The necessary cooperation between governments and public in the fight against COVID-19: why non-pharmaceutical interventions may be ineffective
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Abstract
The coronavirus disease (COVID-19) outbreak is the biggest public health challenge in the last 100 years. No successful pharmaceutical treatment is yet available, thus effective public health interventions to contain COVID-19 include social distancing, isolation and quarantine measures, however the efficiency of these containment measures varied among countries and even within states in the same country. Despite Brazil being deeply affected by coronavirus, the federal government never proposed a coordinated action to control COVID-19 and Brazilian states, which are autonomous, each imposed different containment measures. The state of Goiás declared strict social distancing measures in March 13, but gradually relaxed many of its first measures due specially to public pressure. Here we use a Susceptible-Infected-Recovered (SIR) model combined with Bayesian inference and a time-dependent spreading rate to assess how past state-level interventions affected the spread of COVID-19 in Goiás. The interventions succeeded in decreasing the transmission rate in the state, however, after the third intervention the rate remained positive and exponential. Thus, other stricter interventions were made necessary to avoid the growth of new cases and a collapse in the health system. Governmental interventions need to be taken seriously by the population in order for them have the proposed outcome. Our results reflect the population’s disregard with the measures imposed and the need for cooperation between governments and its citizens in the fight against COVID-19.
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SciScore for 10.1101/2020.08.17.20176347: (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
No key resources detected.
Results from OddPub: Thank you for sharing your code.
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 found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see …
SciScore for 10.1101/2020.08.17.20176347: (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
No key resources detected.
Results from OddPub: Thank you for sharing your code.
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 found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).
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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