TY - JOUR
T1 - Measuring the effects of COVID-19-related disruption on dengue transmission in southeast Asia and Latin America
T2 - a statistical modelling study
AU - CMMID COVID-19 Working Group
AU - Chen, Yuyang
AU - Li, Naizhe
AU - Lourenço, José
AU - Wang, Lin
AU - Cazelles, Bernard
AU - Dong, Lu
AU - Li, Bingying
AU - Liu, Yang
AU - Jit, Mark
AU - Bosse, Nikos I.
AU - Abbott, Sam
AU - Velayudhan, Raman
AU - Wilder-Smith, Annelies
AU - Tian, Huaiyu
AU - Brady, Oliver J.
AU - Procter, Simon R.
AU - Wong, Kerry LM
AU - Hellewell, Joel
AU - Davies, Nicholas G.
AU - Jarvis, Christopher I.
AU - McCarthy, Ciara V.
AU - Medley, Graham
AU - Meakin, Sophie R.
AU - Rosello, Alicia
AU - Finch, Emilie
AU - Lowe, Rachel
AU - Pearson, Carl A.B.
AU - Clifford, Samuel
AU - Quilty, Billy J.
AU - Flasche, Stefan
AU - Gibbs, Hamish P.
AU - Chapman, Lloyd A.C.
AU - Atkins, Katherine E.
AU - Hodgson, David
AU - Barnard, Rosanna C.
AU - Russell, Timothy W.
AU - Klepac, Petra
AU - Jafari, Yalda
AU - Eggo, Rosalind M.
AU - Mee, Paul
AU - Quaife, Matthew
AU - Endo, Akira
AU - Funk, Sebastian
AU - Hué, Stéphane
AU - Kucharski, Adam J.
AU - Edmunds, W. John
AU - O'Reilly, Kathleen
AU - Pung, Rachael
AU - Villabona-Arenas, C. Julian
AU - Gimma, Amy
N1 - Funding Information:
Funding for this study was provided by National Key Research and Development Program of China, Beijing Science and Technology Planning Project (Z201100005420010), Beijing Natural Science Foundation (JQ18025), Beijing Advanced Innovation Program for Land Surface Science, National Natural Science Foundation of China (82073616), and the Young Elite Scientist Sponsorship Program by China Association for Science and Technology (2018QNRC001). HT was supported by the Oxford Martin School. OJB was supported by a Wellcome Trust Sir Henry Wellcome Fellowship (206471/Z/17/Z) and a UK Medical Research Council Career Development Award (MR/V031112/1). This project was supported by a Medical Research Council–São Paulo Research Foundation Centre for Arbovirus Discovery, Diagnosis, Genomics and Epidemiology partnership award (MR/S0195/1 and FAPESP 18/14389-0) to OJB. OJB and AWS are commissioners for the Lancet Commission on arboviral diseases and acknowledge productive conversations with fellow commissioners that helped shape the work. The authors alone are responsible for the views expressed and they do not necessarily represent the decisions, policies or views of WHO.
Publisher Copyright:
© 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license
PY - 2022/5
Y1 - 2022/5
N2 - Background: The COVID-19 pandemic has resulted in unprecedented disruption to society, which indirectly affects infectious disease dynamics. We aimed to assess the effects of COVID-19-related disruption on dengue, a major expanding acute public health threat, in southeast Asia and Latin America. Methods: We assembled data on monthly dengue incidence from WHO weekly reports, climatic data from ERA5, and population variables from WorldPop for 23 countries between January, 2014 and December, 2019 and fit a Bayesian regression model to explain and predict seasonal and multi-year dengue cycles. We compared model predictions with reported dengue data January to December, 2020, and assessed if deviations from projected incidence since March, 2020 are associated with specific public health and social measures (from the Oxford Coronavirus Government Response Tracer database) or human movement behaviours (as measured by Google mobility reports). Findings: We found a consistent, prolonged decline in dengue incidence across many dengue-endemic regions that began in March, 2020 (2·28 million cases in 2020 vs 4·08 million cases in 2019; a 44·1% decrease). We found a strong association between COVID-19-related disruption (as measured independently by public health and social measures and human movement behaviours) and reduced dengue risk, even after taking into account other drivers of dengue cycles including climatic and host immunity (relative risk 0·01–0·17, p<0·01). Measures related to the closure of schools and reduced time spent in non-residential areas had the strongest evidence of association with reduced dengue risk, but high collinearity between covariates made specific attribution challenging. Overall, we estimate that 0·72 million (95% CI 0·12–1·47) fewer dengue cases occurred in 2020 potentially attributable to COVID-19-related disruption. Interpretation: In most countries, COVID-19-related disruption led to historically low dengue incidence in 2020. Continuous monitoring of dengue incidence as COVID-19-related restrictions are relaxed will be important and could give new insights into transmission processes and intervention options. Funding: National Key Research and Development Program of China and the Medical Research Council.
AB - Background: The COVID-19 pandemic has resulted in unprecedented disruption to society, which indirectly affects infectious disease dynamics. We aimed to assess the effects of COVID-19-related disruption on dengue, a major expanding acute public health threat, in southeast Asia and Latin America. Methods: We assembled data on monthly dengue incidence from WHO weekly reports, climatic data from ERA5, and population variables from WorldPop for 23 countries between January, 2014 and December, 2019 and fit a Bayesian regression model to explain and predict seasonal and multi-year dengue cycles. We compared model predictions with reported dengue data January to December, 2020, and assessed if deviations from projected incidence since March, 2020 are associated with specific public health and social measures (from the Oxford Coronavirus Government Response Tracer database) or human movement behaviours (as measured by Google mobility reports). Findings: We found a consistent, prolonged decline in dengue incidence across many dengue-endemic regions that began in March, 2020 (2·28 million cases in 2020 vs 4·08 million cases in 2019; a 44·1% decrease). We found a strong association between COVID-19-related disruption (as measured independently by public health and social measures and human movement behaviours) and reduced dengue risk, even after taking into account other drivers of dengue cycles including climatic and host immunity (relative risk 0·01–0·17, p<0·01). Measures related to the closure of schools and reduced time spent in non-residential areas had the strongest evidence of association with reduced dengue risk, but high collinearity between covariates made specific attribution challenging. Overall, we estimate that 0·72 million (95% CI 0·12–1·47) fewer dengue cases occurred in 2020 potentially attributable to COVID-19-related disruption. Interpretation: In most countries, COVID-19-related disruption led to historically low dengue incidence in 2020. Continuous monitoring of dengue incidence as COVID-19-related restrictions are relaxed will be important and could give new insights into transmission processes and intervention options. Funding: National Key Research and Development Program of China and the Medical Research Council.
UR - http://www.scopus.com/inward/record.url?scp=85127797446&partnerID=8YFLogxK
U2 - 10.1016/S1473-3099(22)00025-1
DO - 10.1016/S1473-3099(22)00025-1
M3 - Article
C2 - 35247320
AN - SCOPUS:85127797446
SN - 1473-3099
VL - 22
SP - 657
EP - 667
JO - The Lancet Infectious Diseases
JF - The Lancet Infectious Diseases
IS - 5
ER -
