OOS 19-2 - Modeling density dependence in helminth parasites to inform optimal intervention strategies for disease control and elimination

Wednesday, August 14, 2019: 1:50 PM
M103, Kentucky International Convention Center
Christopher M. Hoover, Division of Environmental Health Sciences, UC Berkeley, Berkeley, CA, Giulio De Leo, Hopkins Marine Station, Stanford University, Pacific Grove, CA, Susanne H. Sokolow, Marine Science Institute, UC Santa Barbara, Santa Barbara, CA, Jason R. Rohr, Biological Sciences, University of Notre Dame, Notre Dame, IN, Manoj Gambhir, Health Modeling and Analytics, IBM Research, Melbourne, Australia; Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia, Arathi Arakala, Mathematical Sciences, Royal Melbourne Institute of Technology, Melbourne, Australia and Justin V. Remais, Berkeley
Background/Question/Methods

The transmission dynamics of important helminthic diseases that affect billions of people globally—including onchocerciasis, lymphatic filariasis, and schistosomiasis—are influenced by density dependence. Positive density dependent processes influence transmission of these diseases, producing an Allee Effect, which establishes a pathogen population breakpoint. This breakpoint provides a logical target for intervention campaigns that decrease disease burden, e.g., through the use of mass drug administration (MDA), as reducing the pathogen population below its breakpoint can aid in achieving elimination. Other interventions that target intermediate hosts or vectors may also be used to suppress the pathogen population towards the breakpoint. Meanwhile, interventions such as improved access to water, sanitation, and hygiene (WASH) and health education can change the breakpoint itself by permanently altering the transmission environment, potentially yielding a higher (easier) target to achieve through MDA or other means. Identifying combinations of interventions that both raise the breakpoint and suppress the pathogen population may reveal optimal strategies for achieving elimination. Using dynamic epidemiological models of schistosomiasis transmission, we develop methods for estimating population breakpoints, and present a framework based on analysis of the effective reproduction number (Reff) that can be used to determine optimal intervention strategies based on local transmission conditions.

Results/Conclusions

We find that achieving elimination of local populations of helminths by drug administration alone is unlikely in many scenarios, especially in high-transmission settings, as the probability of achieving the breakpoint pathogen population density under reasonable assumptions of drug distribution coverage and efficacy is very low. We show how novel ecologic levers—such as introducing snail predators and reducing snail habitat by composting vegetation—can be combined with more conventional public health approaches such as MDA to efficiently achieve elimination. Finally, we show how more permanent developmental improvements in WASH and education can lead to both elimination and resilience to the reintroduction of infection.