Response capacity to the COVID-19 pandemic in Latin America and the Caribbean
Response capacity to the COVID-19 pandemic in Latin America and the Caribbean
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DOI：
10.26633/rpsr.2020.109
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发表时间：
2020-01-01
影响因子：
2.6
通讯作者：
Debora Acosta, Laura
中科院分区：
文献类型：
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作者：
Debora Acosta, Laura
目标。分析新冠肺炎大流行在拉美和加勒比国家的演变及其与公共卫生措施相关变量以及人口、健康和社会特征的关系。采用Joinpoint回归分析方法，使用Joinpoint回归程序4.8.0.1对新冠肺炎的每日新增病例趋势和粗死亡率进行分析。数据是从我们的世界数据登记处获得的。在每个国家为应对新冠肺炎大流行而采取的公共卫生措施(通过牛津大学严格指数衡量)和卫生、人口和社会条件与大流行演变结果之间进行了多重对应分析。采用SPSS统计软件进行统计分析。Joinpoint回归分析显示，巴西的病例数量增幅最高(11.3%)，墨西哥的CMR增幅最高(16.2%)。多元对应分析显示，CMR与总人口、紧迫度指数、城市化水平、日均生活费低于1美元的人口比例、糖尿病患病率、住院床位数有关。该区域各国新冠肺炎的发病率呈现出异质性演变。这种异质性既与所采取的公共卫生措施有关，也与人口规模、贫困水平和先前存在的卫生系统有关。
Objective. To analyze the evolution of the COVID-19 pandemic in Latin American and Caribbean countries in its first 90 days and its association with variables related to public health measures, and demographic, health and social characteristics.Methods. The trend in new daily cases and the crude mortality rate (CMR) from COVID-19 were analyzed through the Joinpoint regression analysis methodology, using the Joinpoint Regression Program 4.8.0.1. Data was obtained from the Our World in Data registry. A multiple correspondence analysis was performed between the public health measures adopted in each country to face the COVID-19 pandemic (measured through the stringency index, Oxford University) and sanitary, demographic and social conditions, and the results of the evolution of the pandemic. SPSS software was used.Results. The Joinpoint regression analysis showed that the highest increase in the number of cases was observed in Brazil (11.3%) and the highest increase in CMR in Mexico (16.2%). The multiple correspondence analysis showed that CMR was associated with the total population, the stringency index, the level of urbanization, the proportion of the population living on less than one dollar a day, the prevalence of diabetes and the number of hospital beds.Conclusions. The countries of the region show a heterogeneous evolution in the incidence of COVID-19. This heterogeneity is associated with both the public health measures adopted, as well as with the population size, poverty levels and pre-existing health systems.