SARS-CoV-2 Spread Under the Controlled-Distancing Model of Rio Grande do Sul, Brazil

Author:

Rohweder RicardoORCID,Schüler-Faccini LavíniaORCID,Ferraz GonçaloORCID

Abstract

AbstractIn early 2020, the government of Rio Grande do Sul established a public-health assessment-response framework to halt the spread of SARS-CoV-2, called ‘controlled-distancing model’ (CDM). This framework subdivided the state in 21 regions where it evaluated a composite index of disease transmission and health-service capacity. Updated on a weekly basis, the index placed regions on a color-coded scale of flags, which guided adoption of non-pharmaceutical interventions. We aim to evaluate the extent to which the CDM accurately assessed transmission and the effectiveness of its responses throughout 2020. We estimated the weekly effective reproduction number (Rt) of SARS-CoV-2, for each region, using a renewal-equation-based statistical model of notified COVID-19 deaths. UsingRtestimates, we explored whether flag colors assigned by the CDM either reflected or affected SARS-CoV-2 dissemination. Flag assignments did reflect variations inRt, to a limited extent, but we found no evidence that they affected Rtin the short term. Medium-term effects were apparent in only four regions after eight or more weeks of red-flag assignment. Analysis of Google movement metrics showed no evidence that people moved differently under different flags. The dissociation between flag colors and the propagation of SARS-CoV-2 does not support the claim that non-pharmaceutical interventions are ineffective. Our results show, however, that decisions made under the CDM framework were ineffective both for influencing the movement of people and for halting the spread of the virus.

Publisher

Cold Spring Harbor Laboratory

Reference41 articles.

1. An interactive web-based dashboard to track COVID-19 in real time

2. Evolution and epidemic spread of SARS-CoV-2 in Brazil

3. Governo do Estado do Rio Grande do Sul. Decreto n° 55.240, de 10 de maio de 2020; 2020. https://saude.rs.gov.br/upload/arquivos/202005/12091118-55-240.pdf. Accessed April 06, 2023.

4. Report of the Independent Panel for Pandemic Preparedness and Response: making COVID-19 the last pandemic

5. Advances in Decision Analysis

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3