Universidade Estadual de Feira de Santana, Departamento de Saúde, Feira de Santana, BA, Brasil.
Universidade Estadual de Feira de Santana, Departamento de Ciências Exatas, Feira de Santana, BA, Brasil.
Rev Soc Bras Med Trop. 2022 Feb 25;55:e0118. doi: 10.1590/0037-8682-0118-2021. eCollection 2022.
The epidemic curve has been obtained based on the 7-day moving average of the events. Although it facilitates the visualization of discrete variables, it does not allow the calculation of the absolute variation rate. Recently, we demonstrated that the polynomial interpolation method can be used to accurately calculate the daily acceleration of cases and deaths due to COVID-19. This study aimed to measure the diversity of epidemic curves and understand the importance of socioeconomic variables in the acceleration, pek cases, and deaths due to COVID-19 in Brazilian states.
Epidemiological data for COVID-19 from federative units in Brazil were obtained from the Ministry of Health's website from February 25 to July 11, 2020. Socioeconomic data were obtained from the Instituto Brasileiro de Geografia e Estatística (https://www.ibge.gov.br/). Using the polynomial interpolation methods, daily cases, deaths and acceleration were calculated. Moreover, the correlation coefficient between the epidemic curve data and socioeconomic data was determined.
The combination of daily data and case acceleration determined that Brazilian states were in different stages of the epidemic. Maximum case acceleration, peak of cases, maximum death acceleration, and peak of deaths were associated with the Gini index of the gross domestic product of Brazilian states and population density but did not correlate with the per capita gross domestic product of Brazilian states.
Brazilian states showed heterogeneous data curves. Population density and socioeconomic inequality were correlated with a more rapid exponential growth in new cases and deaths.
疫情曲线是基于事件的 7 天移动平均值得出的。虽然它便于离散变量的可视化,但无法计算绝对变化率。最近,我们证明了多项式插值法可用于准确计算 COVID-19 病例和死亡的每日加速率。本研究旨在衡量疫情曲线的多样性,并了解社会经济变量在巴西各州 COVID-19 病例加速、高峰期病例和死亡中的重要性。
从 2020 年 2 月 25 日至 7 月 11 日,从卫生部网站获取巴西联邦单位的 COVID-19 流行病学数据。从巴西地理与统计研究所(https://www.ibge.gov.br/)获取社会经济数据。使用多项式插值法计算每日病例、死亡和加速数。此外,还确定了疫情曲线数据和社会经济数据之间的相关系数。
将每日数据与病例加速相结合,可确定巴西各州处于不同的疫情阶段。最大病例加速、病例高峰、最大死亡加速和死亡高峰与巴西各州国内生产总值的基尼指数和人口密度有关,但与巴西各州人均国内生产总值无关。
巴西各州的疫情数据曲线存在差异。人口密度和社会经济不平等与新病例和死亡的快速指数增长相关。