How copepod demography, fish predation, and seasonality affect dynamics and control of Guinea worm disease Restricted; Files Only
Raytselis, Nadia (Summer 2026)
Abstract
Guinea worm disease (GWD) is a neglected tropical illness and eradication target caused by the parasitic nematode Dracunculus medinensis. The parasite cycles between copepods and mammals, including humans. Great progress has been made towards eradication through behavioral interventions for humans and domestic animals. Now, ecological insights are needed to complement these interventions and drive eradication. For example, the pesticide Abate is currently used to suppress copepods and reduce transmission potential, but little is known about the population dynamics of copepod recovery. Additionally, a newly hypothesized transmission pathway suggests that mammals could become infected after consuming undercooked fish that have eaten infected copepods. Lastly, co-occurrence of copepods and fish is temporally dynamic, shaped by seasonal precipitation patterns and fishing activities, with potential impacts on transmission. My dissertation pairs population- and community- dynamic experiments with mathematical models to understand the net effects of pesticides, fish predators, and seasonality on copepod populations and GW transmission. In an experiment mimicking copepod population control with Abate, I found that populations rapidly recover. Interestingly, model simulations showed that the parasite’s latent infection period interacts with the pesticide application interval to consistently suppress the density of infected copepods. With an experiment on the effects of fish predation on copepod populations, I demonstrated that fish selectively consume larger bodied copepods, the stage most likely to be infected, which contributed to regulation of copepod densities. Integrating these results with transmission models showed that fish density has a unimodal relationship with the density of fish harboring GW parasites, which helps resolve contrasting assertations about the role of fish in GW transmission in the field. Lastly, I modeled copepod-fish-GW dynamics with seasonal precipitation and fishing to examine the effects of dynamic co-occurrence of copepods and fish under conditions more representative of endemic areas. I found that season duration, fish migration rates, fishing effort, and parasite introduction date interact to influence overall GW transmission via traditional and alternative pathways. Altogether, my dissertation enhances our understanding of GW transmission ecology, contributing to global eradication efforts by demonstrating how population stage structure, species interactions, and transient environmental dynamics can drive parasite transmission.
Table of Contents
Table of Contents
Chapter 1: Introduction.….………………………… ………………….....................…........................................……….….…................................................…........….…...................................1
1.1 Parasitic nematodes – disease control informed by ecology………………..................................……………….….…................................................…........….…...................................…3
1.2 System overview and public health importance ………………..................................……………….….…................................................…........….…...................................…................5
1.3 Guinea worm disease control ………………..................................……………….….…................................................…........….…...................................…..........................................5
1.4 Key ecology of Guinea worm disease ………………..................................……………….….…................................................…........….…...................................…................................6
1.5 Gaps in our understanding ………………..................................……………….….…................................................…........….…...................................…..............................................7
1.6 Summary ………………..................................……………….….…................................................…........….…...................................….....................................................................10
Chapter 2: Apparent failure and cryptic success of disease control via intermediate host population reduction .………………..................................……………….….…................................14
2.1 Abstract ………………………………………………………………………………...…...……………………………………….………………………...…...………………………………………..........................15
2.2 Introduction………………………………………………………………………………...…...……………………………………….………………………...…...……………………………………….....................16
2.3 Methods………………………………………………………………………………...…...……………………………………….………………………...…...………………………………………...........................19
2.3.1 Copepod Maintenance and Propagation ………………………………………………………………………………...…...……………………………………….………………………...…...…………………19
2.3.2 Mesocosm Setup, Sampling, and Experimental Design ………………………………………………………………………………...…...……………………………………….………………………...…...19
2.3.3 Copepod Counting ………………………………………………………………………………...…...……………………………………….………………………...…...………………………………………......20
2.3.4 Statistical Analysis of Intervention Effects on Copepod Density ………………………………………………………………………………...…...……………………………………….…………………..21
2.3.5 State Space Modeling (SSM) of Copepod Population Dynamics ………………………………………………………………………………...…...……………………………………….…………………...21
2.3.6 Model-derived estimates of density dependence………………………………………………………………………………...…...……………………………………….…………………........................23
2.3.7 Compartmental (ODE) stage structured model with interventions and infection ………………………………………………………………………………...…...……………………………………...24
2.4. Results………………………………………………………………………………...…...……………………………………….………………….........................................................................................25
2.4.1 Copepod population dynamics and mortality events………………………………………………………………………………...…...……………………………………….…………………...................25
2.4.2 Size-biased removal………………………………………………………………………………...…...……………………………………….………………….................................................................26
2.4.3 Size-unbiased removal ………………………………………………………………………………...…...……………………………………….…………………............................................................26
2.4.4 Transmission scenario simulation results ………………………………………………………………………………...…...……………………………………….………………….................................26
2.4.5 Figures ………………………………………………………………………………...…...……………………………………….…………………...............................................................36, 37, 38, 39, 40
2.5. Discussion ………………………………………………………………………………...…...……………………………………….…………………...................................................................................27
2.6 Chapter 2 Appendix………………………………………………………………………………...…...……………………………………….………………….......................................................................41
Chapter 3: Do fish mitigate or magnify Guinea worm transmission? The epidemiological consequences of selective predation …………………………..........................................................55
3.1 Abstract ………………………………………………………………………………………………………………………………………………...…...……………………………………….........……………...……...56
3.2 Introduction………………………………………………………………………………………………………………………………………………...…...……………………………………….........……………....…57
3.3 Methods………………………………………………………………………………………………………………………………………………...…...……………………………………….........……………...……....60
3.3.1 Fish-copepod dynamic model ……………………….…….....................................……………………….…….....................................……………………….……........................................60
3.3.2 Predictions for copepod population dynamics under fish predation scenarios ….……………………….…….....................................……………………….…….......................................61
3.3.3 Copepod and Fish Maintenance ……………….…………………………….…….....................................……………………….……................................................…………………………......62
3.3.4 Experimental Design, Mesocosm Setup and Sampling …………………………….…….....................................……………………….……............................................……………………...62
3.3.5 State space modeling and parameter estimation………………………………………….…….....................................……………………….……...........................................………………...64
3.3.6 Compartmental (ODE) stage structured model with infection ……………………………….…….....................................……………………….…….........................................…………....66
3.4 Results……………………………………………………………………….…….....................................……………………….…….....................................………..………….....……………………...….67
3.4.1 Simulating predator selectivity …………………………….…….....................................……………………….……...............................................………………….....……………………..….67
3.4.2 Mesocosm and State Space Model Results .…………………………….…….....................................……………………….…….............................................………….....…………..…….….69
3.4.3 Prey Selectivity….....…………………………………………………………………………….…….....................................……………………….……......................................................…….….71
3.4.4 Healthy Herds and fish density….....……….……………………………….…….....................................……………………….……...............................................……………………………...72
3.4.5 Figures ..……………………………….…….....................................……………………….……...................................................……………………………………………………..…...68,70,72,74
3.5 Discussion……………………………………...……………………….…….....................................……………………….……....................................................………………………………………...75
3.6 Chapter 3 Appendix…………………………………………………….…….....................................……………………….……....................................……………….............................................80
Chapter 4: When predators come and go: Seasonal interactions among hosts, parasites, and predators drive Guinea worm disease dynamics .….…................................................…........93
4.1. Graphical Abstract ……………………………………………………………………….…….....................................……………………….……..............................................……………………...…..94
4.2 Abstract …………………………………………………………………………………….…….....................................……………………….……................................................………………..…...…..95
4.3 Introduction…………………………………………………………………………….…….....................................……………………….……................................................……………………….……96
4.4 Methods……………………………………………….…….....................................……………………….……................................................………………………………………………..…….……....99
4.4.1 Model Specifications……………………………….…….....................................……………………….……...................................................……………….………………………………….......99
4.4.2 Ordinary Differential Equations (ODEs; Eq. 1-19). ......……………………….…….....................................……………………….……..........................................................................106
4.4.3 Temporal Simulation…………….…….....................................……………………….…….....................................……………………….……................................................................108
4.4.4 Sensitivity Analysis A……………………………………………………………………….…….....................................……………………….……....................................................…………....108
4.4.5 Sensitivity Analysis B ………………………………………………………………….…….....................................……………………….……...................................................………………....109
4.4.6 Parameter Simulations ………………………………………………………………….…….....................................……………………….…….................................................…………….......109
4.4.7 Tables …………………………………………………………………………….…….....................................……………………….……......................................................…………………..103,105
4.5. Results…………………………………………….…….....................................……………………….……................................................……………………………………….....………………….….110
4.5.1 Temporal Simulation ……………………………….…….....................................……………………….……...................................................………………………………………….………....110
4.5.2 Sensitivity Analysis A ……………………………….…….....................................……………………….……....................................................………………………………………….………..112
4.5.3 Sensitivity Analysis B …………………………………….…….....................................……………………….……...................................................…………………………………….………...114
4.5.4 Parameter Simulations ……………………………….…….....................................……………………….……..................................................………………………………………….………..115
4.5.5 Figures ..…..………………………………………….…….....................................……………………….……..................................................……………………………………...111,113,115,117
4.6 Discussion…………………………………………….…….....................................……………………….……...............................................……………….........……………………………………….118
4.7 Chapter 3 Appendix…………………………….…….....................................……………………….……....................................………………………………………...........................................125
Chapter 5: Conclusion ……………………………………….…….....................................……………………….……...............................................…………………….…...………………………….….127
Literature Cited …………………………………….…….....................................……………………….……..................................................………………….……………………………………………...131
About this Dissertation
| School | |
|---|---|
| Department | |
| Subfield / Discipline | |
| Degree | |
| Submission | |
| Language |
|
| Research Field | |
| Keyword | |
| Committee Chair / Thesis Advisor | |
| Committee Members |
Primary PDF
| Thumbnail | Title | Date Uploaded | Actions |
|---|---|---|---|
|
|
File download under embargo until 20 August 2028 | 2026-06-11 18:37:43 -0400 | File download under embargo until 20 August 2028 |
Supplemental Files
| Thumbnail | Title | Date Uploaded | Actions |
|---|