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Imai N, Rawson T, Knock ES, Sonabend R, Elmaci Y, Perez-Guzman PN, Whittles LK, Kanapram DT, Gaythorpe KAM, Hinsley W, Djaafara BA, Wang H, Fraser K, FitzJohn RG, Hogan AB, Doohan P, Ghani AC, Ferguson NM, Baguelin M, Cori A. Quantifying the effect of delaying the second COVID-19 vaccine dose in England: a mathematical modelling study. Lancet Public Health 2023; 8:e174-e183. [PMID: 36774945 PMCID: PMC9910835 DOI: 10.1016/s2468-2667(22)00337-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 12/09/2022] [Accepted: 12/14/2022] [Indexed: 02/11/2023]
Abstract
BACKGROUND The UK was the first country to start national COVID-19 vaccination programmes, initially administering doses 3 weeks apart. However, early evidence of high vaccine effectiveness after the first dose and the emergence of the SARS-CoV-2 alpha variant prompted the UK to extend the interval between doses to 12 weeks. In this study, we aimed to quantify the effect of delaying the second vaccine dose in England. METHODS We used a previously described model of SARS-CoV-2 transmission, calibrated to COVID-19 surveillance data from England, including hospital admissions, hospital occupancy, seroprevalence data, and population-level PCR testing data, using a Bayesian evidence-synthesis framework. We modelled and compared the epidemic trajectory in the counterfactual scenario in which vaccine doses were administered 3 weeks apart against the real reported vaccine roll-out schedule of 12 weeks. We estimated and compared the resulting numbers of daily infections, hospital admissions, and deaths. In sensitivity analyses, we investigated scenarios spanning a range of vaccine effectiveness and waning assumptions. FINDINGS In the period from Dec 8, 2020, to Sept 13, 2021, the number of individuals who received a first vaccine dose was higher under the 12-week strategy than the 3-week strategy. For this period, we estimated that delaying the interval between the first and second COVID-19 vaccine doses from 3 to 12 weeks averted a median (calculated as the median of the posterior sample) of 58 000 COVID-19 hospital admissions (291 000 cumulative hospitalisations [95% credible interval 275 000-319 000] under the 3-week strategy vs 233 000 [229 000-238 000] under the 12-week strategy) and 10 100 deaths (64 800 deaths [60 200-68 900] vs 54 700 [52 800-55 600]). Similarly, we estimated that the 3-week strategy would have resulted in more infections compared with the 12-week strategy. Across all sensitivity analyses the 3-week strategy resulted in a greater number of hospital admissions. In results by age group, the 12-week strategy led to more hospitalisations and deaths in older people in spring 2021, but fewer following the emergence of the delta variant during summer 2021. INTERPRETATION England's delayed-second-dose vaccination strategy was informed by early real-world data on vaccine effectiveness in the context of limited vaccine supplies in a growing epidemic. Our study shows that rapidly providing partial (single-dose) vaccine-induced protection to a larger proportion of the population was successful in reducing the burden of COVID-19 hospitalisations and deaths overall. FUNDING UK National Institute for Health Research; UK Medical Research Council; Community Jameel; Wellcome Trust; UK Foreign, Commonwealth and Development Office; Australian National Health and Medical Research Council; and EU.
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Affiliation(s)
- Natsuko Imai
- Medical Research Council Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Thomas Rawson
- Medical Research Council Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Edward S Knock
- Medical Research Council Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK; National Institute for Health Research Health Protection Research Unit in Modelling Methodology, Imperial College London, UK Health Security Agency, London School of Hygiene & Tropical Medicine, London, UK
| | - Raphael Sonabend
- Medical Research Council Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK; Department of Computer Science, Technische Universität Kaiserslautern, Kaiserslautern, Germany; Engineering Department, University of Cambridge, Cambridge, UK
| | - Yasin Elmaci
- Medical Research Council Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Pablo N Perez-Guzman
- Medical Research Council Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Lilith K Whittles
- Medical Research Council Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Divya Thekke Kanapram
- Medical Research Council Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Katy A M Gaythorpe
- Medical Research Council Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Wes Hinsley
- Medical Research Council Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Bimandra A Djaafara
- Medical Research Council Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Haowei Wang
- Medical Research Council Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Keith Fraser
- Medical Research Council Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Richard G FitzJohn
- Medical Research Council Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Alexandra B Hogan
- Medical Research Council Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK; School of Population Health, University of New South Wales, Sydney, NSW, Australia
| | - Patrick Doohan
- Medical Research Council Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Azra C Ghani
- Medical Research Council Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Neil M Ferguson
- Medical Research Council Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK; National Institute for Health Research Health Protection Research Unit in Modelling Methodology, Imperial College London, UK Health Security Agency, London School of Hygiene & Tropical Medicine, London, UK
| | - Marc Baguelin
- Medical Research Council Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK; National Institute for Health Research Health Protection Research Unit in Modelling Methodology, Imperial College London, UK Health Security Agency, London School of Hygiene & Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK
| | - Anne Cori
- Medical Research Council Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK; National Institute for Health Research Health Protection Research Unit in Modelling Methodology, Imperial College London, UK Health Security Agency, London School of Hygiene & Tropical Medicine, London, UK.
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Fadilah I, Djaafara BA, Lestari KD, Fajariyani SB, Sunandar E, Makamur BG, Wopari B, Mabui S, Ekawati LL, Sagara R, Lina RN, Argana G, Ginting DE, Sumiwi ME, Laihad FJ, Mueller I, McVernon J, Baird JK, Surendra H, Elyazar IR. Quantifying spatial heterogeneity of malaria in the endemic Papua region of Indonesia: Analysis of epidemiological surveillance data. Lancet Reg Health Southeast Asia 2022; 5:100051. [PMID: 37383667 PMCID: PMC10305992 DOI: 10.1016/j.lansea.2022.100051] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/30/2023]
Abstract
Background As control efforts progress towards elimination, malaria is likely to become more spatially concentrated in few local areas. The purpose of this study was to quantify and characterise spatial heterogeneity in malaria transmission-intensity across highly endemic Indonesian Papua. Methods We analysed individual-level malaria surveillance data for nearly half a million cases (2019-2020) reported in the Papua and West Papua provinces and adapted the Gini index approach to quantify spatial heterogeneity at the district and health-unit levels. In this context, high Gini index implies disproportionately distributed malaria cases across the region. We showed malaria incidence trends and the spatial and temporal distribution of sociodemographic characteristics and aetiological parasites among cases. Findings While Papua province accounted for the majority of malaria cases reported in the region and had seen a rise in transmission since 2015, West Papua province had maintained a comparatively low incidence. We observed that Gini index estimates were high, particularly when the lower spatial scale of health units was evaluated. The Gini index appears to be inversely associated to annual parasite-incidence, as well as the proportions of vivax malaria, male sex, and adults. Interpretation This study suggests that areas with varying levels of transmission-intensities exhibited distinct characteristics. Malaria was distributed in a markedly disproportionate manner throughout the region, emphasising the need for spatially targeted interventions. Periodic quantification and characterisation of risk heterogeneity at various spatial levels using routine malaria surveillance data may aid in tracking progress towards elimination and guiding evidence-informed prioritisation of resource allocation. Funding The study was funded by the Australian Government Department of Foreign Affairs and Trade Indo-Pacific Centre for Health Security through the Strengthening Preparedness in the Asia-Pacific Region through Knowledge (SPARK) project.
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Affiliation(s)
- Ihsan Fadilah
- Oxford University Clinical Research Unit Indonesia, Jakarta, Indonesia
| | - Bimandra A. Djaafara
- Oxford University Clinical Research Unit Indonesia, Jakarta, Indonesia
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Karina D. Lestari
- Oxford University Clinical Research Unit Indonesia, Jakarta, Indonesia
| | - Sri B. Fajariyani
- Sub-Directorate for Malaria Control, Ministry of Health, Jakarta, Indonesia
| | - Edi Sunandar
- West Papua Provincial Health Office, Papua Barat, Indonesia
| | | | - Beeri Wopari
- Papua Provincial Health Office, Papua, Indonesia
| | - Silas Mabui
- Papua Provincial Health Office, Papua, Indonesia
| | - Lenny L. Ekawati
- Oxford University Clinical Research Unit Indonesia, Jakarta, Indonesia
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Rahmat Sagara
- Oxford University Clinical Research Unit Indonesia, Jakarta, Indonesia
| | - Rosa N. Lina
- Oxford University Clinical Research Unit Indonesia, Jakarta, Indonesia
| | - Guntur Argana
- Sub-Directorate for Malaria Control, Ministry of Health, Jakarta, Indonesia
| | | | - Maria E. Sumiwi
- Directorate General of Public Health, Ministry of Health, Jakarta, Indonesia
| | | | - Ivo Mueller
- Division of Population Health and Immunity, Walter and Eliza Hall Institute, Melbourne, Australia
| | - Jodie McVernon
- Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, Australia
| | - J. Kevin Baird
- Oxford University Clinical Research Unit Indonesia, Jakarta, Indonesia
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Henry Surendra
- Oxford University Clinical Research Unit Indonesia, Jakarta, Indonesia
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3
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Whittaker C, Watson OJ, Alvarez-Moreno C, Angkasekwinai N, Boonyasiri A, Carlos Triana L, Chanda D, Charoenpong L, Chayakulkeeree M, Cooke GS, Croda J, Cucunubá ZM, Djaafara BA, Estofolete CF, Grillet ME, Faria NR, Figueiredo Costa S, Forero-Peña DA, Gibb DM, Gordon AC, Hamers RL, Hamlet A, Irawany V, Jitmuang A, Keurueangkul N, Kimani TN, Lampo M, Levin AS, Lopardo G, Mustafa R, Nayagam S, Ngamprasertchai T, Njeri NIH, Nogueira ML, Ortiz-Prado E, Perroud MW, Phillips AN, Promsin P, Qavi A, Rodger AJ, Sabino EC, Sangkaew S, Sari D, Sirijatuphat R, Sposito AC, Srisangthong P, Thompson HA, Udwadia Z, Valderrama-Beltrán S, Winskill P, Ghani AC, Walker PGT, Hallett TB. Understanding the Potential Impact of Different Drug Properties on Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Transmission and Disease Burden: A Modelling Analysis. Clin Infect Dis 2022; 75:e224-e233. [PMID: 34549260 PMCID: PMC9402649 DOI: 10.1093/cid/ciab837] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND The public health impact of the coronavirus disease 2019 (COVID-19) pandemic has motivated a rapid search for potential therapeutics, with some key successes. However, the potential impact of different treatments, and consequently research and procurement priorities, have not been clear. METHODS Using a mathematical model of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission, COVID-19 disease and clinical care, we explore the public-health impact of different potential therapeutics, under a range of scenarios varying healthcare capacity, epidemic trajectories; and drug efficacy in the absence of supportive care. RESULTS The impact of drugs like dexamethasone (delivered to the most critically-ill in hospital and whose therapeutic benefit is expected to depend on the availability of supportive care such as oxygen and mechanical ventilation) is likely to be limited in settings where healthcare capacity is lowest or where uncontrolled epidemics result in hospitals being overwhelmed. As such, it may avert 22% of deaths in high-income countries but only 8% in low-income countries (assuming R = 1.35). Therapeutics for different patient populations (those not in hospital, early in the course of infection) and types of benefit (reducing disease severity or infectiousness, preventing hospitalization) could have much greater benefits, particularly in resource-poor settings facing large epidemics. CONCLUSIONS Advances in the treatment of COVID-19 to date have been focused on hospitalized-patients and predicated on an assumption of adequate access to supportive care. Therapeutics delivered earlier in the course of infection that reduce the need for healthcare or reduce infectiousness could have significant impact, and research into their efficacy and means of delivery should be a priority.
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Affiliation(s)
- Charles Whittaker
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Oliver J Watson
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Carlos Alvarez-Moreno
- Clínica Universitaria Colombia, Clínica Colsanitas, Facultad de Medicina, Universidad Nacional de Colombia, Bogotá, Colombia
| | - Nasikarn Angkasekwinai
- Division of Infectious Diseases and Tropical Medicine, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | | | - Luis Carlos Triana
- Hospital Universitario San Ignacio -Pontificia Universidad Javeriana, Bogotá, Colombia
| | - Duncan Chanda
- Adult Infectious Diseases Centre, University Teaching Hospital, Lusaka, Zambia
- Department of Internal Medicine, University of Zambia School of Medicine, Lusaka, Zambia
| | - Lantharita Charoenpong
- Bamrasnaradura Infectious Diseases Institute, Department of Diseases Control, Ministry of Public Health, Nonthaburi, Thailand
| | - Methee Chayakulkeeree
- Division of Infectious Diseases and Tropical Medicine, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Graham S Cooke
- Department of Infectious Diseases, Imperial College London, London, UK
- NIHR Biomedical Research Centre, Imperial College NHS Trust, London, UK
| | - Julio Croda
- Oswaldo Cruz Foudantion, Mato Grosso do Sul, Campo Grande, Brazil
- School of Medicine, Federal University of Mato Grosso do Sul, Campo Grande, Brazil
- Yale School of Public Health, New Haven, Connecticut, USA
| | - Zulma M Cucunubá
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
- Departamento de Epidemiología Clínica y Bioestadística. Facultad de Medicina, Pontificia Universidad Javeriana, Bogotá, Colombia
| | - Bimandra A Djaafara
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
- Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia
| | - Cassia F Estofolete
- Faculdade de Medicina de São José do Rio Preto (FAMERP), São José do Rio Preto, Brazil
| | - Maria Eugenia Grillet
- Instituto de Zoologia y Ecologia Tropical, Facultad de Ciencias, Universidad Central de Venezuela, Caracas, Venezuela
| | - Nuno R Faria
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
- Departamento de Molestias Infecciosas e Parasitarias and Instituto de Medicina Tropical da Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Department of Zoology, University of Oxford, Oxford, UK
| | - Silvia Figueiredo Costa
- Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - David A Forero-Peña
- Biomedical Research and Therapeutic Vaccines Institute, Ciudad Bolívar, Venezuela
| | - Diana M Gibb
- MRC Clinical Trials Unit at University College London, London, UK
| | - Anthony C Gordon
- Division of Anaesthetics, Pain Medicine and Intensive Care, Imperial College London, London, UK
| | - Raph L Hamers
- Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia
- Centre for Tropical Medicine and Global Health, Nuffield Dept of Medicine, University of Oxford, Oxford, UK
| | - Arran Hamlet
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Vera Irawany
- Fatmawati General Hospital, Faculty of Medicine University of Indonesia, Jakarta, Indonesia
| | - Anupop Jitmuang
- Division of Infectious Diseases and Tropical Medicine, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | | | | | - Margarita Lampo
- Instituto Venezolano de Investigaciones Científicas, Caracas, Venezuela
| | - Anna S Levin
- Department of Infectious Diseases, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | | | - Rima Mustafa
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
| | - Shevanthi Nayagam
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Thundon Ngamprasertchai
- Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
| | | | - Mauricio L Nogueira
- Faculdade de Medicina de São José do Rio Preto (FAMERP), São José do Rio Preto, Brazil
| | - Esteban Ortiz-Prado
- OneHealth Global Research Group, Universidad de las Américas, Quito, Ecuador
| | | | | | - Panuwat Promsin
- Critical Care Division, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Ambar Qavi
- School of Public Health, Imperial College London, London, UK
| | - Alison J Rodger
- Institute for Global Health, University College London, London, UK
| | - Ester C Sabino
- Instituto de Medicina Tropical da Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Sorawat Sangkaew
- Section of Adult Infectious Disease, Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK
| | - Djayanti Sari
- Department of Anesthesiology and Intensive Theraphy, Faculty of Medicine, Public Health and Nursing Universitas Gadjah Mada. Public Hospital Dr. Sardjito, Yogyakarta, Indonesia
| | - Rujipas Sirijatuphat
- Division of Infectious Diseases and Tropical Medicine, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Andrei C Sposito
- Atherosclerosis and Vascular Biology Laboratory, State University of Campinas, Campinas, Brazil
| | | | - Hayley A Thompson
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | | | - Sandra Valderrama-Beltrán
- Division of Infectious Diseases. School of Medicine. Pontificia Universidad Javeriana, Hospital Universitario San Ignacio, Bogotá, Colombia
| | - Peter Winskill
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Azra C Ghani
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Patrick G T Walker
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Timothy B Hallett
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
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Surendra H, Salama N, Lestari KD, Adrian V, Widyastuti W, Oktavia D, Lina RN, Djaafara BA, Fadilah I, Sagara R, Ekawati LL, Nurhasim A, Ahmad RA, Kekalih A, Syam AF, Shankar AH, Thwaites G, Baird JK, Hamers RL, Elyazar IRF. Pandemic inequity in a megacity: a multilevel analysis of individual, community and healthcare vulnerability risks for COVID-19 mortality in Jakarta, Indonesia. BMJ Glob Health 2022; 7:e008329. [PMID: 35728836 PMCID: PMC9213779 DOI: 10.1136/bmjgh-2021-008329] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2021] [Accepted: 05/29/2022] [Indexed: 01/20/2023] Open
Abstract
INTRODUCTION Worldwide, the 33 recognised megacities comprise approximately 7% of the global population, yet account for 20% COVID-19 deaths. The specific inequities and other factors within megacities that affect vulnerability to COVID-19 mortality remain poorly defined. We assessed individual, community-level and healthcare factors associated with COVID-19-related mortality in a megacity of Jakarta, Indonesia, during two epidemic waves spanning 2 March 2020 to 31 August 2021. METHODS This retrospective cohort included residents of Jakarta, Indonesia, with PCR-confirmed COVID-19. We extracted demographic, clinical, outcome (recovered or died), vaccine coverage data and disease prevalence from Jakarta Health Office surveillance records, and collected subdistrict level sociodemographics data from various official sources. We used multilevel logistic regression to examine individual, community and subdistrict-level healthcare factors and their associations with COVID-19 mortality. RESULTS Of 705 503 cases with a definitive outcome by 31 August 2021, 694 706 (98.5%) recovered and 10 797 (1.5%) died. The median age was 36 years (IQR 24-50), 13.2% (93 459) were <18 years and 51.6% were female. The subdistrict level accounted for 1.5% of variance in mortality (p<0.0001). Mortality ranged from 0.9 to 1.8% by subdistrict. Individual-level factors associated with death were older age, male sex, comorbidities and age <5 years during the first wave (adjusted OR (aOR)) 1.56, 95% CI 1.04 to 2.35; reference: age 20-29 years). Community-level factors associated with death were poverty (aOR for the poorer quarter 1.35, 95% CI 1.17 to 1.55; reference: wealthiest quarter) and high population density (aOR for the highest density 1.34, 95% CI 1.14 to 2.58; reference: the lowest). Healthcare factor associated with death was low vaccine coverage (aOR for the lowest coverage 1.25, 95% CI 1.13 to 1.38; reference: the highest). CONCLUSION In addition to individual risk factors, living in areas with high poverty and density, and low healthcare performance further increase the vulnerability of communities to COVID-19-associated death in urban low-resource settings.
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Affiliation(s)
- Henry Surendra
- Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia
- Centre for Tropical Medicine, Faculty of Medicine, Public Health and Nursing, Gadjah Mada University, Yogyakarta, Indonesia
| | | | | | | | | | - Dwi Oktavia
- DKI Jakarta Health Office, Jakarta, Indonesia
| | - Rosa N Lina
- Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia
| | - Bimandra A Djaafara
- Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia
- Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Ihsan Fadilah
- Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia
| | - Rahmat Sagara
- Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia
| | - Lenny L Ekawati
- Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | | | - Riris A Ahmad
- Centre for Tropical Medicine, Faculty of Medicine, Public Health and Nursing, Gadjah Mada University, Yogyakarta, Indonesia
| | - Aria Kekalih
- Faculty of Medicine, University of Indonesia, Jakarta, Indonesia
| | - Ari F Syam
- Faculty of Medicine, University of Indonesia, Jakarta, Indonesia
| | - Anuraj H Shankar
- Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Guy Thwaites
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam
| | - J Kevin Baird
- Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Raph L Hamers
- Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
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Sonabend R, Whittles LK, Imai N, Perez-Guzman PN, Knock ES, Rawson T, Gaythorpe KAM, Djaafara BA, Hinsley W, FitzJohn RG, Lees JA, Kanapram DT, Volz EM, Ghani AC, Ferguson NM, Baguelin M, Cori A. Non-pharmaceutical interventions, vaccination, and the SARS-CoV-2 delta variant in England: a mathematical modelling study. Lancet 2021; 398:1825-1835. [PMID: 34717829 PMCID: PMC8550916 DOI: 10.1016/s0140-6736(21)02276-5] [Citation(s) in RCA: 85] [Impact Index Per Article: 28.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 09/28/2021] [Accepted: 10/07/2021] [Indexed: 01/01/2023]
Abstract
BACKGROUND England's COVID-19 roadmap out of lockdown policy set out the timeline and conditions for the stepwise lifting of non-pharmaceutical interventions (NPIs) as vaccination roll-out continued, with step one starting on March 8, 2021. In this study, we assess the roadmap, the impact of the delta (B.1.617.2) variant of SARS-CoV-2, and potential future epidemic trajectories. METHODS This mathematical modelling study was done to assess the UK Government's four-step process to easing lockdown restrictions in England, UK. We extended a previously described model of SARS-CoV-2 transmission to incorporate vaccination and multi-strain dynamics to explicitly capture the emergence of the delta variant. We calibrated the model to English surveillance data, including hospital admissions, hospital occupancy, seroprevalence data, and population-level PCR testing data using a Bayesian evidence synthesis framework, then modelled the potential trajectory of the epidemic for a range of different schedules for relaxing NPIs. We estimated the resulting number of daily infections and hospital admissions, and daily and cumulative deaths. Three scenarios spanning a range of optimistic to pessimistic vaccine effectiveness, waning natural immunity, and cross-protection from previous infections were investigated. We also considered three levels of mixing after the lifting of restrictions. FINDINGS The roadmap policy was successful in offsetting the increased transmission resulting from lifting NPIs starting on March 8, 2021, with increasing population immunity through vaccination. However, because of the emergence of the delta variant, with an estimated transmission advantage of 76% (95% credible interval [95% CrI] 69-83) over alpha, fully lifting NPIs on June 21, 2021, as originally planned might have led to 3900 (95% CrI 1500-5700) peak daily hospital admissions under our central parameter scenario. Delaying until July 19, 2021, reduced peak hospital admissions by three fold to 1400 (95% CrI 700-1700) per day. There was substantial uncertainty in the epidemic trajectory, with particular sensitivity to the transmissibility of delta, level of mixing, and estimates of vaccine effectiveness. INTERPRETATION Our findings show that the risk of a large wave of COVID-19 hospital admissions resulting from lifting NPIs can be substantially mitigated if the timing of NPI relaxation is carefully balanced against vaccination coverage. However, with the delta variant, it might not be possible to fully lift NPIs without a third wave of hospital admissions and deaths, even if vaccination coverage is high. Variants of concern, their transmissibility, vaccine uptake, and vaccine effectiveness must be carefully monitored as countries relax pandemic control measures. FUNDING National Institute for Health Research, UK Medical Research Council, Wellcome Trust, and UK Foreign, Commonwealth and Development Office.
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Affiliation(s)
- Raphael Sonabend
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Lilith K Whittles
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK; National Institute for Health Research Health Protection Research Unit in Modelling Methodology, Imperial College London, Public Health England, London School of Hygiene & Tropical Medicine, London, UK; Modelling and Economics Unit, National Infection Service, Public Health England, London, UK
| | - Natsuko Imai
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Pablo N Perez-Guzman
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Edward S Knock
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK; National Institute for Health Research Health Protection Research Unit in Modelling Methodology, Imperial College London, Public Health England, London School of Hygiene & Tropical Medicine, London, UK
| | - Thomas Rawson
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Katy A M Gaythorpe
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Bimandra A Djaafara
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Wes Hinsley
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Richard G FitzJohn
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - John A Lees
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Divya Thekke Kanapram
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Erik M Volz
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Azra C Ghani
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Neil M Ferguson
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK; National Institute for Health Research Health Protection Research Unit in Modelling Methodology, Imperial College London, Public Health England, London School of Hygiene & Tropical Medicine, London, UK.
| | - Marc Baguelin
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK; National Institute for Health Research Health Protection Research Unit in Modelling Methodology, Imperial College London, Public Health England, London School of Hygiene & Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK
| | - Anne Cori
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK; National Institute for Health Research Health Protection Research Unit in Modelling Methodology, Imperial College London, Public Health England, London School of Hygiene & Tropical Medicine, London, UK.
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6
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Whittaker C, Walker PGT, Alhaffar M, Hamlet A, Djaafara BA, Ghani A, Ferguson N, Dahab M, Checchi F, Watson OJ. Under-reporting of deaths limits our understanding of true burden of covid-19. BMJ 2021; 375:n2239. [PMID: 34642172 DOI: 10.1136/bmj.n2239] [Citation(s) in RCA: 45] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Affiliation(s)
- Charles Whittaker
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College London, London, UK
| | | | - Mervat Alhaffar
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK
- Syria Research Group (SyRG), co-hosted by the London School of Hygiene and Tropical Medicine, London, UK; and Saw Swee Hock School of Public Health, Singapore
| | - Arran Hamlet
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College London, London, UK
| | - Bimandra A Djaafara
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College London, London, UK
- Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia
| | - Azra Ghani
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College London, London, UK
| | - Neil Ferguson
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College London, London, UK
| | - Maysoon Dahab
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK
| | - Francesco Checchi
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK
| | - Oliver J Watson
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College London, London, UK
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7
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Knock ES, Whittles LK, Lees JA, Perez-Guzman PN, Verity R, FitzJohn RG, Gaythorpe KAM, Imai N, Hinsley W, Okell LC, Rosello A, Kantas N, Walters CE, Bhatia S, Watson OJ, Whittaker C, Cattarino L, Boonyasiri A, Djaafara BA, Fraser K, Fu H, Wang H, Xi X, Donnelly CA, Jauneikaite E, Laydon DJ, White PJ, Ghani AC, Ferguson NM, Cori A, Baguelin M. Key epidemiological drivers and impact of interventions in the 2020 SARS-CoV-2 epidemic in England. Sci Transl Med 2021. [PMID: 34158411 DOI: 10.25561/85146] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/21/2023]
Abstract
We fitted a model of SARS-CoV-2 transmission in care homes and the community to regional surveillance data for England. Compared with other approaches, our model provides a synthesis of multiple surveillance data streams into a single coherent modeling framework, allowing transmission and severity to be disentangled from features of the surveillance system. Of the control measures implemented, only national lockdown brought the reproduction number (Rt eff) below 1 consistently; if introduced 1 week earlier, it could have reduced deaths in the first wave from an estimated 48,600 to 25,600 [95% credible interval (CrI): 15,900 to 38,400]. The infection fatality ratio decreased from 1.00% (95% CrI: 0.85 to 1.21%) to 0.79% (95% CrI: 0.63 to 0.99%), suggesting improved clinical care. The infection fatality ratio was higher in the elderly residing in care homes (23.3%, 95% CrI: 14.7 to 35.2%) than those residing in the community (7.9%, 95% CrI: 5.9 to 10.3%). On 2 December 2020, England was still far from herd immunity, with regional cumulative infection incidence between 7.6% (95% CrI: 5.4 to 10.2%) and 22.3% (95% CrI: 19.4 to 25.4%) of the population. Therefore, any vaccination campaign will need to achieve high coverage and a high degree of protection in vaccinated individuals to allow nonpharmaceutical interventions to be lifted without a resurgence of transmission.
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Affiliation(s)
- Edward S Knock
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
- National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Modelling and Health Economics, London, UK
| | - Lilith K Whittles
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
- National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Modelling and Health Economics, London, UK
- Modelling and Economics Unit, National Infection Service, Public Health England, London NW9 5EQ, UK
| | - John A Lees
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Pablo N Perez-Guzman
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Robert Verity
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Richard G FitzJohn
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Katy A M Gaythorpe
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Natsuko Imai
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Wes Hinsley
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Lucy C Okell
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Alicia Rosello
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK
| | - Nikolas Kantas
- Faculty of Natural Sciences, Department of Mathematics, Imperial College London, London SW7 2BX, UK
| | - Caroline E Walters
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Sangeeta Bhatia
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Oliver J Watson
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Charlie Whittaker
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Lorenzo Cattarino
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Adhiratha Boonyasiri
- Department of Infectious Disease, School of Public Health, Imperial College London, London W2 1PG, UK
| | - Bimandra A Djaafara
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Keith Fraser
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Han Fu
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Haowei Wang
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Xiaoyue Xi
- Faculty of Natural Sciences, Department of Mathematics, Imperial College London, London SW7 2BX, UK
| | - Christl A Donnelly
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
- Department of Statistics, University of Oxford, Oxford OX1 3LB, UK
- NIHR HPRU in Emerging and Zoonotic Infections, Liverpool, UK
| | - Elita Jauneikaite
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Daniel J Laydon
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Peter J White
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
- National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Modelling and Health Economics, London, UK
- Modelling and Economics Unit, National Infection Service, Public Health England, London NW9 5EQ, UK
| | - Azra C Ghani
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Neil M Ferguson
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK.
- National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Modelling and Health Economics, London, UK
| | - Anne Cori
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
- National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Modelling and Health Economics, London, UK
| | - Marc Baguelin
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK.
- National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Modelling and Health Economics, London, UK
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK
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8
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Knock ES, Whittles LK, Lees JA, Perez-Guzman PN, Verity R, FitzJohn RG, Gaythorpe KAM, Imai N, Hinsley W, Okell LC, Rosello A, Kantas N, Walters CE, Bhatia S, Watson OJ, Whittaker C, Cattarino L, Boonyasiri A, Djaafara BA, Fraser K, Fu H, Wang H, Xi X, Donnelly CA, Jauneikaite E, Laydon DJ, White PJ, Ghani AC, Ferguson NM, Cori A, Baguelin M. Key epidemiological drivers and impact of interventions in the 2020 SARS-CoV-2 epidemic in England. Sci Transl Med 2021; 13:eabg4262. [PMID: 34158411 PMCID: PMC8432953 DOI: 10.1126/scitranslmed.abg4262] [Citation(s) in RCA: 55] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Revised: 04/14/2021] [Accepted: 06/16/2021] [Indexed: 01/06/2023]
Abstract
We fitted a model of SARS-CoV-2 transmission in care homes and the community to regional surveillance data for England. Compared with other approaches, our model provides a synthesis of multiple surveillance data streams into a single coherent modeling framework, allowing transmission and severity to be disentangled from features of the surveillance system. Of the control measures implemented, only national lockdown brought the reproduction number (Rt eff) below 1 consistently; if introduced 1 week earlier, it could have reduced deaths in the first wave from an estimated 48,600 to 25,600 [95% credible interval (CrI): 15,900 to 38,400]. The infection fatality ratio decreased from 1.00% (95% CrI: 0.85 to 1.21%) to 0.79% (95% CrI: 0.63 to 0.99%), suggesting improved clinical care. The infection fatality ratio was higher in the elderly residing in care homes (23.3%, 95% CrI: 14.7 to 35.2%) than those residing in the community (7.9%, 95% CrI: 5.9 to 10.3%). On 2 December 2020, England was still far from herd immunity, with regional cumulative infection incidence between 7.6% (95% CrI: 5.4 to 10.2%) and 22.3% (95% CrI: 19.4 to 25.4%) of the population. Therefore, any vaccination campaign will need to achieve high coverage and a high degree of protection in vaccinated individuals to allow nonpharmaceutical interventions to be lifted without a resurgence of transmission.
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Affiliation(s)
- Edward S Knock
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
- National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Modelling and Health Economics, London, UK
| | - Lilith K Whittles
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
- National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Modelling and Health Economics, London, UK
- Modelling and Economics Unit, National Infection Service, Public Health England, London NW9 5EQ, UK
| | - John A Lees
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Pablo N Perez-Guzman
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Robert Verity
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Richard G FitzJohn
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Katy A M Gaythorpe
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Natsuko Imai
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Wes Hinsley
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Lucy C Okell
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Alicia Rosello
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK
| | - Nikolas Kantas
- Faculty of Natural Sciences, Department of Mathematics, Imperial College London, London SW7 2BX, UK
| | - Caroline E Walters
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Sangeeta Bhatia
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Oliver J Watson
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Charlie Whittaker
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Lorenzo Cattarino
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Adhiratha Boonyasiri
- Department of Infectious Disease, School of Public Health, Imperial College London, London W2 1PG, UK
| | - Bimandra A Djaafara
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Keith Fraser
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Han Fu
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Haowei Wang
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Xiaoyue Xi
- Faculty of Natural Sciences, Department of Mathematics, Imperial College London, London SW7 2BX, UK
| | - Christl A Donnelly
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
- Department of Statistics, University of Oxford, Oxford OX1 3LB, UK
- NIHR HPRU in Emerging and Zoonotic Infections, Liverpool, UK
| | - Elita Jauneikaite
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Daniel J Laydon
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Peter J White
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
- National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Modelling and Health Economics, London, UK
- Modelling and Economics Unit, National Infection Service, Public Health England, London NW9 5EQ, UK
| | - Azra C Ghani
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
| | - Neil M Ferguson
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK.
- National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Modelling and Health Economics, London, UK
| | - Anne Cori
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK
- National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Modelling and Health Economics, London, UK
| | - Marc Baguelin
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London W2 1PG, UK.
- National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Modelling and Health Economics, London, UK
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK
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9
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Djaafara BA, Whittaker C, Watson OJ, Verity R, Brazeau NF, Widyastuti, Oktavia D, Adrian V, Salama N, Bhatia S, Nouvellet P, Sherrard-Smith E, Churcher TS, Surendra H, Lina RN, Ekawati LL, Lestari KD, Andrianto A, Thwaites G, Baird JK, Ghani AC, Elyazar IRF, Walker PGT. Using syndromic measures of mortality to capture the dynamics of COVID-19 in Java, Indonesia, in the context of vaccination rollout. BMC Med 2021; 19:146. [PMID: 34144715 PMCID: PMC8212796 DOI: 10.1186/s12916-021-02016-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Accepted: 05/26/2021] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND As in many countries, quantifying COVID-19 spread in Indonesia remains challenging due to testing limitations. In Java, non-pharmaceutical interventions (NPIs) were implemented throughout 2020. However, as a vaccination campaign launches, cases and deaths are rising across the island. METHODS We used modelling to explore the extent to which data on burials in Jakarta using strict COVID-19 protocols (C19P) provide additional insight into the transmissibility of the disease, epidemic trajectory, and the impact of NPIs. We assess how implementation of NPIs in early 2021 will shape the epidemic during the period of likely vaccine rollout. RESULTS C19P burial data in Jakarta suggest a death toll approximately 3.3 times higher than reported. Transmission estimates using these data suggest earlier, larger, and more sustained impact of NPIs. Measures to reduce sub-national spread, particularly during Ramadan, substantially mitigated spread to more vulnerable rural areas. Given current trajectory, daily cases and deaths are likely to increase in most regions as the vaccine is rolled out. Transmission may peak in early 2021 in Jakarta if current levels of control are maintained. However, relaxation of control measures is likely to lead to a subsequent resurgence in the absence of an effective vaccination campaign. CONCLUSIONS Syndromic measures of mortality provide a more complete picture of COVID-19 severity upon which to base decision-making. The high potential impact of the vaccine in Java is attributable to reductions in transmission to date and dependent on these being maintained. Increases in control in the relatively short-term will likely yield large, synergistic increases in vaccine impact.
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Affiliation(s)
- Bimandra A Djaafara
- MRC Centre for Global Infectious Disease Analysis and the Abdul Latif Jameel Institute for Disease and Emergency Analytics, School of Public Health, Imperial College London St Mary's Campus, Norfolk Place, London, W2 1PG, UK.
- Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia.
| | - Charles Whittaker
- MRC Centre for Global Infectious Disease Analysis and the Abdul Latif Jameel Institute for Disease and Emergency Analytics, School of Public Health, Imperial College London St Mary's Campus, Norfolk Place, London, W2 1PG, UK
| | - Oliver J Watson
- MRC Centre for Global Infectious Disease Analysis and the Abdul Latif Jameel Institute for Disease and Emergency Analytics, School of Public Health, Imperial College London St Mary's Campus, Norfolk Place, London, W2 1PG, UK
| | - Robert Verity
- MRC Centre for Global Infectious Disease Analysis and the Abdul Latif Jameel Institute for Disease and Emergency Analytics, School of Public Health, Imperial College London St Mary's Campus, Norfolk Place, London, W2 1PG, UK
| | - Nicholas F Brazeau
- MRC Centre for Global Infectious Disease Analysis and the Abdul Latif Jameel Institute for Disease and Emergency Analytics, School of Public Health, Imperial College London St Mary's Campus, Norfolk Place, London, W2 1PG, UK
| | - Widyastuti
- Jakarta Provincial Department of Health, Jakarta, Indonesia
| | - Dwi Oktavia
- Jakarta Provincial Department of Health, Jakarta, Indonesia
| | - Verry Adrian
- Jakarta Provincial Department of Health, Jakarta, Indonesia
| | - Ngabila Salama
- Jakarta Provincial Department of Health, Jakarta, Indonesia
| | - Sangeeta Bhatia
- MRC Centre for Global Infectious Disease Analysis and the Abdul Latif Jameel Institute for Disease and Emergency Analytics, School of Public Health, Imperial College London St Mary's Campus, Norfolk Place, London, W2 1PG, UK
| | - Pierre Nouvellet
- MRC Centre for Global Infectious Disease Analysis and the Abdul Latif Jameel Institute for Disease and Emergency Analytics, School of Public Health, Imperial College London St Mary's Campus, Norfolk Place, London, W2 1PG, UK
- School of Life Sciences, University of Sussex, Brighton, UK
| | - Ellie Sherrard-Smith
- MRC Centre for Global Infectious Disease Analysis and the Abdul Latif Jameel Institute for Disease and Emergency Analytics, School of Public Health, Imperial College London St Mary's Campus, Norfolk Place, London, W2 1PG, UK
| | - Thomas S Churcher
- MRC Centre for Global Infectious Disease Analysis and the Abdul Latif Jameel Institute for Disease and Emergency Analytics, School of Public Health, Imperial College London St Mary's Campus, Norfolk Place, London, W2 1PG, UK
| | - Henry Surendra
- Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia
- Centre for Tropical Medicine, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia
| | - Rosa N Lina
- Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia
| | | | | | - Adhi Andrianto
- Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia
| | - Guy Thwaites
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - J Kevin Baird
- Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Azra C Ghani
- MRC Centre for Global Infectious Disease Analysis and the Abdul Latif Jameel Institute for Disease and Emergency Analytics, School of Public Health, Imperial College London St Mary's Campus, Norfolk Place, London, W2 1PG, UK
| | | | - Patrick G T Walker
- MRC Centre for Global Infectious Disease Analysis and the Abdul Latif Jameel Institute for Disease and Emergency Analytics, School of Public Health, Imperial College London St Mary's Campus, Norfolk Place, London, W2 1PG, UK
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10
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Djaafara BA, Imai N, Hamblion E, Impouma B, Donnelly CA, Cori A. A Quantitative Framework for Defining the End of an Infectious Disease Outbreak: Application to Ebola Virus Disease. Am J Epidemiol 2021; 190:642-651. [PMID: 33511390 PMCID: PMC8024054 DOI: 10.1093/aje/kwaa212] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Revised: 09/17/2020] [Accepted: 10/02/2020] [Indexed: 11/30/2022] Open
Abstract
The end-of-outbreak declaration is an important step in controlling infectious disease outbreaks. Objective estimation of the confidence level that an outbreak is over is important to reduce the risk of postdeclaration flare-ups. We developed a simulation-based model with which to quantify that confidence and tested it on simulated Ebola virus disease data. We found that these confidence estimates were most sensitive to the instantaneous reproduction number, the reporting rate, and the time between the symptom onset and death or recovery of the last detected case. For Ebola virus disease, our results suggested that the current World Health Organization criterion of 42 days since the recovery or death of the last detected case is too short and too sensitive to underreporting. Therefore, we suggest a shift to a preliminary end-of-outbreak declaration after 63 days from the symptom onset day of the last detected case. This preliminary declaration should still be followed by 90 days of enhanced surveillance to capture potential flare-ups of cases, after which the official end of the outbreak can be declared. This sequence corresponds to more than 95% confidence that an outbreak is over in most of the scenarios examined. Our framework is generic and therefore could be adapted to estimate end-of-outbreak confidence for other infectious diseases.
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Affiliation(s)
- Bimandra A Djaafara
- Correspondence to Bimandra A. Djaafara, MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, Medical School Building, Norfolk Place, London W2 1PG, United Kingdom (e-mail: )
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11
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Surendra H, Elyazar IR, Djaafara BA, Ekawati LL, Saraswati K, Adrian V, Widyastuti, Oktavia D, Salama N, Lina RN, Andrianto A, Lestari KD, Burhan E, Shankar AH, Thwaites G, Baird JK, Hamers RL. Clinical characteristics and mortality associated with COVID-19 in Jakarta, Indonesia: A hospital-based retrospective cohort study. Lancet Reg Health West Pac 2021; 9:100108. [PMID: 33681830 PMCID: PMC7924904 DOI: 10.1016/j.lanwpc.2021.100108] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 01/27/2021] [Accepted: 02/01/2021] [Indexed: 01/08/2023]
Abstract
Background Data on COVID-19-related mortality and associated factors from low-resource settings are scarce. This study examined clinical characteristics and factors associated with in-hospital mortality of COVID-19 patients in Jakarta, Indonesia, from March 2 to July 31, 2020. Methods This retrospective cohort included all hospitalised patients with PCR-confirmed COVID-19 in 55 hospitals. We extracted demographic and clinical data, including hospital outcomes (discharge or death). We used logistic regression to examine factors associated with mortality. Findings Of 4265 patients with a definitive outcome by July 31, 3768 (88%) were discharged and 497 (12%) died. The median age was 46 years (IQR 32-57), 5% were children, and 31% had >1 comorbidity. Age-specific mortalities were 11% (7/61) for <5 years; 4% (1/23) for 5-9; 2% (3/133) for 10-19; 2% (8/638) for 20-29; 3% (26/755) for 30-39; 7% (61/819) for 40-49; 17% (155/941) for 50-59; 22% (132/611) for 60-69; and 34% (96/284) for ≥70. Risk of death was associated with higher age, male sex; pre-existing hypertension, diabetes, or chronic kidney disease; clinical diagnosis of pneumonia; multiple (>3) symptoms; immediate ICU admission, or intubation. Across all ages, risk of death was higher for patients with >1 comorbidity compared to those without; notably the risk was six-fold increased among patients <50 years (adjusted odds ratio 5.87, 95%CI 3.28-10.52; 27% vs 3% mortality). Interpretation Overall in-hospital mortality was lower than reported in high-income countries, probably due to younger age distribution and fewer comorbidities. Deaths occurred across all ages, with >10% mortality among children <5 years and adults >50 years.
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Affiliation(s)
- Henry Surendra
- Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia.,Centre for Tropical Medicine, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia.,Akademi Ilmuwan Muda Indonesia, Jakarta, Indonesia
| | - Iqbal Rf Elyazar
- Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia.,Akademi Ilmuwan Muda Indonesia, Jakarta, Indonesia
| | - Bimandra A Djaafara
- Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia.,MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Lenny L Ekawati
- Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia.,Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Kartika Saraswati
- Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia.,Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Verry Adrian
- Jakarta Provincial Health Office, Jakarta, Indonesia
| | - Widyastuti
- Jakarta Provincial Health Office, Jakarta, Indonesia
| | - Dwi Oktavia
- Jakarta Provincial Health Office, Jakarta, Indonesia
| | | | - Rosa N Lina
- Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia
| | - Adhi Andrianto
- Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia
| | | | - Erlina Burhan
- Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia
| | - Anuraj H Shankar
- Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia.,Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Guy Thwaites
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.,Oxford University Clinical Research Unit, Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam
| | - J Kevin Baird
- Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia.,Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Raph L Hamers
- Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia.,Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.,Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia
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12
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Nouvellet P, Bhatia S, Cori A, Ainslie KEC, Baguelin M, Bhatt S, Boonyasiri A, Brazeau NF, Cattarino L, Cooper LV, Coupland H, Cucunuba ZM, Cuomo-Dannenburg G, Dighe A, Djaafara BA, Dorigatti I, Eales OD, van Elsland SL, Nascimento FF, FitzJohn RG, Gaythorpe KAM, Geidelberg L, Green WD, Hamlet A, Hauck K, Hinsley W, Imai N, Jeffrey B, Knock E, Laydon DJ, Lees JA, Mangal T, Mellan TA, Nedjati-Gilani G, Parag KV, Pons-Salort M, Ragonnet-Cronin M, Riley S, Unwin HJT, Verity R, Vollmer MAC, Volz E, Walker PGT, Walters CE, Wang H, Watson OJ, Whittaker C, Whittles LK, Xi X, Ferguson NM, Donnelly CA. Reduction in mobility and COVID-19 transmission. Nat Commun 2021; 12:1090. [PMID: 33597546 PMCID: PMC7889876 DOI: 10.1038/s41467-021-21358-2] [Citation(s) in RCA: 252] [Impact Index Per Article: 84.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Accepted: 01/13/2021] [Indexed: 01/02/2023] Open
Abstract
In response to the COVID-19 pandemic, countries have sought to control SARS-CoV-2 transmission by restricting population movement through social distancing interventions, thus reducing the number of contacts. Mobility data represent an important proxy measure of social distancing, and here, we characterise the relationship between transmission and mobility for 52 countries around the world. Transmission significantly decreased with the initial reduction in mobility in 73% of the countries analysed, but we found evidence of decoupling of transmission and mobility following the relaxation of strict control measures for 80% of countries. For the majority of countries, mobility explained a substantial proportion of the variation in transmissibility (median adjusted R-squared: 48%, interquartile range - IQR - across countries [27-77%]). Where a change in the relationship occurred, predictive ability decreased after the relaxation; from a median adjusted R-squared of 74% (IQR across countries [49-91%]) pre-relaxation, to a median adjusted R-squared of 30% (IQR across countries [12-48%]) post-relaxation. In countries with a clear relationship between mobility and transmission both before and after strict control measures were relaxed, mobility was associated with lower transmission rates after control measures were relaxed indicating that the beneficial effects of ongoing social distancing behaviours were substantial.
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Affiliation(s)
- Pierre Nouvellet
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK.
- School of Life Sciences, University of Sussex, Brighton, UK.
| | - Sangeeta Bhatia
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Anne Cori
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Kylie E C Ainslie
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Marc Baguelin
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Samir Bhatt
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Adhiratha Boonyasiri
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Nicholas F Brazeau
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Lorenzo Cattarino
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Laura V Cooper
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Helen Coupland
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Zulma M Cucunuba
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Gina Cuomo-Dannenburg
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Amy Dighe
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Bimandra A Djaafara
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Ilaria Dorigatti
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Oliver D Eales
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Sabine L van Elsland
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Fabricia F Nascimento
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Richard G FitzJohn
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Katy A M Gaythorpe
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Lily Geidelberg
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - William D Green
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Arran Hamlet
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Katharina Hauck
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Wes Hinsley
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Natsuko Imai
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Benjamin Jeffrey
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Edward Knock
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Daniel J Laydon
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - John A Lees
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Tara Mangal
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Thomas A Mellan
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Gemma Nedjati-Gilani
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Kris V Parag
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Margarita Pons-Salort
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Manon Ragonnet-Cronin
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Steven Riley
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - H Juliette T Unwin
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Robert Verity
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Michaela A C Vollmer
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Erik Volz
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Patrick G T Walker
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Caroline E Walters
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Haowei Wang
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Oliver J Watson
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Charles Whittaker
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Lilith K Whittles
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Xiaoyue Xi
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Neil M Ferguson
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK
| | - Christl A Donnelly
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, London, UK.
- Department of Statistics, University of Oxford, Oxford, UK.
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13
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Hogan AB, Jewell BL, Sherrard-Smith E, Vesga JF, Watson OJ, Whittaker C, Hamlet A, Smith JA, Winskill P, Verity R, Baguelin M, Lees JA, Whittles LK, Ainslie KEC, Bhatt S, Boonyasiri A, Brazeau NF, Cattarino L, Cooper LV, Coupland H, Cuomo-Dannenburg G, Dighe A, Djaafara BA, Donnelly CA, Eaton JW, van Elsland SL, FitzJohn RG, Fu H, Gaythorpe KAM, Green W, Haw DJ, Hayes S, Hinsley W, Imai N, Laydon DJ, Mangal TD, Mellan TA, Mishra S, Nedjati-Gilani G, Parag KV, Thompson HA, Unwin HJT, Vollmer MAC, Walters CE, Wang H, Wang Y, Xi X, Ferguson NM, Okell LC, Churcher TS, Arinaminpathy N, Ghani AC, Walker PGT, Hallett TB. Potential impact of the COVID-19 pandemic on HIV, tuberculosis, and malaria in low-income and middle-income countries: a modelling study. Lancet Glob Health 2020; 8:e1132-e1141. [PMID: 32673577 PMCID: PMC7357988 DOI: 10.1016/s2214-109x(20)30288-6] [Citation(s) in RCA: 453] [Impact Index Per Article: 113.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Revised: 06/16/2020] [Accepted: 06/18/2020] [Indexed: 01/05/2023]
Abstract
BACKGROUND COVID-19 has the potential to cause substantial disruptions to health services, due to cases overburdening the health system or response measures limiting usual programmatic activities. We aimed to quantify the extent to which disruptions to services for HIV, tuberculosis, and malaria in low-income and middle-income countries with high burdens of these diseases could lead to additional loss of life over the next 5 years. METHODS Assuming a basic reproduction number of 3·0, we constructed four scenarios for possible responses to the COVID-19 pandemic: no action, mitigation for 6 months, suppression for 2 months, or suppression for 1 year. We used established transmission models of HIV, tuberculosis, and malaria to estimate the additional impact on health that could be caused in selected settings, either due to COVID-19 interventions limiting activities, or due to the high demand on the health system due to the COVID-19 pandemic. FINDINGS In high-burden settings, deaths due to HIV, tuberculosis, and malaria over 5 years could increase by up to 10%, 20%, and 36%, respectively, compared with if there was no COVID-19 pandemic. The greatest impact on HIV was estimated to be from interruption to antiretroviral therapy, which could occur during a period of high health system demand. For tuberculosis, the greatest impact would be from reductions in timely diagnosis and treatment of new cases, which could result from any prolonged period of COVID-19 suppression interventions. The greatest impact on malaria burden could be as a result of interruption of planned net campaigns. These disruptions could lead to a loss of life-years over 5 years that is of the same order of magnitude as the direct impact from COVID-19 in places with a high burden of malaria and large HIV and tuberculosis epidemics. INTERPRETATION Maintaining the most critical prevention activities and health-care services for HIV, tuberculosis, and malaria could substantially reduce the overall impact of the COVID-19 pandemic. FUNDING Bill & Melinda Gates Foundation, Wellcome Trust, UK Department for International Development, and Medical Research Council.
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Affiliation(s)
- Alexandra B Hogan
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Britta L Jewell
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Ellie Sherrard-Smith
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Juan F Vesga
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Oliver J Watson
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Charles Whittaker
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Arran Hamlet
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Jennifer A Smith
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Peter Winskill
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Robert Verity
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Marc Baguelin
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - John A Lees
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Lilith K Whittles
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Kylie E C Ainslie
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Samir Bhatt
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Adhiratha Boonyasiri
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Nicholas F Brazeau
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Lorenzo Cattarino
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Laura V Cooper
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Helen Coupland
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Gina Cuomo-Dannenburg
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Amy Dighe
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Bimandra A Djaafara
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Christl A Donnelly
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK; Department of Statistics, University of Oxford, Oxford, UK
| | - Jeff W Eaton
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Sabine L van Elsland
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Richard G FitzJohn
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Han Fu
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Katy A M Gaythorpe
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - William Green
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - David J Haw
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Sarah Hayes
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Wes Hinsley
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Natsuko Imai
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Daniel J Laydon
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Tara D Mangal
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Thomas A Mellan
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Swapnil Mishra
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Gemma Nedjati-Gilani
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Kris V Parag
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Hayley A Thompson
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - H Juliette T Unwin
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Michaela A C Vollmer
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Caroline E Walters
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Haowei Wang
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Yuanrong Wang
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Xiaoyue Xi
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Neil M Ferguson
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Lucy C Okell
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Thomas S Churcher
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Nimalan Arinaminpathy
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Azra C Ghani
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Patrick G T Walker
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Timothy B Hallett
- Medical Research Council Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK.
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