TY - JOUR
T1 - Accessing the syndemic of COVID-19 and malaria intervention in Africa
AU - Shi, Benyun
AU - Zheng, Jinxin
AU - Xia, Shang
AU - Lin, Shan
AU - Wang, Xinyi
AU - Liu, Yang
AU - Zhou, Xiao Nong
AU - Liu, Jiming
N1 - Funding Information:
This work was supported in part by the Hong Kong Research Grants Council (Grant Nos. RGC/HKBU12201619, RGC/HKBU12201318, and RGC/HKBU12202220). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
PY - 2021/1/7
Y1 - 2021/1/7
N2 - 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.
AB - 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.
KW - COVID-19 pandemic
KW - Insecticide-treated nets
KW - Malaria transmission potential
KW - Non-pharmaceutical interventions
KW - Particle Markov chain Monte Carlo
KW - Vectorial capacity
UR - http://www.scopus.com/inward/record.url?scp=85098848609&partnerID=8YFLogxK
U2 - 10.1186/s40249-020-00788-y
DO - 10.1186/s40249-020-00788-y
M3 - Journal article
C2 - 33413680
AN - SCOPUS:85098848609
SN - 2095-5162
VL - 10
JO - Infectious Diseases of Poverty
JF - Infectious Diseases of Poverty
M1 - 5
ER -
