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Supplemental Digital Content is available in the text, Objective: To compare number of days lost to illness or accessing healthcare for HIV-positive and HIV-negative individuals working in the informal and formal sectors in South Africa and Zambia. Design: As part of the HPTN 071 (PopART) study, data on adults aged 18–44 years were gathered from cross-sectional surveys of random general population samples in 21 communities in Zambia and South Africa. Data on the number of productive days lost in the last 3 months, laboratory-confirmed HIV status, labour force status, age, ethnicity, education, and recreational drug use was collected. Methods: Differences in productive days lost between HIV-negative and HIV-positive individuals (’excess productive days lost’) were estimated with negative binomial models, and results disaggregated for HIV-positive individuals after various durations on antiretroviral treatment (ART). Results: From samples of 19 330 respondents in Zambia and 18 004 respondents in South Africa, HIV-positive individuals lost more productive days to illness than HIV-negative individuals in both countries. HIV-positive individuals in Zambia lost 0.74 excess productive days [95% confidence interval (CI) 0.48–1.01; P

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has placed enormous strain on intensive care units (ICUs) in Europe. Ensuring access to care, irrespective of COVID-19 status, in winter 2020-2021 is essential. METHODS: An integrated model of hospital capacity planning and epidemiological projections of COVID-19 patients is used to estimate the demand for and resultant spare capacity of ICU beds, staff and ventilators under different epidemic scenarios in France, Germany and Italy across the 2020-2021 winter period. The effect of implementing lockdowns triggered by different numbers of COVID-19 patients in ICUs under varying levels of effectiveness is examined, using a 'dual-demand' (COVID-19 and non-COVID-19) patient model. RESULTS: Without sufficient mitigation, we estimate that COVID-19 ICU patient numbers will exceed those seen in the first peak, resulting in substantial capacity deficits, with beds being consistently found to be the most constrained resource. Reactive lockdowns could lead to large improvements in ICU capacity during the winter season, with pressure being most effectively alleviated when lockdown is triggered early and sustained under a higher level of suppression. The success of such interventions also depends on baseline bed numbers and average non-COVID-19 patient occupancy. CONCLUSION: Reductions in capacity deficits under different scenarios must be weighed against the feasibility and drawbacks of further lockdowns. Careful, continuous decision-making by national policymakers will be required across the winter period 2020-2021.

In der vorliegenden Studie wurde die komplette Wertschöpfungskette von Öko-Wein mit einer Kombination von qualitativen und quantitativen Methoden systematisch untersucht. Die Analyse erfolgte unter Einbeziehung von Verbänden, Produzenten, Händlern und Endkonsumenten, um die jeweiligen Bedürfnisse und Erwartungen der unterschiedlichen Interessengruppen zu erfassen. Zunächst wurden Bio und konventionelle Winzer in Deutschland interviewt, um die Gründe für oder gegen eine Umstellung auf Bio zu analysieren. Im nächsten Schritt wurden Händler nach ihrer Einschätzung und Einstellung zum Bioweinmarkt in Deutschland befragt, um bereits einen Eindruck von der Biowein-Nachfrage zu erhalten. Anschließend wurden zunächst Gruppendiskussionen durchgeführt und die Datenerhebung mit einer repräsentativen Befragung von Weinkonsumenten abgeschlossen. Die Endverbraucher wurden zu ihrer Wahrnehmung, Einstellung und Erwartung von bzw. an Bio-Wein befragt. Somit wurden alle Stakeholder entlang der Wertschöpfungskette von Bio-Wein in Deutschland involviert. Die Ergebnisse der Analyse helfen zu verstehen, warum 1) Weingüter auf Bio umstellen und warum nicht; 2) Händler Bio-Wein im Sortiment anbieten und wie kommunizieren; 3) die Mehrheit der deutschen Weinkonsumenten Bio-Wein nicht aktiv nachfragt. Darüber hinaus würden die Bio-Weinkonsumenten segmentiert und mithilfe von Marketingund Kommunikationsexperten Handlungsempfehlungen zur Steigerung der Bio-Wein-Nachfrage erarbeitet.

Additional file 1 Figure S1. Daily positive cases and deaths of COVID-19 in London in 2020. Fig. S2. Monthly timeseries of attendances to ED services by region in 2020. Red lines represent mean forecast from ARIMA model, with shadowed area representing the confidence interval (light purple 95% and dark purple 80%) and are compared against observed data (light blue line) from NHS Digital. Fig. S3. Daily ED attendances to ICHNT by age, gender, and mode of arrival in 2020. Table S1. Timeline of Interventions in the UK. Fig. S4. Percent of ED attendances to ICHNT by geographic area of patient residence and method of arrival in 2020. The distance is measured between the centre of the polygon containing the patient’s home address and either the location of St Mary’s or Charing Cross hospital. Table S2. Number (%) of emergency department attendances by age group at Imperial College Healthcare NHS Trust in 2020. Table S3. Number (%) of emergency department attendances by gender at Imperial College Healthcare NHS Trust in 2020. Table S4. Number (%) of emergency department attendances by mode of arrival at Imperial College Healthcare NHS Trust in 2020. Table S5. Linear regression models for reduced number of ED attendances to Imperial College Healthcare NHS Trust by postcode of patient residence. Table S6. Historic (2015–2019) vs present deaths amongst emergency admissions by disease area at Imperial College Healthcare NHS Trust between March 12 and May 31.

Influenza pandemics considerably burden affected health systems due to surges in inpatient admissions and associated costs. Previous studies underestimate or overestimate 2009/2010 influenza A/H1N1 pandemic hospital admissions and costs. We robustly estimate overall and age‐specific weekly H1N1 admissions and costs between June 2009 and March 2011 across 170 English hospitals. We calculate H1N1 admissions and costs as the difference between our administrative data of all influenza‐like‐illness patients (seasonal and pandemic alike) and a counterfactual of expected weekly seasonal influenza admissions and costs established using time‐series models on prepandemic (2004–2008) data. We find two waves of H1N1 admissions: one pandemic wave (June 2009–March 2010) with 10,348 admissions costing £20.5 million and one postpandemic wave (November 2010–March 2011) with 11,775 admissions costing £24.8 million. Patients aged 0–4 years old have the highest H1N1 admission rate, and 25‐ to 44‐ and 65+‐year‐olds have the highest costs. Our estimates are up to 4.3 times higher than previous reports, suggesting that the pandemic's burden on hospitals was formerly underassessed. Our findings can help hospitals manage unexpected surges in admissions and resource use due to pandemics.

Additional file 3. Model equations. Equations used.

There is a profusion of evidence on the population and supply side factors explaining demand for emergency care, but surprisingly very little evidence about how seasonal patterns of demand vary across regions. Such information is crucial to help hospitals manage fluctuations in demand and ease capacity constraints. The objective of this study is to analyse the patterns of weekly attendances to Accident and Emergency departments in England, controlling for a wide range of determinants. The study uses both panel and common trend methods on data for 135 English hospitals and their catchment areas merged from a variety of sources over 156 weeks from 2012 to 2015. Modelling of unobservable factors with common trend models shows systematic patterns in the data related to season and the location of providers. Coastal areas experience more attendances in summer than urban areas, and this trend is reversed in winter, possibly due to temporary population movements. Internal reorganizations between major A&E departments and minor injury units within hospitals lead to structural breaks in attendances. In the panel models, only the share of the working population, weather and socioeconomic deprivation are statistically significant predictors of attendances in the panel models. The forecasting ability of both panel and common trends methods is similar. Fine-tuning funding allocations across trusts and seasons according to temporary population movements could be a promising avenue to help alleviate existing capacity constraints emergency departments.

Additional file 1. Glossary. Definitions of key terms used.

There is a trade-off between the education sector and other economic sectors in the control of SARS-CoV-2 transmission. Here we integrate a dynamic model of SARS-CoV-2 transmission with a 63-sector economic model reflecting sectoral heterogeneity in transmission and economic interdependence between sectors. We identify control strategies which optimize economic production while keeping schools and universities operational and constraining infections such that emergency hospital capacity is not exceeded. The model estimates an economic gain of between £163bn and £205bn for the United Kingdom compared to a blanket lockdown of non-essential activity over six months, depending on hospital capacity. Sectors identified as potential priorities for closure are contact-intensive and/or less economically productive.

Additional file 2. Contains the following sections, referred to throughout the article: 1. Additional information on data and measures (p.2). 2. Characteristics of the analysed sample compared to those not included (p.5). 3. Socio-demographic characteristics and balance of Trial groups (p.6). 4. Additional information on methods and results from propensity score matching (p.8)

Additional file 2. Overview table of model inputs, assumptions and how this was quantified for the analysis. Model input values, assumptions, references to data sources and how inputs were quantified for the purpose of this analysis.

Additional file 3 Contains the following sections, referred to throughout the article: 1. Sample sizes and p-values for main results tables (p.2). 2. Results by type of CT intervention (CCT and UCT) (p.7). 3. Additional results by type of sex of head of household (p.12)

Supplemental Digital Content is available in the text., Background: There is little satisfactory evidence on the harm of safety incidents to patients, in terms of lost potential health and life-years. Objective: To estimate the healthy life-years (HLYs) lost due to 6 incidents in English hospitals between the years 2005/2006 and 2009/2010, to compare burden across incidents, and estimate excess bed-days. Research Design: The study used cross-sectional analysis of the medical records of all inpatients treated in 273 English hospitals. Patients with 6 types of preventable incidents were identified. Total attributable loss of HLYs was estimated through propensity score matching by considering the hypothetical remaining length and quality of life had the incident not occurred. Results: The 6 incidents resulted in an annual loss of 68 HLYs and 934 excess bed-days per 100,000 population. Preventable pressure ulcers caused the loss of 26 HLYs and 555 excess bed-days annually. Deaths in low-mortality procedures resulted in 25 lost life-years and 42 bed-days. Deep-vein thrombosis/pulmonary embolisms cost 12 HLYs, and 240 bed-days. Postoperative sepsis, hip fractures, and central-line infections cost

Supplemental Digital Content is available in the text, Objective: To investigate how ‘real-world’ constraints on the allocative and technical efficiency of HIV prevention programmes affect resource allocation and the number of infections averted. Design: Epidemiological modelling and economic analyses in Benin, South Africa and Tanzania. Methods: We simulated different HIV prevention programmes, and first determined the most efficient allocation of resources, in which the HIV prevention budget is shared among specific interventions, risk-groups and provinces to maximize the number of infections averted. We then identified the efficient allocation of resources and achievable impact given the following constraints to allocative efficiency: earmarking [provinces with budgets fund pre-exposure prophylaxis (PrEP) for low-risk women first], meeting targets [provinces with budgets fund universal test-and-treat (UTT) first] and minimizing changes in the geographical distribution of funds. We modelled technical inefficiencies as a reduction in the coverage of PrEP or UTT, which were factored into the resource allocation process or took effect following the allocation. Each scenario was investigated over a range of budgets, such that the impact reaches its maximum. Results: The ‘earmarking’, ‘meeting targets’ and ‘minimizing change’ constraints reduce the potential impact of HIV prevention programmes, but at the higher budgets these constraints have little to no effect (approximately 35 billion US$ in Tanzania). Over-estimating technical efficiency can result in a loss of impact compared to what would be possible if technical efficiencies were known accurately. Conclusion: Failing to account for constraints on allocative and technical efficiency can result in the overestimation of the health gains possible, and for technical inefficiencies the allocation of an inefficient strategy.

Objective: To determine if obese patients have longer average length of stay once they are admitted to hospital, across a range of specialties. This contributes to measuring the impact of obesity on health care resource use. Data Sources/Study Setting: Administrative hospital data are used for the financial year 2005/06 covering all episodes of patient care (1.3 million) in 122 public hospitals in the state of Victoria, Australia. The data are collected as part of Diagnosis Related Group (DRG) case mix funding arrangements by the state government. Study Design: Statistical analysis are undertaken using quantile regression analysis to determine differences in average length of stay within different specialties for two groups of patients, those classified as obese, and those not classified as obese. Quantile regression allows a comparison of differences between the length of stay of obese and non-obese patients across the whole distribution of length of stay of inpatients, in contrast to more commonly used statistical methods which use only the mean. We condition on a range of patient and hospital characteristics such as age, sex, socioeconomic status, medical complexity of patients, teaching status, size and location of hospitals. Data Collection/Extraction Methods: Data on inpatient episodes with at least one overnight stay in hospital are used. We exclude episodes with missing information on one or more of the explanatory variables and we exclude specialties with less than 50 reported obese inpatients per financial year. The final sample consists of just over 460,000 observations. Principal Findings: Large and significant differences in average length of stay are found between obese and non-obese patients for nearly all specialties. In some specialties, obese patients can stay up to 4 days longer. However, obesity does not necessarily lead to longer hospital stays. In a range of specialties, obese patients have shorter length of stay on average. In general, differences between obese and non-obese patients are more pronounced at greater levels of medical complexity. There is some evidence that differences may arise because obese patients are more likely to be treated medically rather than surgically, to be transferred to another hospital, thus shifting risks and costs, or to die from higher complication rates. Conclusions: Our study sheds new light on the impact of obesity on health care costs. We demonstrate that an analysis across the whole spectrum of medical complexity provides much better estimates of resource use by obese patients than standard techniques. Future research should focus on differences in the way obese patients are managed in hospital. This will show where resource use is most intense, and help policy makers and hospital managers increase efficiency and quality of care for obese patients.

We compare adverse event rates for surgical inpatients across 36 public hospitals in the state of Victoria, Australia, conditioning on differences in patient complexity across hospitals. We estimate separate models for elective and emergency patients which stay at least one night in hospitals, using fixed effects complementary log-log models to estimate AEs as a function of patient and episode characteristics, and hospital effects. We use 4 years of patient level administrative hospital data (2002/03 to 2005/06), and estimate separate models for each year. Averaged over four years, we find that adverse event rates are 12% for elective surgical inpatients, and 12.5% for emergency surgical inpatients. Most teaching hospitals have surprisingly low adverse event rates, at least after adjusting for the higher medical complexity of their patients. Some larger regional hospitals have high adverse events rates, in particular after adjusting for the below average complexity of their patients. Also, some suburban hospitals have high rates, especially the ones located in areas of low socioeconomic profile. We speculate that high rates may be due to factors beyond the control of the hospitals, such as staff shortages. We conclude that at present, care should be taken when using adverse event rates as indicators of hospital quality

Adverse Health mobility is a statistical measure of inter-temporal fluctuations in health of a group of individuals. Increased availability of panel data has led to a number of studies which analyse and compare health mobility across subgroups. Mobility can differ systematically across patient subgroups, even if prevalence measured at one point in time is the same. There is a lack of discussion regarding whether health mobility is a relevant concept for resource allocation decisions. In this think piece, we explore whether and how health mobility is incorporated in cost-effectiveness analysis (CEA). CEA takes health mobility into account where it matters in terms of efficiency and -depending on treatment programs- either favours groups with low mobility or gives equal priority to groups of differing levels of mobility. However, CEA fails to take into account the equity dimension of mobility. There is qualitative research to suggest that some members of the public find that patient groups with low health mobility should be given priority even if some efficiency was sacrificed. Results also indicate that this may depend on the nature of the condition, the actual lengths involved and the magnitude of the efficiency sacrifice. Health mobility may also have political implications which affect resource allocation decisions, possibly in opposing directions. Further research is required to investigate the extent to which the public is concerned with health mobility, to determine conditions for which health mobility matters most, and to explore ways of how the equity dimension of health mobility can be incorporated into CEA.

Additional file 1. Contains more details on the literature review on CTs and HIV/STI prevention.

BACKGROUND: The life expectancy of HIV-positive individuals receiving antiretroviral therapy (ART) is approaching that of HIV-negative people. However, little is known about how these populations compare in terms of health-related quality of life (HRQoL). We aimed to compare HRQoL between HIV-positive and HIV-negative people in Zambia and South Africa. METHODS: As part of the HPTN 071 (PopART) study, data from adults aged 18-44 years were gathered between Nov 28, 2013, and March 31, 2015, in large cross-sectional surveys of random samples of the general population in 21 communities in Zambia and South Africa. HRQoL data were collected with a standardised generic measure of health across five domains. We used β-distributed multivariable models to analyse differences in HRQoL scores between HIV-negative and HIV-positive individuals who were unaware of their status; aware, but not in HIV care; in HIV care, but who had not initiated ART; on ART for less than 5 years; and on ART for 5 years or more. We included controls for sociodemographic variables, herpes simplex virus type-2 status, and recreational drug use. FINDINGS: We obtained data for 19 750 respondents in Zambia and 18 941 respondents in South Africa. Laboratory-confirmed HIV status was available for 19 330 respondents in Zambia and 18 004 respondents in South Africa; 4128 (21%) of these 19 330 respondents in Zambia and 4012 (22%) of 18 004 respondents in South Africa had laboratory-confirmed HIV. We obtained complete HRQoL information for 19 637 respondents in Zambia and 18 429 respondents in South Africa. HRQoL scores did not differ significantly between individuals who had initiated ART more than 5 years previously and HIV-negative individuals, neither in Zambia (change in mean score -0·002, 95% CI -0·01 to 0·001; p=0·219) nor in South Africa (0·000, -0·002 to 0·003; p=0·939). However, scores did differ between HIV-positive individuals who had initiated ART less than 5 years previously and HIV-negative individuals in Zambia (-0·006, 95% CI -0·008 to -0·003; p

Additional file 1. Contains more details on the literature review on CTs and HIV/STI prevention.

Infectious diseases remain the main cause of death in low-income countries. Because of this, efforts to control the circulation of infectious agents are a priority for public policy makers. This control is challenged by a combination of complex disease dynamics, funding constraints or lack of political and societal commitment. These challenges are generally heterogeneous between geographical settings making the impact of control strategies hard to assess. In view of this, the purpose of this research is to integrate economic and epidemiological tools in order to improve support for disease control planning and implementation. To do this, I develop a metapopulation model framework to analyse the impact of control strategies when there are neighbouring populations with different epidemiological conditions. The results from this framework can be incorporated into further economic analysis and optimisations. The first section of this project aims to understand interventions’ effects when transmission intensity varies between populations. As a first approach, I implement the framework to analyse indirect effects of interventions for a transmission-stratified population, using generic models. Then, to contextualise the findings from the generic model, I analyse optimal intervention allocation for malaria control. Results from this section evidenced the importance of aligning local and global control strategies. The second section of this project focuses on understanding the consequences of disease control when intervention uptake varies between populations. For this, the metapopulation framework is applied to estimate the burden populations undergo due to the presence of an anti-vaccination movement. First, I analyse the burden of an outbreak of a vaccine preventable disease in a population where there are opposing vaccine acceptance views, implementing a measles transmission. Finally, I use the same approach to estimate the likely impact of vaccine hesitancy on the control of the COVID-19 pandemic. Results of this section highlight the importance of addressing vaccine hesitancy as a public health priority Open Access

Influenza is one of the most widespread respiratory illnesses worldwide with annual seasonal and occasional pandemic outbreaks that excise heavy health and economic tolls on unprepared health systems. Therefore, countries invest considerable resources into combatting both seasonal and pandemic influenza, albeit in dissimilar manners due to their differing natures. Due to the unpredictability of pandemics, health policymakers focus on hospital capacity and resource allocation planning. They need accurate estimates of how hospitalizations, their severity, and costs dynamically change throughout pandemic and post-pandemic waves of infection. Compliance with preventive measures, including vaccination, is key for seasonal influenza. Better understanding of behavioral drivers of influenza vaccination and potential interventions that could increase uptake is crucial. This thesis thus addresses policymakers’ needs to mitigate seasonal influenza by examining the impact of social norms messaging, a behavioral intervention, on vaccination intention (Chapter 2). I find evidence of both bandwagoning and free-riding effects, depending on the level of social norms intensity. I further investigate behavioral drivers of child vaccination uptake given the dual risk-taking parents undergo when making vaccination decisions for themselves and their children (Chapter 3). Parent vaccination is associated with increased child vaccination only for children aged 10-years-old or over. To address policymakers’ needs to mitigate pandemic influenza, I estimate hospital admissions and associated costs due to the 2009 H1N1 pandemic and the 2010/11 post-pandemic flu season in England (Chapter 4). I find 22,123 H1N1 hospitalizations across England, costing an extra £45.4 million GBP. Furthermore, I estimate hospitalization severity, mortality, and time lags between infection and hospitalization (Chapter 5). Hospitalization rates are 34% higher and severity is 20-90% greater during the post-pandemic period compared to the pandemic. The results from this thesis can help inform mitigation strategies to prevent and combat seasonal and pandemic influenza and help policymakers design future healthcare interventions. Open Access

Most countries will miss the UNAIDS target of reducing new HIV infections by 75% by 2020 compared to 2010. HIV prevention cascades have been proposed to assist in the advocacy for and planning, monitoring, and improved delivery of HIV prevention programmes and interventions by identifying gaps in effective use of prevention methods, similar to treatment cascades. The overarching aim of this thesis was to develop and pilot-test a generic HIV prevention cascade framework that can be used for different populations, prevention methods, and purposes. This proposed prevention cascade consists of three steps of motivation to use a prevention method, access to it, and effective use in a priority population. Characterising reasons underlying gaps across motivation, access, and effective use creates a comprehensive framework. To develop this framework, I conducted consultations and data analyses. In a study of data from eastern and southern Africa, I demonstrated increases in both non-regular partnerships and condom use, exemplifying complexities of population-level HIV risks and challenges in defining priority populations for prevention cascades. As it has previously been proposed as the first step in prevention cascades, I analysed HIV risk perception using longitudinal data from Manicaland, Zimbabwe. Results suggest that 1) risk perception can be accurate as there were associations between perceptions and actual HIV acquisition but there were considerable gaps in risk perception and 2) increasing risk perception was associated with condom use but fractions of condom use attributable to risk perception were small, highlighting that HIV prevention behaviour is influenced by a range of factors. The importance of structural factors for HIV prevention was underlined by analyses of cash transfers and HIV prevention in Manicaland. Finally, I operationalised the proposed HIV prevention cascade framework using newly collected data from Manicaland, demonstrating the utility of the concept for identifying gaps in prevention. Open Access

Gender equality is a moral imperative and a key enabler for economic growth and organizational performance. Women make up 40% of the global labour force; however, policies to support women in the workplace are lacking. Workplace policies are important to mitigate career interruptions due to child birth and discriminatory practices that women face more often than men that will ultimately affect women’s health and employment outcomes. In this thesis, we study a type of workplace policy that enables a better work environment by encouraging mothers to combine childcare and employment responsibilities—a workplace breastfeeding policy. The United States has implemented workplace breastfeeding policies that allow mothers to express breast milk during the first year of child birth. Policies have been introduced in a selective group of 25 out of 51 states over 1990-2011 in a staggered way where some states encourage and other states require employers to provide facilities and break time. Through robust quasi-experimental methods and rich datasets, we investigate the direct and indirect impacts of the policy. We first find that the policy was successful in its primary objective to increase state-level breastfeeding rates by approximately 5 to 7.1 percentage points. We then study the indirect impacts on mothers’ and fathers’ absenteeism and the within-couple gender earnings gap through an intra-household perspective. We find that the policy reduces mothers’ absenteeism by 10 to 16 days. However, we do not find a spillover effect on fathers. Finally, we find that the policy makes household economic characteristics more balanced and reduces the earnings gap between mothers and fathers by 25%. The findings of this thesis provide several implications for policy makers, firms, and the wider economy. Implementing workplace policies that allow parents to reconcile employment and childcare can be an important avenue to achieve gender equality. Open Access

The robust measurement of quality in healthcare is a pre-requisite for monitoring health system performance and is key in driving health system improvements. Despite the rise in process and outcome indicators, little agreement exists amongst health experts regarding the suitability of a single metric to measure quality in healthcare across multiple dimensions, such as safety, effectiveness and efficiency. However, over the past decade, hospital emergency readmission rates have developed into a prominent marker of healthcare quality, with an enhanced policy focus on reducing readmission to improve quality. Particularly, in England following the 2010 government white paper Equity and Excellence: Liberating the NHS, several policies were introduced, including financial penalties for hospitals with excess readmission rates, or funding transfers to social care services to reduce future hospital readmissions. Despite this effort to reduce readmission rates, little is known in the literature about the impact of this enhanced policy focus in England and thus, in this thesis, I examine the dynamics in quality of care based on changes in readmission rates. Following a review of the literature on the methodological consideration when using readmission rates as a measure for healthcare quality, I assess trends and variation in readmission rates across NHS Trusts between 2006 and 2016. Next, I validate the readmission metric against patient-reported outcome measures in hip and knee replacement patients in chapter 4. The final two substantive chapters present an impact evaluation of two English health policies on quality of care, one national-level payment reform (i.e. financial penalties for hospitals with excess readmission rates), and one area-level health system reorganisation (i.e. centralisation of stroke care in London). Open Access