Abstract
COVID-19 is generally transmitted from person to person through small droplets of saliva emitted when talking, sneezing, coughing, or breathing. For this reason, social distancing and ventilation have been widely emphasized to control the pandemic. The spread of the virus has brought with it many challenges in locating people under distance constraints. The effects of wakes between turbines have been studied extensively in the literature on wind energy, and there are well-established interference models. Does this apply to the propagation functions of the virus? In this work, a parallel relationship between the two problems is proposed. A mixed-integer linear programming (MIP) model and a mixed-integer quadratic programming model (MIQP) are formulated to locate people to avoid the spread of COVID-19. Both models were constructed according to the distance constraints proposed by the World Health Organization and the interference functions representing the effects of wake between turbines. Extensive computational tests show that people should not be less than two meters apart, in agreement with the adapted Wells–Riley model, which indicates that 1.6 to 3.0 m (5.2 to 9.8 ft) is the safe social distance when considering the aerosol transmission of large droplets exhaled when speaking, while the distance can be up to 8.2 m (26 ft) if all the droplets in a calm air environment are taken into account.
Highlights
After its discovery in China in December 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), began to spread through most countries of the world, resulting in a large number of infections and deaths, and placing significant pressure on the health systems and governments of different countries, which, in many cases, did not have the resources or infrastructure to face the pandemic caused by the virus, as was the case in Chile [1,2]
According to the information provided by the Ministry of Health, SARS-CoV-2 is a strain of the coronavirus family that had not been previously identified in humans
After500.00 the computational times are analyzed, the results obtained by applying Interference Functions (A1) and (A2) are verified
Summary
After its discovery in China in December 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), began to spread through most countries of the world, resulting in a large number of infections and deaths, and placing significant pressure on the health systems and governments of different countries, which, in many cases, did not have the resources or infrastructure to face the pandemic caused by the virus, as was the case in Chile [1,2]. Coronaviruses cause diseases, ranging from the common cold to more complex diseases, such as severe acute respiratory failure [3,4]. According to World Health Organization (WHO) information, SARS-CoV-2 is transmitted mainly by person-to-person contact with an infected person (even if he or she does not present symptoms) [5].
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