Examining healthcare inequality for non-communicable diseases in Malawi: a hierarchical geospatial modelling approach

Abstract

Objectives: The prevalence of non-communicable diseases (NCDs) is rising in low- and middle-income countries, including Malawi, yet spatial inequalities in NCD healthcare coverage remain poorly understood. In this research, we aim to: (1) develop a novel hierarchical geospatial framework to assess population coverage and accessibility of NCD services in Malawi and (2) identify underserved areas and provide evidence for targeted resource allocation.

Methods: Using 2019 Malawi Harmonized Health Facility Assessment Survey, hierarchical catchment areas were defined by facility type-primary healthcare (PHCs), district-level and central hospitals, with distance thresholds of 5 km walking, 25 km driving and 100 km driving, respectively. Incorporating facility readiness, we computed population coverage at the third administrative level. When estimating spatial accessibility, we used enhanced two-step floating catchment area, applying Gaussian distance decay for chronic conditions and inverse power for acute conditions.

Results: Secondary and tertiary facilities (STFs) covered over 60% of population, providing broader NCD service than PHCs, where coverage was lower than 20%, particularly for acute conditions. Population coverage was higher in central and southeastern Malawi, notably around Mzuzu, Lilongwe and Blantyre. However, at least 24% of the population were not covered for any NCD conditions. Additionally, only 11.9% of the population lived in regions of high or very high accessibility to PHCs.

Discussion: We found substantial geographic inequalities in NCD service coverage and access, highlighting underserved regions and the demand to strengthen PHC readiness.

Conclusion: This hierarchical geospatial approach offers insights for resource allocation and improving healthcare equity in other low-resource settings.

Keywords: Computing Methodologies; Global Health; Health Equity; Health Services Accessibility.

Figure 1. Research framework for population coverage and spatial accessibility.

Figure 2. Population coverage for each NCD condition: (a) all facilities; (b) PHCs; (c) STFs. AA-MM, acute asthma (mild/moderate); AA-MS, acute asthma (moderate/severe); ADE, acute diabetic event; AE, acute epilepsy; IAMSC, injuries/acute minor surgical conditions+; CA, chronic asthma; CHTN, complicated hypertension; CRHD, chronic RHD; HF, heart failure; HTN, hypertension (stage 1 or 2); IPC, injectable pain care; OPC, oral pain care; PHC, primary healthcare; STFs, secondary and tertiary facilities; T1DM, type 1 diabetes mellitus; T2DM, type 2 diabetes mellitus.

Figure 3. Readiness weighted population coverage for (a) PHC acute conditions; (b) PHC chronic conditions; (c) STF acute conditions; (d) STF chronic conditions. PHC, primary healthcare; STFs, secondary and tertiary facilities.

Figure 4. Spatial accessibility to healthcare facilities, highlighting the spatial variation in the combined access for each ADM3 region.

Figure 5. Spatial accessibility in each third-level administrative (ADM3) zone, showcasing spatial inequalities throughout different areas and types of facilities (a) primary healthcare services; (b) district-level hospitals; (c) central hospitals.