RR:C19 Evidence Scale rating by reviewer:
Reliable. The main study claims are generally justified by its methods and data. The results and conclusions are likely to be similar to the hypothetical ideal study. There are some minor caveats or limitations, but they would/do not change the major claims of the study. The study provides sufficient strength of evidence on its own that its main claims should be considered actionable, with some room for future revision.
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Review:
This paper integrates knowledge about virology, epidemiology, and the physical flow of customers in retail stores to develop and analyze a model to investigate the impacts of different operational interventions on disease spreading. This work is interesting and timely, especially at this moment. Overall, the paper is well-structured and well-written. The authors present a rigorous derivation of the analytical results and also provide some significant practical implications that are useful for policymaking.
There are some issues that might need to be addressed before publication. The explanation of the model is not detailed and not intuitive enough. For example:
(1) It is not intuitive to reach Eq. (4), the authors should illustrate the derivation of Eq. (4) as detailed as that of Eq. (1).
(2) Before Eq. (8), "it can be shown that the wake transmission rate... who arrived at time t is" arrived where? What's the meaning of time t? the time in whose journey?
(3) Before Eq. (9), " In fact, customer q will encounter the wake of any infectious ‘customer p’ who has passed through that spot at time τ, 0 ≤ τ ≤ (L − qt)/p earlier, ..." What's the meaning of the constraint on τ?
Maybe the authors should add some figures to illustrate the moving patterns of customers (just as Fig. 1, but not only show the focal customer, but also the infectious customers) for different scenarios, which can help readers better understand the model.
I am not sure if it is appropriate to compare the results of direct exposure (Fig. 2, left one) with the car accident example. It is common sense that the probability of a car accident increases if you drive too fast. However, it is not straightforward to conclude that people should keep a median speed for a lower risk of getting infected. The authors should provide more explanation about it except for the car accident example.
On page 14, the authors used a discrete event simulation to explore the variability around the average results, but do not provide details about the simulations, for example, how many times they run the simulation. It would be better they could further use the simulations to validate their analytical results.
The manuscript needs further grammar checking, there are several mistakes. For example,
(1) Abstract: "We find that the effectiveness ... are sensitive to ..." are-> is.
(2) Abstract: "the rate of direct transmission under full compliance with one-way movement is less than one-third the rate under two-way movement." one-third -> one-third of
(3) respiratory droplet -> respiratory droplets
(4) aerosal -> aerosol
(5) Page 3: "may occur in front" -> occur in the front
(6) Page 16: "The benefits of this intervention is ..." -> are
(7) Page 18: "Given this uncertainty... need to be filled to..." -> need to be filled too
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