School of Computer Science and Technology, Nanjing Tech University, Nanjing, 211800, Jiangsu, China.
National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai, 200025, China.
Infect Dis Poverty. 2021 Jan 7;10(1):5. doi: 10.1186/s40249-020-00788-y.
The pandemic of the coronavirus disease 2019 (COVID-19) has caused substantial disruptions to health services in the low and middle-income countries with a high burden of other diseases, such as malaria in sub-Saharan Africa. The aim of this study is to assess the impact of COVID-19 pandemic on malaria transmission potential in malaria-endemic countries in Africa.
We present a data-driven method to quantify the extent to which the COVID-19 pandemic, as well as various non-pharmaceutical interventions (NPIs), could lead to the change of malaria transmission potential in 2020. First, we adopt a particle Markov Chain Monte Carlo method to estimate epidemiological parameters in each country by fitting the time series of the cumulative number of reported COVID-19 cases. Then, we simulate the epidemic dynamics of COVID-19 under two groups of NPIs: (1) contact restriction and social distancing, and (2) early identification and isolation of cases. Based on the simulated epidemic curves, we quantify the impact of COVID-19 epidemic and NPIs on the distribution of insecticide-treated nets (ITNs). Finally, by treating the total number of ITNs available in each country in 2020, we evaluate the negative effects of COVID-19 pandemic on malaria transmission potential based on the notion of vectorial capacity.
We conduct case studies in four malaria-endemic countries, Ethiopia, Nigeria, Tanzania, and Zambia, in Africa. The epidemiological parameters (i.e., the basic reproduction number [Formula: see text] and the duration of infection [Formula: see text]) of COVID-19 in each country are estimated as follows: Ethiopia ([Formula: see text], [Formula: see text]), Nigeria ([Formula: see text], [Formula: see text]), Tanzania ([Formula: see text], [Formula: see text]), and Zambia ([Formula: see text], [Formula: see text]). Based on the estimated epidemiological parameters, the epidemic curves simulated under various NPIs indicated that the earlier the interventions are implemented, the better the epidemic is controlled. Moreover, the effect of combined NPIs is better than contact restriction and social distancing only. By treating the total number of ITNs available in each country in 2020 as a baseline, our results show that even with stringent NPIs, malaria transmission potential will remain higher than expected in the second half of 2020.
By quantifying the impact of various NPI response to the COVID-19 pandemic on malaria transmission potential, this study provides a way to jointly address the syndemic between COVID-19 and malaria in malaria-endemic countries in Africa. The results suggest that the early intervention of COVID-19 can effectively reduce the scale of the epidemic and mitigate its impact on malaria transmission potential.
2019 年冠状病毒病(COVID-19)大流行对中低收入国家的卫生服务造成了重大干扰,这些国家还面临着疟疾等其他疾病的沉重负担,如撒哈拉以南非洲的疟疾。本研究旨在评估 COVID-19 大流行对非洲疟疾流行国家疟疾传播潜力的影响。
我们提出了一种数据驱动的方法来量化 COVID-19 大流行以及各种非药物干预(NPIs)在多大程度上可能导致 2020 年疟疾传播潜力的变化。首先,我们采用粒子马尔可夫链蒙特卡罗方法,通过拟合累积报告 COVID-19 病例数的时间序列来估计每个国家的流行病学参数。然后,我们模拟了两组 NPIs 下的 COVID-19 流行动态:(1)接触限制和社会距离,以及(2)病例的早期识别和隔离。基于模拟的流行曲线,我们量化了 COVID-19 流行和 NPIs 对驱虫蚊帐(ITN)分布的影响。最后,通过处理每个国家 2020 年可用的 ITN 总数,我们根据媒介容量的概念评估 COVID-19 大流行对疟疾传播潜力的负面影响。
我们在非洲的四个疟疾流行国家,即埃塞俄比亚、尼日利亚、坦桑尼亚和赞比亚进行了案例研究。每个国家的 COVID-19 流行病学参数(即基本繁殖数 [Formula: see text]和感染持续时间 [Formula: see text])估计如下:埃塞俄比亚([Formula: see text],[Formula: see text]),尼日利亚([Formula: see text],[Formula: see text]),坦桑尼亚([Formula: see text],[Formula: see text])和赞比亚([Formula: see text],[Formula: see text])。基于估计的流行病学参数,在各种 NPIs 下模拟的流行曲线表明,干预措施越早实施,疫情控制得越好。此外,联合 NPIs 的效果优于仅接触限制和社会距离。通过将每个国家 2020 年可用的 ITN 总数作为基线,我们的结果表明,即使采取严格的 NPIs,疟疾传播潜力仍将在 2020 年下半年高于预期。
通过量化 COVID-19 大流行对各种 NPI 反应对疟疾传播潜力的影响,本研究提供了一种方法来共同应对非洲疟疾流行国家 COVID-19 和疟疾之间的综合征。结果表明,COVID-19 的早期干预可以有效减少疫情规模,并减轻其对疟疾传播潜力的影响。