1
|
Dymond A, Green W, Edwards M, Pont MAL, Gupta G. Economic Evaluation of Tirbanibulin for the Treatment of Actinic Keratosis in Scotland. Pharmacoecon Open 2023; 7:443-454. [PMID: 37012513 PMCID: PMC10170011 DOI: 10.1007/s41669-023-00410-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 03/19/2023] [Indexed: 05/11/2023]
Abstract
BACKGROUND Tirbanibulin 1% ointment is a new treatment for actinic keratosis (AK) on the face or scalp. A health economic model was developed as part of a submission to the Scottish Medicines Consortium to evaluate the cost-effectiveness of tirbanibulin compared to the most frequently prescribed treatments. METHODS A decision tree approach was used to calculate the costs and benefits of different treatment strategies for AK on the face or scalp over a one-year time horizon. Data on the relative efficacy of treatments, which were based on the probability of complete clearance of AK, were obtained from a network meta-analysis. Sensitivity and scenario analyses were performed to determine the robustness of the model results. RESULTS Tirbanibulin is estimated to be cost saving versus diclofenac sodium 3%, imiquimod 5% and fluorouracil 5%. Tirbanibulin remains cost saving when inputs are varied in sensitivity and scenario analyses. While the complete clearance rates are deemed similar across comparators, tirbanibulin is associated with a lower rate of severe local skin reactions, and a shorter treatment duration, which may improve treatment adherence. CONCLUSIONS Tirbanibulin is a cost saving intervention for the treatment of AK from the perspective of the Scottish Healthcare System.
Collapse
Affiliation(s)
- Amy Dymond
- York Health Economics Consortium, York, UK.
| | - Will Green
- York Health Economics Consortium, York, UK
| | | | | | - Girish Gupta
- Department of Dermatology, Edinburgh Royal Infirmary and College of Medicine and Veterinary Medicine, The University of Edinburgh, Edinburgh, UK
| |
Collapse
|
2
|
Hayne D, Stockler M, Martin A, Mccombie S, Zebic D, Krieger L, Anderson P, Bastick P, Beardsley E, Blatt A, Frydenberg M, Green W, Grummet J, Hawks C, Ischia J, Mitterdorfer A, Patel M, Roberts M, Sengupta S, Srivastav R, Winter M, Redfern A, Davis I. Adding Mitomycin to BCG as adjuvant intravesical therapy for high-risk, non-muscle-invasive -bladder cancer: A randomised phase 3 trial: The BCG+MM Study (ANZUP1301). Eur Urol 2023. [DOI: 10.1016/s0302-2838(23)00567-5] [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: 02/12/2023]
|
3
|
Bewley A, Barker E, Baker H, Green W, Avey B, Pi-Blanque A, Galván J, Trebbien P, Praestegaard M. An anchored matching-adjusted indirect comparison of fixed-dose combination calcipotriol and betamethasone dipropionate (Cal/BDP) cream versus Cal/BDP foam for the treatment of psoriasis. J DERMATOL TREAT 2022; 33:3191-3198. [PMID: 36036596 DOI: 10.1080/09546634.2022.2116924] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
OBJECTIVES To undertake a comparison of Cal/BDP cream versus foam for the treatment of plaque psoriasis, with cross-trial population differences accounted for. MATERIALS AND METHODS An anchored matching-adjusted indirect comparison was undertaken, using individual patient data for Cal/BDP cream and published aggregated data for Cal/BDP foam. Altogether, 11 outcomes were analyzed, including PGA success, mPASI75, DLQI-related outcomes and treatment satisfaction across numerous domains. For each outcome an odds ratio or mean difference was calculated to represent the relative efficacy of Cal/BDP cream versus foam. Methods were guided by NICE Decision Support Unit recommendations. RESULTS After adjustment, baseline characteristics were balanced across treatment arms in each analysis. There were no statistically significant differences in PGA success, mPASI75 or DLQI outcomes between Cal/BDP cream and foam when they were compared after their recommended treatment durations (8 weeks for cream and 4 weeks for foam). For treatment satisfaction after 1 week of treatment, Cal/BDP cream was significantly superior to the Cal/BDP foam in all but one domain of the questionnaire. CONCLUSIONS Cal/BDP cream and Cal/BDP foam have equivalent efficacy and HRQoL (measured in DLQI) outcomes when used for the topical treatment of plaque psoriasis at their recommended treatment durations. A comparison of treatment satisfaction assessments after 1 week of treatment demonstrated that patients find Cal/BDP cream to be more convenient than foam.
Collapse
Affiliation(s)
| | | | | | - Will Green
- York Health Economics Consortium, York, UK
| | | | | | | | | | | |
Collapse
|
4
|
Dymond A, Afonso D, Green W. Cost analysis of lurasidone for the treatment of schizophrenia in adolescents and adults within the United Kingdom. BMC Health Serv Res 2022; 22:1084. [PMID: 36002828 PMCID: PMC9404623 DOI: 10.1186/s12913-022-08436-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] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Accepted: 08/04/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Schizophrenia is a serious mental health condition characterised by distortions in thought processes, perception, mood, sense of self, and behaviour. Lurasidone, a second-generation atypical antipsychotic, represents an additional treatment option alongside existing antipsychotics for adolescents and adults with schizophrenia. An economic model was developed to evaluate the incremental costs of lurasidone as a first-line treatment option compared to existing antipsychotics. METHODS A Markov model was developed to estimate the cost impact of lurasidone as a first-line treatment option for both adolescents and adults. The sequence-based model incorporated the following health states: stable (no relapse or discontinuation), discontinuation (due to adverse events or other reasons), and relapse. Data used to determine the movement of patients between health states were obtained from network meta-analyses (NMAs). The time horizon ranged from three to five years (depending on the patient population) and a six-weekly cycle length was used. Unit costs and resource use were reflective of the UK NHS and Personal Social Services and consisted of the following categories: outpatient, adverse events, primary and residential care. Extensive deterministic sensitivity analysis was undertaken to assess the level of uncertainty associated with the base case results. RESULTS Lurasidone is demonstrated to be cost-saving as a first-line treatment within the adolescent and adult populations when compared to second-line and third-line respectively. Lurasidone is more expensive in terms of treatment costs, resource use (in the stable health state) and the treatment of adverse events. However, these costs are outweighed by the savings associated with the relapse health state. Lurasidone remains cost-saving when inputs are varied in sensitivity analysis and scenario analysis. CONCLUSIONS Lurasidone is a cost-saving first-line treatment for schizophrenia for both adolescents and adults.
Collapse
Affiliation(s)
- Amy Dymond
- York Health Economics Consortium (YHEC), York, UK.
| | | | - Will Green
- York Health Economics Consortium (YHEC), York, UK
| |
Collapse
|
5
|
Green W, Carrie S, Ahmed S, Goromonzi F, Stockle J, Bell E. A cost analysis of local anaesthetic nose and sinus surgery for the treatment of chronic rhinosinusitis. RHINOL 2022. [DOI: 10.4193/rhinol/21.050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
Background: People with chronic rhinosinusitis may be referred for endoscopic sinus surgery (ESS), a procedure commonly performed under general anaesthesia, once maximal medical therapy has failed. A new pathway of care is emerging: Local Anaesthetic Nose & Sinus Surgery (LANSS). With LANSS the patient is not placed under general anaesthesia, but instead the procedure is performed under a local anaesthetic. Methodology: A decision analytic model was developed from the perspective of the UK National Health Service (NHS) to assess the potential cost impact of LANSS versus current standard care pathway for ESS. Results: Modelling indicated that the introduction of LANSS would generate substantial savings of around £84,500 per year if introduced to a typical NHS trust with a large otolaryngology department undertaking 300 ESS procedures per year. These savings are generated as a proportion of the ESS procedures no longer need to be completed in an operating theatre, which reduces operational costs (saving around £64,500 per year), plus the use of local anaesthetic instead of general anaesthetic and a reduction in the time a patient spends as an inpatient. Conclusions: The uptake of LANSS could generate cost-savings of around £84,500 per year to a typical NHS trust in the UK.
Collapse
|
6
|
Thompson HA, Imai N, Dighe A, Ainslie KEC, Baguelin M, Bhatia S, Bhatt S, Boonyasiri A, Boyd O, Brazeau NF, Cattarino L, Cooper LV, Coupland H, Cucunuba Z, Cuomo-Dannenburg G, Djaafara B, Dorigatti I, van Elsland S, FitzJohn R, Fu H, Gaythorpe KAM, Green W, Hallett T, Hamlet A, Haw D, Hayes S, Hinsley W, Jeffrey B, Knock E, Laydon DJ, Lees J, Mangal TD, Mellan T, Mishra S, Mousa A, Nedjati-Gilani G, Nouvellet P, Okell L, Parag KV, Ragonnet-Cronin M, Riley S, Unwin HJT, Verity R, Vollmer M, Volz E, Walker PGT, Walters C, Wang H, Wang Y, Watson OJ, Whittaker C, Whittles LK, Winskill P, Xi X, Donnelly CA, Ferguson NM. SARS-CoV-2 infection prevalence on repatriation flights from Wuhan City, China. J Travel Med 2020; 27:5896041. [PMID: 32830853 PMCID: PMC7499665 DOI: 10.1093/jtm/taaa135] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Accepted: 08/14/2020] [Indexed: 11/14/2022]
Affiliation(s)
- Hayley A Thompson
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Natsuko Imai
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Amy Dighe
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Kylie E C Ainslie
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Marc Baguelin
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Sangeeta Bhatia
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Samir Bhatt
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Adhiratha Boonyasiri
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, London, UK
| | - Olivia Boyd
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Nicholas F Brazeau
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Lorenzo Cattarino
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Laura V Cooper
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Helen Coupland
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Zulma Cucunuba
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Gina Cuomo-Dannenburg
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Bimandra Djaafara
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Ilaria Dorigatti
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Sabine van Elsland
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Richard FitzJohn
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Han Fu
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Katy A M Gaythorpe
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Will Green
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Timothy Hallett
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Arran Hamlet
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - David Haw
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Sarah Hayes
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Wes Hinsley
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Benjamin Jeffrey
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Edward Knock
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Daniel J Laydon
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - John Lees
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Tara D Mangal
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Thomas Mellan
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Swapnil Mishra
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Andria Mousa
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Gemma Nedjati-Gilani
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Pierre Nouvellet
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK.,School of Life Sciences, University of Sussex, Sussex, UK
| | - Lucy Okell
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Kris V Parag
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Manon Ragonnet-Cronin
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Steven Riley
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - H Juliette T Unwin
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Robert Verity
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Michaela Vollmer
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Erik Volz
- 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
| | - Caroline Walters
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Haowei Wang
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Yuanrong Wang
- 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
| | - Charles Whittaker
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Lilith K Whittles
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Peter Winskill
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Xiaoyue Xi
- Department of Mathematics, Imperial College London, London, UK
| | - Christl A Donnelly
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK.,Department of Statistics, University of Oxford, Oxford, UK
| | - Neil M Ferguson
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| |
Collapse
|
7
|
Ainslie KEC, Walters CE, Fu H, Bhatia S, Wang H, Xi X, Baguelin M, Bhatt S, Boonyasiri A, Boyd O, Cattarino L, Ciavarella C, Cucunuba Z, Cuomo-Dannenburg G, Dighe A, Dorigatti I, van Elsland SL, FitzJohn R, Gaythorpe K, Ghani AC, Green W, Hamlet A, Hinsley W, Imai N, Jorgensen D, Knock E, Laydon D, Nedjati-Gilani G, Okell LC, Siveroni I, Thompson HA, Unwin HJT, Verity R, Vollmer M, Walker PGT, Wang Y, Watson OJ, Whittaker C, Winskill P, Donnelly CA, Ferguson NM, Riley S. Evidence of initial success for China exiting COVID-19 social distancing policy after achieving containment. Wellcome Open Res 2020; 5:81. [PMID: 32500100 PMCID: PMC7236587 DOI: 10.12688/wellcomeopenres.15843.2] [Citation(s) in RCA: 65] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/17/2020] [Indexed: 11/20/2022] Open
Abstract
Background: The COVID-19 epidemic was declared a Global Pandemic by WHO on 11 March 2020. By 24 March 2020, over 440,000 cases and almost 20,000 deaths had been reported worldwide. In response to the fast-growing epidemic, which began in the Chinese city of Wuhan, Hubei, China imposed strict social distancing in Wuhan on 23 January 2020 followed closely by similar measures in other provinces. These interventions have impacted economic productivity in China, and the ability of the Chinese economy to resume without restarting the epidemic was not clear. Methods: Using daily reported cases from mainland China and Hong Kong SAR, we estimated transmissibility over time and compared it to daily within-city movement, as a proxy for economic activity. Results: Initially, within-city movement and transmission were very strongly correlated in the five mainland provinces most affected by the epidemic and Beijing. However, that correlation decreased rapidly after the initial sharp fall in transmissibility. In general, towards the end of the study period, the correlation was no longer apparent, despite substantial increases in within-city movement. A similar analysis for Hong Kong shows that intermediate levels of local activity were maintained while avoiding a large outbreak. At the very end of the study period, when China began to experience the re-introduction of a small number of cases from Europe and the United States, there is an apparent up-tick in transmission. Conclusions: Although these results do not preclude future substantial increases in incidence, they suggest that after very intense social distancing (which resulted in containment), China successfully exited its lockdown to some degree. Elsewhere, movement data are being used as proxies for economic activity to assess the impact of interventions. The results presented here illustrate how the eventual decorrelation between transmission and movement is likely a key feature of successful COVID-19 exit strategies.
Collapse
Affiliation(s)
- Kylie E. C. Ainslie
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Caroline E. Walters
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Han Fu
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Sangeeta Bhatia
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Haowei Wang
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Xiaoyue Xi
- Department of Mathematics, Imperial College London, London, SW7 2AZ, UK
| | - Marc Baguelin
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Samir Bhatt
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Adhiratha Boonyasiri
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, London, SW7 2AZ, UK
| | - Olivia Boyd
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Lorenzo Cattarino
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Constanze Ciavarella
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Zulma Cucunuba
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Gina Cuomo-Dannenburg
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Amy Dighe
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Ilaria Dorigatti
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Sabine L van Elsland
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Rich FitzJohn
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Katy Gaythorpe
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Azra C Ghani
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Will Green
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Arran Hamlet
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Wes Hinsley
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Natsuko Imai
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - David Jorgensen
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Edward Knock
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Daniel Laydon
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Gemma Nedjati-Gilani
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Lucy C Okell
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Igor Siveroni
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Hayley A Thompson
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - H. Juliette T. Unwin
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Robert Verity
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Michaela Vollmer
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Patrick G T Walker
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Yuanrong Wang
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Oliver J Watson
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
- Department of Laboratory Medicine and Pathology, Brown University, Providence, RI, 02912, USA
| | - Charles Whittaker
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Peter Winskill
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Christl A Donnelly
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
- Department of Statistics, University of Oxford, Oxford, OX1 3LB, UK
| | - Neil M Ferguson
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Steven Riley
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| |
Collapse
|
8
|
Walker PGT, Whittaker C, Watson OJ, Baguelin M, Winskill P, Hamlet A, Djafaara BA, Cucunubá Z, Olivera Mesa D, Green W, Thompson H, Nayagam S, Ainslie KEC, Bhatia S, Bhatt S, Boonyasiri A, Boyd O, Brazeau NF, Cattarino L, Cuomo-Dannenburg G, Dighe A, Donnelly CA, Dorigatti I, van Elsland SL, FitzJohn R, Fu H, Gaythorpe KAM, Geidelberg L, Grassly N, Haw D, Hayes S, Hinsley W, Imai N, Jorgensen D, Knock E, Laydon D, Mishra S, Nedjati-Gilani G, Okell LC, Unwin HJ, Verity R, Vollmer M, Walters CE, Wang H, Wang Y, Xi X, Lalloo DG, Ferguson NM, Ghani AC. The impact of COVID-19 and strategies for mitigation and suppression in low- and middle-income countries. Science 2020; 369:413-422. [PMID: 32532802 PMCID: PMC7292504 DOI: 10.1126/science.abc0035] [Citation(s) in RCA: 483] [Impact Index Per Article: 120.8] [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: 04/01/2020] [Accepted: 06/09/2020] [Indexed: 12/28/2022]
Abstract
The ongoing coronavirus disease 2019 (COVID-19) pandemic poses a severe threat to public health worldwide. We combine data on demography, contact patterns, disease severity, and health care capacity and quality to understand its impact and inform strategies for its control. Younger populations in lower-income countries may reduce overall risk, but limited health system capacity coupled with closer intergenerational contact largely negates this benefit. Mitigation strategies that slow but do not interrupt transmission will still lead to COVID-19 epidemics rapidly overwhelming health systems, with substantial excess deaths in lower-income countries resulting from the poorer health care available. Of countries that have undertaken suppression to date, lower-income countries have acted earlier. However, this will need to be maintained or triggered more frequently in these settings to keep below available health capacity, with associated detrimental consequences for the wider health, well-being, and economies of these countries.
Collapse
Affiliation(s)
- Patrick G T Walker
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
| | - Charles Whittaker
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Oliver J Watson
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
- Pathology and Laboratory Medicine, Warren Alpert Medical School, Brown University, Providence, RI, USA
| | - Marc Baguelin
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Peter Winskill
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Arran Hamlet
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Bimandra A Djafaara
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Zulma Cucunubá
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Daniela Olivera Mesa
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Will Green
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Hayley Thompson
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Shevanthi Nayagam
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Kylie E C Ainslie
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Sangeeta Bhatia
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Samir Bhatt
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Adhiratha Boonyasiri
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Olivia Boyd
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Nicholas F Brazeau
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Lorenzo Cattarino
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Gina Cuomo-Dannenburg
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Amy Dighe
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Christl A Donnelly
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
- Department of Statistics, University of Oxford, Oxford, UK
| | - Ilaria Dorigatti
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Sabine L van Elsland
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Rich FitzJohn
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Han Fu
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Katy A M Gaythorpe
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Lily Geidelberg
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Nicholas Grassly
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - David Haw
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Sarah Hayes
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Wes Hinsley
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Natsuko Imai
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - David Jorgensen
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Edward Knock
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Daniel Laydon
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Swapnil Mishra
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Gemma Nedjati-Gilani
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Lucy C Okell
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - H Juliette Unwin
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Robert Verity
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Michaela Vollmer
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Caroline E Walters
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Haowei Wang
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Yuanrong Wang
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Xiaoyue Xi
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | | | - Neil M Ferguson
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
| | - Azra C Ghani
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
| |
Collapse
|
9
|
Walker PGT, Whittaker C, Watson OJ, Baguelin M, Winskill P, Hamlet A, Djafaara BA, Cucunubá Z, Olivera Mesa D, Green W, Thompson H, Nayagam S, Ainslie KEC, Bhatia S, Bhatt S, Boonyasiri A, Boyd O, Brazeau NF, Cattarino L, Cuomo-Dannenburg G, Dighe A, Donnelly CA, Dorigatti I, van Elsland SL, FitzJohn R, Fu H, Gaythorpe KAM, Geidelberg L, Grassly N, Haw D, Hayes S, Hinsley W, Imai N, Jorgensen D, Knock E, Laydon D, Mishra S, Nedjati-Gilani G, Okell LC, Unwin HJ, Verity R, Vollmer M, Walters CE, Wang H, Wang Y, Xi X, Lalloo DG, Ferguson NM, Ghani AC. The impact of COVID-19 and strategies for mitigation and suppression in low- and middle-income countries. Science 2020; 369:413-422. [PMID: 32532802 DOI: 10.25561/77735] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Accepted: 06/09/2020] [Indexed: 05/26/2023]
Abstract
The ongoing coronavirus disease 2019 (COVID-19) pandemic poses a severe threat to public health worldwide. We combine data on demography, contact patterns, disease severity, and health care capacity and quality to understand its impact and inform strategies for its control. Younger populations in lower-income countries may reduce overall risk, but limited health system capacity coupled with closer intergenerational contact largely negates this benefit. Mitigation strategies that slow but do not interrupt transmission will still lead to COVID-19 epidemics rapidly overwhelming health systems, with substantial excess deaths in lower-income countries resulting from the poorer health care available. Of countries that have undertaken suppression to date, lower-income countries have acted earlier. However, this will need to be maintained or triggered more frequently in these settings to keep below available health capacity, with associated detrimental consequences for the wider health, well-being, and economies of these countries.
Collapse
Affiliation(s)
- Patrick G T Walker
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
| | - Charles Whittaker
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Oliver J Watson
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
- Pathology and Laboratory Medicine, Warren Alpert Medical School, Brown University, Providence, RI, USA
| | - Marc Baguelin
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Peter Winskill
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Arran Hamlet
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Bimandra A Djafaara
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Zulma Cucunubá
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Daniela Olivera Mesa
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Will Green
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Hayley Thompson
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Shevanthi Nayagam
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Kylie E C Ainslie
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Sangeeta Bhatia
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Samir Bhatt
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Adhiratha Boonyasiri
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Olivia Boyd
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Nicholas F Brazeau
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Lorenzo Cattarino
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Gina Cuomo-Dannenburg
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Amy Dighe
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Christl A Donnelly
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
- Department of Statistics, University of Oxford, Oxford, UK
| | - Ilaria Dorigatti
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Sabine L van Elsland
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Rich FitzJohn
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Han Fu
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Katy A M Gaythorpe
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Lily Geidelberg
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Nicholas Grassly
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - David Haw
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Sarah Hayes
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Wes Hinsley
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Natsuko Imai
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - David Jorgensen
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Edward Knock
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Daniel Laydon
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Swapnil Mishra
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Gemma Nedjati-Gilani
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Lucy C Okell
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - H Juliette Unwin
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Robert Verity
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Michaela Vollmer
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Caroline E Walters
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Haowei Wang
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Yuanrong Wang
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Xiaoyue Xi
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | | | - Neil M Ferguson
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
| | - Azra C Ghani
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
| |
Collapse
|
10
|
Verity R, Okell LC, Dorigatti I, Winskill P, Whittaker C, Imai N, Cuomo-Dannenburg G, Thompson H, Walker PGT, Fu H, Dighe A, Griffin JT, Baguelin M, Bhatia S, Boonyasiri A, Cori A, Cucunubá Z, FitzJohn R, Gaythorpe K, Green W, Hamlet A, Hinsley W, Laydon D, Nedjati-Gilani G, Riley S, van Elsland S, Volz E, Wang H, Wang Y, Xi X, Donnelly CA, Ghani AC, Ferguson NM. Estimates of the severity of coronavirus disease 2019: a model-based analysis. Lancet Infect Dis 2020; 20:669-677. [PMID: 32240634 PMCID: PMC7158570 DOI: 10.1016/s1473-3099(20)30243-7] [Citation(s) in RCA: 2105] [Impact Index Per Article: 526.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Revised: 03/20/2020] [Accepted: 03/20/2020] [Indexed: 02/07/2023]
Abstract
BACKGROUND In the face of rapidly changing data, a range of case fatality ratio estimates for coronavirus disease 2019 (COVID-19) have been produced that differ substantially in magnitude. We aimed to provide robust estimates, accounting for censoring and ascertainment biases. METHODS We collected individual-case data for patients who died from COVID-19 in Hubei, mainland China (reported by national and provincial health commissions to Feb 8, 2020), and for cases outside of mainland China (from government or ministry of health websites and media reports for 37 countries, as well as Hong Kong and Macau, until Feb 25, 2020). These individual-case data were used to estimate the time between onset of symptoms and outcome (death or discharge from hospital). We next obtained age-stratified estimates of the case fatality ratio by relating the aggregate distribution of cases to the observed cumulative deaths in China, assuming a constant attack rate by age and adjusting for demography and age-based and location-based under-ascertainment. We also estimated the case fatality ratio from individual line-list data on 1334 cases identified outside of mainland China. Using data on the prevalence of PCR-confirmed cases in international residents repatriated from China, we obtained age-stratified estimates of the infection fatality ratio. Furthermore, data on age-stratified severity in a subset of 3665 cases from China were used to estimate the proportion of infected individuals who are likely to require hospitalisation. FINDINGS Using data on 24 deaths that occurred in mainland China and 165 recoveries outside of China, we estimated the mean duration from onset of symptoms to death to be 17·8 days (95% credible interval [CrI] 16·9-19·2) and to hospital discharge to be 24·7 days (22·9-28·1). In all laboratory confirmed and clinically diagnosed cases from mainland China (n=70 117), we estimated a crude case fatality ratio (adjusted for censoring) of 3·67% (95% CrI 3·56-3·80). However, after further adjusting for demography and under-ascertainment, we obtained a best estimate of the case fatality ratio in China of 1·38% (1·23-1·53), with substantially higher ratios in older age groups (0·32% [0·27-0·38] in those aged <60 years vs 6·4% [5·7-7·2] in those aged ≥60 years), up to 13·4% (11·2-15·9) in those aged 80 years or older. Estimates of case fatality ratio from international cases stratified by age were consistent with those from China (parametric estimate 1·4% [0·4-3·5] in those aged <60 years [n=360] and 4·5% [1·8-11·1] in those aged ≥60 years [n=151]). Our estimated overall infection fatality ratio for China was 0·66% (0·39-1·33), with an increasing profile with age. Similarly, estimates of the proportion of infected individuals likely to be hospitalised increased with age up to a maximum of 18·4% (11·0-37·6) in those aged 80 years or older. INTERPRETATION These early estimates give an indication of the fatality ratio across the spectrum of COVID-19 disease and show a strong age gradient in risk of death. FUNDING UK Medical Research Council.
Collapse
Affiliation(s)
- Robert Verity
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Lucy C Okell
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Ilaria Dorigatti
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Peter Winskill
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Charles Whittaker
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Natsuko Imai
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Gina Cuomo-Dannenburg
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Hayley Thompson
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Patrick G T Walker
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Han Fu
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Amy Dighe
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Jamie T Griffin
- School of Mathematical Sciences, Queen Mary University of London, London, UK
| | - Marc Baguelin
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Sangeeta Bhatia
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Adhiratha Boonyasiri
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Anne Cori
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Zulma Cucunubá
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Rich FitzJohn
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Katy Gaythorpe
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Will Green
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Arran Hamlet
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Wes Hinsley
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Daniel Laydon
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Gemma Nedjati-Gilani
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Steven Riley
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Sabine van Elsland
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Erik Volz
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Haowei Wang
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Yuanrong Wang
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Xiaoyue Xi
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Christl A Donnelly
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK; Department of Statistics, University of Oxford, Oxford, UK
| | - Azra C Ghani
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
| | - Neil M Ferguson
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
| |
Collapse
|
11
|
Verity R, Okell LC, Dorigatti I, Winskill P, Whittaker C, Imai N, Cuomo-Dannenburg G, Thompson H, Walker PGT, Fu H, Dighe A, Griffin JT, Baguelin M, Bhatia S, Boonyasiri A, Cori A, Cucunubá Z, FitzJohn R, Gaythorpe K, Green W, Hamlet A, Hinsley W, Laydon D, Nedjati-Gilani G, Riley S, van Elsland S, Volz E, Wang H, Wang Y, Xi X, Donnelly CA, Ghani AC, Ferguson NM. Estimates of the severity of coronavirus disease 2019: a model-based analysis. Lancet Infect Dis 2020; 20:669-677. [PMID: 32240634 DOI: 10.1101/2020.03.09.20033357] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Revised: 03/20/2020] [Accepted: 03/20/2020] [Indexed: 05/25/2023]
Abstract
BACKGROUND In the face of rapidly changing data, a range of case fatality ratio estimates for coronavirus disease 2019 (COVID-19) have been produced that differ substantially in magnitude. We aimed to provide robust estimates, accounting for censoring and ascertainment biases. METHODS We collected individual-case data for patients who died from COVID-19 in Hubei, mainland China (reported by national and provincial health commissions to Feb 8, 2020), and for cases outside of mainland China (from government or ministry of health websites and media reports for 37 countries, as well as Hong Kong and Macau, until Feb 25, 2020). These individual-case data were used to estimate the time between onset of symptoms and outcome (death or discharge from hospital). We next obtained age-stratified estimates of the case fatality ratio by relating the aggregate distribution of cases to the observed cumulative deaths in China, assuming a constant attack rate by age and adjusting for demography and age-based and location-based under-ascertainment. We also estimated the case fatality ratio from individual line-list data on 1334 cases identified outside of mainland China. Using data on the prevalence of PCR-confirmed cases in international residents repatriated from China, we obtained age-stratified estimates of the infection fatality ratio. Furthermore, data on age-stratified severity in a subset of 3665 cases from China were used to estimate the proportion of infected individuals who are likely to require hospitalisation. FINDINGS Using data on 24 deaths that occurred in mainland China and 165 recoveries outside of China, we estimated the mean duration from onset of symptoms to death to be 17·8 days (95% credible interval [CrI] 16·9-19·2) and to hospital discharge to be 24·7 days (22·9-28·1). In all laboratory confirmed and clinically diagnosed cases from mainland China (n=70 117), we estimated a crude case fatality ratio (adjusted for censoring) of 3·67% (95% CrI 3·56-3·80). However, after further adjusting for demography and under-ascertainment, we obtained a best estimate of the case fatality ratio in China of 1·38% (1·23-1·53), with substantially higher ratios in older age groups (0·32% [0·27-0·38] in those aged <60 years vs 6·4% [5·7-7·2] in those aged ≥60 years), up to 13·4% (11·2-15·9) in those aged 80 years or older. Estimates of case fatality ratio from international cases stratified by age were consistent with those from China (parametric estimate 1·4% [0·4-3·5] in those aged <60 years [n=360] and 4·5% [1·8-11·1] in those aged ≥60 years [n=151]). Our estimated overall infection fatality ratio for China was 0·66% (0·39-1·33), with an increasing profile with age. Similarly, estimates of the proportion of infected individuals likely to be hospitalised increased with age up to a maximum of 18·4% (11·0-37·6) in those aged 80 years or older. INTERPRETATION These early estimates give an indication of the fatality ratio across the spectrum of COVID-19 disease and show a strong age gradient in risk of death. FUNDING UK Medical Research Council.
Collapse
Affiliation(s)
- Robert Verity
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Lucy C Okell
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Ilaria Dorigatti
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Peter Winskill
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Charles Whittaker
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Natsuko Imai
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Gina Cuomo-Dannenburg
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Hayley Thompson
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Patrick G T Walker
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Han Fu
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Amy Dighe
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Jamie T Griffin
- School of Mathematical Sciences, Queen Mary University of London, London, UK
| | - Marc Baguelin
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Sangeeta Bhatia
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Adhiratha Boonyasiri
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Anne Cori
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Zulma Cucunubá
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Rich FitzJohn
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Katy Gaythorpe
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Will Green
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Arran Hamlet
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Wes Hinsley
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Daniel Laydon
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Gemma Nedjati-Gilani
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Steven Riley
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Sabine van Elsland
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Erik Volz
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Haowei Wang
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Yuanrong Wang
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Xiaoyue Xi
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Christl A Donnelly
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK; Department of Statistics, University of Oxford, Oxford, UK
| | - Azra C Ghani
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
| | - Neil M Ferguson
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
| |
Collapse
|
12
|
Verity R, Okell LC, Dorigatti I, Winskill P, Whittaker C, Imai N, Cuomo-Dannenburg G, Thompson H, Walker PGT, Fu H, Dighe A, Griffin JT, Baguelin M, Bhatia S, Boonyasiri A, Cori A, Cucunubá Z, FitzJohn R, Gaythorpe K, Green W, Hamlet A, Hinsley W, Laydon D, Nedjati-Gilani G, Riley S, van Elsland S, Volz E, Wang H, Wang Y, Xi X, Donnelly CA, Ghani AC, Ferguson NM. Estimates of the severity of coronavirus disease 2019: a model-based analysis. Lancet Infect Dis 2020; 20:669-677. [PMID: 32240634 DOI: 10.1101/2020.03.09.20033357v1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Revised: 03/20/2020] [Accepted: 03/20/2020] [Indexed: 05/23/2023]
Abstract
BACKGROUND In the face of rapidly changing data, a range of case fatality ratio estimates for coronavirus disease 2019 (COVID-19) have been produced that differ substantially in magnitude. We aimed to provide robust estimates, accounting for censoring and ascertainment biases. METHODS We collected individual-case data for patients who died from COVID-19 in Hubei, mainland China (reported by national and provincial health commissions to Feb 8, 2020), and for cases outside of mainland China (from government or ministry of health websites and media reports for 37 countries, as well as Hong Kong and Macau, until Feb 25, 2020). These individual-case data were used to estimate the time between onset of symptoms and outcome (death or discharge from hospital). We next obtained age-stratified estimates of the case fatality ratio by relating the aggregate distribution of cases to the observed cumulative deaths in China, assuming a constant attack rate by age and adjusting for demography and age-based and location-based under-ascertainment. We also estimated the case fatality ratio from individual line-list data on 1334 cases identified outside of mainland China. Using data on the prevalence of PCR-confirmed cases in international residents repatriated from China, we obtained age-stratified estimates of the infection fatality ratio. Furthermore, data on age-stratified severity in a subset of 3665 cases from China were used to estimate the proportion of infected individuals who are likely to require hospitalisation. FINDINGS Using data on 24 deaths that occurred in mainland China and 165 recoveries outside of China, we estimated the mean duration from onset of symptoms to death to be 17·8 days (95% credible interval [CrI] 16·9-19·2) and to hospital discharge to be 24·7 days (22·9-28·1). In all laboratory confirmed and clinically diagnosed cases from mainland China (n=70 117), we estimated a crude case fatality ratio (adjusted for censoring) of 3·67% (95% CrI 3·56-3·80). However, after further adjusting for demography and under-ascertainment, we obtained a best estimate of the case fatality ratio in China of 1·38% (1·23-1·53), with substantially higher ratios in older age groups (0·32% [0·27-0·38] in those aged <60 years vs 6·4% [5·7-7·2] in those aged ≥60 years), up to 13·4% (11·2-15·9) in those aged 80 years or older. Estimates of case fatality ratio from international cases stratified by age were consistent with those from China (parametric estimate 1·4% [0·4-3·5] in those aged <60 years [n=360] and 4·5% [1·8-11·1] in those aged ≥60 years [n=151]). Our estimated overall infection fatality ratio for China was 0·66% (0·39-1·33), with an increasing profile with age. Similarly, estimates of the proportion of infected individuals likely to be hospitalised increased with age up to a maximum of 18·4% (11·0-37·6) in those aged 80 years or older. INTERPRETATION These early estimates give an indication of the fatality ratio across the spectrum of COVID-19 disease and show a strong age gradient in risk of death. FUNDING UK Medical Research Council.
Collapse
Affiliation(s)
- Robert Verity
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Lucy C Okell
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Ilaria Dorigatti
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Peter Winskill
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Charles Whittaker
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Natsuko Imai
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Gina Cuomo-Dannenburg
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Hayley Thompson
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Patrick G T Walker
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Han Fu
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Amy Dighe
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Jamie T Griffin
- School of Mathematical Sciences, Queen Mary University of London, London, UK
| | - Marc Baguelin
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Sangeeta Bhatia
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Adhiratha Boonyasiri
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Anne Cori
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Zulma Cucunubá
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Rich FitzJohn
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Katy Gaythorpe
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Will Green
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Arran Hamlet
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Wes Hinsley
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Daniel Laydon
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Gemma Nedjati-Gilani
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Steven Riley
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Sabine van Elsland
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Erik Volz
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Haowei Wang
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Yuanrong Wang
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Xiaoyue Xi
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Christl A Donnelly
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK; Department of Statistics, University of Oxford, Oxford, UK
| | - Azra C Ghani
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
| | - Neil M Ferguson
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics, and Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
| |
Collapse
|
13
|
Ainslie KEC, Walters CE, Fu H, Bhatia S, Wang H, Xi X, Baguelin M, Bhatt S, Boonyasiri A, Boyd O, Cattarino L, Ciavarella C, Cucunuba Z, Cuomo-Dannenburg G, Dighe A, Dorigatti I, van Elsland SL, FitzJohn R, Gaythorpe K, Ghani AC, Green W, Hamlet A, Hinsley W, Imai N, Jorgensen D, Knock E, Laydon D, Nedjati-Gilani G, Okell LC, Siveroni I, Thompson HA, Unwin HJT, Verity R, Vollmer M, Walker PGT, Wang Y, Watson OJ, Whittaker C, Winskill P, Donnelly CA, Ferguson NM, Riley S. Evidence of initial success for China exiting COVID-19 social distancing policy after achieving containment. Wellcome Open Res 2020; 5:81. [PMID: 32500100 PMCID: PMC7236587 DOI: 10.12688/wellcomeopenres.15843.1] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/14/2020] [Indexed: 11/20/2022] Open
Abstract
Background: The COVID-19 epidemic was declared a Global Pandemic by WHO on 11 March 2020. By 24 March 2020, over 440,000 cases and almost 20,000 deaths had been reported worldwide. In response to the fast-growing epidemic, which began in the Chinese city of Wuhan, Hubei, China imposed strict social distancing in Wuhan on 23 January 2020 followed closely by similar measures in other provinces. These interventions have impacted economic productivity in China, and the ability of the Chinese economy to resume without restarting the epidemic was not clear. Methods: Using daily reported cases from mainland China and Hong Kong SAR, we estimated transmissibility over time and compared it to daily within-city movement, as a proxy for economic activity. Results: Initially, within-city movement and transmission were very strongly correlated in the five mainland provinces most affected by the epidemic and Beijing. However, that correlation decreased rapidly after the initial sharp fall in transmissibility. In general, towards the end of the study period, the correlation was no longer apparent, despite substantial increases in within-city movement. A similar analysis for Hong Kong shows that intermediate levels of local activity were maintained while avoiding a large outbreak. At the very end of the study period, when China began to experience the re-introduction of a small number of cases from Europe and the United States, there is an apparent up-tick in transmission. Conclusions: Although these results do not preclude future substantial increases in incidence, they suggest that after very intense social distancing (which resulted in containment), China successfully exited its lockdown to some degree. Elsewhere, movement data are being used as proxies for economic activity to assess the impact of interventions. The results presented here illustrate how the eventual decorrelation between transmission and movement is likely a key feature of successful COVID-19 exit strategies.
Collapse
Affiliation(s)
- Kylie E. C. Ainslie
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Caroline E. Walters
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Han Fu
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Sangeeta Bhatia
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Haowei Wang
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Xiaoyue Xi
- Department of Mathematics, Imperial College London, London, SW7 2AZ, UK
| | - Marc Baguelin
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Samir Bhatt
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Adhiratha Boonyasiri
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, London, SW7 2AZ, UK
| | - Olivia Boyd
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Lorenzo Cattarino
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Constanze Ciavarella
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Zulma Cucunuba
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Gina Cuomo-Dannenburg
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Amy Dighe
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Ilaria Dorigatti
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Sabine L van Elsland
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Rich FitzJohn
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Katy Gaythorpe
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Azra C Ghani
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Will Green
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Arran Hamlet
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Wes Hinsley
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Natsuko Imai
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - David Jorgensen
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Edward Knock
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Daniel Laydon
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Gemma Nedjati-Gilani
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Lucy C Okell
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Igor Siveroni
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Hayley A Thompson
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - H. Juliette T. Unwin
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Robert Verity
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Michaela Vollmer
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Patrick G T Walker
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Yuanrong Wang
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Oliver J Watson
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
- Department of Laboratory Medicine and Pathology, Brown University, Providence, RI, 02912, USA
| | - Charles Whittaker
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Peter Winskill
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Christl A Donnelly
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
- Department of Statistics, University of Oxford, Oxford, OX1 3LB, UK
| | - Neil M Ferguson
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| | - Steven Riley
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, UK
| |
Collapse
|
14
|
Liow ECH, Hayne D, Stockler MR, Martin AJ, Sengupta S, Anderson P, Ford K, Frydenberg M, Gorzeman M, Green W, Grummet J, Hawks C, Krieger LEM, Ischia J, McCombie S, Patel M, Davis ID. Adding mitomycin to Bacillus Calmette-Guérin as adjuvant intravesical therapy for high-risk, nonmuscle-invasive urothelial bladder cancer (BCGMM; ANZUP 1301). J Clin Oncol 2020. [DOI: 10.1200/jco.2020.38.6_suppl.tps602] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
TPS602 Background: Adjuvant intravesical bacillus Calmette-Guérin (BCG) decreases disease recurrence and progression in people with high-risk, non-muscle invasive urothelial bladder cancer (NMIBC), however recurrence occurs in 30% despite optimal therapy. Recent meta-analyses evaluating addition of intravesical mitomycin (MM) to BCG showed lower rates of recurrence and cancer-specific mortality in people with NMIBC who received combination regimens. Good quality randomized trials to definitively test this combination are lacking. The BCGMM trial (NCT02948543) will be the largest study to date evaluating this approach in people with high-risk NMIBC. Methods: This open-label phase 3 trial aims to randomize 500 participants, stratified by stage, site of disease, and presence of carcinoma in-situ, to Arm A (BCG induction weekly x6 then monthly x10) or Arm B (BCG + MM weekly x9 then monthly x9). This study is powered to detect a 10% improvement in 2-year disease free survival (DFS) at 5% level of significance with 85% power. Stage 1 of this study, designed to recruit 130 patients to determine rates of treatment completion, activity reflected by cystoscopic findings at 3 months, adverse events, resource use, and health related quality of life, has completed enrolment and successfully established feasibility of this trial protocol. Stage 2, aiming for a further 370 patients, will inform on additional endpoints including differences in DFS, time to recurrence and progression, overall survival, and potential predictive biomarkers, is estimated to complete accrual in December 2020. Successful treatment completion, defined as 75% or more of planned treatment doses, has been achieved in 76% of patients treated in the experimental arm of Stage 1, compared to 60% in those allocated BCG alone. Clinical trial information: NCT02948543.
Collapse
Affiliation(s)
| | - Dickon Hayne
- UWA Medical School, University of Western Australia, Perth, Australia
| | - Martin R. Stockler
- NHMRC Clinical Trials Centre, The University of Sydney, Sydney, Australia
| | | | - Shomik Sengupta
- Olivia Newton-John Cancer Wellness and Research Centre, Melbourne, Australia
| | | | - Kate Ford
- NHMRC Clinical Trials Centre, The University of Sydney, Sydney, Australia
| | | | - Margot Gorzeman
- NHMRC Clinical Trials Centre, University of Sydney, Sydney, Australia
| | - Will Green
- Nottingham University Hospital, Nottingham, United Kingdom
| | | | | | | | | | | | | | - Ian D. Davis
- Monash University Eastern Health Clinical School, Melbourne, Australia
| | | |
Collapse
|
15
|
Thomas HJD, Myers‐Smith IH, Bjorkman AD, Elmendorf SC, Blok D, Cornelissen JHC, Forbes BC, Hollister RD, Normand S, Prevéy JS, Rixen C, Schaepman‐Strub G, Wilmking M, Wipf S, Cornwell WK, Kattge J, Goetz SJ, Guay KC, Alatalo JM, Anadon‐Rosell A, Angers‐Blondin S, Berner LT, Björk RG, Buchwal A, Buras A, Carbognani M, Christie K, Siegwart Collier L, Cooper EJ, Eskelinen A, Frei ER, Grau O, Grogan P, Hallinger M, Heijmans MMPD, Hermanutz L, Hudson JMG, Hülber K, Iturrate‐Garcia M, Iversen CM, Jaroszynska F, Johnstone JF, Kaarlejärvi E, Kulonen A, Lamarque LJ, Lévesque E, Little CJ, Michelsen A, Milbau A, Nabe‐Nielsen J, Nielsen SS, Ninot JM, Oberbauer SF, Olofsson J, Onipchenko VG, Petraglia A, Rumpf SB, Semenchuk PR, Soudzilovskaia NA, Spasojevic MJ, Speed JDM, Tape KD, te Beest M, Tomaselli M, Trant A, Treier UA, Venn S, Vowles T, Weijers S, Zamin T, Atkin OK, Bahn M, Blonder B, Campetella G, Cerabolini BEL, Chapin III FS, Dainese M, de Vries FT, Díaz S, Green W, Jackson RB, Manning P, Niinemets Ü, Ozinga WA, Peñuelas J, Reich PB, Schamp B, Sheremetev S, van Bodegom PM. Traditional plant functional groups explain variation in economic but not size-related traits across the tundra biome. Glob Ecol Biogeogr 2019; 28:78-95. [PMID: 31007605 PMCID: PMC6472633 DOI: 10.1111/geb.12783] [Citation(s) in RCA: 5] [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] [Subscribe] [Scholar Register] [Received: 09/20/2017] [Revised: 05/24/2018] [Accepted: 05/29/2018] [Indexed: 06/01/2023]
Abstract
AIM Plant functional groups are widely used in community ecology and earth system modelling to describe trait variation within and across plant communities. However, this approach rests on the assumption that functional groups explain a large proportion of trait variation among species. We test whether four commonly used plant functional groups represent variation in six ecologically important plant traits. LOCATION Tundra biome. TIME PERIOD Data collected between 1964 and 2016. MAJOR TAXA STUDIED 295 tundra vascular plant species. METHODS We compiled a database of six plant traits (plant height, leaf area, specific leaf area, leaf dry matter content, leaf nitrogen, seed mass) for tundra species. We examined the variation in species-level trait expression explained by four traditional functional groups (evergreen shrubs, deciduous shrubs, graminoids, forbs), and whether variation explained was dependent upon the traits included in analysis. We further compared the explanatory power and species composition of functional groups to alternative classifications generated using post hoc clustering of species-level traits. RESULTS Traditional functional groups explained significant differences in trait expression, particularly amongst traits associated with resource economics, which were consistent across sites and at the biome scale. However, functional groups explained 19% of overall trait variation and poorly represented differences in traits associated with plant size. Post hoc classification of species did not correspond well with traditional functional groups, and explained twice as much variation in species-level trait expression. MAIN CONCLUSIONS Traditional functional groups only coarsely represent variation in well-measured traits within tundra plant communities, and better explain resource economic traits than size-related traits. We recommend caution when using functional group approaches to predict tundra vegetation change, or ecosystem functions relating to plant size, such as albedo or carbon storage. We argue that alternative classifications or direct use of specific plant traits could provide new insights for ecological prediction and modelling.
Collapse
Affiliation(s)
- H. J. D. Thomas
- School of GeosciencesUniversity of EdinburghEdinburghUnited Kingdom
| | | | - A. D. Bjorkman
- School of GeosciencesUniversity of EdinburghEdinburghUnited Kingdom
- Ecoinformatics and Biodiversity, Department of Bioscience, Aarhus UniversityAarhusDenmark
- Senckenberg Gesellschaft für Naturforschung, Biodiversity and Climate Research Centre (SBiK‐F)FrankfurtGermany
| | - S. C. Elmendorf
- Institute of Arctic and Alpine Research, University of ColoradoBoulderColorado
| | - D. Blok
- Department of Physical Geography and Ecosystem Science, Lund UniversityLundSweden
| | | | - B. C. Forbes
- Arctic Centre, University of LaplandRovaniemiFinland
| | - R. D. Hollister
- Biology Department, Grand Valley State UniversityAllendaleMichigan
| | - S. Normand
- Ecoinformatics and Biodiversity, Department of Bioscience, Aarhus UniversityAarhusDenmark
| | - J. S. Prevéy
- WSL Institute for Snow and Avalanche Research SLFDavosSwitzerland
| | - C. Rixen
- WSL Institute for Snow and Avalanche Research SLFDavosSwitzerland
| | - G. Schaepman‐Strub
- Department of Evolutionary Biology and Environmental Studies, University of ZurichZurichSwitzerland
| | - M. Wilmking
- Institute for Botany and Landscape Ecology, Greifswald UniversityGreifswaldGermany
| | - S. Wipf
- WSL Institute for Snow and Avalanche Research SLFDavosSwitzerland
| | - W. K. Cornwell
- School of Biological Earth and Environmental Sciences, University of New South WalesSydneyNew South WalesAustralia
| | - J. Kattge
- Max Planck Institute for BiogeochemistryJenaGermany
- German Centre for Integrative Biodiversity Research (iDiv)Halle‐Jena‐LeipzigGermany
| | - S. J. Goetz
- School of Informatics, Computing, and Cyber Systems, Northern Arizona UniversityFlagstaffArizona
| | - K. C. Guay
- Bigelow Laboratory for Ocean SciencesBoothbayMaine
| | - J. M. Alatalo
- Department of Biological and Environmental Sciences, Qatar UniversityDohaQatar
| | - A. Anadon‐Rosell
- Institute for Botany and Landscape Ecology, Greifswald UniversityGreifswaldGermany
- Department of Evolutionary Biology, Ecology and Environmental Sciences, University of BarcelonaBarcelonaSpain
- Biodiversity Research InstituteUniversity of BarcelonaBarcelonaSpain
| | | | - L. T. Berner
- School of Informatics, Computing, and Cyber Systems, Northern Arizona UniversityFlagstaffArizona
| | - R. G. Björk
- Department of Earth Sciences, University of GothenburgGothenburgSweden
- Gothenburg Global Biodiversity CentreGothenburgSweden
| | - A. Buchwal
- Institute of Geoecology and Geoinformation, Adam Mickiewicz UniversityPoznanPoland
- Department of Biological Sciences, University of Alaska AnchorageAnchorageAlaska
| | - A. Buras
- Forest Ecology and Forest Management, Wageningen University and Research, WageningenNetherlands
| | - M. Carbognani
- Department of Chemistry, Life Sciences and Environmental Sustainability, University of ParmaParmaItaly
| | - K. Christie
- The Alaska Department of Fish and GameJuneauAlaska
| | - L. Siegwart Collier
- Department of Biology, Memorial UniversitySt John’s, Newfoundland and LabradorCanada
| | - E. J. Cooper
- Department of Arctic and Marine Biology, UiT‐The Arctic University of NorwayTromsøNorway
| | - A. Eskelinen
- German Centre for Integrative Biodiversity Research (iDiv)Halle‐Jena‐LeipzigGermany
- Department of Physiological Diversity, Helmholtz Centre for Environmental Research – UFZLeipzigGermany
- Department of Ecology and Genetics, University of OuluOuluFinland
| | - E. R. Frei
- Department of Geography, University of British ColumbiaVancouverBritish ColumbiaCanada
| | - O. Grau
- Global Ecology Unit, CREAF‐CSIC‐UAB‐UBBellaterraSpain
| | - P. Grogan
- Department of Biology, Queen's UniversityKingston, OntarioCanada
| | - M. Hallinger
- Biology Department, Swedish Agricultural University (SLU)UppsalaSweden
| | - M. M. P. D. Heijmans
- Plant Ecology and Nature Conservation Group, Wageningen University & ResearchWageningenThe Netherlands
| | - L. Hermanutz
- Department of Biology, Memorial UniversitySt John’s, Newfoundland and LabradorCanada
| | | | - K. Hülber
- Department of Botany and Biodiversity Research, University of ViennaViennaAustria
| | - M. Iturrate‐Garcia
- Department of Evolutionary Biology and Environmental Studies, University of ZurichZurichSwitzerland
| | - C. M. Iversen
- Climate Change Science Institute and Environmental Sciences Division, Oak Ridge National LaboratoryOak RidgeTennessee
| | | | - J. F. Johnstone
- Department of Biology, University of SaskatchewanSaskatoonCanada
| | - E. Kaarlejärvi
- Department of Ecology and Environmental Sciences, Umeå UniversityUmeåSweden
- Department of Biology, Vrije Universiteit Brussel (VUB)BrusselsBelgium
- Faculty of Biological and Environmental Sciences, University of HelsinkiHelsinkiFinland
| | - A. Kulonen
- WSL Institute for Snow and Avalanche Research SLFDavosSwitzerland
- Department of Biology, University of BergenBergenNorway
| | - L. J. Lamarque
- Département des Sciences de l'Environnement and Centres d'études nordiques, Université du Québec à Trois‐RivièresTrois‐RivièresQuebecCanada
| | - E. Lévesque
- Département des Sciences de l'Environnement and Centres d'études nordiques, Université du Québec à Trois‐RivièresTrois‐RivièresQuebecCanada
| | - C. J. Little
- Department of Evolutionary Biology and Environmental Studies, University of ZurichZurichSwitzerland
- Eawag Swiss Federal Institute of Aquatic Science & TechnologyDubendorfSwitzerland
| | - A. Michelsen
- Department of Biology, University of CopenhagenCopenhagenDenmark
- Center for Permafrost (CENPERM), University of CopenhagenCopenhagenDenmark
| | - A. Milbau
- Research Institute for Nature and Forest (INBO)BrusselsBelgium
| | - J. Nabe‐Nielsen
- Ecoinformatics and Biodiversity, Department of Bioscience, Aarhus UniversityAarhusDenmark
| | - S. S. Nielsen
- Ecoinformatics and Biodiversity, Department of Bioscience, Aarhus UniversityAarhusDenmark
| | - J. M. Ninot
- Department of Evolutionary Biology, Ecology and Environmental Sciences, University of BarcelonaBarcelonaSpain
- Biodiversity Research InstituteUniversity of BarcelonaBarcelonaSpain
| | - S. F. Oberbauer
- Department of Biological Sciences, Florida International UniversityMiamiFlorida
| | - J. Olofsson
- Department of Ecology and Environmental Sciences, Umeå UniversityUmeåSweden
| | - V. G. Onipchenko
- Department of Geobotany, Lomonosov Moscow State UniversityMoscowRussia
| | - A. Petraglia
- Department of Chemistry, Life Sciences and Environmental Sustainability, University of ParmaParmaItaly
| | - S. B. Rumpf
- Department of Botany and Biodiversity Research, University of ViennaViennaAustria
| | - P. R. Semenchuk
- Department of Arctic and Marine Biology, UiT‐The Arctic University of NorwayTromsøNorway
- Department of Botany and Biodiversity Research, University of ViennaViennaAustria
| | - N. A. Soudzilovskaia
- Environmental Biology, Department Institute of Environmental Sciences, CML, Leiden UniversityLeidenThe Netherlands
| | - M. J. Spasojevic
- Department of Biology, University of California RiversideRiversideCalifornia
| | - J. D. M. Speed
- NTNU University Museum, Norwegian University of Science and TechnologyTrondheimNorway
| | - K. D. Tape
- Water and Environmental Research Center, University of AlaskaFairbanksAlaska
| | - M. te Beest
- Department of Ecology and Environmental Sciences, Umeå UniversityUmeåSweden
- Environmental Sciences, Copernicus Institute of Sustainable Development, Utrecht UniversityUtrechtThe Netherlands
| | - M. Tomaselli
- Department of Chemistry, Life Sciences and Environmental Sustainability, University of ParmaParmaItaly
| | - A. Trant
- Department of Biology, Memorial UniversitySt John’s, Newfoundland and LabradorCanada
- School of Environment, Resources and Sustainability, University of WaterlooWaterlooOntarioCanada
| | - U. A. Treier
- Ecoinformatics and Biodiversity, Department of Bioscience, Aarhus UniversityAarhusDenmark
| | - S. Venn
- Research School of Biology, Australian National UniversityActon, ACTAustralia
- Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin UniversityBurwoodVictoriaAustralia
| | - T. Vowles
- Department of Earth Sciences, University of GothenburgGothenburgSweden
| | - S. Weijers
- Department of Geography, University of BonnBonnGermany
| | - T. Zamin
- Department of Biology, Queen's UniversityKingston, OntarioCanada
| | - O. K. Atkin
- Research School of Biology, Australian National UniversityActon, ACTAustralia
| | - M. Bahn
- Department of Ecology, University of InnsbruckInnsbruckAustria
| | - B. Blonder
- Environmental Change Institute, School of Geography and the Environment, University of OxfordOxfordUnited Kingdom
- Rocky Mountain Biological LaboratoryCrested ButteColorado
| | - G. Campetella
- School of Biosciences & Veterinary Medicine ‐ Plant Diversity and Ecosystems Management Unit, University of CamerinoCamerinoItaly
| | | | - F. S. Chapin III
- Institute of Arctic Biology, University of AlaskaFairbanksAlaska
| | - M. Dainese
- Department of Animal Ecology and Tropical Biology, University of WürzburgWürzburgGermany
| | - F. T. de Vries
- School of Earth and Environmental Sciences, The University of ManchesterManchesterUnited Kingdom
| | - S. Díaz
- Instituto Multidisciplinario de Biología Vegetal (IMBIV), CONICET and FCEFyN, Universidad Nacional de CórdobaCórdobaArgentina
| | - W. Green
- Department of Organismic and Evolutionary Biology, Harvard University Cambridge, Massachusetts
| | - R. B. Jackson
- Department of Earth System Science, Stanford UniversityStanford, California
| | - P. Manning
- Senckenberg Gesellschaft für Naturforschung, Biodiversity and Climate Research Centre (SBiK‐F)FrankfurtGermany
| | - Ü. Niinemets
- Institute of Agricultural and Environmental Sciences, Estonian University of Life SciencesTartuEstonia
| | - W. A. Ozinga
- Plant Ecology and Nature Conservation Group, Wageningen University & ResearchWageningenThe Netherlands
| | - J. Peñuelas
- Global Ecology Unit, CREAF‐CSIC‐UAB‐UBBellaterraSpain
- CREAFCerdanyola del VallèsSpain
| | - P. B. Reich
- Department of Forest Resources, University of MinnesotaSt. Paul, MinneapolisMinnesota
- Hawkesbury Institute for the Environment, Western Sydney UniversityPenrith, NSWAustralia
| | - B. Schamp
- Department of Biology, Algoma UniversitySault Ste. MarieOntarioCanada
| | | | - P. M. van Bodegom
- Environmental Biology, Department Institute of Environmental Sciences, CML, Leiden UniversityLeidenThe Netherlands
| |
Collapse
|
16
|
Green W, McMaster J, Babela R, Buchs S. Cost-effectiveness of the SQ HDM SLIT-tablet for the treatment of allergic asthma in three Eastern European Countries. Eur Ann Allergy Clin Immunol 2018; 51:68-74. [PMID: 30417636 DOI: 10.23822/eurannaci.1764-1489.78] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Summary Background.The SQ® house dust mite (HDM) sublingual immunotherapy (SLIT)-tablet (ACARIZAX®, ALK-Abelló A/S, Hørsholm, Denmark) is an allergy immunotherapy tablet for people with allergic respiratory disease. This analysis aims to assess the cost-effectiveness of the SQ HDM SLIT-tablet from the perspective of three Eastern European countries: Czech Republic, Poland and Slovakia. Methods.A cost-utility model per country was developed, which compared the SQ HDM SLIT-tablet as add-on to pharmacotherapy with pharmacotherapy alone in patients with HDM allergic asthma (AA) over a five year time horizon. The effectiveness of the two interventions was based on the results from a large-scale randomised controlled trial. In the models, annual costs and quality-adjusted life year (QALY) scores from the trial were extrapolated over a five year period, and the incremental cost-effectiveness ratios (ICERs) were estimated. One-way deterministic sensitivity and scenario analyses were undertaken. Results.The SQ HDM SLIT-tablet is cost-effective in all three markets over the five year time horizon (ICERs of less than € 10,000 per additional QALY). Treatment with the SQ HDM SLIT-tablet improves patient outcomes, with QALY gains of 0.35, versus pharmacotherapy only. In all three countries, the SQ HDM SLIT-tablet also incurs increased costs compared to pharma-cotherapy treatment only. The sensitivity analysis identified utility values from the clinical trial as the main driver of the model results. Conclusion.The SQ HDM SLIT-tablet is a cost-effective treatment option for people with HDM AA in three different health care settings in Eastern Europe.
Collapse
Affiliation(s)
- W Green
- York Health Economics Consortium, Enterprise House, Innovation Way, University of York, Heslington, York, UK
| | - J McMaster
- York Health Economics Consortium, Enterprise House, Innovation Way, University of York, Heslington, York, UK
| | - R Babela
- St. Elisabeth University, Institute of Healthcare Disciplines, Bratislava, Slovakia. ALK-Abelló, Denmark
| | | |
Collapse
|
17
|
Abstract
Clinical, laboratory, and pathologic findings from a case of primary extramedullary plasmacytoma of the testis and sinuses in a patient with acquired immunodeficiency syndrome (AIDS) are presented. To our knowledge this is the first case in the English literature of a primary testicular plasmacytoma in an HIV-infected patient. The findings in this report and those of others confirm the difference in the pattern of plasma cell tumor (PCT) presentation in patients infected with AIDS from those in non-infected individuals, suggesting that these tumors should be considered in the differential diagnosis of AIDS-associated malignancies.
Collapse
Affiliation(s)
- A Ramadan
- Pathology Department, Howard University Hospital, Washington, DC 20060, USA.
| | | | | | | |
Collapse
|
18
|
Savioli L, Albonico M, Colley DG, Correa-Oliveira R, Fenwick A, Green W, Kabatereine N, Kabore A, Katz N, Klohe K, LoVerde PT, Rollinson D, Stothard JR, Tchuem Tchuenté LA, Waltz J, Zhou XN. Building a global schistosomiasis alliance: an opportunity to join forces to fight inequality and rural poverty. Infect Dis Poverty 2017; 6:65. [PMID: 28330495 PMCID: PMC5363045 DOI: 10.1186/s40249-017-0280-8] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2016] [Accepted: 03/06/2017] [Indexed: 01/24/2023] Open
Abstract
Schistosomiasis, one of the 17 neglected tropical diseases listed by the World Health Organization, presents a substantial public health and economic burden. Of the 261 million people requiring preventive chemotherapy for schistosomiasis in 2013, 92% of them lived in sub-Saharan Africa and only 12.7% received preventive chemotherapy. Moreover, in 2010, the WHO reported that schistosomiasis mortality could be as high as 280 000 per year in Africa alone.In May 2012 delegates to the sixty-fifth World Health Assembly adopted resolution WHA65.21 that called for the elimination of schistosomiasis, and foresees the regular treatment of at least 75% of school age children in at-risk areas. The resolution urged member states to intensify schistosomiasis control programmes and to initiate elimination campaigns where possible.Despite this, in June 2015, schistosomiasis was indicated to have the lowest level of preventive chemotherapy implementation in the spectrum of neglected tropical diseases. It was also highlighted as the disease most lacking in progress. This is perhaps unsurprising, given that it was also the only NTD with access to drug donations but without a coalition of stakeholders that collaborates to boost commitment and implementation.As a consequence, and to ensure that the WHO NTDs Roadmap Targets of 2012 and World Health Assembly Resolution WHA65.21 are met, the Global Schistosomiasis Alliance (GSA) has been set up. Diverse and representative, the GSA aims to be a partnership of endemic countries, academic and research institutions, international development agencies and foundations, international organizations, non-governmental development organizations, private sector companies and advocacy and resource mobilisation partners. Ultimately, the GSA calls for a partnership to work for the benefit of endemic countries by addressing health inequity and rural poverty.
Collapse
Affiliation(s)
| | - Marco Albonico
- Center for Tropical Diseases, Sacro Cuore Hospital - WHO Collaborating Centre on strongyloidiasis and other intestinal parasitic infections, Negrar, Verona Italy
| | - Daniel G. Colley
- Schistosomiasis Consortium for Operational Research and Evaluation, The University of Georgia, Athens, Georgia USA
| | - Rodrigo Correa-Oliveira
- Centro de Pesquisas René Rachou – Fiocruz, Belo Horizonte, Brazil and Universidade Federal de Ouro Preto, Ouro Preto, Brazil
| | - Alan Fenwick
- Department of Infectious Disease Epidemiology, SCI, Imperial College, London, UK
| | - Will Green
- Trinity College Cambridge, Cambridge, UK
| | | | | | - Naftale Katz
- Research Center René Rachou – Oswaldo Cruz Foundation, Belo Horizonte, Brazil
| | | | | | - David Rollinson
- Life Sciences Department, The Natural History Museum, London, UK
| | - J. Russell Stothard
- Department of Parasitology, Liverpool School of Tropical Medicine, Liverpool, L3 5QA UK
| | | | | | - Xiao-Nong Zhou
- National Institute of Parasitic Diseases Chinese Center for Disease Control and Prevention, Shanghai, China
| |
Collapse
|
19
|
Hahn-Pedersen J, Worm M, Green W, Andreasen JN, Taylor M. Cost utility analysis of the SQ(®) HDM SLIT-tablet in house dust mite allergic asthma patients in a German setting. Clin Transl Allergy 2016; 6:35. [PMID: 27610217 PMCID: PMC5015209 DOI: 10.1186/s13601-016-0127-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2016] [Accepted: 08/29/2016] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Asthma affects an estimated 300 million people worldwide with the condition associated with significant healthcare utilisation costs and a large impact on patient quality of life. The SQ(®) HDM SLIT-tablet (ACARIZAX(®), Hørsholm, Denmark) is a sublingually administered allergy immunotherapy tablet for house dust mite allergic asthma and allergic rhinitis and has recently been licensed in Europe. OBJECTIVE To assess the cost-effectiveness of ACARIZAX plus pharmacotherapy versus placebo plus pharmacotherapy in patients with house dust mite allergic asthma that is uncontrolled by inhaled corticosteroids, in a German setting. Eligible patients should also have symptoms of mild to severe allergic rhinitis. METHODS A cost utility analysis was undertaken, based on the results of a European phase III randomised controlled trial, in which ACARIZAX was compared with placebo with both treatment groups also receiving pharmacotherapy in the form of inhaled corticosteroids and short-acting β2-agonists. Cost and quality-adjusted life years from the trial were extrapolated over a nine year time horizon and the incremental cost-effectiveness ratio calculated to compare treatment options. RESULTS ACARIZAX plus pharmacotherapy was estimated to generate 6.16 quality-adjusted life years per patient at a cost of €5658, compared with 5.50 quality-adjusted life years (QALYs) at a cost of €2985 for placebo plus pharmacotherapy. This equated to an incremental cost of €2673, incremental QALYs of 0.66 and an incremental cost-effectiveness ratio (ICER) of €4041. The ICER was, therefore, substantially lower than the €40,000 willingness-to-pay threshold per QALY adopted for the analysis. Deterministic sensitivity analyses indicate the results are most sensitive to the utility score of ACARIZAX patients during years 2 and 3 of treatment. CONCLUSION This analysis indicates that ACARIZAX plus pharmacotherapy is cost-effective compared with placebo plus pharmacotherapy for house dust mite allergic asthma patients in Germany. If a disease-modifying effect can be proven the results of this analysis may underestimate the true benefits of ACARIZAX.
Collapse
Affiliation(s)
| | - M Worm
- Clinic for Dermatology, Venereology and Allergology, Universitätsmedizin Berlin, Berlin, Germany
| | - W Green
- York Health Economics Consortium, University of York, York, UK
| | | | - M Taylor
- York Health Economics Consortium, University of York, York, UK
| |
Collapse
|
20
|
Buczek ME, Miles AK, Green W, Johnson C, Boocock DJ, Pockley AG, Rees RC, Hulman G, van Schalkwyk G, Parkinson R, Hulman J, Powe DG, Regad T. Cytoplasmic PML promotes TGF-β-associated epithelial-mesenchymal transition and invasion in prostate cancer. Oncogene 2016; 35:3465-75. [PMID: 26549027 PMCID: PMC4932557 DOI: 10.1038/onc.2015.409] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2015] [Revised: 07/22/2015] [Accepted: 09/18/2015] [Indexed: 12/18/2022]
Abstract
Epithelial-mesenchymal transition (EMT) is a key event that is involved in the invasion and dissemination of cancer cells. Although typically considered as having tumour-suppressive properties, transforming growth factor (TGF)-β signalling is altered during cancer and has been associated with the invasion of cancer cells and metastasis. In this study, we report a previously unknown role for the cytoplasmic promyelocytic leukaemia (cPML) tumour suppressor in TGF-β signalling-induced regulation of prostate cancer-associated EMT and invasion. We demonstrate that cPML promotes a mesenchymal phenotype and increases the invasiveness of prostate cancer cells. This event is associated with activation of TGF-β canonical signalling pathway through the induction of Sma and Mad related family 2 and 3 (SMAD2 and SMAD3) phosphorylation. Furthermore, the cytoplasmic localization of promyelocytic leukaemia (PML) is mediated by its nuclear export in a chromosomal maintenance 1 (CRM1)-dependent manner. This was clinically tested in prostate cancer tissue and shown that cytoplasmic PML and CRM1 co-expression correlates with reduced disease-specific survival. In summary, we provide evidence of dysfunctional TGF-β signalling occurring at an early stage in prostate cancer. We show that this disease pathway is mediated by cPML and CRM1 and results in a more aggressive cancer cell phenotype. We propose that the targeting of this pathway could be therapeutically exploited for clinical benefit.
Collapse
Affiliation(s)
- M E Buczek
- John van Geest Cancer Research Centre, School of Science and Technology, Nottingham Trent University, Clifton Lane, Nottingham, UK
| | - A K Miles
- John van Geest Cancer Research Centre, School of Science and Technology, Nottingham Trent University, Clifton Lane, Nottingham, UK
| | - W Green
- Department of Urology, City Hospital, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - C Johnson
- John van Geest Cancer Research Centre, School of Science and Technology, Nottingham Trent University, Clifton Lane, Nottingham, UK
| | - D J Boocock
- John van Geest Cancer Research Centre, School of Science and Technology, Nottingham Trent University, Clifton Lane, Nottingham, UK
| | - A G Pockley
- John van Geest Cancer Research Centre, School of Science and Technology, Nottingham Trent University, Clifton Lane, Nottingham, UK
| | - R C Rees
- John van Geest Cancer Research Centre, School of Science and Technology, Nottingham Trent University, Clifton Lane, Nottingham, UK
| | - G Hulman
- Department of Cellular Pathology, Queen's Medical Centre, Nottingham University Hospitals Trust, Nottingham, UK
| | - G van Schalkwyk
- Department of Histopathology, Royal Derby Hospital, Derby, UK
| | - R Parkinson
- Department of Urology, City Hospital, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - J Hulman
- Department of Cellular Pathology, Queen's Medical Centre, Nottingham University Hospitals Trust, Nottingham, UK
| | - D G Powe
- John van Geest Cancer Research Centre, School of Science and Technology, Nottingham Trent University, Clifton Lane, Nottingham, UK
- Department of Cellular Pathology, Queen's Medical Centre, Nottingham University Hospitals Trust, Nottingham, UK
| | - T Regad
- John van Geest Cancer Research Centre, School of Science and Technology, Nottingham Trent University, Clifton Lane, Nottingham, UK
| |
Collapse
|
21
|
Hart JA, Phlips EJ, Badylak S, Dix N, Petrinec K, Mathews AL, Green W, Srifa A. Phytoplankton biomass and composition in a well-flushed, sub-tropical estuary: The contrasting effects of hydrology, nutrient loads and allochthonous influences. Mar Environ Res 2015; 112:9-20. [PMID: 26385174 DOI: 10.1016/j.marenvres.2015.08.010] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/10/2015] [Revised: 07/28/2015] [Accepted: 08/31/2015] [Indexed: 06/05/2023]
Abstract
The primary objective of this study was to examine trends in phytoplankton biomass and species composition under varying nutrient load and hydrologic regimes in the Guana Tolomato Matanzas estuary (GTM), a well-flushed sub-tropical estuary located on the northeast coast of Florida. The GTM contains both regions of significant human influence and pristine areas with only modest development, providing a test case for comparing and contrasting phytoplankton community dynamics under varying degrees of nutrient load. Water temperature, salinity, Secchi disk depth, nutrient concentrations and chlorophyll concentrations were determined on a monthly basis from 2002 to 2012 at three representative sampling sites in the GTM. In addition, microscopic analyses of phytoplankton assemblages were carried out monthly for a five year period from 2005 through 2009 at all three sites. Results of this study indicate that phytoplankton biomass and composition in the GTM are strongly influenced by hydrologic factors, such as water residence times and tidal exchanges of coastal waters, which in turn are affected by shifts in climatic conditions, most prominently rainfall levels. These influences are exemplified by the observation that the region of the GTM with the longest water residence times but lowest nutrient loads exhibited the highest phytoplankton peaks of autochthonous origin. The incursion of a coastal bloom of the toxic dinoflagellate Karenia brevis into the GTM in 2007 demonstrates the potential importance of allochthonous influences on the ecosystem.
Collapse
Affiliation(s)
- J A Hart
- Fisheries and Aquatic Sciences Program, SFRC, University of Florida, 7922 NW 71st Street, Gainesville, FL 32653, USA
| | - E J Phlips
- Fisheries and Aquatic Sciences Program, SFRC, University of Florida, 7922 NW 71st Street, Gainesville, FL 32653, USA.
| | - S Badylak
- Fisheries and Aquatic Sciences Program, SFRC, University of Florida, 7922 NW 71st Street, Gainesville, FL 32653, USA
| | - N Dix
- Guana Tolomato Matanzas National Estuarine Research Reserve, 505 Guana River Road, Ponte Vedra, FL 32082, USA.
| | - K Petrinec
- Guana Tolomato Matanzas National Estuarine Research Reserve, 505 Guana River Road, Ponte Vedra, FL 32082, USA
| | - A L Mathews
- Georgia Southern University, Department of Biology, Statesboro, GA 30460, USA.
| | - W Green
- St. Johns River Water Management District, 4049 Reid Street, Palatka, FL 32177, USA.
| | - A Srifa
- Fisheries and Aquatic Sciences Program, SFRC, University of Florida, 7922 NW 71st Street, Gainesville, FL 32653, USA
| |
Collapse
|
22
|
De Palma G, Blennerhassett P, Lu J, Deng Y, Park AJ, Green W, Denou E, Silva MA, Santacruz A, Sanz Y, Surette MG, Verdu EF, Collins SM, Bercik P. Microbiota and host determinants of behavioural phenotype in maternally separated mice. Nat Commun 2015. [DOI: 10.1038/ncomms8735] [Citation(s) in RCA: 299] [Impact Index Per Article: 33.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
|
23
|
Roppolo L, Burdette S, Green W, Shinthia N, Ye P, Nelson J, Hynan L. 392 A Prospective Study Evaluating QT Intervals After Antiemetics and Antihistamines in Unfunded Emergent Dialysis With Baseline QT Prolongation. Ann Emerg Med 2014. [DOI: 10.1016/j.annemergmed.2014.07.420] [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: 12/01/2022]
|
24
|
Schott M, Promes S, Swoboda T, Green W, O‘Rourke K, Kedia R, Liu R, Santen S. Introducing the Critical Care Direct Observation Tool: Building Validity Evidence for Direct Observation to Measure Emergency Medicine Milestones. Ann Emerg Med 2013. [DOI: 10.1016/j.annemergmed.2013.07.328] [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: 10/26/2022]
|
25
|
Affiliation(s)
- Will Green
- Department of Urology, Royal Derby Hospital, Derby, United Kingdom.
| | | |
Collapse
|
26
|
Green W, Rohan M. Opposition to aerial 1080 poisoning for control of invasive mammals in New Zealand: risk perceptions and agency responses. J R Soc N Z 2012. [DOI: 10.1080/03036758.2011.556130] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
|
27
|
Palaniyandi S, Odaka Y, Green W, Abreo F, Caldito G, Benedetti AD, Sunavala-Dossabhoy G. Adenoviral delivery of Tousled kinase for the protection of salivary glands against ionizing radiation damage. Gene Ther 2010; 18:275-82. [DOI: 10.1038/gt.2010.142] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
|
28
|
Brennan TC, Rybchyn MS, Green W, Atwa S, Conigrave AD, Mason RS. Osteoblasts play key roles in the mechanisms of action of strontium ranelate. Br J Pharmacol 2009; 157:1291-300. [PMID: 19563530 PMCID: PMC2743848 DOI: 10.1111/j.1476-5381.2009.00305.x] [Citation(s) in RCA: 159] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2009] [Accepted: 03/19/2009] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND AND PURPOSE Strontium ranelate reduces fracture risk in postmenopausal women with osteoporosis. Evidence from non-clinical studies and analyses of bone markers in phase III trials indicate that this is due to an increase in osteoblast formation and a decrease of osteoclastic resorption. The aim of this work was to investigate, in human cells, the mechanisms by which strontium ranelate is able to influence the activities of osteoblasts and osteoclasts. EXPERIMENTAL APPROACH Human primary osteoblasts were used to examine effects of strontium ranelate on replication (thymidine incorporation), differentiation (Runx2 and alkaline phosphatase) and cell survival (cell counts and caspase activity). Osteoprotegerin (OPG) was measured by quantitative reverse transcription PCR (qRT-PCR) and elisa and receptor activator of NFkappaB ligand (RANKL) by qRT-PCR and Western blot. As strontium ranelate has been proposed as an agonist of the calcium-sensing receptor (CaSR), the involvement of CaSR in the effects of strontium ranelate on OPG and RANKL expression, and cell replication was examined using siRNA. KEY RESULTS Strontium ranelate increased mRNA and protein levels of OPG and suppressed those of RANKL. Strontium ranelate also stimulated osteoblast replication and differentiation and increased cell survival under stress. Knocking down CaSR suppressed strontium ranelate-induced stimulation of OPG mRNA, reduction of RANKL mRNA, and increase in replication, indicating the involvement of CaSR in these responses. CONCLUSIONS AND IMPLICATIONS Our results demonstrate that osteoblasts play a key role in the mechanism of action of the anti-fracture agent, strontium ranelate by mediating both its anabolic and anti-resorptive actions, at least in part, via activation of CaSR.
Collapse
Affiliation(s)
- T C Brennan
- Department of Physiology, University of Sydney, NSW, Australia
| | | | | | | | | | | |
Collapse
|
29
|
Abstract
CONTEXT In this time of rapid expansion of the scientific knowledge base, subject matter runs the risk of becoming outdated within a relatively short time. Instead of adding more content to already crowded curricula, the focus should be on equipping students to adapt to their changing world. The ability to access, evaluate and apply new knowledge for the benefit of patients has been acknowledged as an important goal for dental education. Information literacy is key to achieving this. METHODS An information literacy programme for first year oral health students was instituted. This was integrated within a biosciences course and linked with its assessment. Small group instruction reinforced by the use of a tailored online Assignment Guide was used in the context of a specific task. Effectiveness was measured in terms of assessment outcome, processes used and student experience. RESULTS Twenty-seven students participated in the intervention which was effective in enhancing foundation literacy skills and confidence of students in accessing and evaluating information sources in the context of a clinical problem. Improvement in higher level literacy skills required to articulate this information in the synthesis of a scientific review was not demonstrated. CONCLUSIONS Integration of this information literacy programme within the learning activities and assessment of a basic sciences course resulted in significantly enhanced information literacy skills. As this is highly relevant for higher education students in general, the wider promotion of information literacy should be encouraged.
Collapse
Affiliation(s)
- P J Ford
- The University of Queensland, School of Dentistry, Brisbane, QLD 4000, Australia.
| | | | | |
Collapse
|
30
|
Marinelli L, Green W, Panacek E. 426: What Really Glows: Analysis of the Wood's Lamp in Detecting Semen and Saliva on Human Skin. Ann Emerg Med 2008. [DOI: 10.1016/j.annemergmed.2008.06.454] [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: 11/29/2022]
|
31
|
Green W, Ho G. Small scale sanitation technologies. Water Sci Technol 2005; 51:29-38. [PMID: 16104403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Small scale systems can improve the sustainability of sanitation systems as they more easily close the water and nutrient loops. They also provide alternate solutions to centrally managed large scale infrastructures. Appropriate sanitation provision can improve the lives of people with inadequate sanitation through health benefits, reuse products as well as reduce ecological impacts. In the literature there seems to be no compilation of a wide range of available onsite sanitation systems around the world that encompasses black and greywater treatment plus stand-alone dry and urine separation toilet systems. Seventy technologies have been identified and classified according to the different waste source streams. Sub-classification based on major treatment methods included aerobic digestion, composting and vermicomposting, anaerobic digestion, sand/soil/peat filtration and constructed wetlands. Potential users or suppliers of sanitation systems can choose from wide range of technologies available and examine the different treatment principles used in the technologies. Sanitation systems need to be selected according to the local social, economic and environmental conditions and should aim to be sustainable.
Collapse
Affiliation(s)
- W Green
- Murdoch University, West Australia, Environmental Technology Centre, Australia.
| | | |
Collapse
|
32
|
Abstract
A number of studies have suggested that prior chemotherapy correlates negatively with the efficiency of hematopoietic stem cell mobilization. However, little data exist with regard to the relative effects of the specific chemotherapeutic drug classes. We retrospectively reviewed the records of 201 consecutive patients with nonmyeloid malignancies undergoing CD34+ cell mobilization with chemotherapy+granulocyte colony-stimulating factor (G-CSF). The number of prior chemotherapy courses correlated negatively with the peripheral CD34+ cell concentration (pCD34) on the first day of collection (P<0.001). No significant correlation was found for age, gender, tumor primary, mobilization chemotherapy regimen, disease status, marrow involvement, prior radiation therapy, or dose and timing of G-CSF administration. When the number of courses of individual classes of chemotherapeutic agents was correlated with pCD34, only exposures to platinum compounds (P=0.001) and alkylating agents (P=0.01) were found to be independent negative predictive factors for pCD34. Within classes, DNA crosslinking agents and etoposide appeared possibly more damaging than DNA methylating agents and doxorubicin, respectively. None of the drug classes showed evidence of recovery. We conclude that exposure to chemotherapy, especially platinum compounds and alkylating agents, should be minimized prior to mobilization.
Collapse
Affiliation(s)
- C D Ford
- Utah Blood and Bone Marrow Transplantation Program, LDS Hospital and University of Utah, Salt Lake City 84143, USA.
| | | | | | | |
Collapse
|
33
|
|
34
|
|
35
|
Abstract
UNLABELLED We sought to evaluate the effects of aprotinin on the number and function of the platelet glycoprotein (GP) IIb-IIIa receptor and on the expression of P-selectin in vitro in order to gain insight into the potential mechanisms involved in the platelet-protective action of aprotinin during cardiopulmonary bypass. Aprotinin at 50 to 200 kallikrein inhibiting units/mL decreased the expression of activated GP IIb-IIIa complex in response to adenosine diphosphate or thrombin receptor activator peptide 6 in a dose-dependent manner in both citrated and heparinized whole blood experiments. Aprotinin inhibited adenosine diphosphate-induced platelet aggregation, but it exhibited no effect on the expression of GP IIIa and P-selectin. These results indicate that aprotinin interferes with the platelet fibrinogen receptor function during pharmacological activation. Reduced aggregability and platelet adhesion to fibrinogen adsorbed to synthetic surfaces in the presence of aprotinin may prevent platelet consumption during clinical cardiopulmonary bypass. This in vitro study demonstrates that aprotinin decreases the agonist-induced expression of activated GP IIb-IIIa receptors that play a major role in platelet aggregation and adhesion to biomaterial surfaces. IMPLICATIONS This in vitro study demonstrates that aprotinin decreases the agonist-induced expression of activated glycoprotein IIb-IIIa receptors that play a major role in platelet aggregation and adhesion to biomaterial surfaces.
Collapse
|
36
|
Ernst AA, Green E, Ferguson MT, Weiss SJ, Green W. Emergency department evaluation of male victims of sexual assault. Ann Emerg Med 1999. [DOI: 10.1016/s0196-0644(99)80236-4] [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: 11/29/2022]
|
37
|
Abstract
BACKGROUND The uremic state is characterized by subnormal platelet aggregation. Fibrinogen fragments, usually absent in normal human blood, but present in uremic plasma, may play a role in uremic platelet dysfunction. METHODS To examine this hypothesis, we investigated the availability and function of fibrinogen receptors [glycoprotein (GP) IIb-IIIa] on uremic and normal platelets, as well as the effect of fragments obtained from chymotrypsin digestion of human fibrinogen on normal platelets. The availability of fibrinogen receptors was examined using anti-GP IIb-IIIa antibodies and flow cytometry, whereas receptor function was assessed by the receptor's ability to mediate fibrinogen binding and platelet aggregation. RESULTS Platelet aggregation and the availability of GP IIb-IIIa were lower in uremic patients when compared with normal controls. Flow cytometric analysis showed that fibrinogen fragments decreased the binding of anti-CD61, an activation-independent anti-GP IIIa monoclonal antibody, to resting normal platelets. These fragments also reduced the binding of PAC-1, an activation-dependent anti-GP IIb-IIIa monoclonal antibody, to adenosine diphosphate (ADP)-activated normal platelets. In addition, the binding of radiolabeled fibrinogen to activated normal platelets and platelet aggregation in response to ADP were both decreased by fibrinogen fragments. CONCLUSIONS These findings suggest that fibrinogen fragments impair platelet function by occupying fibrinogen receptors prior to cell activation, thus preventing the binding of intact fibrinogen to platelets after subsequent stimulation. These observations also suggest a plausible mechanism by which endogenous fibrinogen fragments present in uremic plasma may contribute to platelet dysfunction.
Collapse
|
38
|
Green W, Feddersen R, Yousef O, Behr M, Smith K, Nestler J, Jenison S, Yamada T, Hjelle B. Tissue distribution of hantavirus antigen in naturally infected humans and deer mice. J Infect Dis 1998; 177:1696-700. [PMID: 9607851 DOI: 10.1086/515325] [Citation(s) in RCA: 35] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022] Open
Abstract
The Sin Nombre virus (SNV) is the etiologic agent of hantavirus pulmonary syndrome in humans but does not cause disease in chronically infected deer mice (Peromyscus maniculatus), the natural host. In this study, murine antiserum raised against recombinant SNV nucleocapsid protein was utilized to localize viral antigen immunohistochemically in tissues from both humans (n = 20; 11 positive, 9 negative) and deer mice (n = 6; 4 positive, 2 negative). Viral infection status was confirmed by Western blot or reverse transcriptase-polymerase chain reaction. SNV antigen was detected in pulmonary and cardiac endothelium in both species, but positive cells in deer mice were rare. Other deer mouse tissues, including kidney, were negative; in contrast, vascular elements of several tissues from infected humans were positive, with strong staining of renal endothelium. The paucity of positive cells in chronically infected mice suggests a low virus burden compared with that of acutely infected humans.
Collapse
Affiliation(s)
- W Green
- Department of Pathology, University of New Mexico School of Medicine, Albuquerque 87131, USA
| | | | | | | | | | | | | | | | | |
Collapse
|
39
|
Abstract
STUDY OBJECTIVES To describe the pulmonary complications in patients with HIV infection, and the changes in the incidence of these complications over a 12-year period. DESIGN Retrospective review of autopsy records. SETTING Two university-affiliated medical centers. PATIENTS We studied autopsy findings from 233 patients with HIV infection who died between 1985 and 1996. Demographic data, risk factors for HIV infection, and the lengths of hospital stay were obtained. The histologic and microbiological findings of the respiratory system, and the extrapulmonary organ involvement by Kaposi's sarcoma (KS), Pneumocystis carinii, Mycobacterium tuberculosis, and Mycobacterium avium complex were reviewed. RESULTS Ninety-two percent of the patients were black and 75% were male. The two most common identified risk factors for HIV infection were homosexuality (34%) and injection drug use (27%). Bacterial pneumonia was the most frequent pulmonary complication (42%). The two most common causes of bacterial pneumonia were Pseudomonas aeruginosa and Staphylococcus aureus. P carinii pneumonia (PCP) was found in 24%, with extrapulmonary involvement in 13%. Pulmonary mycobacterial infections were seen in 33%, with multiple extrapulmonary involvement. The most common site affected by KS was the lung. Of all pulmonary complications, only the incidence of PCP decreased over the 12-year period. CONCLUSIONS Recognizing the high incidence rate of bacterial pneumonia, the high frequency of pulmonary KS and the not uncommon occurrence of extrapulmonary P carinii infection in patients with HIV helps in improving their care.
Collapse
Affiliation(s)
- B Afessa
- Division of Critical Care, University of Florida Health Science Center, Jacksonville, USA
| | | | | | | |
Collapse
|
40
|
Abstract
Cyclandelate is a vasodilating agent that, like papaverine, acts directly on the smooth muscles of blood vessels. The drug has been used primarily as an adjunctive treatment for various peripheral vascular diseases; some studies advocate its use for treating ischemic cerebrovascular disease. Early nonrandomized and uncontrolled studies suggest that cyclandelate is efficacious in treating tinnitus. Recent personal communications regarding cyclandelate's effectiveness in treating tinnitus prompted this study. Fifty-nine adult patients with constant tinnitus for more than 1 year were randomly selected for this prospective, placebo-controlled, double-blind study with a treatment period of 3 months. Audiometric testing with tinnitus pitch and loudness matching was performed before initiation of treatment and at the end of treatment, and frequent questionnaire evaluations were performed during the treatment period. Four patients in the cyclandelate group and three in the placebo group reported a subjective reduction in the loudness of their tinnitus. Audiologic testing before and after treatment showed no significant changes in tinnitus pitch or loudness. Although cyclandelate treatment was beneficial for some patients and the decrease in subjective loudness scoring was significant for the cyclandelate group, the impact of its effect did not appear to warrant its continued use by those patients. A significant percentage of patients could not tolerate the drug because of side effects.
Collapse
Affiliation(s)
- T O Hester
- Division of Otolaryngology-Head and Neck Surgery, University of Kentucky Chandler Medical Center, Lexington 40536-0084, USA
| | | | | | | |
Collapse
|
41
|
Abstract
Cyclandelate is a vasodilating agent that, like papaverine, acts directly on the smooth muscles of blood vessels. The drug has been used primarily as an adjunctive treatment for various peripheral vascular diseases; some studies advocate its use for treating ischemic cerebrovascular disease. Early nonrandomized and uncontrolled studies suggest that cyclandelate is efficacious in treating tinnitus. Recent personal communications regarding cyclandelate's effectiveness in treating tinnitus prompted this study. Fifty-nine adult patients with constant tinnitus for more than 1 year were randomly selected for this prospective, placebo-controlled, double-blind study with a treatment period of 3 months. Audiometric testing with tinnitus pitch and loudness matching was performed before initiation of treatment and at the end of treatment, and frequent questionnaire evaluations were performed during the treatment period. Four patients in the cyclandelate group and three in the placebo group reported a subjective reduction in the loudness of their tinnitus. Audiologic testing before and after treatment showed no significant changes in tinnitus pitch or loudness. Although cyclandelate treatment was beneficial for some patients and the decrease in subjective loudness scoring was significant for the cyclandelate group, the impact of its effect did not appear to warrant its continued use by those patients. A significant percentage of patients could not tolerate the drug because of side effects.
Collapse
Affiliation(s)
- T O Hester
- Division of Otolaryngology-Head and Neck Surgery, University of Kentucky Chandler Medical Center, Lexington 40536-0084, USA
| | | | | | | |
Collapse
|
42
|
Karesh WB, Rothstein A, Green W, Reuter HO, Braselton WE, Torres A, Cook RA. Health evaluation of black-faced impala (Aepyceros melampus petersi) using blood chemistry and serology. J Zoo Wildl Med 1997; 28:361-7. [PMID: 9523628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
As part of ongoing ecological studies of black-faced impala (Aepyceros melampus petersi) in northern Namibia, blood samples were collected and analyzed from 26 animals captured for translocation in 1992. All animals appeared to be in good condition and no abnormality was noted during physical examination. Serum chemistry and mineral levels were measured and correlated with the results of bacterial and viral serology and were within the normal ranges for domestic ruminants. Antibody titers for infectious bovine rhinotracheitis and bovine viral diarrhea were detected. Serological tests for bluetongue, foot-and-mouth disease, rinderpest, parainfluenza 3, brucellosis, leptospirosis, and anaplasmosis were negative. Significant differences in disease prevalence were not found between sexes.
Collapse
Affiliation(s)
- W B Karesh
- Wildlife Conservation Society, Bronx, New York 10460, USA
| | | | | | | | | | | | | |
Collapse
|
43
|
Abstract
The human autosomal recessive disorder Chediak-Higashi syndrome and its murine homologue beige are associated with the formation of giant lysosomes that cluster near the perinuclear region of cells. We prepared a polyclonal antiserum against a glutathione S-transferase-Beige fusion protein and demonstrated by Western analysis that the beige gene encodes a protein of 400 kDa that is expressed in cultured murine fibroblasts as well as most mouse tissues. The protein was not detected in either cultured fibroblasts or mouse tissues from two different beige mutants. Cultured fibroblasts transformed with multiple copies of yeast artificial chromosomes that contain the full-length beige gene showed much higher levels of Beige protein than either wild type fibroblasts or mouse tissues. Subcellular fractionation experiments demonstrated that the Beige protein was cytosolic and, under the conditions of isolation, had no measurable membrane association. Cultured mouse fibroblasts in which the Beige protein was overexpressed had smaller than normal lysosomes that were more peripherally distributed than in control cells. These findings, coupled with earlier published results, suggest that the Beige protein regulates lysosomal fission.
Collapse
Affiliation(s)
- C M Perou
- Department of Pathology, University of Utah, Salt Lake City, Utah 84132, USA
| | | | | | | | | | | |
Collapse
|
44
|
Abstract
Pap smear, colposcopy, and biopsy results were collected from 1988-1993 at a group of family planning clinics. Positive predictive values and likelihood ratios were calculated for diagnosis of high-grade lesions based on age and Pap smear results. One thousand and forty-seven colposcopies were logged; 771 had a biopsy or endocervical curettage. Seventy-nine (10%) were high-grade lesions. If only human papillomavirus (HPV) was reported on the Pap smear, the likelihood of a high-grade biopsy was lowest (positive predictive value, 4.5%; likelihood ratio, 0.4). Women under age 25 were less likely to have high-grade biopsies (positive predictive value, 7.3%; likelihood ratio 0.7). Repeat Pap smears for atypical cells of undetermined significance (ASCUS) and low grade squamous intra-epithelial lesion (LGSIL) showing only HPV in women under age 30 would have reduced the immediate colposcopy rate by 60% and delayed diagnosis by 23% of high-grade lesions. Consideration of patient age and whether HPV is the only Pap smear finding may reduce referral for immediate colposcopy.
Collapse
Affiliation(s)
- J Melnikow
- Department of Family and Community Medicine, University of California, Davis 95817, USA.
| | | | | | | | | | | |
Collapse
|
45
|
Malviya S, Voepel-Lewis T, Huntington J, Siewert M, Green W. Effects of anesthetic technique on side effects associated with fentanyl Oralet premedication. J Clin Anesth 1997; 9:374-8. [PMID: 9257202 DOI: 10.1016/s0952-8180(97)00064-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
STUDY OBJECTIVES To evaluate the efficacy of 5 to 10 micrograms/kg of oral transmucosal fentanyl citrate (OTFC) as an anesthetic premedication, and to determine whether propofol induction reduces postoperative nausea and vomiting (PONV) in pediatric patients premedicated with OTFC undergoing outpatient surgery. DESIGN Prospective, randomized, double-blinded study. SETTINGS University of Michigan Health Care Systems and University of Arizona. PARTICIPANTS 62 ASA physical status I and II children aged 4 to 14 years (8.9 +/- 0.5 years). INTERVENTIONS Subjects were randomly assigned to one of four groups: (1) OTFC premedication and halothane induction; (2) OTFC premedication and propofol induction; (3) placebo premedication and halothane induction; and (4) placebo premedication and propofol induction. OTFC or placebo was administered 30 minutes prior to induction, and activity (sedation), apprehension, and cooperation scores were recorded before, at 15 and 30 minutes after study drug, and on induction. All perioperative adverse events were recorded. MEASUREMENTS AND MAIN RESULTS Children who received OTFC became drowsier and had a significant change from baseline in combined activity, apprehension, and cooperation scores, whereas those who received placebo became less cooperative at induction. Patients who received OTFC experienced more adverse events overall (p < 0.001) than patients who received placebo. Additionally, OTFC patients experienced more vomiting (p < 0.001) and pruritus (p = 0.049) than controls. The incidence of PONV in patients who received OTFC and halothane induction was 50%, compared to 30% in patients receiving OTFC and a propofol induction (p = NS). CONCLUSIONS OTFC in doses of 5 to 10 micrograms/kg was effective in producing sedation and facilitating cooperation with induction; however, it was associated with significant PONV in our study. Although propofol induction did not significantly reduce PONV in our study, further study with a larger sample, and with propofol as the sole anesthetic, may be warranted.
Collapse
Affiliation(s)
- S Malviya
- Department of Anesthesiology, University of Michigan Medical Center, Ann Arbor 48109-0211, USA
| | | | | | | | | |
Collapse
|
46
|
Green W. Musical medicine. Mich Health Hosp 1996; 32:16. [PMID: 10162201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 02/11/2023]
Affiliation(s)
- W Green
- St. Joseph's Mercy of Macomb, MI, USA
| |
Collapse
|
47
|
Luckie AP, Wroblewski JJ, Hamilton P, Bird AC, Sanders M, Slater N, Green W. A randomised prospective study of outpatient haemodilution for central retinal vein obstruction. Aust N Z J Ophthalmol 1996; 24:223-32. [PMID: 8913124 DOI: 10.1111/j.1442-9071.1996.tb01584.x] [Citation(s) in RCA: 21] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
PURPOSE Central retinal vein obstruction (CRVO) has significant visual morbidity. We prospectively evaluated an outpatient haemodilution (HD) regimen for CRVO. METHODS We recruited 59 patients with CRVO of less than three months' duration and visual acuity (VA) worse than or equal to 6/9.5. Thirty patients underwent HD (packed cell volume of <0.35, 12 weeks); there were 29 controls and follow-up was for six months. RESULTS Incidence rates for VA improvement (P = 0.708) and rubeosis iridis (P = 0.619) between the two groups were not different. The incidence rate of VA deterioration was 5.315 times higher with HD (P = 0.035, Cox Proportional analysis). CONCLUSION This data does not support the previous studies on haemodilution.
Collapse
|
48
|
Luckie AP, Wroblewski JJ, Bird AC, Hamilton AM, Sanders MD, Green W, Slater NG. The venous closing pressure in central retinal vein obstruction. Aust N Z J Ophthalmol 1996; 24:233-8. [PMID: 8913125 DOI: 10.1111/j.1442-9071.1996.tb01585.x] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To assess the rate of change in the central retinal venous closing pressure in central retinal vein obstruction over time, and its relationship to visual acuity improvement and the development of rubeosis iridis. METHODS Fifty patients presenting with central retinal vein obstruction of less than three months' duration, between the ages of 40 and 80 years, were reviewed prospectively. The central retinal venous closing pressure was measured by digital ocular compression. Patients were discharged from the study after the six-month visit. RESULTS All patients had elevated venous closing pressure at presentation, whereas at six months only 24 patients had persistent elevation. Of 16 patients with lowering of the venous closing pressure within four months of onset of central retinal vein obstruction, 11 (69%) had two or more lines of visual acuity improvement. Only two of 10 patients (20%) developing lowering of the venous closing pressure thereafter had visual improvement. No patient developed rubeosis iridis after the venous closing pressure lowered. CONCLUSION The central retinal venous closing pressure is raised in central retinal vein obstruction to about central retinal arterial diastolic pressure, and is its pathognomonic sign. This sign is easily elicited via digital pressure on the eyelid, and has prognostic significance for visual acuity improvement and the development of rubeosis iridis.
Collapse
|
49
|
Limb GA, Chignell AH, Woon H, Green W, Cole CJ, Dumonde DC. Evidence of chronic inflammation in retina excised after relaxing retinotomy for anterior proliferative vitreoretinopathy. Graefes Arch Clin Exp Ophthalmol 1996; 234:213-20. [PMID: 8964525 DOI: 10.1007/bf00430412] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND Epiretinal membranes from eyes with proliferative vitreoretinopathy (PVR) frequently express molecules associated with chronic inflammation. To investigate the extent to which inflammation may compromise the detached retina, we determined the expression of inflammatory molecules in anterior retina removed after relaxing retinotomy for retinal detachment complicated by anterior PVR. METHODS Surgical retinal specimens were studied immunohistochemically for the distribution of the vascular cell adhesion molecules VCAM, E-selectin, P-selectin, ICAM and PECAM and for the presence of the cytokine TNF alpha and of T lymphocytes (CD3-positive cells), macrophages (CD68-positive cells) and HLA-DR molecules. The findings were compared with those in control cadaveric retina. RESULTS Aberrant expression of ICAM-1 was observed in four of nine retinal specimens from eyes with PVR, whereas its expression in control retinas was confined to the external limiting membrane and ganglion cell layers. PECAM was observed in seven of nine surgical retinal specimens and in four of five controls. E-selectin and P-selectin were expressed within the luminal aspects of four of nine retinal specimens from eyes with PVR, and VCAM was present in three of nine surgical specimens investigated. All cadaveric control retinas were negative for E-selectin and VCAM, whilst one was positive for P-selectin. Staining for TNF alpha was observed within luminal aspects and walls of retinal vessels from eight of nine surgical specimens, but was not seen in any of the cadaveric controls. T lymphocytes and cells expressing the macrophage marker CD68 were identified in two and seven of nine diseased retinas respectively, but not in any of the controls. Cells staining for HLA-DR were observed in eight of nine surgical retinal specimens and in three of five controls. CONCLUSION The present findings indicate that retina from eyes with advanced PVR may itself be subject to inflammatory changes, and indicate that the PVR process is not limited to retinal membranes, but involves a more widespread distribution of inflammation than is generally appreciated.
Collapse
Affiliation(s)
- G A Limb
- Immunology Research Unit, Rayne Institute, St Thomas' Hospital, London, UK
| | | | | | | | | | | |
Collapse
|
50
|
Limb GA, Chignell AH, Green W, LeRoy F, Dumonde DC. Distribution of TNF alpha and its reactive vascular adhesion molecules in fibrovascular membranes of proliferative diabetic retinopathy. Br J Ophthalmol 1996; 80:168-73. [PMID: 8814750 PMCID: PMC505411 DOI: 10.1136/bjo.80.2.168] [Citation(s) in RCA: 122] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
AIMS This study investigated the presence of the cytokine tumour necrosis factor alpha (TNF alpha) and the vascular adhesion glycoproteins ICAM-1, VCAM-1, E-selectin, P-selectin, and PECAM within fibrovascular membranes of eyes with proliferative diabetic retinopathy (PDR). METHODS The presence of these molecules was determined by immunohistochemical staining using monoclonal antibodies and the APAAP technique. RESULTS Staining for TNF alpha was observed on the retinal vascular endothelium of five of 12 specimens, on infiltrating cells within all membranes, and on the extracellular matrix of nine specimens. This staining wa abolished by absorption of the monoclonal antibody with human recombinant TNF alpha. Likewise, ICAM-1 staining was given by infiltrating cells and extracellular matrix of nine membranes and by the endothelium of three of the specimens. VCAM-1, E-selectin, and P-selectin staining was observed on the vascular endothelium of 5/12, 4/12, and 3/12 epiretinal membranes respectively. PECAM was expressed by the endothelium of 4/12 specimens, by infiltrating cells of 8/12 membranes, and also by the extracellular matrix of two of the specimens. CONCLUSION The widespread distribution of TNF alpha and the nature of the adhesion molecules expressed by vascular endothelial cells in PDR membranes suggest that local activation of TNF alpha and enhanced expression of vascular cell adhesion molecules may play an important role in the development of the proliferative phase of diabetic retinopathy.
Collapse
Affiliation(s)
- G A Limb
- Department of Immunology, St Thomas's Hospital, London
| | | | | | | | | |
Collapse
|