Batteries that extend performance beyond the intrinsic limits of Li-ion batteries are among the most important developments required to continue the revolution promised by electrochemical devices. Of these next-generation batteries, lithium sulfur (Li–S) chemistry is among the most commercially mature, with cells offering a substantial increase in gravimetric energy density, reduced costs and improved safety prospects. However, there remain outstanding issues to advance the commercial prospects of the technology and benefit from the economies of scale felt by Li-ion cells, including improving both the rate performance and longevity of cells. To address these challenges, the Faraday Institution, the UK's independent institute for electrochemical energy storage science and technology, launched the Lithium Sulfur Technology Accelerator (LiSTAR) programme in October 2019. This Roadmap, authored by researchers and partners of the LiSTAR programme, is intended to highlight the outstanding issues that must be addressed and provide an insight into the pathways towards solving them adopted by the LiSTAR consortium. In compiling this Roadmap we hope to aid the development of the wider Li–S research community, providing a guide for academia, industry, government and funding agencies in this important and rapidly developing research space.
Batteries that extend performance beyond the intrinsic limits of Li-ion batteries are among the most important developments required to continue the revolution promised by electrochemical devices. Of these next-generation batteries, lithium sulfur (Li–S) chemistry is among the most commercially mature, with cells offering a substantial increase in gravimetric energy density, reduced costs and improved safety prospects. However, there remain outstanding issues to advance the commercial prospects of the technology and benefit from the economies of scale felt by Li-ion cells, including improving both the rate performance and longevity of cells. To address these challenges, the Faraday Institution, the UK's independent institute for electrochemical energy storage science and technology, launched the Lithium Sulfur Technology Accelerator (LiSTAR) programme in October 2019. This Roadmap, authored by researchers and partners of the LiSTAR programme, is intended to highlight the outstanding issues that must be addressed and provide an insight into the pathways towards solving them adopted by the LiSTAR consortium. In compiling this Roadmap we hope to aid the development of the wider Li–S research community, providing a guide for academia, industry, government and funding agencies in this important and rapidly developing research space.
Genome sequencing, assembly and annotation were conducted by the Novogene Bioinformatics Institute, Beijing, China; mutual contracts were No. NHT140016 and NVT140016004. This work was supported by funding from the Scientific Project of Shenzhen Urban Administration (201519) and a Major Technical Research Project of the Innovation of Science and Technology Commission of Shenzhen (JSGG20140515164852417). Additional funding was provided in particular by the Scientific Research Program of Sino-Africa Joint Research Center (SAJL201607). We thank X.Q. Wang, G.W. Hu, Z.D. Chen and Y.H. Guo for comments on gnetophyte phylogenetic relationships and ecological issues; H. Wu and X.P. Ning for discussion of related organ development; K.K. Wan and S. Sun for additional help on the analysis of repeats. We also thank X.Y. for support of funding coordination. Y.V.d.P. acknowledges the Multidisciplinary Research Partnership 'Bioinformatics: from nucleotides to networks' Project (no. 01MR0310W) of Ghent University, and funding from the European Union Seventh Framework Programme (FP7/2007-2013) under European Research Council Advanced Grant Agreement 322739-DOUBLEUP.
The β decay of the N = 83 nucleus ¹³¹Cd has been studied at the RIBF facility at the RIKEN Nishina Center. The main purpose of the study was to identify the position of the 1p₃/₂ and 0 f₅/₂ proton-hole states and the energies of core-excited configurations in the semi-magic nucleus ¹³¹In. From the radiation emitted following the ββ decay, a level scheme of ¹³¹In was established and the β feeding to each excited state determined. Similarities between the single-particle transitions observed in the ββ decays of the N = 83 isotones ¹³²In and ¹³¹Cd are discussed. Finally the excitation energies of several core-excited configurations in ¹³¹In are compared to QRPA and shell-model calculations. ; This work was supported by the Spanish Ministerio de Ciencia e Innovaci´on under contract FPA2011-29854-C04 and the Spanish Ministerio de Econom´ıa y Competitividad under contract FPA2014-57196-C5-4-P, the Generalitat Valenciana (Spain) under grant PROMETEO/2010/101, the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No. NRF-2014S1A2A2028636), the Priority Centers Research Program in Korea (2009-0093817), OTKA contract number K-100835, JSPS KAKENHI (Grant No. 25247045), the Grant by IN2P3-RFBR under Agreement No. 110291054, the STFC (UK), the European Commission through the Marie Curie Actions call FP7-PEOPLE-2011- IEF under Contract No. 300096, the U.S. Department of Energy, Office of Nuclear Physics, under Contract No. DE-AC02- 06CH11357, the "RIKEN foreign research program" and the German BMBF (No. 05P12RDCIA and 05P12RDNUP) and HIC for FAIR.
The β decay of the semi-magic nucleus has been studied at the RIBF facility at the RIKEN Nishina Center. The high statistics of the present experiment allowed for a revision of the established level scheme of ¹³⁰In and the observation of additional β feeding to high-lying core-excited states in ¹³⁰In. The experimental results are compared to shell-model calculations employing a model space consisting of the full major N = 50–82 neutron and Z = 28–50 proton shells and the NA-14 interaction, and good agreement is found. ; This work was supported by the Spanish Ministerio de Ciencia e Innovaci´on under contract FPA2011-29854-C04 and the Spanish Ministerio de Econom´ıa y Competitividad under Contract No. FPA2014-57196-C5- 4-P, the Generalitat Valenciana (Spain) under Grant No. PROMETEO/2010/101, the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (NRF-2014S1A2A2028636, 2016K1A3A7A09005579), the Priority Centers Research Program in Korea (2009-0093817), OTKA Contract No. K-100835, JSPS KAKENHI (Grant No. 25247045), the European Commission through the Marie Curie Actions call FP7-PEOPLE-2011-IEF under Contract No. 300096, the US Department of Energy, Office of Nuclear Physics, under Contract No.DE-AC02-06CH11357, the STFC (UK), the "RIKEN foreign research program," the German BMBF (No. 05P12RDCIA, No. 05P12RDNUP, and No. 05P12PKFNE), HIC for FAIR, the DFG cluster of excellence "Origin and Structure of the Universe," and DFG (Contract No. KR2326/2-1).
OBJECTIVE: To generate a global reference for caesarean section (CS) rates at health facilities. DESIGN: Cross-sectional study. SETTING: Health facilities from 43 countries. POPULATION/SAMPLE: Thirty eight thousand three hundred and twenty-four women giving birth from 22 countries for model building and 10,045,875 women giving birth from 43 countries for model testing. METHODS: We hypothesised that mathematical models could determine the relationship between clinical-obstetric characteristics and CS. These models generated probabilities of CS that could be compared with the observed CS rates. We devised a three-step approach to generate the global benchmark of CS rates at health facilities: creation of a multi-country reference population, building mathematical models, and testing these models. MAIN OUTCOME MEASURES: Area under the ROC curves, diagnostic odds ratio, expected CS rate, observed CS rate. RESULTS: According to the different versions of the model, areas under the ROC curves suggested a good discriminatory capacity of C-Model, with summary estimates ranging from 0.832 to 0.844. The C-Model was able to generate expected CS rates adjusted for the case-mix of the obstetric population. We have also prepared an e-calculator to facilitate use of C-Model (www.who.int/reproductivehealth/publications/maternal_perinatal_health/c-model/en/). CONCLUSIONS: This article describes the development of a global reference for CS rates. Based on maternal characteristics, this tool was able to generate an individualised expected CS rate for health facilities or groups of health facilities. With C-Model, obstetric teams, health system managers, health facilities, health insurance companies, and governments can produce a customised reference CS rate for assessing use (and overuse) of CS. TWEETABLE ABSTRACT: The C-Model provides a customized benchmark for caesarean section rates in health facilities and systems.
ObjectiveTo generate a global reference for caesarean section (CS) rates at health facilities. DesignCross-sectional study. SettingHealth facilities from 43 countries. Population/SampleThirty eight thousand three hundred and twenty-four women giving birth from 22 countries for model building and 10045875 women giving birth from 43 countries for model testing. MethodsWe hypothesised that mathematical models could determine the relationship between clinical-obstetric characteristics and CS. These models generated probabilities of CS that could be compared with the observed CS rates. We devised a three-step approach to generate the global benchmark of CS rates at health facilities: creation of a multi-country reference population, building mathematical models, and testing these models. Main outcome measuresArea under the ROC curves, diagnostic odds ratio, expected CS rate, observed CS rate. ResultsAccording to the different versions of the model, areas under the ROC curves suggested a good discriminatory capacity of C-Model, with summary estimates ranging from 0.832 to 0.844. The C-Model was able to generate expected CS rates adjusted for the case-mix of the obstetric population. We have also prepared an e-calculator to facilitate use of C-Model (). ConclusionsThis article describes the development of a global reference for CS rates. Based on maternal characteristics, this tool was able to generate an individualised expected CS rate for health facilities or groups of health facilities. With C-Model, obstetric teams, health system managers, health facilities, health insurance companies, and governments can produce a customised reference CS rate for assessing use (and overuse) of CS. Tweetable abstractThe C-Model provides a customized benchmark for caesarean section rates in health facilities and systems. Tweetable abstract The C-Model provides a customized benchmark for caesarean section rates in health facilities and systems. ; NICHD NIH HHS ; World Health Organization ; Univ Sao Paulo, Ribeirao Preto Med Sch, Dept Social Med, Av Bandeirantes, BR-3900 Ribeirao Preto, Brazil ; WHO, World Bank Special Programme Res Dev & Res Traini, UNDP UNFPA UNICEF WHO, Dept Reprod Hlth & Res, CH-1211 Geneva, Switzerland ; Univ Paris 05, Sorbonne Paris Cite, UMR 216, Inst Dev Res, Paris, France ; WHO Reg Off Amer, Women & Reprod Hlth CLAP WR, Latin Amer Ctr Perinatol, Montevideo, Uruguay ; Emory Univ, Rollins Sch Publ Hlth, Dept Epidemiol, Atlanta, GA 30322 USA ; Paris Descartes Univ, Ctr Epidemiol & Biostat, Obstetr Perinatal & Pediat Epidemiol Res Team, Inserm U1153, Paris, France ; Natl Inst Publ Hlth, Ctr Populat Hlth Res, Cuernavaca, Morelos, Mexico ; Univ Technol, Fac Hlth, Sydney, NSW, Australia ; Natl Ctr Child Hlth & Dev, Dept Hlth Policy, Tokyo, Japan ; Ctr Rosarino Estudios Perinat, Rosario, Argentina ; Lindsay Stewart R&D Ctr, Off Res & Clin Audit, Royal Coll Obstetricians & Gynaecologists, London, England ; London Sch Hyg & Trop Med, Dept Hlth Serv Res & Policy, London WC1, England ; Shanghai Jiao Tong Univ, Sch Med, Xinhua Hosp, Shanghai Key Lab Childrens Environ Hlth,Minist Ed, Shanghai 200030, Peoples R China ; Univ Estadual Campinas, Sch Med Sci, Dept Obstet & Gynaecol, Campinas, SP, Brazil ; Family Hlth Bur, Minist Hlth, Colombo, Sri Lanka ; Fiocruz MS, ENSP, BR-21045900 Rio De Janeiro, Brazil ; Natl Inst Hlth & Welf, Helsinki, Finland ; Univ Tokyo, Grad Sch Med, Dept Paediat, Tokyo, Japan ; Bayer Krankenhausgesellschaft, Bayer Arbeitsgemeinschaft Qualitatssicherun Stati, Munich, Germany ; Khon Kaen Univ, Fac Med, Dept Obstet & Gynecol, Khon, Kaen, Thailand ; Univ Sao Paulo, Ribeirao Preto Med Sch, Dept Obstet & Gynaecol, BR-14049 Ribeirao Preto, Brazil ; Minist Sante, Direct Sante Famille, Ouagadougou, Burkina Faso ; Univ Washington, Inst Hlth Metr & Evaluat, Seattle, WA 98195 USA ; Univ Mongolia, Hlth Sci, Sch Publ Hlth, Ulaanbaatar, Mongol Peo Rep ; GLIDE Tech Cooperat & Res, Ribeirao Preto, SP, Brazil ; Univ Sao Paulo, Ribeirao Preto Med Sch, Dept Paediat, BR-14049 Ribeirao Preto, SP, Brazil ; Univ Calif San Francisco, Dept Obstet & Gynaecol & Global Hlth Sci, San Francisco, CA 94143 USA ; Khon Kaen Univ, Fac Publ Hlth, Dept Biostat & Demog, Khon Kaen, Thailand ; Univ Fed Sao Paulo, Sch Med Sao Paulo, Dept Obstet, Sao Paulo, Brazil ; Inter Amer Dev Bank, Social Protect & Hlth Div, Mexico City, DF, Mexico ; Fortis Mem Res Inst, Gurgaon, Haryana, India ; Hosp Nacl Itaugua, Itaugua, Paraguay ; Univ Fed Sao Paulo, Sch Med Sao Paulo, Dept Obstet, Sao Paulo, Brazil ; NICHD NIH HHS: T32 HD052460 ; World Health Organization: 001 ; Web of Science
ObjectiveTo generate a global reference for caesarean section (CS) rates at health facilities. DesignCross-sectional study. SettingHealth facilities from 43 countries. Population/SampleThirty eight thousand three hundred and twenty-four women giving birth from 22 countries for model building and 10045875 women giving birth from 43 countries for model testing. MethodsWe hypothesised that mathematical models could determine the relationship between clinical-obstetric characteristics and CS. These models generated probabilities of CS that could be compared with the observed CS rates. We devised a three-step approach to generate the global benchmark of CS rates at health facilities: creation of a multi-country reference population, building mathematical models, and testing these models. Main outcome measuresArea under the ROC curves, diagnostic odds ratio, expected CS rate, observed CS rate. ResultsAccording to the different versions of the model, areas under the ROC curves suggested a good discriminatory capacity of C-Model, with summary estimates ranging from 0.832 to 0.844. The C-Model was able to generate expected CS rates adjusted for the case-mix of the obstetric population. We have also prepared an e-calculator to facilitate use of C-Model (). ConclusionsThis article describes the development of a global reference for CS rates. Based on maternal characteristics, this tool was able to generate an individualised expected CS rate for health facilities or groups of health facilities. With C-Model, obstetric teams, health system managers, health facilities, health insurance companies, and governments can produce a customised reference CS rate for assessing use (and overuse) of CS. Tweetable abstractThe C-Model provides a customized benchmark for caesarean section rates in health facilities and systems. Tweetable abstract The C-Model provides a customized benchmark for caesarean section rates in health facilities and systems. ; NICHD NIH HHS ; World Health Organization ; Univ Sao Paulo, Ribeirao Preto Med Sch, Dept Social Med, Av Bandeirantes, BR-3900 Ribeirao Preto, Brazil ; WHO, World Bank Special Programme Res Dev & Res Traini, UNDP UNFPA UNICEF WHO, Dept Reprod Hlth & Res, CH-1211 Geneva, Switzerland ; Univ Paris 05, Sorbonne Paris Cite, UMR 216, Inst Dev Res, Paris, France ; WHO Reg Off Amer, Women & Reprod Hlth CLAP WR, Latin Amer Ctr Perinatol, Montevideo, Uruguay ; Emory Univ, Rollins Sch Publ Hlth, Dept Epidemiol, Atlanta, GA 30322 USA ; Paris Descartes Univ, Ctr Epidemiol & Biostat, Obstetr Perinatal & Pediat Epidemiol Res Team, Inserm U1153, Paris, France ; Natl Inst Publ Hlth, Ctr Populat Hlth Res, Cuernavaca, Morelos, Mexico ; Univ Technol, Fac Hlth, Sydney, NSW, Australia ; Natl Ctr Child Hlth & Dev, Dept Hlth Policy, Tokyo, Japan ; Ctr Rosarino Estudios Perinat, Rosario, Argentina ; Lindsay Stewart R&D Ctr, Off Res & Clin Audit, Royal Coll Obstetricians & Gynaecologists, London, England ; London Sch Hyg & Trop Med, Dept Hlth Serv Res & Policy, London WC1, England ; Shanghai Jiao Tong Univ, Sch Med, Xinhua Hosp, Shanghai Key Lab Childrens Environ Hlth,Minist Ed, Shanghai 200030, Peoples R China ; Univ Estadual Campinas, Sch Med Sci, Dept Obstet & Gynaecol, Campinas, SP, Brazil ; Family Hlth Bur, Minist Hlth, Colombo, Sri Lanka ; Fiocruz MS, ENSP, BR-21045900 Rio De Janeiro, Brazil ; Natl Inst Hlth & Welf, Helsinki, Finland ; Univ Tokyo, Grad Sch Med, Dept Paediat, Tokyo, Japan ; Bayer Krankenhausgesellschaft, Bayer Arbeitsgemeinschaft Qualitatssicherun Stati, Munich, Germany ; Khon Kaen Univ, Fac Med, Dept Obstet & Gynecol, Khon, Kaen, Thailand ; Univ Sao Paulo, Ribeirao Preto Med Sch, Dept Obstet & Gynaecol, BR-14049 Ribeirao Preto, Brazil ; Minist Sante, Direct Sante Famille, Ouagadougou, Burkina Faso ; Univ Washington, Inst Hlth Metr & Evaluat, Seattle, WA 98195 USA ; Univ Mongolia, Hlth Sci, Sch Publ Hlth, Ulaanbaatar, Mongol Peo Rep ; GLIDE Tech Cooperat & Res, Ribeirao Preto, SP, Brazil ; Univ Sao Paulo, Ribeirao Preto Med Sch, Dept Paediat, BR-14049 Ribeirao Preto, SP, Brazil ; Univ Calif San Francisco, Dept Obstet & Gynaecol & Global Hlth Sci, San Francisco, CA 94143 USA ; Khon Kaen Univ, Fac Publ Hlth, Dept Biostat & Demog, Khon Kaen, Thailand ; Univ Fed Sao Paulo, Sch Med Sao Paulo, Dept Obstet, Sao Paulo, Brazil ; Inter Amer Dev Bank, Social Protect & Hlth Div, Mexico City, DF, Mexico ; Fortis Mem Res Inst, Gurgaon, Haryana, India ; Hosp Nacl Itaugua, Itaugua, Paraguay ; Univ Fed Sao Paulo, Sch Med Sao Paulo, Dept Obstet, Sao Paulo, Brazil ; NICHD NIH HHS: T32 HD052460 ; World Health Organization: 001 ; Web of Science
Background: The amount of resources, particularly prepaid resources, available for health can affect access to health care and health outcomes. Although health spending tends to increase with economic development, tremendous variation exists among health financing systems. Estimates of future spending can be beneficial for policy makers and planners, and can identify financing gaps. In this study, we estimate future gross domestic product (GDP), all-sector government spending, and health spending disaggregated by source, and we compare expected future spending to potential future spending. Methods: We extracted GDP, government spending in 184 countries from 1980–2015, and health spend data from 1995–2014. We used a series of ensemble models to estimate future GDP, all-sector government spending, development assistance for health, and government, out-of-pocket, and prepaid private health spending through 2040. We used frontier analyses to identify patterns exhibited by the countries that dedicate the most funding to health, and used these frontiers to estimate potential health spending for each low-income or middle-income country. All estimates are inflation and purchasing power adjusted. Findings: We estimated that global spending on health will increase from US$9·21 trillion in 2014 to $24·24 trillion (uncertainty interval [UI] 20·47–29·72) in 2040. We expect per capita health spending to increase fastest in upper-middle-income countries, at 5·3% (UI 4·1–6·8) per year. This growth is driven by continued growth in GDP, government spending, and government health spending. Lower-middle income countries are expected to grow at 4·2% (3·8–4·9). High-income countries are expected to grow at 2·1% (UI 1·8–2·4) and low-income countries are expected to grow at 1·8% (1·0–2·8). Despite this growth, health spending per capita in low-income countries is expected to remain low, at $154 (UI 133–181) per capita in 2030 and $195 (157–258) per capita in 2040. Increases in national health spending to reach the level of the countries who spend the most on health, relative to their level of economic development, would mean $321 (157–258) per capita was available for health in 2040 in low-income countries. Interpretation: Health spending is associated with economic development but past trends and relationships suggest that spending will remain variable, and low in some low-resource settings. Policy change could lead to increased health spending, although for the poorest countries external support might remain essential.
Background: The amount of resources, particularly prepaid resources, available for health can affect access to health care and health outcomes. Although health spending tends to increase with economic development, tremendous variation exists among health financing systems. Estimates of future spending can be beneficial for policy makers and planners, and can identify financing gaps. In this study, we estimate future gross domestic product (GDP), all-sector government spending, and health spending disaggregated by source, and we compare expected future spending to potential future spending. Methods: We extracted GDP, government spending in 184 countries from 1980-2015, and health spend data from 1995-2014. We used a series of ensemble models to estimate future GDP, all-sector government spending, development assistance for health, and government, out-of-pocket, and prepaid private health spending through 2040. We used frontier analyses to identify patterns exhibited by the countries that dedicate the most funding to health, and used these frontiers to estimate potential health spending for each low-income or middle-income country. All estimates are inflation and purchasing power adjusted. Findings: We estimated that global spending on health will increase from US$9.21 trillion in 2014 to $24.24 trillion (uncertainty interval [UI] 20.47-29.72) in 2040. We expect per capita health spending to increase fastest in upper-middle-income countries, at 5.3% (UI 4.1-6.8) per year. This growth is driven by continued growth in GDP, government spending, and government health spending. Lower-middle income countries are expected to grow at 4.2% (3.8-4.9). High-income countries are expected to grow at 2.1% (UI 1.8-2.4) and low-income countries are expected to grow at 1.8% (1.0-2.8). Despite this growth, health spending per capita in low-income countries is expected to remain low, at $154 (UI 133-181) per capita in 2030 and $195 (157-258) per capita in 2040. Increases in national health spending to reach the level of the countries who spend the most on health, relative to their level of economic development, would mean $321 (157-258) per capita was available for health in 2040 in low-income countries. Interpretation: Health spending is associated with economic development but past trends and relationships suggest that spending will remain variable, and low in some low-resource settings. Policy change could lead to increased health spending, although for the poorest countries external support might remain essential.
Using the data sets taken at center-of-mass energies above 4 GeV by the BESIII detector at the BEPCII storage ring, we search for the reaction e(+)e(-) -> gamma(ISR) X(3872) -> gamma(ISR)pi(+)pi(-) J/psi via the Initial State Radiation technique. The production of a resonance with quantum numbers J(PC) = 1(++) such as the X(3872) via single photon e(+)e(-) annihilation is forbidden, but is allowed by a next-to-leading order box diagram. We do not observe a significant signal of X(3872), and therefore give an upper limit for the electronic width times the branching fraction Gamma B-X(3872)(ee)(X(3872) -> pi(+)pi(-) J/psi) < 0.13 eVat the 90% confidence level. This measurement improves upon existing limits by a factor of 46. Using the same final state, we also measure the electronic width of the psi(3686) to be Gamma(psi)(ee)(3686) ee = 2213 +/- 18(stat) +/- 99(sys) eV. ; Funding: The BESIII collaboration thanks the staff of BEPCII and the IHEP computing center for their strong support. This work is supported in part by the National Key Basic Research Program of China under Contract No. 2015CB856700; National Natural Science Foundation of China (NSFC) under Contract Nos. 11125525, 11235011, 11322544, 11335008, 11425524; the Chinese Academy of Sciences (CAS) Large-Scale Scientific Facility Program; Joint Large-Scale Scientific Facility Funds of the NSFC and CAS under Contract Nos. 11179007, U1232201, U1332201; CAS under Contract Nos. KJCX2-YW-N29, KJCX2-YW-N45; 100 Talents Program of CAS; INPAC and Shanghai Key Laboratory for Particle Physics and Cosmology; German Research Foundation DFG under Contract No. CRC-1044; Seventh Framework Programme of the European Union under Marie Curie International Incoming Fellowship Grant Agreement No. 627240; Istituto Nazionale di Fisica Nucleare, Italy; Ministry of Development of Turkey under Contract No. DPT2006K-120470; Russian Foundation for Basic Research under Contract No. 14-07-91152; U.S. Department of Energy under Contract Nos. DE-FG02-04ER41291, DE-FG02-05ER41374, DE-FG02-94ER40823, DESC0010118; U.S. National Science Foundation; University of Groningen (RuG) and the Helmholtzzentrum fur Schwerionenforschung (GSI), Darmstadt; WCU Program of National Research Foundation of Korea under Contract No. R32-2008-000-10155-0.
Background Surgery is the main modality of cure for solid cancers and was prioritised to continue during COVID-19 outbreaks. This study aimed to identify immediate areas for system strengthening by comparing the delivery of elective cancer surgery during the COVID-19 pandemic in periods of lockdown versus light restriction. Methods This international, prospective, cohort study enrolled 20 006 adult (≥18 years) patients from 466 hospitals in 61 countries with 15 cancer types, who had a decision for curative surgery during the COVID-19 pandemic and were followed up until the point of surgery or cessation of follow-up (Aug 31, 2020). Average national Oxford COVID-19 Stringency Index scores were calculated to define the government response to COVID-19 for each patient for the period they awaited surgery, and classified into light restrictions (index 60). The primary outcome was the non-operation rate (defined as the proportion of patients who did not undergo planned surgery). Cox proportional-hazards regression models were used to explore the associations between lockdowns and non-operation. Intervals from diagnosis to surgery were compared across COVID-19 government response index groups. This study was registered at ClinicalTrials.gov, NCT04384926. Findings Of eligible patients awaiting surgery, 2003 (10·0%) of 20 006 did not receive surgery after a median follow-up of 23 weeks (IQR 16–30), all of whom had a COVID-19-related reason given for non-operation. Light restrictions were associated with a 0·6% non-operation rate (26 of 4521), moderate lockdowns with a 5·5% rate (201 of 3646; adjusted hazard ratio [HR] 0·81, 95% CI 0·77–0·84; p<0·0001), and full lockdowns with a 15·0% rate (1775 of 11 827; HR 0·51, 0·50–0·53; p<0·0001). In sensitivity analyses, including adjustment for SARS-CoV-2 case notification rates, moderate lockdowns (HR 0·84, 95% CI 0·80–0·88; p<0·001), and full lockdowns (0·57, 0·54–0·60; p<0·001), remained independently associated with non-operation. Surgery beyond 12 weeks from diagnosis in patients without neoadjuvant therapy increased during lockdowns (374 [9·1%] of 4521 in light restrictions, 317 [10·4%] of 3646 in moderate lockdowns, 2001 [23·8%] of 11 827 in full lockdowns), although there were no differences in resectability rates observed with longer delays. Interpretation Cancer surgery systems worldwide were fragile to lockdowns, with one in seven patients who were in regions with full lockdowns not undergoing planned surgery and experiencing longer preoperative delays. Although short-term oncological outcomes were not compromised in those selected for surgery, delays and non-operations might lead to long-term reductions in survival. During current and future periods of societal restriction, the resilience of elective surgery systems requires strengthening, which might include protected elective surgical pathways and long-term investment in surge capacity for acute care during public health emergencies to protect elective staff and services. Funding National Institute for Health Research Global Health Research Unit, Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, Medtronic, Sarcoma UK, The Urology Foundation, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research.
Background Surgery is the main modality of cure for solid cancers and was prioritised to continue during COVID-19 outbreaks. This study aimed to identify immediate areas for system strengthening by comparing the delivery of elective cancer surgery during the COVID-19 pandemic in periods of lockdown versus light restriction. Methods This international, prospective, cohort study enrolled 20 006 adult (≥18 years) patients from 466 hospitals in 61 countries with 15 cancer types, who had a decision for curative surgery during the COVID-19 pandemic and were followed up until the point of surgery or cessation of follow-up (Aug 31, 2020). Average national Oxford COVID-19 Stringency Index scores were calculated to define the government response to COVID-19 for each patient for the period they awaited surgery, and classified into light restrictions (index 60). The primary outcome was the non-operation rate (defined as the proportion of patients who did not undergo planned surgery). Cox proportional-hazards regression models were used to explore the associations between lockdowns and non-operation. Intervals from diagnosis to surgery were compared across COVID-19 government response index groups. This study was registered at ClinicalTrials.gov, NCT04384926. Findings Of eligible patients awaiting surgery, 2003 (10·0%) of 20 006 did not receive surgery after a median follow-up of 23 weeks (IQR 16–30), all of whom had a COVID-19-related reason given for non-operation. Light restrictions were associated with a 0·6% non-operation rate (26 of 4521), moderate lockdowns with a 5·5% rate (201 of 3646; adjusted hazard ratio [HR] 0·81, 95% CI 0·77–0·84; p<0·0001), and full lockdowns with a 15·0% rate (1775 of 11 827; HR 0·51, 0·50–0·53; p<0·0001). In sensitivity analyses, including adjustment for SARS-CoV-2 case notification rates, moderate lockdowns (HR 0·84, 95% CI 0·80–0·88; p<0·001), and full lockdowns (0·57, 0·54–0·60; p<0·001), remained independently associated with non-operation. Surgery beyond 12 weeks from diagnosis in patients without neoadjuvant therapy increased during lockdowns (374 [9·1%] of 4521 in light restrictions, 317 [10·4%] of 3646 in moderate lockdowns, 2001 [23·8%] of 11827 in full lockdowns), although there were no differences in resectability rates observed with longer delays. Interpretation Cancer surgery systems worldwide were fragile to lockdowns, with one in seven patients who were in regions with full lockdowns not undergoing planned surgery and experiencing longer preoperative delays. Although short-term oncological outcomes were not compromised in those selected for surgery, delays and non-operations might lead to long-term reductions in survival. During current and future periods of societal restriction, the resilience of elective surgery systems requires strengthening, which might include protected elective surgical pathways and long- term investment in surge capacity for acute care during public health emergencies to protect elective staff and services. Funding National Institute for Health Research Global Health Research Unit, Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, Medtronic, Sarcoma UK, The Urology Foundation, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research.