Keywords

Conflict, Infectious Diseases, Community Health Workers, Ecological Disturbance, Health System Resilience, Africa

Abstract

This dissertation examines the relationship between armed conflict and infectious disease transmission through a novel theoretical framework that integrates ecological disturbance and health systems resilience theories into epidemiological contexts. The framework conceptualizes diseases along a continuum from "pulse" to "press." Pulse diseases, like Ebola, are characterized by sudden onset, high mortality, and short-term outbreaks. Press diseases, like HIV, progress gradually with lower mortality and long-term persistence. Grounded in this pulse–press disease typology and ecological and health systems resilience, the theory suggests that the absorptive capacity, adaptive capacity, and resilience of community health workers in conflict areas can influence disease transmission, depending on whether a disease follows a pulse or press pattern.

Several advanced spatiotemporal statistical techniques are used to investigate the impact of armed conflict on disease transmission across African countries between 2000 and 2018. To address gaps in Ebola reporting, a modified inverse distance weighting interpolation method was developed, incorporating variables such as fruit bat habitat distribution, outbreak timing, geographic proximity, regional context, and precipitation patterns. A spatially autocorrelated zero-inflated negative binomial model accommodates overdispersed and spatially dependent Ebola data. To evaluate the impact of conflict on HIV spread, a generalized linear model incorporating spatial basis functions was used to correct for spatial structure and autocorrelation in the data.

The empirical analysis suggests the relationship between conflict and disease operates through more complex mechanisms than the pulse and press theoretical framework predicts at the country-year level. Although the hypothesized direct pathways linking conflict events to pulse and press disease transmission patterns do not reach statistical significance, the methods provide a foundation for future research in several directions: examining dynamics at sub-national scales; applying spatial basis functions to better capture geographic dependencies; and developing modified interpolation techniques to estimate missing disease data across time and space.

Completion Date

2025

Semester

Summer

Committee Chair

Baggio, Jacopo

Degree

Doctor of Philosophy (Ph.D.)

College

College of Sciences

Department

School of Politics, Security, and International Affairs

Format

PDF

Identifier

DP0029534

Language

English

Document Type

Thesis

Campus Location

Orlando (Main) Campus

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