Benyun Shi1, Jinxin Zheng2,3,4,5,6,7, Shang Xia2,3,4,5,6,7, Shan Lin8, Xinyi Wang2,3,4,5,6,7, Yang Liu9, Xiao-Nong Zhou2,3,4,5,6,7, Jiming Liu10. 1. School of Computer Science and Technology, Nanjing Tech University, Nanjing, 211800, Jiangsu, China. 2. National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai, 200025, China. 3. Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, 200025, China. 4. Chinese Center for Tropical Diseases Research, Shanghai, 200025, China. 5. WHO Collaborating Centre for Tropical Diseases, Shanghai, 200025, China. 6. National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, 200025, China. 7. School of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China. 8. College of Information Engineering, Nanjing University of Finance & Economics, Nanjing, 210003, Jiangsu, China. 9. Department of Computer Science, Hong Kong Baptist University, Hong Kong, China. 10. Department of Computer Science, Hong Kong Baptist University, Hong Kong, China. jiming@comp.hkbu.edu.hk.
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 [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. 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.
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 [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. 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.
Authors: Amy Wesolowski; Nathan Eagle; Andrew J Tatem; David L Smith; Abdisalan M Noor; Robert W Snow; Caroline O Buckee Journal: Science Date: 2012-10-12 Impact factor: 47.728
Authors: S Bhatt; D J Weiss; E Cameron; D Bisanzio; B Mappin; U Dalrymple; K Battle; C L Moyes; A Henry; P A Eckhoff; E A Wenger; O Briët; M A Penny; T A Smith; A Bennett; J Yukich; T P Eisele; J T Griffin; C A Fergus; M Lynch; F Lindgren; J M Cohen; C L J Murray; D L Smith; S I Hay; R E Cibulskis; P W Gething Journal: Nature Date: 2015-09-16 Impact factor: 49.962
Authors: Alexandra B Hogan; Britta L Jewell; Ellie Sherrard-Smith; Juan F Vesga; Oliver J Watson; Charles Whittaker; Arran Hamlet; Jennifer A Smith; Peter Winskill; Robert Verity; Marc Baguelin; John A Lees; Lilith K Whittles; Kylie E C Ainslie; Samir Bhatt; Adhiratha Boonyasiri; Nicholas F Brazeau; Lorenzo Cattarino; Laura V Cooper; Helen Coupland; Gina Cuomo-Dannenburg; Amy Dighe; Bimandra A Djaafara; Christl A Donnelly; Jeff W Eaton; Sabine L van Elsland; Richard G FitzJohn; Han Fu; Katy A M Gaythorpe; William Green; David J Haw; Sarah Hayes; Wes Hinsley; Natsuko Imai; Daniel J Laydon; Tara D Mangal; Thomas A Mellan; Swapnil Mishra; Gemma Nedjati-Gilani; Kris V Parag; Hayley A Thompson; H Juliette T Unwin; Michaela A C Vollmer; Caroline E Walters; Haowei Wang; Yuanrong Wang; Xiaoyue Xi; Neil M Ferguson; Lucy C Okell; Thomas S Churcher; Nimalan Arinaminpathy; Azra C Ghani; Patrick G T Walker; Timothy B Hallett Journal: Lancet Glob Health Date: 2020-07-13 Impact factor: 26.763