Accessing the syndemic of COVID-19 and malaria intervention in Africa

Benyun SHI, Jinxin Zheng, Shang Xia, Shan Lin, Xinyi Wang, Yang LIU, Xiao Nong Zhou, Jiming LIU*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Background: 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. Methods: 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. Results: 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 R and the duration of infection DI) of COVID-19 in each country are estimated as follows: Ethiopia (R= 1.57 , DI= 5.32), Nigeria (R= 2.18 , DI= 6.58), Tanzania (R= 2.47 , DI= 6.01), and Zambia (R= 2.12 , DI= 6.96). 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. Conclusions: 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.

Original languageEnglish
Article number5
JournalInfectious Diseases of Poverty
Volume10
Issue number1
DOIs
Publication statusPublished - 7 Jan 2021

Scopus Subject Areas

  • Public Health, Environmental and Occupational Health
  • Infectious Diseases

User-Defined Keywords

  • COVID-19 pandemic
  • Insecticide-treated nets
  • Malaria transmission potential
  • Non-pharmaceutical interventions
  • Particle Markov chain Monte Carlo
  • Vectorial capacity

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