Dynamic resource allocation for controlling pathogen spread on a large metapopulation network.

Lina Cristancho-Fajardo,Pauline Ezanno,Elisabeta Vergu

doi:10.1098/rsif.2021.0744

Abstract

To control the spread of an infectious disease over a large network, the optimal allocation by a social planner of a limited resource is a fundamental and difficult problem. We address this problem for a livestock disease that propagates on an animal trade network according to an epidemiological–demographic model based on animal demographics and trade data. We assume that the resource is dynamically allocated following a certain score, up to the limit of resource availability. We adapt a greedy approach to the metapopulation framework, obtaining new scores that minimize approximations of two different objective functions, for two control measures: vaccination and treatment. Through intensive simulations, we compare the greedy scores with several heuristics. Although topology-based scores can limit the spread of the disease, information on herd health status seems crucial to eradicating the disease. In particular, greedy scores are among the most effective in reducing disease prevalence, even though they do not always perform the best. However, some scores may be preferred in real life because they are easier to calculate or because they use a smaller amount of resources. The developed approach could be adapted to other epidemiological models or to other control measures in the metapopulation setting.

Highlights

Infectious disease spread is a problem that can have important social, sanitary and economic consequences
We are concerned with the problem of dynamically deciding where to allocate a limited available resource in an optimal manner, in order to minimize disease spread on a large animal metapopulation network
To control an infectious disease that spreads in a metapopulation network, allocating a limited resource is a fundamental yet difficult question, especially for large networks

Summary

Introduction

Infectious disease spread is a problem that can have important social, sanitary and economic consequences. Like for human diseases, this is a major public health concern for animal diseases, for guaranteeing animal welfare and food security [1]. In this context, epidemiological models, together with other relevant mathematical approaches, can help in the description and understanding of the mechanisms involved in disease propagation, as well as in assessing the effectiveness of control measures [2]. Many questions can arise in this context: how much resource is needed to restrain the disease propagation to a certain level [4–6], when should it be allocated [7] and where. We are concerned with the problem of dynamically deciding where to allocate a limited available resource in an optimal manner, in order to minimize disease spread on a large animal metapopulation network

Methods

Results

Conclusion