Department of Electronics, Rajkiya Engineering College Kannauj, UP, 209732, India.
Department of Geography, Banaras Hindu University, Varanasi, 221005, India.
Diabetes Metab Syndr. 2021 May-Jun;15(3):993-999. doi: 10.1016/j.dsx.2021.04.025. Epub 2021 May 10.
In India, COVID-19 case fatality rates (CFRs) have consistently been very high in states like Punjab and Maharashtra and very low in Kerala and Assam. To investigate the discrepancy in state-wise CFRs, datasets on various factors related to demography, socio-economy, public health, and healthcare capacity have been collected to study their association with CFR.
State-wise COVID-19 data was collected till April 22, 2021. The latest data on the various factors have been collected from reliable sources. Pearson correlation, two-tailed P test, Spearman rank correlation, and Artificial Neural Network (ANN) structures have been used to assess the association between various factors and CFR.
Life expectancies, prevalence of overweight, COVID-19 test positive rates, and H1N1 fatality rates show a significant positive association with CFR. Human Development Index, per capita GDP, public affairs index, health expenditure per capita, availability of govt. doctors & hospital beds, prevalence of certain diseases, and comorbidities like diabetes and hypertension show insignificant association with CFR. Sex ratio, health expenditure as a percent of GSDP, and availability of govt. hospitals show a significant negative correlation with CFR.
The study indicates that older people, males of younger age groups, and overweight people are at more fatality risk from COVID-19. Certain diseases and common comorbidities like diabetes and hypertension do not seem to have any significant effect on CFR. States with better COVID-19 testing rates, health expenditure, and healthcare capacity seem to perform better with regard to COVID-19 fatality rates.
在印度，旁遮普邦和马哈拉施特拉邦等邦的 COVID-19 病死率 (CFR) 一直很高，而喀拉拉邦和阿萨姆邦则非常低。为了调查各州 CFR 之间的差异，收集了与人口统计学、社会经济、公共卫生和医疗保健能力相关的各种因素的数据集，以研究它们与 CFR 的关联。
截至 2021 年 4 月 22 日，收集了各州的 COVID-19 数据。从可靠来源收集了有关各种因素的最新数据。使用 Pearson 相关性、双尾 P 检验、Spearman 秩相关和人工神经网络 (ANN) 结构来评估各种因素与 CFR 之间的关联。
预期寿命、超重患病率、COVID-19 检测阳性率和 H1N1 死亡率与 CFR 呈显著正相关。人类发展指数、人均国内生产总值、公共事务指数、人均卫生支出、政府医生和病床的可用性、某些疾病的患病率以及糖尿病和高血压等合并症与 CFR 无显著关联。性别比、卫生支出占 GSDP 的百分比和政府医院的可用性与 CFR 呈显著负相关。
该研究表明，老年人、年轻男性和超重人群感染 COVID-19 的死亡风险更高。某些疾病和常见合并症如糖尿病和高血压似乎对 CFR 没有任何显著影响。COVID-19 检测率、卫生支出和医疗保健能力较好的州在 COVID-19 死亡率方面表现更好。
