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Pandemics are a source of extensive mortality, economic impairment, and dramatic social fluctuation. Once a pandemic occurs, policymakers are faced with the highly challenging task of controlling it over time and space. In this article, a novel pandemic intervention policy that relies on the strategic deployment of inspection units (IUs) is proposed. These IUs are allocated in the environment, represented as a graph, and sample individuals who pass through the same node. If a sampled individual is identified as infected, she is extracted from the environment until she recovers (or dies). A realistic simulation‐based evaluation of the Influenza A pathogen using both synthetic and real‐world data is provided. The results demonstrate potential significant benefits of the proposed PIP in mitigating a pandemic spread which can complement other standard policies such as social distancing and mask‐wearing.

A single paragraph of about 200 words maximum. For research articles, abstracts should give a pertinent overview of the work. We strongly encourage authors to use the following style of structured abstracts, but without headings: (1) Background: place the question addressed in a broad context and highlight the purpose of the study; (2) Methods: describe briefly the main methods or treatments applied; (3) Results: summarize the article’s main findings; (4) Conclusions: indicate the main conclusions or interpretations. The abstract should be an objective representation of the article, it must not contain results which are not presented and substantiated in the main text and should not exaggerate the main conclusions. Airborne diseases cause high mortality and adverse socioeconomic consequences. Due to urbanization, more people spend more time indoors. According to recent research, air ventilation reduces long-range airborne transmission in indoor settings. However, air ventilation solutions often incur significant energy costs and ecological footprints. The trade-offs between energy consumption and pandemic control indoors have not yet been thoroughly analyzed. In this work, we use advanced sensors to monitor the energy consumption and pandemic control capabilities of an air-conditioning system, a pedestal fan, and an open window in hospital rooms, classrooms, and conference rooms. A simulation of an indoor airborne pandemic spread of Coronavirus (COVID-19) is used to analyze the Pareto front. For the three examined room types, the Pareto front consists of all three air ventilation solutions, with some ventilation configurations demonstrating significant inefficiencies. Specifically, air-conditioning is found to be efficient only at a very high energy cost and fans seem to pose a reasonable alternative. To conclude, a more informed ventilation policy can bring about a more desirable compromise between energy consumption and pandemic spread control.

No abstract