Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China.
Department of Mathematics, Kano University of Science and Technology, Wudil, Nigeria.
Infect Dis Poverty. 2022 Apr 6;11(1):40. doi: 10.1186/s40249-022-00961-5.
The ongoing COVID-19 pandemic hit South America badly with multiple waves. Different COVID-19 variants have been storming across the region, leading to more severe infections and deaths even in places with high vaccination coverage. This study aims to assess the spatiotemporal variability of the COVID-19 pandemic and estimate the infection fatality rate (IFR), infection attack rate (IAR) and reproduction number ([Formula: see text]) for twelve most affected South American countries.
We fit a susceptible-exposed-infectious-recovered (SEIR)-based model with a time-varying transmission rate to the reported COVID-19 deaths for the twelve South American countries with the highest mortalities. Most of the epidemiological datasets analysed in this work are retrieved from the disease surveillance systems by the World Health Organization, Johns Hopkins Coronavirus Resource Center and Our World in Data. We investigate the COVID-19 mortalities in these countries, which could represent the situation for the overall South American region. We employ COVID-19 dynamic model with-and-without vaccination considering time-varying flexible transmission rate to estimate IFR, IAR and [Formula: see text] of COVID-19 for the South American countries.
We simulate the model in each scenario under suitable parameter settings and yield biologically reasonable estimates for IFR (varies between 0.303% and 0.723%), IAR (varies between 0.03 and 0.784) and [Formula: see text] (varies between 0.7 and 2.5) for the 12 South American countries. We observe that the severity, dynamical patterns of deaths and time-varying transmission rates among the countries are highly heterogeneous. Further analysis of the model with the effect of vaccination highlights that increasing the vaccination rate could help suppress the pandemic in South America.
This study reveals possible reasons for the two waves of COVID-19 outbreaks in South America. We observed reductions in the transmission rate corresponding to each wave plausibly due to improvement in nonpharmaceutical interventions measures and human protective behavioral reaction to recent deaths. Thus, strategies coupling social distancing and vaccination could substantially suppress the mortality rate of COVID-19 in South America.
持续的 COVID-19 大流行在南美洲造成了多波严重冲击。不同的 COVID-19 变体在该地区肆虐,导致即使在疫苗接种覆盖率较高的地方,感染和死亡情况也更加严重。本研究旨在评估 COVID-19 大流行的时空变异性,并估计 12 个受影响最严重的南美国家的感染病死率(IFR)、感染攻击率(IAR)和繁殖数([Formula: see text])。
我们根据报告的 COVID-19 死亡人数,为死亡率最高的 12 个南美国家拟合了一个基于易感-暴露-感染-恢复(SEIR)的模型,并对其进行了时变传播率的修正。本研究分析的大多数流行病学数据集均来自世界卫生组织、约翰霍普金斯冠状病毒资源中心和我们的世界数据中的疾病监测系统。我们研究了这些国家的 COVID-19 死亡率,这可能代表了整个南美洲地区的情况。我们使用考虑时变灵活传播率的 COVID-19 动态模型,结合和不结合疫苗接种情况,来估计 COVID-19 在南美国家的 IFR、IAR 和[Formula: see text]。
我们根据适当的参数设置模拟了每种情况下的模型,并得出了 IFR(在 0.303%到 0.723%之间变化)、IAR(在 0.03 到 0.784 之间变化)和[Formula: see text](在 0.7 到 2.5 之间变化)的合理估计值。我们观察到各国之间的严重程度、死亡的动态模式和时变传播率存在高度异质性。对考虑疫苗接种效果的模型进行进一步分析表明,提高疫苗接种率有助于抑制南美洲的大流行。
本研究揭示了南美洲 COVID-19 爆发的两波可能原因。我们观察到每一波传播率的降低,这可能是由于非药物干预措施的改善和对近期死亡的人类保护性行为反应。因此,结合社交距离和疫苗接种的策略可以显著降低南美洲 COVID-19 的死亡率。