Data Science Research Unit, School of Computing and Mathematics, Charles Sturt University, Wagga Wagga, NSW 2678, Australia.
Australian Institute of Tropical Health and Medicine, James Cook University, Townsville, QLD 4810, Australia.
Biomed Res Int. 2021 May 27;2021:5089184. doi: 10.1155/2021/5089184. eCollection 2021.
The new Coronavirus Disease 19, officially known as COVID-19, originated in China in 2019 and has since spread worldwide. We presented an age-structured Susceptible-Latent-Mild-Critical-Removed (SLMCR) compartmental model of COVID-19 disease transmission with nonlinear incidence during the pandemic period. We provided the model calibration to estimate parameters with day-wise COVID-19 data, i.e., reported cases by worldometer from 15 February to 30 March 2020 in six high-burden countries, including Australia, Italy, Spain, the USA, the UK, and Canada. We estimate transmission rates for each country and found that the country with the highest transmission rate is Spain, which may increase the new cases and deaths than the other countries. We found that saturation infection negatively impacted the dynamics of COVID-19 cases in all the six high-burden countries. The study used a sensitivity analysis to identify the most critical parameters through the partial rank correlation coefficient method. We found that the transmission rate of COVID-19 had the most significant influence on prevalence. The prediction of new cases in COVID-19 until 30 April 2020 using the developed model was also provided with recommendations to control strategies of COVID-19. We also found that adults are more susceptible to infection than both children and older people in all six countries. However, in Italy, Spain, the UK, and Canada, older people show more susceptibility to infection than children, opposite to the case in Australia and the USA. The information generated from this study would be helpful to the decision-makers of various organisations across the world, including the Ministry of Health in Australia, Italy, Spain, the USA, the UK, and Canada, to control COVID-19.
新型冠状病毒病（COVID-19），俗称新冠肺炎，于 2019 年在中国首次出现，并已在全球范围内传播。我们提出了一个具有非线性发病率的年龄结构易感-潜伏-轻症-重症-清除（SLMCR）的 COVID-19 疾病传播 compartmental 模型。我们对模型进行了校准，以利用从 2020 年 2 月 15 日至 3 月 30 日期间世界卫生组织报告的六个人口负担沉重的国家（包括澳大利亚、意大利、西班牙、美国、英国和加拿大）的每日 COVID-19 数据来估计参数。我们估计了每个国家的传播率，发现传播率最高的国家是西班牙，这可能会导致其新增病例和死亡人数高于其他国家。我们发现饱和感染对所有六个高负担国家的 COVID-19 病例动态产生负面影响。该研究使用敏感性分析通过偏秩相关系数法来确定最关键的参数。我们发现 COVID-19 的传播率对流行率有最显著的影响。我们还提供了利用所开发模型对 COVID-19 直至 2020 年 4 月 30 日的新增病例进行预测的结果，并提出了 COVID-19 控制策略的建议。我们还发现，在所有六个国家中，成年人比儿童和老年人更容易感染，但在意大利、西班牙、英国和加拿大，老年人比儿童更容易感染，与澳大利亚和美国的情况相反。这项研究提供的信息将有助于包括澳大利亚、意大利、西班牙、美国、英国和加拿大在内的世界各国的各个组织的决策者，包括卫生部，来控制 COVID-19。
