The COVID-19 pandemic has caused ~ 2 million fatalities. Significant progress has been made in advancing our understanding of the disease process, one of the unanswered questions, however, is the anomaly in the case/mortality ratio with Mexico as a clear example. Herein, this anomaly is explored by spatial analysis and whether mortality varies locally according to local factors. To address this, hexagonal cartogram maps (hexbin) used to spatially map COVID-19 mortality and visualise association with patient-level data on demographics and pre-existing health conditions. This was further interrogated at local Mexico City level by choropleth mapping. Our data show that the use of hexagonal cartograms is a better approach for spatial mapping of COVID-19 data in Mexico as it addresses bias in area size and population. We report sex/age-related spatial relationship with mortality amongst the Mexican states and a trend between health conditions and mortality at the state level. Within Mexico City, there is a clear south, north divide with higher mortality in the northern municipalities. Deceased patients in these northern municipalities have the highest pre-existing health conditions. Taken together, this study provides an improved presentation of COVID-19 mapping in Mexico and demonstrates spatial divergence of the mortality in Mexico.
翻译:COVID-19大流行已造成约200万人死亡,在增进我们对疾病过程的理解方面已取得重大进展,但一个尚未解答的问题是,与墨西哥的病例/死亡率比率异常是一个明显的例子。在这里,通过空间分析来探讨这一异常现象,以及死亡率是否因当地因素而异。为了解决这个问题,六边形的地图(Hexbin)用于空间测绘COVID-19死亡率,并与病人一级的人口和先前存在的健康状况数据有可视联系。在墨西哥城地方一级,通过染色体绘图对此进行了进一步调查。我们的数据显示,使用六边形图表是墨西哥CVID-19数据空间制图的更好方法,因为它处理地区大小和人口方面的偏差。我们报告墨西哥各州与死亡率有关的性别/年龄空间关系,以及州一级健康状况和死亡率的趋势。在墨西哥城,北部城市有明显的南北差距,死亡率较高。这些北部城市的病人患病前健康状况最高。墨西哥的COVI空间死亡率调查显示,墨西哥的COVI死亡率也有所改善。