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Population Replacement Strategies for Controlling Vector Populations and the Use of Wolbachia pipientis for Genetic Drive

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Resource Allocation for Epidemic Control Across Multiple Sub-populations.

Ciara E Dangerfield¹, Martin Vyska², Christopher A Gilligan²

¹Department of Plant Sciences, University of Cambridge, Downing Street, Cambridge, CB2 3EA, UK. ced57@cam.ac.uk.

Bulletin of Mathematical Biology

|February 28, 2019

Summary

This summary is machine-generated.

Limited resources demand focused disease control. Mathematical modeling shows concentrating treatment on specific populations, approximated by a knapsack problem, is more effective than widespread, less intensive interventions for plant, animal, and human health.

Keywords:

Epidemiological modelling Metapopulation model Optimal control of epidemics

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Area of Science:

Epidemiology
Mathematical Biology
Resource Allocation

Background:

Increasing pathogenic threats to plant, animal, and human health necessitate efficient control strategies.
Limited resources present a significant challenge for decision-makers in allocating control efforts across multiple threats.
Effective disease management requires optimizing resource allocation to minimize collective damage from pathogen spread.

Purpose of the Study:

To determine optimal resource allocation strategies for controlling pathogen spread across multiple populations with limited budgets.
To analyze the dynamics of disease control using the susceptible-infected-susceptible model under resource constraints.
To evaluate the effectiveness of focused treatment strategies versus broadly distributed interventions.

Main Methods:

Mathematical analysis of system dynamics using the susceptible-infected-susceptible (SIS) model.
Approximation of optimal resource allocation using a knapsack-type problem.
Comparison of the knapsack approximation against simpler control strategies.

Main Results:

Focused treatment on a subset of populations is more effective than less intensive treatment across all populations.
The knapsack problem provides a close approximation to the exact optimal resource allocation.
The knapsack approximation outperforms simpler disease control strategies.

Conclusions:

Resource allocation for disease control should prioritize specific populations to maximize effectiveness within budget constraints.
The knapsack approximation offers valuable insights into economic and epidemiological factors influencing optimal control strategies.
This approach accounts for indirect population interactions and initial condition dependencies in resource allocation for disease control.