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2020-2022 年里约热内卢州卫生区的 COVID-19 疫情在空间上是否具有同步性？一项分析。

Was the COVID-19 epidemic synchronous in space? An analysis in the health regions of the Rio de Janeiro state, 2020-2022.

机构信息

Fundação Oswaldo Cruz, National School of Public Health - Rio de Janeiro (RJ), Brazil.

Barcelona Supercomputing Center - Barcelona, Spain.

出版信息

Rev Bras Epidemiol. 2024 Feb 26;27:e240010. doi: 10.1590/1980-549720240010. eCollection 2024.

DOI:10.1590/1980-549720240010
PMID:38422234
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10896236/
Abstract

OBJECTIVE

To analyze the spatio-temporal dynamics of COVID-19 in the Rio de Janeiro state within the nine health regions, between March 2020 and December 2022.

METHODS

The Poisson model with random effects was used to smooth and estimate the incidence of COVID-19 hospitalizations reported in the Influenza Epidemiological Surveillance Information System (SIVEP-Gripe) to verify the synchronicity of the epidemic in the state.

RESULTS

The COVID-19 epidemic in the state is characterized by the presence of seven peaks during the analyzed period corresponding to seven found. An asynchrony in hospitalizations was identified, varying according to the different virus variants in the nine health regions of the state. The incidence peaks of hospitalizations ranged from 1 to 12 cases per 100,000 inhabitants during the pandemic.

CONCLUSION

This spatio-temporal analysis is applicable to other scenarios, enabling monitoring and decision-making for the control of epidemic diseases in different areas.

摘要

目的

分析 2020 年 3 月至 2022 年 12 月期间，里约热内卢州九个卫生区 COVID-19 的时空动态。

方法

采用具有随机效应的泊松模型对流感监测信息系统（SIVEP-Gripe）中报告的 COVID-19 住院发病率进行平滑和估计，以验证该州疫情的同步性。

结果

在分析期间，该州的 COVID-19 疫情呈现出七个高峰期，与实际发现的高峰期相对应。在州内的九个卫生区中，根据不同的病毒变异，存在住院时间的不同步。在大流行期间，住院发病率的峰值范围为每 10 万居民 1 至 12 例。

结论

这种时空分析适用于其他情况，能够对不同地区的传染病控制进行监测和决策。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e280/10896236/bf5af14758c3/1980-5497-rbepid-27-e240010-gf4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e280/10896236/3c0bd1ca61d6/1980-5497-rbepid-27-e240010-gf1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e280/10896236/bfe999debeed/1980-5497-rbepid-27-e240010-gf2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e280/10896236/8d41c6c52713/1980-5497-rbepid-27-e240010-gf3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e280/10896236/bf5af14758c3/1980-5497-rbepid-27-e240010-gf4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e280/10896236/3c0bd1ca61d6/1980-5497-rbepid-27-e240010-gf1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e280/10896236/bfe999debeed/1980-5497-rbepid-27-e240010-gf2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e280/10896236/8d41c6c52713/1980-5497-rbepid-27-e240010-gf3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e280/10896236/bf5af14758c3/1980-5497-rbepid-27-e240010-gf4.jpg

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