Local protection bubbles: an interpretation of the decrease in the velocity of coronavirus’s spread in the city of São Paulo
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Abstract
After four months of dealing with the pandemic, the city of São Paulo entered a phase of relaxed social-distancing measures in July 2020, and saw its social isolation rate fall at the same time as the number of cases, deaths, and hospital bed occupation declined. We use a calibrated multi-agent model to describe these dynamics. We assert here that this phenomenon can be understood as the result of local protective bubbles formed in the city’s sub-environments at the same time that there was an exhaustion of contagion networks. Both reduce the velocity of the virus’s spread, causing temporary reductions in the epidemic curve, albeit in an unstable equilibrium. These local bubbles can burst anytime and anywhere due to the reintroduction of a few infected people at the same time that there is a reduction in non-pharmaceutical interventions (NPI), such as social-distancing practices. It is important to stress that this hypothesis aligns with the dynamics of the virus’s spread observed so far, without needing ad hoc suppositions about natural collective immunity thresholds or heterogeneity in the population’s transmission rate, which come with the risk of making mistaken predictions that may could lead to the loss of many lives. The safe way to move ahead is to continue doing all we can to avoid new infections until a vaccine is found that properly and safely creates herd immunity.
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SciScore for 10.1101/2020.08.11.20173039: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources As for all the multi-agent models, “MD Corona” is a stochastic process that depends on the initial conditions randomly determined by the simulator each time (the relative position of infected and immobilized individuals). Corona”suggested: NoneTo account for this fluctuation we ran all the simulated scenarios 100 times with the aid of a Python program and examined the average results. Pythonsuggested: (IPython, RRID:SCR_001658)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Res…SciScore for 10.1101/2020.08.11.20173039: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources As for all the multi-agent models, “MD Corona” is a stochastic process that depends on the initial conditions randomly determined by the simulator each time (the relative position of infected and immobilized individuals). Corona”suggested: NoneTo account for this fluctuation we ran all the simulated scenarios 100 times with the aid of a Python program and examined the average results. Pythonsuggested: (IPython, RRID:SCR_001658)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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