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Article ; Online: Forecasting COVID-19 impact on hospital bed-days, ICU-days, ventilator-days and deaths by US state in the next 4 months

Murray, Christopher JL

Abstract: Key Points Question: Assuming social distancing measures are maintained, what are the forecasted gaps in available health service resources and number of deaths from the COVID-19 pandemic for each state in the United States? Findings: Using a statistical ...

Abstract	Key Points Question: Assuming social distancing measures are maintained, what are the forecasted gaps in available health service resources and number of deaths from the COVID-19 pandemic for each state in the United States? Findings: Using a statistical model, we predict excess demand will be 64,175 (95% UI 7,977 to 251,059) total beds and 17,380 (95% UI 2,432 to 57,955) ICU beds at the peak of COVID-19. Peak ventilator use is predicted to be 19,481 (95% UI 9,767 to 39,674) ventilators. Peak demand will be in the second week of April. We estimate 81,114 (95% UI 38,242 to 162,106) deaths in the United States from COVID-19 over the next 4 months. Meaning: Even with social distancing measures enacted and sustained, the peak demand for hospital services due to the COVID-19 pandemic is likely going to exceed capacity substantially. Alongside the implementation and enforcement of social distancing measures, there is an urgent need to develop and implement plans to reduce non-COVID-19 demand for and temporarily increase capacity of health facilities. Abstract Importance: This study presents the first set of estimates of predicted health service utilization and deaths due to COVID-19 by day for the next 4 months for each state in the US. Objective: To determine the extent and timing of deaths and excess demand for hospital services due to COVID-19 in the US. Design, Setting, and Participants: This study used data on confirmed COVID-19 deaths by day from WHO websites and local and national governments; data on hospital capacity and utilization for US states; and observed COVID-19 utilization data from select locations to develop a statistical model forecasting deaths and hospital utilization against capacity by state for the US over the next 4 months. Exposure(s): COVID-19. Main outcome(s) and measure(s): Deaths, bed and ICU occupancy, and ventilator use. Results: Compared to licensed capacity and average annual occupancy rates, excess demand from COVID-19 at the peak of the pandemic in the second week of April is predicted to be 64,175 (95% UI 7,977 to 251,059) total beds and 17,380 (95% UI 2,432 to 57,955) ICU beds. At the peak of the pandemic, ventilator use is predicted to be 19,481 (95% UI 9,767 to 39,674). The date of peak excess demand by state varies from the second week of April through May. We estimate that there will a total of 81,114 (95% UI 38,242 to 162,106) deaths from COVID-19 over the next 4 months in the US. Deaths from COVID-19 are estimated to drop below 10 deaths per day between May 31 and June 6. Conclusions and Relevance: In addition to a large number of deaths from COVID-19, the epidemic in the US will place a load well beyond the current capacity of hospitals to manage, especially for ICU care. These estimates can help inform the development and implementation of strategies to mitigate this gap, including reducing non-COVID-19 demand for services and temporarily increasing system capacity. These are urgently needed given that peak volumes are estimated to be only three weeks away. The estimated excess demand on hospital systems is predicated on the enactment of social distancing measures in all states that have not done so already within the next week and maintenance of these measures throughout the epidemic, emphasizing the importance of implementing, enforcing, and maintaining these measures to mitigate hospital system overload and prevent deaths.
Keywords	covid19
Publisher	MedRxiv
Document type	Article ; Online
DOI	10.1101/2020.03.27.20043752
Database	COVID19

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Article ; Online: Forecasting the impact of the first wave of the COVID-19 pandemic on hospital demand and deaths for the USA and European Economic Area countries

Murray, Christopher JL

Abstract: Summary Background: Hospitals need to plan for the surge in demand in each state or region in the United States and the European Economic Area (EEA) due to the COVID-19 pandemic. Planners need forecasts of the most likely trajectory in the coming weeks ... ...

Abstract	Summary Background: Hospitals need to plan for the surge in demand in each state or region in the United States and the European Economic Area (EEA) due to the COVID-19 pandemic. Planners need forecasts of the most likely trajectory in the coming weeks and will want to plan for the higher values in the range of those forecasts. To date, forecasts of what is most likely to occur in the weeks ahead are not available for states in the USA or for all countries in the EEA. Methods: This study used data on confirmed COVID-19 deaths by day from local and national government websites and WHO. Data on hospital capacity and utilisation and observed COVID-19 utilisation data from select locations were obtained from publicly available sources and direct contributions of data from select local governments. We develop a mixed effects non-linear regression framework to estimate the trajectory of the cumulative and daily death rate as a function of the implementation of social distancing measures, supported by additional evidence from mobile phone data. An extended mixture model was used in data rich settings to capture asymmetric daily death patterns. Health service needs were forecast using a micro-simulation model that estimates hospital admissions, ICU admissions, length of stay, and ventilator need using available data on clinical practices in COVID-19 patients. We assume that those jurisdictions that have not implemented school closures, non-essential business closures, and stay at home orders will do so within twenty-one days. Findings: Compared to licensed capacity and average annual occupancy rates, excess demand in the USA from COVID-19 at the estimated peak of the epidemic (the end of the second week of April) is predicted to be 9,079 (95% UI 253-61,937) total beds and 9,356 (3,526-29,714) ICU beds. At the peak of the epidemic, ventilator use is predicted to be 16,545 (8,083-41,991). The corresponding numbers for EEA countries are 120,080 (119,183-121,107), 32,291 (32,157-32,425) and 28,973 (28,868-29,085) at a peak of April 6. The date of peak daily deaths varies from March 30 through May 12 by state in the USA and March 27 through May 4 by country in the EEA. We estimate that through the end of July, there will be 60,308 (34,063-140,381) deaths from COVID-19 in the USA and 143,088 (101,131-253,163) deaths in the EEA. Deaths from COVID-19 are estimated to drop below 0.3 per million between May 4 and June 29 by state in the USA and between May 4 and July 13 by country in the EEA. Timing of the peak need for hospital resource requirements varies considerably across states in the USA and across regions of Europe. Interpretation: In addition to a large number of deaths from COVID-19, the epidemic will place a load on health system resources well beyond the current capacity of hospitals in the USA and EEA to manage, especially for ICU care and ventilator use. These estimates can help inform the development and implementation of strategies to mitigate this gap, including reducing non-COVID-19 demand for services and temporarily increasing system capacity. The estimated excess demand on hospital systems is predicated on the enactment of social distancing measures within three weeks in all locations that have not done so already and maintenance of these measures throughout the epidemic, emphasising the importance of implementing, enforcing, and maintaining these measures to mitigate hospital system overload and prevent deaths.
Keywords	covid19
Publisher	MedRxiv
Document type	Article ; Online
DOI	10.1101/2020.04.21.20074732
Database	COVID19

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Article ; Online: GBD 2017 and HIV estimates for Taiwan - Authors' reply.

Kyu, Hmwe Hmwe / Jahagirdar, Deepa / Carter, Austin / Murray, Christopher Jl

The lancet. HIV

2020 Volume 7, Issue 4, Page(s) e224–e225

MeSH term(s)	Global Burden of Disease ; HIV Infections ; Humans ; Incidence ; Prevalence ; Risk Factors ; Taiwan
Language	English
Publishing date	2020-03-31
Publishing country	Netherlands
Document type	Letter ; Comment
ISSN	2352-3018
ISSN (online)	2352-3018
DOI	10.1016/S2352-3018(20)30044-8
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: The burden of bacterial antimicrobial resistance in Croatia in 2019: a country-level systematic analysis.

Meštrović, Tomislav / Ikuta, Kevin Shunji / Swetschinski, Lucien / Gray, Authia / Robles Aguilar, Gisela / Han, Chieh / Wool, Eve / Gershberg Hayoon, Anna / Murray, Christopher Jl / Naghavi, Mohsen

Croatian medical journal

2023 Volume 64, Issue 4, Page(s) 272–283

Abstract: Aim: To deliver the most wide-ranging set of antimicrobial resistance (AMR) burden estimates for Croatia to date.: Methods: A complex modeling approach with five broad modeling components was used to estimate the disease burden for 12 main infectious ...

Abstract	Aim: To deliver the most wide-ranging set of antimicrobial resistance (AMR) burden estimates for Croatia to date. Methods: A complex modeling approach with five broad modeling components was used to estimate the disease burden for 12 main infectious syndromes and one residual group, 23 pathogenic bacteria, and 88 bug-drug combinations. This was represented by two relevant counterfactual scenarios: deaths/disability-adjusted life years (DALYs) that are attributable to AMR considering a situation where drug-resistant infections are substituted with sensitive ones, and deaths/DALYs associated with AMR considering a scenario where people with drug-resistant infections would instead present without any infection. The 95% uncertainty intervals (UI) were based on 1000 posterior draws in each modeling step, reported at the 2.5% and 97.5% of the draws' distribution, while out-of-sample predictive validation was pursued for all the models. Results: The total burden associated with AMR in Croatia was 2546 (95% UI 1558-3803) deaths and 46958 (28,033-71,628) DALYs, while the attributable burden was 614 (365-943) deaths and 11321 (6,544-17,809) DALYs. The highest number of deaths was established for bloodstream infections, followed by peritoneal and intra-abdominal infections and infections of the urinary tract. Five leading pathogenic bacterial agents were responsible for 1808 deaths associated with resistance: Escherichia coli, Staphylococcus aureus, Acinetobacter baumannii, Klebsiella pneumoniae, and Pseudomonas aeruginosa (ordered by the number of deaths). Trimethoprim/sulfamethoxazole-resistant E coli and methicillin-resistant S. aureus were dominant pathogen-drug combinations in regard to mortality associated with and attributable to AMR, respectively. Conclusion: We showed that AMR represented a substantial public health concern in Croatia, which reflects global trends; hence, our detailed country-level findings may fast-track the implementation of multipronged strategies tailored in accordance with leading pathogens and pathogen-drug combinations.
MeSH term(s)	Humans ; Anti-Bacterial Agents/pharmacology ; Anti-Bacterial Agents/therapeutic use ; Croatia/epidemiology ; Escherichia coli ; Methicillin-Resistant Staphylococcus aureus ; Drug Resistance, Bacterial ; Bacteria ; Anti-Infective Agents
Chemical Substances	Anti-Bacterial Agents ; Anti-Infective Agents
Language	English
Publishing date	2023-08-31
Publishing country	Croatia
Document type	Journal Article
ZDB-ID	1157623-6
ISSN	1332-8166 ; 0353-9504
ISSN (online)	1332-8166
ISSN	0353-9504
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Article ; Online: Forecasting the impact of the first wave of the COVID-19 pandemic on hospital demand and deaths for the USA and European Economic Area countries

team, IHME COVID-19 health service utilization forecasting / Murray, Christopher JL

Abstract	Summary Background: Hospitals need to plan for the surge in demand in each state or region in the United States and the European Economic Area (EEA) due to the COVID-19 pandemic. Planners need forecasts of the most likely trajectory in the coming weeks and will want to plan for the higher values in the range of those forecasts. To date, forecasts of what is most likely to occur in the weeks ahead are not available for states in the USA or for all countries in the EEA. Methods: This study used data on confirmed COVID-19 deaths by day from local and national government websites and WHO. Data on hospital capacity and utilisation and observed COVID-19 utilisation data from select locations were obtained from publicly available sources and direct contributions of data from select local governments. We develop a mixed effects non-linear regression framework to estimate the trajectory of the cumulative and daily death rate as a function of the implementation of social distancing measures, supported by additional evidence from mobile phone data. An extended mixture model was used in data rich settings to capture asymmetric daily death patterns. Health service needs were forecast using a micro-simulation model that estimates hospital admissions, ICU admissions, length of stay, and ventilator need using available data on clinical practices in COVID-19 patients. We assume that those jurisdictions that have not implemented school closures, non-essential business closures, and stay at home orders will do so within twenty-one days. Findings: Compared to licensed capacity and average annual occupancy rates, excess demand in the USA from COVID-19 at the estimated peak of the epidemic (the end of the second week of April) is predicted to be 9,079 (95% UI 253-61,937) total beds and 9,356 (3,526-29,714) ICU beds. At the peak of the epidemic, ventilator use is predicted to be 16,545 (8,083-41,991). The corresponding numbers for EEA countries are 120,080 (119,183-121,107), 32,291 (32,157-32,425) and 28,973 (28,868-29,085) at a peak of April 6. The date of peak daily deaths varies from March 30 through May 12 by state in the USA and March 27 through May 4 by country in the EEA. We estimate that through the end of July, there will be 60,308 (34,063-140,381) deaths from COVID-19 in the USA and 143,088 (101,131-253,163) deaths in the EEA. Deaths from COVID-19 are estimated to drop below 0.3 per million between May 4 and June 29 by state in the USA and between May 4 and July 13 by country in the EEA. Timing of the peak need for hospital resource requirements varies considerably across states in the USA and across regions of Europe. Interpretation: In addition to a large number of deaths from COVID-19, the epidemic will place a load on health system resources well beyond the current capacity of hospitals in the USA and EEA to manage, especially for ICU care and ventilator use. These estimates can help inform the development and implementation of strategies to mitigate this gap, including reducing non-COVID-19 demand for services and temporarily increasing system capacity. The estimated excess demand on hospital systems is predicated on the enactment of social distancing measures within three weeks in all locations that have not done so already and maintenance of these measures throughout the epidemic, emphasising the importance of implementing, enforcing, and maintaining these measures to mitigate hospital system overload and prevent deaths.
Keywords	covid19
Publisher	MedRxiv; WHO
Document type	Article ; Online
Note	WHO #Covidence: #20074732
DOI	10.1101/2020.04.21.20074732
Database	COVID19

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Article ; Online: Forecasting COVID-19 impact on hospital bed-days, ICU-days, ventilator-days and deaths by US state in the next 4 months

team, IHME COVID-19 health service utilization forecasting / Murray, Christopher JL

Abstract: ImportanceThis study presents the first set of estimates of predicted health service utilization and deaths due to COVID-19 by day for the next 4 months for each state in the US. ObjectiveTo determine the extent and timing of deaths and excess demand for ...

Abstract	ImportanceThis study presents the first set of estimates of predicted health service utilization and deaths due to COVID-19 by day for the next 4 months for each state in the US. ObjectiveTo determine the extent and timing of deaths and excess demand for hospital services due to COVID-19 in the US. Design, Setting, and ParticipantsThis study used data on confirmed COVID-19 deaths by day from WHO websites and local and national governments; data on hospital capacity and utilization for US states; and observed COVID-19 utilization data from select locations to develop a statistical model forecasting deaths and hospital utilization against capacity by state for the US over the next 4 months. Exposure(s)COVID-19. Main outcome(s) and measure(s)Deaths, bed and ICU occupancy, and ventilator use. ResultsCompared to licensed capacity and average annual occupancy rates, excess demand from COVID-19 at the peak of the pandemic in the second week of April is predicted to be 64,175 (95% UI 7,977 to 251,059) total beds and 17,380 (95% UI 2,432 to 57,955) ICU beds. At the peak of the pandemic, ventilator use is predicted to be 19,481 (95% UI 9,767 to 39,674). The date of peak excess demand by state varies from the second week of April through May. We estimate that there will be a total of 81,114 (95% UI 38,242 to 162,106) deaths from COVID-19 over the next 4 months in the US. Deaths from COVID-19 are estimated to drop below 10 deaths per day between May 31 and June 6. Conclusions and RelevanceIn addition to a large number of deaths from COVID-19, the epidemic in the US will place a load well beyond the current capacity of hospitals to manage, especially for ICU care. These estimates can help inform the development and implementation of strategies to mitigate this gap, including reducing non-COVID-19 demand for services and temporarily increasing system capacity. These are urgently needed given that peak volumes are estimated to be only three weeks away. The estimated excess demand on hospital systems is predicated on the enactment of social distancing measures in all states that have not done so already within the next week and maintenance of these measures throughout the epidemic, emphasizing the importance of implementing, enforcing, and maintaining these measures to mitigate hospital system overload and prevent deaths. Data availability statementA full list of data citations are available by contacting the corresponding author. Funding StatementBill & Melinda Gates Foundation and the State of Washington Key PointsO_ST_ABSQuestionC_ST_ABSAssuming social distancing measures are maintained, what are the forecasted gaps in available health service resources and number of deaths from the COVID-19 pandemic for each state in the United States? FindingsUsing a statistical model, we predict excess demand will be 64,175 (95% UI 7,977 to 251,059) total beds and 17,380 (95% UI 2,432 to 57,955) ICU beds at the peak of COVID-19. Peak ventilator use is predicted to be 19,481 (95% UI 9,767 to 39,674) ventilators. Peak demand will be in the second week of April. We estimate 81,114 (95% UI 38,242 to 162,106) deaths in the United States from COVID-19 over the next 4 months. MeaningEven with social distancing measures enacted and sustained, the peak demand for hospital services due to the COVID-19 pandemic is likely going to exceed capacity substantially. Alongside the implementation and enforcement of social distancing measures, there is an urgent need to develop and implement plans to reduce non-COVID-19 demand for and temporarily increase capacity of health facilities.
Keywords	covid19
Publisher	MedRxiv; WHO
Document type	Article ; Online
Note	WHO #Covidence: #20043752
DOI	10.1101/2020.03.27.20043752
Database	COVID19

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Article ; Online: Estimating health care delivery system value for each US state and testing key associations.

Dieleman, Joseph L / Kaldjian, Alexander S / Sahu, Maitreyi / Chen, Carina / Liu, Angela / Chapin, Abby / Scott, Kirstin Woody / Aravkin, Aleksandr / Zheng, Peng / Mokdad, Ali / Murray, Christopher Jl / Schulman, Kevin / Milstein, Arnold

Health services research

2021 Volume 57, Issue 3, Page(s) 557–567

Abstract: Objective: To estimate health care systems' value in treating major illnesses for each US state and identify system characteristics associated with value.: Data sources: Annual condition-specific death and incidence estimates for each US state from ... ...

Abstract	Objective: To estimate health care systems' value in treating major illnesses for each US state and identify system characteristics associated with value. Data sources: Annual condition-specific death and incidence estimates for each US state from the Global Burden Disease 2019 Study and annual health care spending per person for each state from the National Health Expenditure Accounts. Study design: Using non-linear meta-stochastic frontier analysis, mortality incidence ratios for 136 major treatable illnesses were regressed separately on per capita health care spending and key covariates such as age, obesity, smoking, and educational attainment. State- and year-specific inefficiency estimates were extracted for each health condition and combined to create a single estimate of health care delivery system value for each US state for each year, 1991-2014. The association between changes in health care value and changes in 23 key health care system characteristics and state policies was measured. Data collection/extraction methods: Not applicable. Principal findings: US state with relatively high spending per person or relatively poor health-outcomes were shown to have low health care delivery system value. New Jersey, Maryland, Florida, Arizona, and New York attained the highest value scores in 2014 (81 [95% uncertainty interval 72-88], 80 [72-87], 80 [71-86], 77 [69-84], and 77 [66-85], respectively), after controlling for health care spending, age, obesity, smoking, physical activity, race, and educational attainment. Greater market concentration of hospitals and of insurers were associated with worse health care value (p-value ranging from <0.01 to 0.02). Higher hospital geographic density and use were also associated with worse health care value (p-value ranging from 0.03 to 0.05). Enrollment in Medicare Advantage HMOs was associated with better value, as was more generous Medicaid income eligibility (p-value 0.04 and 0.01). Conclusions: Substantial variation in the value of health care exists across states. Key health system characteristics such as market concentration and provider density were associated with value.
MeSH term(s)	Aged ; Delivery of Health Care ; Health Expenditures ; Humans ; Medicaid ; Medicare ; Obesity ; United States
Language	English
Publishing date	2021-05-24
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	410435-3
ISSN	1475-6773 ; 0017-9124
ISSN (online)	1475-6773
ISSN	0017-9124
DOI	10.1111/1475-6773.13676
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Book: Measuring the global burden of disease

Eyal, Nir M. / Hurst-Majno, Samia / Murray, Christopher J.L. / Schroeder, S. Andrew / Wikler, Daniel

philosophical dimensions

(Population level bioethics series)

2020

Author's details	edited by Nir Eyal, Samia A. Hurst, Christopher J.L. Murray, S. Andrew Schroeder, and Daniel Wikler
Series title	Population level bioethics series
Language	English
Size	x, 328 Seiten
Publisher	Oxford University Press
Publishing place	Oxford
Publishing country	Great Britain
Document type	Book
HBZ-ID	HT020476531
ISBN	978-0-19-008254-3 ; 9780190082574 ; 0-19-008254-2 ; 0190082577
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Article: Correction: Robust metrics for assessing the performance of different verbal autopsy cause assignment methods in validation studies.

Murray, Christopher Jl / Lozano, Rafael / Flaxman, Abraham D / Vahdatpour, Alireza / Lopez, Alan D

Population health metrics

2014 Volume 12, Issue 1, Page(s) 7

Language	English
Publishing date	2014-04-10
Publishing country	England
Document type	Journal Article ; Published Erratum
ZDB-ID	2127230-X
ISSN	1478-7954 ; 1478-7954 ; 2155-7772
ISSN (online)	1478-7954
ISSN	1478-7954 ; 2155-7772
DOI	10.1186/1478-7954-12-7
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Article ; Online: Towards good practice for health statistics: lessons from the Millennium Development Goal health indicators.

Murray, Christopher Jl

Lancet (London, England)

2007 Volume 369, Issue 9564, Page(s) 862–873

Abstract: Health statistics are at the centre of an increasing number of worldwide health controversies. Several factors are sharpening the tension between the supply and demand for high quality health information, and the health-related Millennium Development ... ...

Abstract	Health statistics are at the centre of an increasing number of worldwide health controversies. Several factors are sharpening the tension between the supply and demand for high quality health information, and the health-related Millennium Development Goals (MDGs) provide a high-profile example. With thousands of indicators recommended but few measured well, the worldwide health community needs to focus its efforts on improving measurement of a small set of priority areas. Priority indicators should be selected on the basis of public-health significance and several dimensions of measurability. Health statistics can be divided into three types: crude, corrected, and predicted. Health statistics are necessary inputs to planning and strategic decision making, programme implementation, monitoring progress towards targets, and assessment of what works and what does not. Crude statistics that are biased have no role in any of these steps; corrected statistics are preferred. For strategic decision making, when corrected statistics are unavailable, predicted statistics can play an important part. For monitoring progress towards agreed targets and assessment of what works and what does not, however, predicted statistics should not be used. Perhaps the most effective method to decrease controversy over health statistics and to encourage better primary data collection and the development of better analytical methods is a strong commitment to provision of an explicit data audit trail. This initiative would make available the primary data, all post-data collection adjustments, models including covariates used for farcasting and forecasting, and necessary documentation to the public.
MeSH term(s)	Benchmarking ; Data Collection/methods ; Global Health ; Health Priorities ; Health Status Indicators ; Humans ; Organizational Objectives ; Social Change ; Statistics as Topic/methods
Keywords	covid19
Language	English
Publishing date	2007-03-08
Publishing country	England
Document type	Journal Article
ZDB-ID	3306-6
ISSN	1474-547X ; 0023-7507 ; 0140-6736
ISSN (online)	1474-547X
ISSN	0023-7507 ; 0140-6736
DOI	10.1016/S0140-6736(07)60415-2
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