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Kura K, Milton P, Hamley JID, Walker M, Bakajika DK, Kanza EM, Opoku NO, Howard H, Nigo MM, Asare S, Olipoh G, Attah SK, Mambandu GL, Kennedy KK, Kataliko K, Mumbere M, Halleux CM, Hopkins A, Kuesel AC, Kinrade S, Basáñez MG. Can mass drug administration of moxidectin accelerate onchocerciasis elimination in Africa? Philos Trans R Soc Lond B Biol Sci 2023; 378:20220277. [PMID: 37598705 PMCID: PMC10440165 DOI: 10.1098/rstb.2022.0277] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 04/11/2023] [Indexed: 08/22/2023] Open
Abstract
Epidemiological and modelling studies suggest that elimination of Onchocerca volvulus transmission (EoT) throughout Africa may not be achievable with annual mass drug administration (MDA) of ivermectin alone, particularly in areas of high endemicity and vector density. Single-dose Phase II and III clinical trials demonstrated moxidectin's superiority over ivermectin for prolonged clearance of O. volvulus microfilariae. We used the stochastic, individual-based EPIONCHO-IBM model to compare the probabilities of reaching EoT between ivermectin and moxidectin MDA for a range of endemicity levels (30 to 70% baseline microfilarial prevalence), treatment frequencies (annual and biannual) and therapeutic coverage/adherence values (65 and 80% of total population, with, respectively, 5 and 1% of systematic non-adherence). EPIONCHO-IBM's projections indicate that biannual (six-monthly) moxidectin MDA can reduce by half the number of years necessary to achieve EoT in mesoendemic areas and might be the only strategy that can achieve EoT in hyperendemic areas. Data needed to improve modelling projections include (i) the effect of repeated annual and biannual moxidectin treatment; (ii) inter- and intra-individual variation in response to successive treatments with moxidectin or ivermectin; (iii) the effect of moxidectin and ivermectin treatment on L3 development into adult worms; and (iv) patterns of adherence to moxidectin and ivermectin MDA. This article is part of the theme issue 'Challenges in the fight against neglected tropical diseases: a decade from the London Declaration on NTDs'.
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Affiliation(s)
- Klodeta Kura
- London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London W2 1PG, UK
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London W2 1PG, UK
| | - Philip Milton
- London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London W2 1PG, UK
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London W2 1PG, UK
| | - Jonathan I. D. Hamley
- London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London W2 1PG, UK
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London W2 1PG, UK
| | - Martin Walker
- London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London W2 1PG, UK
- Department of Pathobiology and Population Sciences, Royal Veterinary College, Hatfield AL9 7TA, UK
| | - Didier K. Bakajika
- Expanded Special Project for Elimination of Neglected Tropical Diseases (ESPEN), African Regional Office of the World Health Organization (WHO/AFRO/ESPEN), Brazzaville, Democratic Republic of Congo
| | - Eric M. Kanza
- Programme Nationale de Lutte contre les Maladies Tropicales Négligées à Chimiothérapie Préventive (PNLMTN-CTP), Ministère de la Santé Publique, Kinshasa, Democratic Republic of the Congo
| | - Nicholas O. Opoku
- Department of Epidemiology and Biostatistics, School of Public Health, University of Health and Allied Sciences, Hohoe, Ghana
| | - Hayford Howard
- Liberia Institute for Biomedical Research (LIBR), Monrovia, Liberia
| | - Maurice M. Nigo
- Institut Supérieur des Techniques Médicales de Nyankunde, Bunia, Democratic Republic of the Congo
| | | | - George Olipoh
- Precious Minerals Marketing Company, National Assay Centre, Technical Department, Diamond House, Accra, GA-143-2548, Ghana
| | - Simon K. Attah
- Department of Medical Microbiology, University of Ghana Medical School, College of Health Sciences, Accra, Ghana
| | - Germain L. Mambandu
- Inspection Provinciale de la Santé de la Tshopo, Kisangani, Democratic Republic of the Congo
| | - Kambale Kasonia Kennedy
- Department of Clinical Research, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK
| | - Kambale Kataliko
- Centre de Santé CECA 20 de Mabakanga, Beni, Nord Kivu, Democratic Republic of the Congo
| | - Mupenzi Mumbere
- Medicines Development for Global Health, 18 Kavanagh Street, Southbank, Victoria 3006, Australia
| | - Christine M. Halleux
- UNICEF/UNDP/World Bank/WHO Special Programme for Research and Training in Tropical Diseases (TDR), World Health Organization, 1211 Geneva 27, Switzerland
| | - Adrian Hopkins
- Neglected and Disabling Diseases of Poverty Consultant, Gravesend, Kent DA11 OSL, UK
| | - Annette C. Kuesel
- UNICEF/UNDP/World Bank/WHO Special Programme for Research and Training in Tropical Diseases (TDR), World Health Organization, 1211 Geneva 27, Switzerland
| | - Sally Kinrade
- Medicines Development for Global Health, 18 Kavanagh Street, Southbank, Victoria 3006, Australia
| | - Maria-Gloria Basáñez
- London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London W2 1PG, UK
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London W2 1PG, UK
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Willen L, Milton P, Hamley JID, Walker M, Osei-Atweneboana MY, Volf P, Basáñez MG, Courtenay O. Demographic patterns of human antibody levels to Simulium damnosum s.l. saliva in onchocerciasis-endemic areas: An indicator of exposure to vector bites. PLoS Negl Trop Dis 2022; 16:e0010108. [PMID: 35020729 PMCID: PMC8789114 DOI: 10.1371/journal.pntd.0010108] [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] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 01/25/2022] [Accepted: 12/17/2021] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND In onchocerciasis endemic areas in Africa, heterogenous biting rates by blackfly vectors on humans are assumed to partially explain age- and sex-dependent infection patterns with Onchocerca volvulus. To underpin these assumptions and further improve predictions made by onchocerciasis transmission models, demographic patterns in antibody responses to salivary antigens of Simulium damnosum s.l. are evaluated as a measure of blackfly exposure. METHODOLOGY/PRINCIPAL FINDINGS Recently developed IgG and IgM anti-saliva immunoassays for S. damnosum s.l. were applied to blood samples collected from residents in four onchocerciasis endemic villages in Ghana. Demographic patterns in antibody levels according to village, sex and age were explored by fitting generalized linear models. Antibody levels varied between villages but showed consistent patterns with age and sex. Both IgG and IgM responses declined with increasing age. IgG responses were generally lower in males than in females and exhibited a steeper decline in adult males than in adult females. No sex-specific difference was observed in IgM responses. CONCLUSIONS/SIGNIFICANCE The decline in age-specific antibody patterns suggested development of immunotolerance or desensitization to blackfly saliva antigen in response to persistent exposure. The variation between sexes, and between adults and youngsters may reflect differences in behaviour influencing cumulative exposure. These measures of antibody acquisition and decay could be incorporated into onchocerciasis transmission models towards informing onchocerciasis control, elimination, and surveillance.
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Affiliation(s)
- Laura Willen
- Department of Parasitology, Faculty of Science, Charles University, Prague, Czech Republic
- Centre for the Evaluation of Vaccinations, Vaccine and Infectious Disease Institute, University of Antwerp, Wilrijk, Belgium
- * E-mail: (LW); (OC)
| | - Philip Milton
- MRC Centre for Global Infectious Disease Analysis and London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
| | - Jonathan I. D. Hamley
- MRC Centre for Global Infectious Disease Analysis and London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
| | - Martin Walker
- London Centre for Neglected Tropical Disease Research and Department of Pathobiology and Population Sciences, Royal Veterinary College, Hatfield, United Kingdom
| | | | - Petr Volf
- Department of Parasitology, Faculty of Science, Charles University, Prague, Czech Republic
| | - Maria-Gloria Basáñez
- MRC Centre for Global Infectious Disease Analysis and London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
| | - Orin Courtenay
- Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research and School of Life Sciences, University of Warwick, Coventry, United Kingdom
- * E-mail: (LW); (OC)
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Liu KC, Sheard J, Frixou T, Milton P, Luna EP, Piatrikova E, Williams S, Parr J, Roe G, Kramer M. Comparing critical speed modelling approaches and exploring relationships with match-play variables in elite male youth soccer players. S Afr J Sports Med 2021; 33:v33i1a9738. [PMID: 36816890 PMCID: PMC9924614 DOI: 10.17159/2078-516x/2021/v33i1a9738] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
Background A novel bi-exponential method has emerged to estimate critical speed (CS) and D-prime (D') from a 3-min all-out test (3MT). Objectives To compare CS analysis methods to determine whether parameter estimations were interchangeable. Reference values and relationships with key soccer match-play variables were explored. Methods Thirteen elite male youth (14-15 years old) players completed a 30 m shuttle run 3MT to estimate CS, D', rate of speed decline time constant, maximal speed (S max), time to S max (t max), and fatigue index (FI), using the traditional method and bi-exponential model on average (Bi-ExpAverage) and max speed settings (Bi-ExpMax-Speed). High-speed running (HSR) and sprinting distances and counts, and the number of accelerations were collected from two matches. Magnitude-based inferences (p < 0.05) with smallest worthwhile change of 0.2 effect sizes were used to analyse differences. Pearson's and Spearman's correlation coefficients were used to measure associations between CS model variables and match-play parameters. Results There were significant differences between the traditional method and both bi-exponential models for CS and D', as well as between the bi-exponential models for all variables except t max. Using the Bi-ExpAverage model, strong correlations (r = 0.70-0.73; p < 0.05) were observed for D' and FI with the number of standardised and individualised HSRs, respectively. With the Bi-ExpMax-Speed model, there were strong correlations (r/ρ = 0.64-0.68; p < 0.05) between D' and the number of standardised HSRs and sprints, and the number of individualised sprints. Conclusion There is a lack of interchangeability between analysis methods. It appears that D' and FI from the bi-exponential models could be associated with high-intensity actions in soccer match-play.
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Affiliation(s)
- KC Liu
- Department of Health, University of Bath, Bath, UK
| | - J Sheard
- Department of Health, University of Bath, Bath, UK
| | - T Frixou
- Department of Health, University of Bath, Bath, UK
| | - P Milton
- Department of Health, University of Bath, Bath, UK
| | - E Prato Luna
- Department of Health, University of Bath, Bath, UK
| | - E Piatrikova
- Department of Health, University of Bath, Bath, UK
| | - S Williams
- Department of Health, University of Bath, Bath, UK
| | - J Parr
- Manchester United Football Club, Manchester, UK
| | | | - M Kramer
- Physical Activity, Sport, and Recreation (PhASRec) Unit, North-West University, Potchefstroom, South Africa
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Walker M, Hamley JID, Milton P, Monnot F, Kinrade S, Specht S, Pedrique B, Basáñez MG. Supporting drug development for neglected tropical diseases using mathematical modelling. Clin Infect Dis 2021; 73:e1391-e1396. [PMID: 33893482 PMCID: PMC8442785 DOI: 10.1093/cid/ciab350] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Indexed: 11/14/2022] Open
Abstract
Drug-based interventions are at the heart of global efforts to reach elimination as a public health problem (trachoma, soil-transmitted helminthiases, schistosomiasis, lymphatic filariasis) or elimination of transmission (onchocerciasis) for 5 of the most prevalent neglected tropical diseases tackled via the World Health Organization preventive chemotherapy strategy. While for some of these diseases there is optimism that currently available drugs will be sufficient to achieve the proposed elimination goals, for others—particularly onchocerciasis—there is a growing consensus that novel therapeutic options will be needed. Since in this area no high return of investment is possible, minimizing wasted money and resources is essential. Here, we use illustrative results to show how mathematical modeling can guide the drug development pathway, yielding resource-saving and efficiency payoffs, from the refinement of target product profiles and intended context of use to the design of clinical trials.
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Affiliation(s)
- Martin Walker
- Department of Pathobiology and Population Sciences and London Centre for Neglected Tropical Disease Research, Royal Veterinary College, UK.,MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology and London Centre for Neglected Tropical Disease Research, Imperial College London, UK
| | - Jonathan I D Hamley
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology and London Centre for Neglected Tropical Disease Research, Imperial College London, UK
| | - Philip Milton
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology and London Centre for Neglected Tropical Disease Research, Imperial College London, UK
| | - Frédéric Monnot
- Drugs for Neglected Diseases initiative (DNDi), Geneva, Switzerland
| | - Sally Kinrade
- Medicines Development for Global Health, Southbank VIC, Australia
| | - Sabine Specht
- Drugs for Neglected Diseases initiative (DNDi), Geneva, Switzerland
| | - Bélen Pedrique
- Drugs for Neglected Diseases initiative (DNDi), Geneva, Switzerland
| | - Maria-Gloria Basáñez
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology and London Centre for Neglected Tropical Disease Research, Imperial College London, UK
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5
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Hamley JID, Blok DJ, Walker M, Milton P, Hopkins AD, Hamill LC, Downs P, de Vlas SJ, Stolk WA, Basáñez MG. What does the COVID-19 pandemic mean for the next decade of onchocerciasis control and elimination? Trans R Soc Trop Med Hyg 2021; 115:269-280. [PMID: 33515042 PMCID: PMC7928565 DOI: 10.1093/trstmh/traa193] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Revised: 12/16/2020] [Accepted: 12/29/2020] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Mass drug administration (MDA) of ivermectin for onchocerciasis has been disrupted by the coronavirus disease 2019 (COVID-19) pandemic. Mathematical modelling can help predict how missed/delayed MDA will affect short-term epidemiological trends and elimination prospects by 2030. METHODS Two onchocerciasis transmission models (EPIONCHO-IBM and ONCHOSIM) are used to simulate microfilarial prevalence trends, elimination probabilities and age profiles of Onchocerca volvulus microfilarial prevalence and intensity for different treatment histories and transmission settings, assuming no interruption, a 1-y (2020) interruption or a 2-y (2020-2021) interruption. Biannual MDA or increased coverage upon MDA resumption are investigated as remedial strategies. RESULTS Programmes with shorter MDA histories and settings with high pre-intervention endemicity will be the most affected. Biannual MDA is more effective than increasing coverage for mitigating COVID-19's impact on MDA. Programmes that had already switched to biannual MDA should be minimally affected. In high-transmission settings with short treatment history, a 2-y interruption could lead to increased microfilarial load in children (EPIONCHO-IBM) and adults (ONCHOSIM). CONCLUSIONS Programmes with shorter (annual MDA) treatment histories should be prioritised for remedial biannual MDA. Increases in microfilarial load could have short- and long-term morbidity and mortality repercussions. These results can guide decision-making to mitigate the impact of COVID-19 on onchocerciasis elimination.
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Affiliation(s)
- Jonathan I D Hamley
- London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine (St Mary's campus), Imperial College London, Norfolk Place, London W2 1PG, UK.,MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine (St Mary's campus), Imperial College London, Norfolk Place, London W2 1PG, UK
| | - David J Blok
- Department of Public Health, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2040, 3000 CA Rotterdam, The Netherlands
| | - Martin Walker
- London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine (St Mary's campus), Imperial College London, Norfolk Place, London W2 1PG, UK.,London Centre for Neglected Tropical Disease Research (LCNTDR), Department of Pathobiology and Population Sciences, Royal Veterinary College, University of London, Hatfield AL9 7TA, UK
| | - Philip Milton
- London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine (St Mary's campus), Imperial College London, Norfolk Place, London W2 1PG, UK.,MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine (St Mary's campus), Imperial College London, Norfolk Place, London W2 1PG, UK
| | - Adrian D Hopkins
- Neglected and Disabling Diseases of Poverty Consultant, Kent, UK
| | - Louise C Hamill
- Sightsavers, 35 Perrymount Road, Haywards Heath, RH16 3BW, UK
| | - Philip Downs
- Sightsavers, 35 Perrymount Road, Haywards Heath, RH16 3BW, UK
| | - Sake J de Vlas
- Department of Public Health, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2040, 3000 CA Rotterdam, The Netherlands
| | - Wilma A Stolk
- Department of Public Health, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2040, 3000 CA Rotterdam, The Netherlands
| | - Maria-Gloria Basáñez
- London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine (St Mary's campus), Imperial College London, Norfolk Place, London W2 1PG, UK.,MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine (St Mary's campus), Imperial College London, Norfolk Place, London W2 1PG, UK
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6
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Hamley JID, Walker M, Coffeng LE, Milton P, de Vlas SJ, Stolk WA, Basáñez MG. Structural Uncertainty in Onchocerciasis Transmission Models Influences the Estimation of Elimination Thresholds and Selection of Age Groups for Seromonitoring. J Infect Dis 2021; 221:S510-S518. [PMID: 32173745 PMCID: PMC7289547 DOI: 10.1093/infdis/jiz674] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND The World Health Organization recommends monitoring Onchocerca volvulus Ov16 serology in children aged <10 years for stopping mass ivermectin administration. Transmission models can help to identify the most informative age groups for serological monitoring and investigate the discriminatory power of serology-based elimination thresholds. Model predictions depend on assumed age-exposure patterns and transmission efficiency at low infection levels. METHODS The individual-based transmission model, EPIONCHO-IBM, was used to assess (1) the most informative age groups for serological monitoring using receiver operating characteristic curves for different elimination thresholds under various age-dependent exposure assumptions, including those of ONCHOSIM (another widely used model), and (2) the influence of within-human density-dependent parasite establishment (included in EPIONCHO-IBM but not ONCHOSIM) on positive predictive values for different serological thresholds. RESULTS When assuming EPIONCHO-IBM exposure patterns, children aged <10 years are the most informative for seromonitoring; when assuming ONCHOSIM exposure patterns, 5-14 year olds are the most informative (as published elsewhere). Omitting density-dependent parasite establishment results in more lenient seroprevalence thresholds, even for higher baseline infection prevalence and shorter treatment durations. CONCLUSIONS Selecting appropriate seromonitoring age groups depends critically on age-dependent exposure patterns. The role of density dependence on elimination thresholds largely explains differing EPIONCHO-IBM and ONCHOSIM elimination predictions.
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Affiliation(s)
- Jonathan I D Hamley
- London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, Imperial College London, London, UK.,Medical Research Council Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Martin Walker
- London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, Imperial College London, London, UK.,London Centre for Neglected Tropical Disease Research, Department of Pathobiology and Population Sciences, Royal Veterinary College, University of London, Hatfield, UK
| | - Luc E Coffeng
- Department of Public Health, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Philip Milton
- London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, Imperial College London, London, UK.,Medical Research Council Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Sake J de Vlas
- Department of Public Health, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Wilma A Stolk
- Department of Public Health, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Maria-Gloria Basáñez
- London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, Imperial College London, London, UK.,Medical Research Council Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
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Unwin HJT, Mishra S, Bradley VC, Gandy A, Mellan TA, Coupland H, Ish-Horowicz J, Vollmer MAC, Whittaker C, Filippi SL, Xi X, Monod M, Ratmann O, Hutchinson M, Valka F, Zhu H, Hawryluk I, Milton P, Ainslie KEC, Baguelin M, Boonyasiri A, Brazeau NF, Cattarino L, Cucunuba Z, Cuomo-Dannenburg G, Dorigatti I, Eales OD, Eaton JW, van Elsland SL, FitzJohn RG, Gaythorpe KAM, Green W, Hinsley W, Jeffrey B, Knock E, Laydon DJ, Lees J, Nedjati-Gilani G, Nouvellet P, Okell L, Parag KV, Siveroni I, Thompson HA, Walker P, Walters CE, Watson OJ, Whittles LK, Ghani AC, Ferguson NM, Riley S, Donnelly CA, Bhatt S, Flaxman S. State-level tracking of COVID-19 in the United States. Nat Commun 2020. [PMID: 33273462 DOI: 10.25561/78677] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/13/2023] Open
Abstract
As of 1st June 2020, the US Centres for Disease Control and Prevention reported 104,232 confirmed or probable COVID-19-related deaths in the US. This was more than twice the number of deaths reported in the next most severely impacted country. We jointly model the US epidemic at the state-level, using publicly available death data within a Bayesian hierarchical semi-mechanistic framework. For each state, we estimate the number of individuals that have been infected, the number of individuals that are currently infectious and the time-varying reproduction number (the average number of secondary infections caused by an infected person). We use changes in mobility to capture the impact that non-pharmaceutical interventions and other behaviour changes have on the rate of transmission of SARS-CoV-2. We estimate that Rt was only below one in 23 states on 1st June. We also estimate that 3.7% [3.4%-4.0%] of the total population of the US had been infected, with wide variation between states, and approximately 0.01% of the population was infectious. We demonstrate good 3 week model forecasts of deaths with low error and good coverage of our credible intervals.
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Affiliation(s)
- H Juliette T Unwin
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK.
| | - Swapnil Mishra
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | | | - Axel Gandy
- Department of Mathematics, Imperial College, London, UK
| | - Thomas A Mellan
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Helen Coupland
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | | | - Michaela A C Vollmer
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Charles Whittaker
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | | | - Xiaoyue Xi
- Department of Mathematics, Imperial College, London, UK
| | - Mélodie Monod
- Department of Mathematics, Imperial College, London, UK
| | | | | | | | - Harrison Zhu
- Department of Mathematics, Imperial College, London, UK
| | - Iwona Hawryluk
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Philip Milton
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Kylie E C Ainslie
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Marc Baguelin
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Adhiratha Boonyasiri
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, London, UK
| | - Nick F Brazeau
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Lorenzo Cattarino
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Zulma Cucunuba
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Gina Cuomo-Dannenburg
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Ilaria Dorigatti
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Oliver D Eales
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Jeffrey W Eaton
- MRC Centre for Global Infectious Disease Analysis, Imperial College, London, UK
| | - Sabine L van Elsland
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Richard G FitzJohn
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Katy A M Gaythorpe
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - William Green
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Wes Hinsley
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Benjamin Jeffrey
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Edward Knock
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Daniel J Laydon
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - John Lees
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Gemma Nedjati-Gilani
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Pierre Nouvellet
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
- School of Life Sciences, University of Sussex, Brighton, UK
| | - Lucy Okell
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Kris V Parag
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Igor Siveroni
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Hayley A Thompson
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Patrick Walker
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Caroline E Walters
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, 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, UK
- Department of Laboratory Medicine and Pathology, Brown University, Providence, RI, USA
| | - Lilith K Whittles
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Azra C Ghani
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Neil M Ferguson
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Steven Riley
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Christl A Donnelly
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
- Department of Statistics, University of Oxford, Oxford, UK
| | - Samir Bhatt
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK.
| | - Seth Flaxman
- Department of Mathematics, Imperial College, London, UK.
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8
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Unwin HJT, Mishra S, Bradley VC, Gandy A, Mellan TA, Coupland H, Ish-Horowicz J, Vollmer MAC, Whittaker C, Filippi SL, Xi X, Monod M, Ratmann O, Hutchinson M, Valka F, Zhu H, Hawryluk I, Milton P, Ainslie KEC, Baguelin M, Boonyasiri A, Brazeau NF, Cattarino L, Cucunuba Z, Cuomo-Dannenburg G, Dorigatti I, Eales OD, Eaton JW, van Elsland SL, FitzJohn RG, Gaythorpe KAM, Green W, Hinsley W, Jeffrey B, Knock E, Laydon DJ, Lees J, Nedjati-Gilani G, Nouvellet P, Okell L, Parag KV, Siveroni I, Thompson HA, Walker P, Walters CE, Watson OJ, Whittles LK, Ghani AC, Ferguson NM, Riley S, Donnelly CA, Bhatt S, Flaxman S. State-level tracking of COVID-19 in the United States. Nat Commun 2020; 11:6189. [PMID: 33273462 PMCID: PMC7712910 DOI: 10.1038/s41467-020-19652-6] [Citation(s) in RCA: 67] [Impact Index Per Article: 16.8] [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: 07/15/2020] [Accepted: 10/15/2020] [Indexed: 02/07/2023] Open
Abstract
As of 1st June 2020, the US Centres for Disease Control and Prevention reported 104,232 confirmed or probable COVID-19-related deaths in the US. This was more than twice the number of deaths reported in the next most severely impacted country. We jointly model the US epidemic at the state-level, using publicly available death data within a Bayesian hierarchical semi-mechanistic framework. For each state, we estimate the number of individuals that have been infected, the number of individuals that are currently infectious and the time-varying reproduction number (the average number of secondary infections caused by an infected person). We use changes in mobility to capture the impact that non-pharmaceutical interventions and other behaviour changes have on the rate of transmission of SARS-CoV-2. We estimate that Rt was only below one in 23 states on 1st June. We also estimate that 3.7% [3.4%-4.0%] of the total population of the US had been infected, with wide variation between states, and approximately 0.01% of the population was infectious. We demonstrate good 3 week model forecasts of deaths with low error and good coverage of our credible intervals.
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Affiliation(s)
- H Juliette T Unwin
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK.
| | - Swapnil Mishra
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | | | - Axel Gandy
- Department of Mathematics, Imperial College, London, UK
| | - Thomas A Mellan
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Helen Coupland
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | | | - Michaela A C Vollmer
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Charles Whittaker
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | | | - Xiaoyue Xi
- Department of Mathematics, Imperial College, London, UK
| | - Mélodie Monod
- Department of Mathematics, Imperial College, London, UK
| | | | | | | | - Harrison Zhu
- Department of Mathematics, Imperial College, London, UK
| | - Iwona Hawryluk
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Philip Milton
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Kylie E C Ainslie
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Marc Baguelin
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Adhiratha Boonyasiri
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, London, UK
| | - Nick F Brazeau
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Lorenzo Cattarino
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Zulma Cucunuba
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Gina Cuomo-Dannenburg
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Ilaria Dorigatti
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Oliver D Eales
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Jeffrey W Eaton
- MRC Centre for Global Infectious Disease Analysis, Imperial College, London, UK
| | - Sabine L van Elsland
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Richard G FitzJohn
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Katy A M Gaythorpe
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - William Green
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Wes Hinsley
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Benjamin Jeffrey
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Edward Knock
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Daniel J Laydon
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - John Lees
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Gemma Nedjati-Gilani
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Pierre Nouvellet
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
- School of Life Sciences, University of Sussex, Brighton, UK
| | - Lucy Okell
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Kris V Parag
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Igor Siveroni
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Hayley A Thompson
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Patrick Walker
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Caroline E Walters
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, 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, UK
- Department of Laboratory Medicine and Pathology, Brown University, Providence, RI, USA
| | - Lilith K Whittles
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Azra C Ghani
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Neil M Ferguson
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Steven Riley
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Christl A Donnelly
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
- Department of Statistics, University of Oxford, Oxford, UK
| | - Samir Bhatt
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK.
| | - Seth Flaxman
- Department of Mathematics, Imperial College, London, UK.
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9
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Unwin HJT, Mishra S, Bradley VC, Gandy A, Mellan TA, Coupland H, Ish-Horowicz J, Vollmer MAC, Whittaker C, Filippi SL, Xi X, Monod M, Ratmann O, Hutchinson M, Valka F, Zhu H, Hawryluk I, Milton P, Ainslie KEC, Baguelin M, Boonyasiri A, Brazeau NF, Cattarino L, Cucunuba Z, Cuomo-Dannenburg G, Dorigatti I, Eales OD, Eaton JW, van Elsland SL, FitzJohn RG, Gaythorpe KAM, Green W, Hinsley W, Jeffrey B, Knock E, Laydon DJ, Lees J, Nedjati-Gilani G, Nouvellet P, Okell L, Parag KV, Siveroni I, Thompson HA, Walker P, Walters CE, Watson OJ, Whittles LK, Ghani AC, Ferguson NM, Riley S, Donnelly CA, Bhatt S, Flaxman S. State-level tracking of COVID-19 in the United States. Nat Commun 2020. [PMID: 33273462 DOI: 10.25561/79231] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/22/2023] Open
Abstract
As of 1st June 2020, the US Centres for Disease Control and Prevention reported 104,232 confirmed or probable COVID-19-related deaths in the US. This was more than twice the number of deaths reported in the next most severely impacted country. We jointly model the US epidemic at the state-level, using publicly available death data within a Bayesian hierarchical semi-mechanistic framework. For each state, we estimate the number of individuals that have been infected, the number of individuals that are currently infectious and the time-varying reproduction number (the average number of secondary infections caused by an infected person). We use changes in mobility to capture the impact that non-pharmaceutical interventions and other behaviour changes have on the rate of transmission of SARS-CoV-2. We estimate that Rt was only below one in 23 states on 1st June. We also estimate that 3.7% [3.4%-4.0%] of the total population of the US had been infected, with wide variation between states, and approximately 0.01% of the population was infectious. We demonstrate good 3 week model forecasts of deaths with low error and good coverage of our credible intervals.
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Affiliation(s)
- H Juliette T Unwin
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK.
| | - Swapnil Mishra
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | | | - Axel Gandy
- Department of Mathematics, Imperial College, London, UK
| | - Thomas A Mellan
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Helen Coupland
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | | | - Michaela A C Vollmer
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Charles Whittaker
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | | | - Xiaoyue Xi
- Department of Mathematics, Imperial College, London, UK
| | - Mélodie Monod
- Department of Mathematics, Imperial College, London, UK
| | | | | | | | - Harrison Zhu
- Department of Mathematics, Imperial College, London, UK
| | - Iwona Hawryluk
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Philip Milton
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Kylie E C Ainslie
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Marc Baguelin
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Adhiratha Boonyasiri
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, London, UK
| | - Nick F Brazeau
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Lorenzo Cattarino
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Zulma Cucunuba
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Gina Cuomo-Dannenburg
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Ilaria Dorigatti
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Oliver D Eales
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Jeffrey W Eaton
- MRC Centre for Global Infectious Disease Analysis, Imperial College, London, UK
| | - Sabine L van Elsland
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Richard G FitzJohn
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Katy A M Gaythorpe
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - William Green
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Wes Hinsley
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Benjamin Jeffrey
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Edward Knock
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Daniel J Laydon
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - John Lees
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Gemma Nedjati-Gilani
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Pierre Nouvellet
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
- School of Life Sciences, University of Sussex, Brighton, UK
| | - Lucy Okell
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Kris V Parag
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Igor Siveroni
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Hayley A Thompson
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Patrick Walker
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Caroline E Walters
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, 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, UK
- Department of Laboratory Medicine and Pathology, Brown University, Providence, RI, USA
| | - Lilith K Whittles
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Azra C Ghani
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Neil M Ferguson
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Steven Riley
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
| | - Christl A Donnelly
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK
- Department of Statistics, University of Oxford, Oxford, UK
| | - Samir Bhatt
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College, London, UK.
| | - Seth Flaxman
- Department of Mathematics, Imperial College, London, UK.
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Abstract
INTRODUCTION Moxidectin is a milbemycin endectocide recently approved for the treatment of human onchocerciasis. Onchocerciasis, earmarked for elimination of transmission, is a filarial infection endemic in Africa, Yemen, and the Amazonian focus straddling Venezuela and Brazil. Concerns over whether the predominant treatment strategy (yearly mass drug administration (MDA) of ivermectin) is sufficient to achieve elimination in all endemic foci have refocussed attention upon alternative treatments. Moxidectin's stronger and longer microfilarial suppression compared to ivermectin in both phase II and III clinical trials indicates its potential as a novel powerful drug for onchocerciasis elimination. AREAS COVERED This work summarizes the chemistry and pharmacology of moxidectin, reviews the phase II and III clinical trials evidence on tolerability, safety, and efficacy of moxidectin versus ivermectin, and discusses the implications of moxidectin's current regulatory status. EXPERT OPINION Moxidectin's superior clinical performance has the potential to substantially reduce times to elimination compared to ivermectin. If donated, moxidectin could mitigate the additional programmatic costs of biannual ivermectin distribution because, unlike other alternatives, it can use the existing community-directed treatment infrastructure. A pediatric indication (for children <12 years) and determination of its usefulness in onchocerciasis-loiasis co-endemic areas will greatly help fulfill the potential of moxidectin for the treatment and elimination of onchocerciasis.
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Affiliation(s)
- Philip Milton
- London Centre for Neglected Tropical Disease Research and MRC Centre for Global Infectious Disease Analysis (MRC GIDA), Department of Infectious Disease Epidemiology, Imperial College London , London, UK
| | - Jonathan I D Hamley
- London Centre for Neglected Tropical Disease Research and MRC Centre for Global Infectious Disease Analysis (MRC GIDA), Department of Infectious Disease Epidemiology, Imperial College London , London, UK
| | - Martin Walker
- London Centre for Neglected Tropical Disease Research and MRC Centre for Global Infectious Disease Analysis (MRC GIDA), Department of Infectious Disease Epidemiology, Imperial College London , London, UK.,London Centre for Neglected Tropical Disease Research, Department of Pathobiology and Population Sciences, Royal Veterinary College , Hatfield, UK
| | - María-Gloria Basáñez
- London Centre for Neglected Tropical Disease Research and MRC Centre for Global Infectious Disease Analysis (MRC GIDA), Department of Infectious Disease Epidemiology, Imperial College London , London, UK
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11
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Hamley JID, Milton P, Walker M, Basáñez MG. Modelling exposure heterogeneity and density dependence in onchocerciasis using a novel individual-based transmission model, EPIONCHO-IBM: Implications for elimination and data needs. PLoS Negl Trop Dis 2019; 13:e0007557. [PMID: 31805049 PMCID: PMC7006940 DOI: 10.1371/journal.pntd.0007557] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [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: 01/27/2019] [Revised: 02/07/2020] [Accepted: 06/18/2019] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND Density dependence in helminth establishment and heterogeneity in exposure to infection are known to drive resilience to interventions based on mass drug administration (MDA). However, the interaction between these processes is poorly understood. We developed a novel individual-based model for onchocerciasis transmission, EPIONCHO-IBM, which accounts for both processes. We fit the model to pre-intervention epidemiological data and explore parasite dynamics during MDA with ivermectin. METHODOLOGY/PRINCIPAL FINDINGS Density dependence and heterogeneity in exposure to blackfly (vector) bites were estimated by fitting the model to matched pre-intervention microfilarial prevalence, microfilarial intensity and vector biting rate data from savannah areas of Cameroon and Côte d'Ivoire/Burkina Faso using Latin hypercube sampling. Transmission dynamics during 25 years of annual and biannual ivermectin MDA were investigated. Density dependence in parasite establishment within humans was estimated for different levels of (fixed) exposure heterogeneity to understand how parametric uncertainty may influence treatment dynamics. Stronger overdispersion in exposure to blackfly bites results in the estimation of stronger density-dependent parasite establishment within humans, consequently increasing resilience to MDA. For all levels of exposure heterogeneity tested, the model predicts a departure from the functional forms for density dependence assumed in the deterministic version of the model. CONCLUSIONS/SIGNIFICANCE This is the first, stochastic model of onchocerciasis, that accounts for and estimates density-dependent parasite establishment in humans alongside exposure heterogeneity. Capturing the interaction between these processes is fundamental to our understanding of resilience to MDA interventions. Given that uncertainty in these processes results in very different treatment dynamics, collecting data on exposure heterogeneity would be essential for improving model predictions during MDA. We discuss possible ways in which such data may be collected as well as the importance of better understanding the effects of immunological responses on establishing parasites prior to and during ivermectin treatment.
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Affiliation(s)
- Jonathan I. D. Hamley
- London Centre for Neglected Tropical Disease Research (LCNTDR), Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine (St Mary’s campus), Imperial College London, London, United Kingdom
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine (St Mary’s campus), Imperial College London, London, United Kingdom
- * E-mail:
| | - Philip Milton
- London Centre for Neglected Tropical Disease Research (LCNTDR), Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine (St Mary’s campus), Imperial College London, London, United Kingdom
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine (St Mary’s campus), Imperial College London, London, United Kingdom
| | - Martin Walker
- London Centre for Neglected Tropical Disease Research (LCNTDR), Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine (St Mary’s campus), Imperial College London, London, United Kingdom
- London Centre for Neglected Tropical Disease Research (LCNTDR), Department of Pathobiology and Population Sciences, Royal Veterinary College, University of London, Hatfield, Untied Kingdom
| | - Maria-Gloria Basáñez
- London Centre for Neglected Tropical Disease Research (LCNTDR), Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine (St Mary’s campus), Imperial College London, London, United Kingdom
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine (St Mary’s campus), Imperial College London, London, United Kingdom
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Milton P, Coupland H, Giorgi E, Bhatt S. Spatial analysis made easy with linear regression and kernels. Epidemics 2019; 29:100362. [PMID: 31561884 DOI: 10.1016/j.epidem.2019.100362] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2019] [Revised: 08/05/2019] [Accepted: 08/19/2019] [Indexed: 11/29/2022] Open
Abstract
Kernel methods are a popular technique for extending linear models to handle non-linear spatial problems via a mapping to an implicit, high-dimensional feature space. While kernel methods are computationally cheaper than an explicit feature mapping, they are still subject to cubic cost on the number of points. Given only a few thousand locations, this computational cost rapidly outstrips the currently available computational power. This paper aims to provide an overview of kernel methods from first-principals (with a focus on ridge regression) and progress to a review of random Fourier features (RFF), a method that enables the scaling of kernel methods to big datasets. We show how the RFF method is capable of approximating the full kernel matrix, providing a significant computational speed-up for a negligible cost to accuracy and can be incorporated into many existing spatial methods using only a few lines of code. We give an example of the implementation of RFFs on a simulated spatial data set to illustrate these properties. Lastly, we summarise the main issues with RFFs and highlight some of the advanced techniques aimed at alleviating them. At each stage, the associated R code is provided.
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Affiliation(s)
- Philip Milton
- MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
| | - Helen Coupland
- MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
| | - Emanuele Giorgi
- CHICAS, Lancaster Medical School, Lancaster University, Lancaster, UK.
| | - Samir Bhatt
- MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
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Gong L, Ye Z, Zeng Z, Xia M, Zhong Y, Yao Y, Lee E, Ionescu A, Dwivedi G, Mahadevan G, Jiminez D, Frenneaux M, Steeds R, Moore C, Samad Z, Jackson K, Castellucci J, Kisslo J, Von Ramm O, D'ascenzi F, Zaca' V, Cameli M, Lisi M, Natali B, Malandrino A, Mondillo S, Barbier P, Guerrini U, Franzosi M, Castiglioni L, Nobili E, Colazzo F, Li Causi T, Sironi L, Tremoli E, Clausen H, Macdonald S, Basaggianis C, Newton J, Cameli M, Lisi M, Bennati E, Reccia R, Malandrino A, Bigio E, Maccherini M, Chiavarelli M, Henein M, Mondillo S, Floria M, Jamart J, Arsenescu Georgescu C, Mantovani F, Barbieri A, Bursi F, Valenti C, Quaglia M, Modena M, Kutty S, Gribben P, Padiyath A, Polak A, Scott C, Waiss M, Danford D, Bech-Hanssen O, Selimovic N, Rundqvist B, Schmiedel L, Hohmann C, Katzke S, Haacke K, Rauwolf T, Strasser R, Tumasyan LR, Adamyan K, Kosmala W, Derzhko R, Przewlocka-Kosmala M, Mysiak A, Stachowska B, Jedrzejuk D, Bednarek-Tupikowska G, Chrzanowski L, Kasprzak J, Wojciechowska C, Wita K, Busz-Papiez B, Gasior Z, Mizia-Stec K, Kukulski T, Gosciniak P, Sinkiewicz W, Moelmen H, Stoylen A, Thorstensen A, Torp H, Dalen H, Groves A, Nicholson G, Lopez L, Goh CW, Ahn H, Byun Y, Kim J, Park J, Lee J, Park J, Kim B, Rhee K, Kim K, Park J, Yoon H, Hong Y, Park H, Kim J, Ahn Y, Jeong M, Cho J, Kang J, Grapsa J, Dawson D, Karfopoulos K, Jakaj G, Punjabi P, Nihoyannopoulos P, Ruisanchez Villar C, Lerena Saenz P, Gonzalez Vilchez F, Gonzalez Fernandez C, Zurbano Goni F, Cifrian Martinez J, Mons Lera R, Ruano Calvo J, Martin Duran R, Vazquez De Prada Tiffe J, Pietrzak R, Werner B, Voillot D, Huttin O, Zinzius P, Schwartz J, Sellal J, Lemoine S, Christophe C, Popovic B, Juilliere Y, Selton-Suty C, Ishii K, Furukawa A, Nagai T, Kataoka K, Seino Y, Shimada K, Yoshikawa J, Tekkesin A, Yildirimturk O, Tayyareci Y, Yurdakul S, Aytekin S, Jaroch J, Loboz-Grudzien K, Bociaga Z, Kowalska A, Kruszynska E, Wilczynska M, Dudek K, Kakihara R, Naruse C, Hironaka H, Tsuzuku T, Cucchini U, Muraru D, Badano L, Solda' E, Tuveri M, Al Nono O, Sarais C, Iliceto S, Santos L, Cortez-Dias N, Ribeiro S, Goncalves S, Jorge C, Carrilho-Ferreira P, Silva D, Silva-Marques J, Lopes M, Diogo A, Hristova K, Vassilev D, Pavlov P, Katova T, Simova I, Kostova V, Esposito R, Santoro A, Schiano Lomoriello V, Raia R, De Palma D, Dores E, De Simone G, Galderisi M, Zaborska B, Makowska E, Pilichowska E, Maciejewski P, Bednarz B, Wasek W, Stec S, Budaj A, Spinelli L, Morisco C, Assante Di Panzillo E, Crispo S, Di Marino S, Trimarco B, Santoro A, Schiano Lomoriello V, Esposito R, Farina F, Innelli P, Rapacciuolo A, Galderisi M, Polgar B, Banyai F, Rokusz L, Tomcsanyi I, Vaszily M, Nieszner E, Borsanyi T, Kerecsen G, Preda I, Kiss RG, Bull S, Suttie J, Augustine D, Francis J, Karamitsos T, Becher H, Prendergast B, Neubauer S, Myerson S, Lodge F, Broyd C, Milton P, Mikhail G, Mayet J, Davies J, Francis D, Clavel MA, Ennezat PV, Marechaux S, Dumesnil J, Bellouin A, Bergeron S, Meimoun P, Le Tourneau T, Pasquet A, Pibarot P, Herrmann S, Stoerk S, Niemann M, Hu K, Voelker W, Ertl G, Weidemann F, Tayyareci Y, Yurdakul S, Yildirimturk O, Aytekin V, Aytekin S, Kogoj P, Ambrozic J, Bunc M, Di Salvo G, Rea A, Castaldi B, Gala S, D'aiello A, Mormile A, Pisacane F, Pacileo G, Russo M, Calabro R, Nguyen L, Ricksten SE, Jeppsson A, Schersten H, Bech-Hanssen O, Boerlage-Van Dijk K, Yong Z, Bouma B, Koch K, Vis M, Piek J, Baan J, Scandura S, Ussia G, Caggegi A, Cammalleri V, Sarkar K, Mangiafico S, Chiaranda' M, Imme' S, Pistritto A, Tamburino C, Ring L, Nair S, Wells F, Shapiro L, Rusk R, Rana B, Madrid Marcano G, Solis Martin J, Gonzalez Mansilla A, Bravo L, Menarguez Palanca C, Munoz P, Bouza E, Yotti R, Bermejo Thomas J, Fernandez Aviles F, Tamayo T, Denes M, Balint O, Csepregi A, Csillik A, Erdei T, Temesvari A, Fernandez-Pastor J, Linde-Estrella A, Cabrera-Bueno F, Pena-Hernandez J, Barrera-Cordero A, Alzueta-Rodriguez F, De Teresa-Galvan E, Merlo M, Pinamonti M, Finocchiaro G, Pyxaras S, Barbati G, Buiatti A, Dilenarda A, Sinagra G, Kuperstein R, Freimark D, Hirsch S, Feinberg M, Arad M, Mitroi C, Garcia Lunar I, Monivas Palomero V, Mingo Santos S, Beltran Correas P, Gonzalez Lopez E, Garcia Pavia P, Gonzalez Mirelis J, Cavero Gibanel M, Alonso Pulpon L, Finocchiaro G, Pinamonti B, Merlo M, Barbati G, Dilenarda A, Sinagra G, Zaidi A, Ghani S, Sheikh N, Gati S, Howes R, Sharma R, Sharma S, Calcagnino M, O'mahony C, Coats C, Cardona M, Garcia A, Murphy E, Lachmann R, Mehta A, Hughes D, Elliott P, Di Bella G, Madaffari A, Donato R, Mazzeo A, Casale M, Zito C, Vita G, Carerj S, Marek D, Indrakova J, Rusinakova Z, Skala T, Kocianova E, Taborsky M, Musca F, De Chiara B, Belli O, Cataldo S, Brunati C, Colussi G, Quattrocchi G, Santambrogio G, Spano F, Moreo A, Rustad L, Nytroen K, Gullestad L, Amundsen B, Aakhus S, Maroz-Vadalazhskaya N, Shumavetc V, Kurganovich S, Seljun Y, Ostrovskiy A, Ostrovskiy Y, Rustad L, Nytroen K, Segers P, Amundsen B, Aakhus S, Przewlocka-Kosmala M, Orda A, Karolko B, Mysiak A, Driessen MMP, Eising JB, Uiterwaal C, Van Der Ent CK, Meijboom FJ, Shang Q, Tam L, Sun J, Sanderson J, Zhang Q, Li E, Yu C, Arroyo Ucar E, De La Rosa Hernandez A, Hernandez Garcia C, Jorge Perez P, Lacalzada Almeida J, Jimenez Rivera J, Duque Garcia A, Barragan Acea A, Laynez Cerdena I, Kaldararova M, Simkova I, Pacak J, Tittel P, Masura J, Tadic M, Ivanovic B, Zlatanovic M, Damjanov N, Maggiolini S, Gentile G, Bozzano A, Suraci S, Meles E, Carbone C, Tempesta A, Malafronte C, Piatti L, Achilli F, Luijendijk P, Stevens A, De Bruin-Bon H, Vriend J, Van Den Brink R, Vliegen H, Mulder B, Bouma B, Chow V, Ng A, Chung T, Kritharides L, Iancu M, Serban M, Craciunescu I, Hodo A, Ghiorghiu I, Popescu B, Ginghina C, Styczynski G, Szmigielski CA, Kaczynska A, Leszczynski J, Rosinski G, Kuch-Wocial A, Slavich M, Ancona M, Fisicaro A, Oppizzi M, Marone E, Bertoglio L, Melissano G, Margonato A, Chiesa R, Agricola E, Zito C, Mohammed M, Cusma-Piccione M, Piluso S, Arcidiaco S, Nava R, Giuffre R, Ciraci L, Ferro M, Carerj S, Uusitalo V, Luotolahti M, Pietila M, Wendelin-Saarenhovi M, Hartiala J, Saraste M, Knuuti J, Saraste A, Kochanowski J, Scislo P, Piatkowski R, Grabowski M, Marchel M, Roik M, Kosior D, Opolski G, Bartko PE, Graf S, Khorsand A, Rosenhek R, Burwash I, Beanlands R, Clavel MA, Baumgartner H, Pibarot P, Mundigler G, Kudrnova S, Apor A, Huttl H, Kudrnova S, Apor A, Huttl H, Mori F, Santoro G, Oddo A, Rosso G, Meucci F, Pieri F, Squillantini G, Gensini G, Scislo P, Kochanowski J, Piatkowski R, Roik M, Postula M, Opolski G, Park DG, Hong JY, Kim SE, Lee JH, Han KR, Oh DJ, Muraru D, Dal Bianco L, Beraldo M, Solda' E, Cucchini U, Peluso D, Tuveri M, Al Mamary A, Badano L, Iliceto S, Aggeli C, Felekos I, Poulidakis E, Pietri P, Roussakis G, Siasos G, Stefanadis C, Furukawa A, Hoshiba H, Miyasaka C, Sato H, Nagai T, Yamanaka A, Kataoka K, Seino Y, Ishii K, Lilli A, Baratto M, Magnacca M, Comella A, Poddighe R, Talini E, Canale M, Chioccioli M, Del Meglio J, Casolo G, Kuznetsov VA, Melnikov NN, Krinochkin DV, Calin A, Enache R, Popescu B, Beladan C, Rosca M, Lupascu L, Purcarea F, Calin C, Gurzun M, Ginghina C, Dulgheru R, Ciobanu A, Magda S, Mihaila S, Rimbas R, Margulescu A, Cinteza M, Vinereanu D, Sumin AN, Arhipov O, Yoon J, Moon J, Rim S, Nyktari E, Patrianakos A, Solidakis G, Psathakis E, Parthenakis F, Vardas P, Kordybach M, Kowalski M, Kowalik E, Hoffman P, Nagy KV, Kutyifa V, Edes E, Apor A, Merkely B, Gerlach A, Rost C, Schmid M, Rost M, Flachskampf F, Daniel W, Breithardt O, Altekin E, Karakas S, Yanikoglu A, Er A, Baktir A, Demir I, Deger N, Klitsie L, Hazekamp M, Roest A, Van Der Hulst A, Gesink- Van Der Veer B, Kuipers I, Blom N, Ten Harkel A, Farsalinos K, Tsiapras D, Kyrzopoulos S, Avramidou E, Vasilopoulou D, Voudris V, Werner B, Florianczyk T, Ivanovic B, Tadic M, Kalinowski M, Szulik M, Streb W, Rybus-Kalinowska B, Sliwinska A, Stabryla J, Kukla M, Nowak J, Kukulski T, Kalarus Z, Florescu M, Mihalcea D, Magda L, Suran B, Enescu O, Mincu R, Cinteza M, Vinereanu D, Salerno G, Scognamiglio G, D'andrea A, Dinardo G, Gravino R, Sarubbi B, Disalvo G, Pacileo G, Russo M, Calabro R, Liao JN, Sung S, Chen C, Park S, Shin S, Kim M, Shim S, Yildirimturk O, Helvacioglu F, Ulusoy O, Duran C, Tayyareci Y, Yurdakul S, Aytekin S, Kirschner R, Simor T, Moreo A, Ambrosio G, De Chiara B, Tran T, Raman S, Vidal Perez RC, Carreras F, Leta R, Pujadas S, Barros A, Hidalgo A, Alomar X, Pons-Llado G, Olofsson M, Boman K, Ledakowicz-Polak A, Polak L, Zielinska M, Fontana A, Schirone V, Mauro A, Zambon A, Giannattasio C, Trocino G, Dekleva M, Dungen H, Inkrot S, Gelbrich G, Suzic Lazic J, Kleut M, Markovic Nikolic N, Waagstein F, Khoor S, Balogh N, Simon I, Fugedi K, Kovacs I, Khoor M, Florian G, Kocsis A, Szuszai T, O'driscoll J, Saha A, Smith R, Gupta S, Sharma R, Lenkey Z, Gaszner B, Illyes M, Sarszegi Z, Horvath IG, Magyari B, Molnar F, Cziraki A, Elnoamany MF, Badran H, Ebraheem H, Reda A, Elsheekh N. Poster Session 5: Saturday 10 December 2011, 08:30-12:30 * Location: Poster Area. European Journal of Echocardiography 2011. [DOI: 10.1093/ejechocard/jer218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
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Banfield P, Milton P. Gynaecology. Postgrad Med J 1993. [DOI: 10.1136/pgmj.69.817.898-b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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Hardy KJ, Milton P, Derham P, Fletcher DR, MacLellan DG, Jones RM, Shulkes A. Attitudes towards liver transplantation in Victoria, Australia. Aust N Z J Surg 1993; 63:520-4. [PMID: 8317976 DOI: 10.1111/j.1445-2197.1993.tb00444.x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
Liver transplantation commenced on a regular basis in Australia in 1985. This followed the first successful orthotopic transplant in Brisbane in 1985 and the setting up of a National Centre for Liver Transplantation in Sydney in 1985 with clinical transplantation beginning there in 1986. A centre was subsequently developed in Melbourne in 1988. As this procedure was perceived to be expensive, and because of discussion on rationing of medical services, the authors were prompted to test the Victorian community awareness and attitude to government funding of transplantation. One year after the establishment of the Victorian Liver Transplantation Programme, a random survey of the Victorian population and of general practitioners in Melbourne was conducted with the assistance of a professional polling company. Sixty-five per cent of the Victorian population knew liver transplantation was available in Victoria, 12% said it was not available and 23% did not know. Among general practitioners, 79% knew liver transplantation was available 14% said it was not available and 7% did not know. Eighty-eight per cent of Victorians and a similar proportion of general practitioners said the State Government should provide funding. Forty-seven per cent of the Victorian population said government should provide total funding and a further 39% funding of more than 50%. Among general practitioners, 33% said total funding should be provided and a further 46% thought that more than 50% of funding should be provided. This survey has revealed convincingly that Victorians have decided that their health care should include the expense of liver transplantation paid for by government. Awareness of the availability of the operation of liver transplantation is developing rapidly.
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Affiliation(s)
- K J Hardy
- Department of Surgery, Austin Hospital, Melbourne, Victoria, Australia
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Crocker SG, Milton P, King RJ. Proceedings: (3H)progesterone-binding to tissues of the human reproductive tract. J Endocrinol 1973; 59:17-8. [PMID: 4759584] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
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