SCSO-PUR) methodology, leveraging satellite data to establish denominators for 321 health facilities, as exemplified in a malaria surveillance epidemiological case study spanning 2017 to 2024. Study no. 3 presented and quantified the econosyndemic framework within an ecological longitudinal study of 62 health centres and posts from 2017 to 2023, employing beta regression and structural equation models (SEM) to analyze the interaction between flood exposure and health system capacity concerning maternal and child health, as well as overall general utilization (i.e., outpatient visits). Study no. 4 utilized time-series forecasting and an Interrupted Time Series (ITS) analysis on the same dataset to measure the dynamic effects of three distinct shocks—the 2019 drought, the 2021 COVID-19 pandemic, and the 2023 complex flood event —on overall utilization, namely outpatient visits. The Policy Brief, Preliminary Assessment (Phase I), employed a Set Covering Problem (SCP) model on the network of 321 facilities to optimize geographic coverage and identify system-wide efficiencies.

Findings Geographic access constitutes a primary barrier, with projected declines in facilities per capita and estimated mean travel times ranging from 6.6 to 13.9 hours. A substantial proportion of the population (26.4%, exceeding 322,000 individuals) resides beyond the World Health Organization's recommended two-hour travel time to a comprehensive Health Centre. The SCSO-PUR methodology has demonstrated feasibility in establishing standardized denominators, thereby elucidating previously obscured spatial-demographic disparities in malaria risk. The econosyndemic framework has been empirically validated; notably, the interaction between high flood depths and health system stressors was found to significantly disrupt essential services, including antenatal care (ANC) and facility-based births. The Interrupted Time Series (ITS) analysis indicates that various shocks yield distinct and quantifiable impacts on overall utilization patterns, ranging from immediate declines (drought) to paradoxical increases (COVID-19) and gradual recoveries (i.e., complex flood event). Lastly, the health system optimization analysis uncovers significant spatial redundancy; specifically, while comprehensive geographic coverage could be theoretically achieved with only 46 of the 321 existing facilities, this would entail accepting travel times of up to 7.5 hours, thereby underscoring a crucial trade-off between efficiency and equitable access.

Conclusion This dissertation provides a comprehensive, empirically grounded framework for understanding and strengthening health system resilience in a climate-vulnerable setting. It demonstrates that the adverse synergistic interaction between environmental shocks and systemic supply- and demand-side stressors creates an econosyndemic that dynamically and inequitably disrupts access to and utilization of essential health services. The novel methodologies developed offer scalable, data-driven tools for ministries of health to transition from reactive to proactive, evidence-based planning. The findings provide a clear policy directive: building health system resilience for climate adaptation requires targeted, context-specific interventions that address underlying vulnerabilities in infrastructure and geographic accessibility.