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BackgroundThe COVID-19 pandemic and associated national lockdowns created unprecedented disruption to healthcare, with reduced access to services and planned clinical encounters postponed or cancelled. It was widely anticipated that failure to obtain timely treatment would cause progression of illness and increased hospital admissions. Additional concerns were that social and spatial inequalities would widen given the disproportionate impacts of COVID-19 directly. The aim of our study is to determine whether this was observable in England. MethodsWith the approval of NHS England we utilised individual-level electronic health records from OpenSAFELY, which covered [~]40% of general practices in England (mean monthly population size 23.5 million people). We estimated crude and directly age-standardised rates for potentially preventable unplanned hospital admissions: ambulatory care sensitive conditions and urgent emergency sensitive conditions. We considered how trends in these outcomes varied by three measures of social and spatial inequality: neighbourhood socioeconomic deprivation, ethnicity, and geographical region. FindingsThere were large declines in avoidable hospitalisations during the first national lockdown, which then reversed post-lockdown albeit never reaching pre-pandemic levels. While trends were consistent by each measure of inequality, absolute levels of inequalities narrowed throughout 2020 (especially during the first national lockdown) and remained lower than pre-pandemic trends. While the scale of inequalities remained similar into 2021 for deprivation and ethnicity, we found evidence of widening absolute and relative inequalities by geographic region in 2021 and 2022. InterpretationThe anticipation that healthcare disruption from the COVID-19 pandemic and lockdowns would result in more (avoidable) hospitalisations and widening social inequalities was wrong. However, the recent growing gap between geographic regions suggests that the effects of the pandemic has reinforced spatial inequalities.
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BackgroundMental health problems increased during the COVID-19 pandemic. Knowledge that one is less at risk after being vaccinated may alleviate distress, but this hypothesis remains unexplored. Here we test whether psychological distress declined in those vaccinated against COVID-19 in the US and whether changes in perceived risk mediated any association. MethodsA nationally-representative cohort of U.S. adults (N=5,792) in the Understanding America Study were interviewed every two weeks from March 2020 to June 2021 (28 waves). Difference-in-difference regression tested whether getting vaccinated reduced distress (PHQ-4 scores), with mediation analysis used to identify potential mechanisms, including perceived risks of infection, hospitalization, and death. ResultsVaccination was associated with a 0.09 decline in distress scores (95% CI:-0.15 to -0.04) (0-12 scale), a 5.7% relative decrease compared to mean scores in the wave prior to vaccination. Vaccination was also associated with an 8.44 percentage point reduction in perceived risk of infection (95% CI:-9.15% to -7.73%), a 7.44-point reduction in perceived risk of hospitalization (95% CI:-8.07% to -6.82%), and a 5.03-point reduction in perceived risk of death (95% CI:-5.57% to -4.49%). Adjusting for risk perceptions decreased the vaccination-distress association by two-thirds. Event study models suggest vaccinated and never vaccinated respondents followed similar PHQ-4 trends pre-vaccination, diverging significantly post-vaccination. Analyses were robust to individual and wave fixed effects, time-varying controls, and several alternative modelling strategies. Results were similar across sociodemographic groups. ConclusionReceiving a COVID-19 vaccination was associated with declines in distress and perceived risks of infection, hospitalization, and death. Vaccination campaigns could promote these additional benefits of being vaccinated.
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Industrialised countries have varied in their early response to the Covid-19 pandemic, and how they have adapted to new situations and knowledge since the pandemic began. These variations in preparedness and policy may lead to different death tolls from Covid-19 as well as from other diseases. We applied an ensemble of 16 Bayesian probabilistic models to vital statistics data to estimate the impacts of the pandemic on weekly all-cause mortality for 40 industrialised countries from mid-February 2020 through mid-February 2021, before a large segment of the population was vaccinated in any of these countries. Taken over the entire year, an estimated 1,401,900 (95% credible interval 1,259,700-1,572,500) more people died in these 40 countries than would have been expected had the pandemic not taken place. This is equivalent to 140 (126-157) additional deaths per 100,000 people and a 15% (13-17) increase in deaths over this period in all of these countries combined. In Iceland, Australia and New Zealand, mortality was lower over this period than what would be expected if the pandemic had not occurred, while South Korea and Norway experienced no detectable change in mortality. In contrast, the populations of the USA, Czechia, Slovakia and Poland experienced at least 20% higher mortality. There was substantial heterogeneity across countries in the dynamics of excess mortality. The first wave of the pandemic, from mid-February to the end of May 2020, accounted for over half of excess deaths in Scotland, Spain, England and Wales, Canada, Sweden, Belgium and Netherlands. At the other extreme, the period between mid-September 2020 and mid-February 2021 accounted for over 90% of excess deaths in Bulgaria, Croatia, Czechia, Hungary, Latvia, Montenegro, Poland, Slovakia and Slovenia. Until the great majority of national and global populations have vaccine-acquired immunity, minimising the death toll of the pandemic from Covid-19 and other diseases will remain dependent on actions to delay and contain infections and continue routine health and social care.
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BackgroundMigrants, including refugees, asylum seekers, labour migrants, and undocumented migrants, now constitute a considerable proportion of most high-income countries populations, including their skilled and unskilled workforces. Migrants may be at increased risk of COVID-19 due to their health and social circumstances, yet the extent to which they are being affected and their predisposing risk factors are not clearly understood. We did a systematic review to assess clinical outcomes of COVID-19 in migrant populations (cases, hospitalisations, deaths), indirect health and social impacts, and to determine key risk factors. MethodsWe did a systematic review following PRISMA guidelines, registered with PROSPERO (CRD42020222135). We searched databases including PubMed, Global Health, Scopus, CINAHL, and pre-print databases (medRxiv) via the WHO Global Research on COVID-19 database to Nov 18, 2020 for peer-reviewed and grey literature pertaining to migrants (defined as foreign born) and COVID-19 in 82 high-income countries. We used our international networks to source national datasets and grey literature. Data were extracted on our primary outcomes (cases, hospitalisations, deaths) and we evaluated secondary outcomes on indirect health and social impacts, and risk factors, using narrative synthesis. Results3016 data sources were screened with 158 from 15 countries included in the analysis (35 data sources for primary outcomes: cases [21], hospitalisations [4]; deaths [15]; 123 for secondary outcomes). We found that migrants are at increased risk of infection and are disproportionately represented among COVID-19 cases. Available datasets suggest a similarly disproportionate representation of migrants in reported COVID-19 deaths, as well as increased all-cause mortality in migrants in some countries in 2020. Undocumented migrants, migrant health and care workers, and migrants housed in camps and labour compounds may have been especially affected. In general, migrants have higher levels of many risk factors and vulnerabilities relevant to COVID-19, including increased exposure to SARS-CoV-2 due to high-risk occupations and overcrowded accommodation, and barriers to health care including inadequate information, language barriers, and reduced entitlement to healthcare coverage related to their immigration status. ConclusionsMigrants in high-income countries are at high risk of exposure to, and infection with, COVID-19. These data are of immediate relevance to national public health responses to the pandemic and should inform policymaking on strategies for reducing transmission of COVID-19 in this population. Robust data on testing uptake and clinical outcomes in migrants, and barriers and facilitators to COVID-19 vaccination, are urgently needed, alongside strengthening engagement with diverse migrant groups.
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BackgroundFood supply concerns have featured prominently in the UK response to the COVID-19 pandemic. We assess changes in food insecurity in the UK population from April to July 2020. MethodWe analyze 11,095 respondents from the April through July waves of the Understanding Society COVID-19 longitudinal study survey linked with Wave 9 of the UK Understanding Society study. Food insecurity was defined as having used a food bank in the last 4 weeks; being hungry but not eating in the last week; or not able to eat healthy and nutritious food in the last week. Unadjusted estimates to examine changes in population prevalence and logistic regression were used to assess the association between employment transitions and food insecurity. FindingsThe prevalence of reporting at least one form of food insecurity rose from 7{middle dot}1% in April to 20{middle dot}2% by July 2020. Some of the largest increases were among Asian respondents (22{middle dot}91 percentage points), the self-employed (15{middle dot}90 percentage points), and 35-44-year-olds (17{middle dot}08 percentage points). In logistic regression models, those moving from employment to unemployment had higher odds of reporting food insecurity relative to furloughed individuals (OR = 2{middle dot}23; 95% CI: 1{middle dot}20-4{middle dot}131) and to the persistently employed (OR=2{middle dot}38; 95% CI: 1{middle dot}33-4{middle dot}27), adjusting for sociodemographic characteristics. Furloughed individuals did not differ significantly in their probability of experiencing food insecurity compared to the persistently employed (OR=1{middle dot}07; 95% CI: 0{middle dot}83 to 1{middle dot}37). InterpretationFood insecurity has increased substantially in the UK. Steps are needed to provide subsidies or food support to vulnerable groups. O_TEXTBOXEvidence before this studyWe searched Google Scholar with the terms "COVID-19" and "food insecurity" and "UK"; and "food insecurity" and "UK" and "coronavirus", published between January 1st and October 31st, 2020. One cross-sectional report was identified, which found higher levels of food insecurity in early April 2020 relative to 2018. Importantly, the report relied on items used to measure food insecurity that referred to a 12-month time span in 2018 and then a 30-day time span in April 2020, a potential source of bias for examining changes in population prevalence over time. Added value of this studyHere we provide the first longitudinal national probability study that tracks temporal changes in population prevalence of food insecurity several months following the initial COVID-19-related lockdown measures in the UK. The prevalence of food insecurity rose for all socioeconomic and demographic and groups from April to July 2020, but did so for some more than others. Some of the largest increases in food insecurity were among Asian respondents, the self-employed, respondents aged 35-44, and those living in Scotland, London, and the North West of England. At the individual level, losing employment was associated with a higher odds of food insecurity compared to those furloughed under the Coronavirus Job Retention Scheme and the persistently employed. Importantly, furloughed individuals did not differ in their probability of food insecurity relative to the persistently employed. Implications of all the available evidenceThis study documents an alarming increase in food insecurity in the United Kingdom during the pandemic, with important implications for policy. While Coronavirus the Job Retention Scheme appeared to have conferred some protection, it is clear that not enough has been done to mitigate overall increases food insecurity in the UK. Steps are needed to provide subsidies or food support, especially since during the pandemic emergency food assistance may not be readily accessible. Taken together our results show that, while COVID is first of all a health crisis, it also has potential to become an escalating social and economic crisis if steps are not taken to protect the weak. C_TEXTBOX
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ObjectivesTo determine the impact of restrictions on mobility on reducing transmission of COVID-19. DesignDaily incidence rates lagged by 14 days were regressed on mobility changes using LOESS regression and logit regression between the day of the 100th case in each country to August 31, 2020. Setting34 OECD countries plus Singapore and Taiwan. ParticipantsGoogle mobility data were obtained from people who turned on mobile device-based global positioning system (GPS) and agreed to share their anonymized position information with Google. InterventionsWe examined the association of COVID-19 incidence rates with mobility changes, defined as changes in categories of domestic location, against a pre-pandemic baseline, using country-specific daily incidence data on newly confirmed COVID-19 cases and mobility data. ResultsIn two thirds of examined countries, reductions of up to 40% in commuting mobility (to workplaces, transit stations, retailers, and recreation) were associated with decreased COVID-19 incidence, more so early in the pandemic. However, these decreases plateaued as mobility remained low or decreased further. We found smaller or negligible associations between mobility restriction and incidence rates in the late phase in most countries. ConclusionMild to moderate degrees of mobility restriction in most countries were associated with reduced incidence rates of COVID-19 that appear to attenuate over time, while some countries exhibited no effect of such restrictions. More detailed research is needed to precisely understand the benefits and limitations of mobility restrictions as part of the public health response to the COVID-19 pandemic. WHAT IS ALREADY KNOWN ON THIS TOPICSince SARS-CoV-2 became a pandemic, restrictions on mobility such as limitations on travel and closure of offices, restaurants, and shops have been imposed in an unprecedented way in both scale and scope to prevent the spread of COVID-19 in the absence of effective treatment options or a vaccine. Although mobility restriction has also brought about tremendous costs such as negative economic growth and other collateral impacts on health such as increased morbidity and mortality from lack of access to other essential health services, little evidence exists on the effectiveness of mobility restriction for the prevention of disease transmission. A search of PUBMED and Google Scholar for publications on this topic through Sep 20, 2020 revealed that most of the evidence on the effectiveness of physical distancing comes from mathematical modeling studies using a variety of assumptions. One study investigated only the combined effect of several interventions, including physical distancing, among SARS-CoV-2 infected patients. WHAT THIS STUDY ADDSThis is the first study to investigate the association between change in mobility and incidence of COVID-19 globally using real-time measures of mobility at the population level. For this, we used Google Global Mobility data and the daily incidence of COVID-19 for 36 countries from the day of 100th case detection through August 31, 2020. Our findings from LOESS regression show that in two-thirds of countries, reductions of up to 40% in commuting mobility were associated with decreased COVID-19 incidence, more so early in the pandemic. This decrease, however, plateaued as mobility decreased further. We found that associations between mobility restriction and incidence became smaller or negligible in the late phase of the pandemic in most countries. The reduced incidence rate of COVID-19 cases with a mild to moderate degree of mobility restriction in most countries suggests some value to limited mobility restriction in early phases of epidemic mitigation. The lack of impact in some others, however, suggests further research is needed to confirm these findings and determine the distinguishing factors for when mobility restrictions are helpful in decreasing viral transmission. Governments should carefully consider the level and period of mobility restriction necessary to achieve the desired benefits and minimize harm.
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BackgroundConcerns have been raised that the response to the UK COVID-19 pandemic may have worsened physical and mental health, and reduced use of health services. However, the scale of the problem is unquantified, impeding development of effective mitigations. We asked what has happened to general practice contacts for acute physical and mental health outcomes during the pandemic? MethodsUsing electronic health records from the Clinical Research Practice Datalink (CPRD) Aurum (2017-2020), we calculated weekly primary care contacts for selected acute physical and mental health conditions (including: anxiety, depression, acute alcohol-related events, asthma and chronic obstructive pulmonary disease [COPD] exacerbations, cardiovascular and diabetic emergencies). We used interrupted time series (ITS) analysis to formally quantify changes in conditions after the introduction of population-wide restrictions ( lockdown) compared to the period prior to their introduction in March 2020. FindingsThe overall population included 9,863,903 individuals on 1st January 2017. Primary care contacts for all conditions dropped dramatically after introduction of population-wide restrictions. By July 2020, except for unstable angina and acute alcohol-related events, contacts for all conditions had not recovered to pre-lockdown levels. The largest reductions were for contacts for: diabetic emergencies (OR: 0.35, 95% CI: 0.25-0.50), depression (OR: 0.53, 95% CI: 0.52-0.53), and self-harm (OR: 0.56, 95% CI: 0.54-0.58). InterpretationThere were substantial reductions in primary care contacts for acute physical and mental conditions with restrictions, with limited recovery by July 2020. It is likely that much of the deficit in care represents unmet need, with implications for subsequent morbidity and premature mortality. The conditions we studied are sufficiently severe that any unmet need will have substantial ramifications for the people experiencing the conditions and healthcare provision. Maintaining access must be a key priority in future public health planning (including further restrictions). FundingWellcome Trust Senior Fellowship (SML), Health Data Research UK. RESULTS IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSA small study in 47 GP practices in a largely deprived, urban area of the UK (Salford) reported that primary care consultations for four broad diagnostic groups (circulatory disease, common mental health problems, type 2 diabetes mellitus and malignant cancer) declined by 16-50% between March and May 2020, compared to what was expected based on data from January 2010 to March 2020. We searched Medline for other relevant evidence of the indirect effect of the COVID-19 pandemic on physical and mental health from inception to September 25th 2020, for articles published in English, with titles including the search terms ("covid*" or "coronavirus" or "sars-cov-2"), and title or abstracts including the search terms ("indirect impact" or "missed diagnos*" or "missing diagnos*" or "delayed diagnos*" or (("present*" or "consult*" or "engag*" or "access*") AND ("reduction" or "decrease" or "decline")). We found no further studies investigating the change in primary care contacts for specific physical- and mental-health conditions indirectly resulting from the COVID-19 pandemic or its control measures. There has been a reduction in hospital admissions and presentations to accident and emergency departments in the UK, particularly for myocardial infarctions and cerebrovascular accidents. However, there is no published evidence specifically investigating the changes in primary care contacts for severe acute physical and mental health conditions. Added value of this studyTo our knowledge this is the first study to explore changes in healthcare contacts for acute physical and mental health conditions in a large population representative of the UK. We used electronic primary care health records of nearly 10 million individuals across the UK to investigate the indirect impact of COVID-19 on primary care contacts for mental health, acute alcohol-related events, asthma/chronic obstructive pulmonary disease (COPD) exacerbations, and cardiovascular and diabetic emergencies up to July 2020. For all conditions studied, we found primary care contacts dropped dramatically following the introduction of population-wide restriction measures in March 2020. By July 2020, with the exception of unstable angina and acute alcohol-related events, primary care contacts for all conditions studied had not recovered to pre-lockdown levels. In the general population, estimates of the absolute reduction in the number of primary care contacts up to July 2020, compared to what we would expect from previous years varied from fewer than 10 contacts per million for some cardiovascular outcomes, to 12,800 per million for depression and 6,600 for anxiety. In people with COPD, we estimated there were 43,900 per million fewer contacts for COPD exacerbations up to July 2020 than what we would expect from previous years. Implicatins of all the available evidenceWhile our results may represent some genuine reduction in disease frequency (e.g. the restriction measures may have improved diabetic glycaemic control due to more regular daily routines at home), it is more likely the reduced primary care conatcts we saw represent a substantial burden of unmet need (particularly for mental health conditions) that may be reflected in subsequent increased mortality and morbidity. Health service providers should take steps to prepare for increased demand in the coming months and years due to the short and longterm ramifications of reduced access to care for severe acute physical and mental health conditions. Maintaining access to primary care is key to future public health planning in relation to the pandemic.
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Many countries have implemented strict social distancing measures in the hope of reducing transmission of SARS-CoV-2 but the effectiveness of these measures is determined by the willingness of populations to comply with restrictions. Consequently, a system of monitoring population movement using existing data sources can inform those making decisions about policy responses to the COVID-19 pandemic. We describe a collaboration with all 3 major domestic telecommunication companies in Hungary to use aggregated anonymous mobile phone usage data to calculate two indices for assessing the effect of movement restrictions: a "mobility-index" and a "stay-at-home (or resting) index". The strengths and weaknesses of this approach are compared with the smartphone-based, COVID-19 Community Mobility Reports from Google. Data generated by mobile phones have long been identified as a potential means to analyse mass population movement, but its operationalisation raises several technical questions, such as making sense of Call Detail Records, collation of data from different mobile network providers, and personal data protection concerns. The method described here addresses these issues and offers an effective and inexpensive tool to monitor the impact of social distancing measures, achieving high levels of accuracy and resolution. Especially in populations where uptake of smartphones is modest, this method has certain advantages over app-based solutions, with greater population coverage, but it is not an alternative to smartphone-based solutions used for contact tracing and quarantine monitoring. We believe that this method can easily be adapted by other countries.
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The Covid-19 pandemic affects mortality directly through infection as well as through changes in the social, environmental and healthcare determinants of health1. The impacts on mortality are likely to vary across countries in magnitude, timing, and age and sex composition. Here, we applied an ensemble of 16 Bayesian probabilistic models to vital statistics data, by age group and sex, to consistently and comparably estimate the impacts of the first phase of the pandemic on all-cause mortality for 17 industrialised countries. The models accounted for factors that affect death rates including seasonality, temperature, and public holidays, as well as for medium-long-term secular trends and the dependency of death rates in each week on those in preceding week(s). From mid-February through the end of May 2020, an estimated 202,900 (95% credible interval 179,400-224,900) more people died in these 17 countries than would have had the pandemic not taken place. Nearly three quarters of these excess deaths occurred in England and Wales, Italy and Spain, where less than half of the total population of these countries live. When all-cause mortality is considered, the total number of deaths, deaths per 100,000 people, and relative increase in deaths were similar between men and women in most countries. Further, in many countries, the balance of excess deaths changed from male-dominated early in the pandemic to being equal or female-dominated later on. Taken over the entire first phase of the pandemic, there was no detectable rise in all-cause mortality in New Zealand, Bulgaria, Hungary, Norway, Denmark and Finland and for women in Austria and Switzerland (posterior probability of an increase in deaths <90%). Women in Portugal and men in Austria experienced relatively small increases in all-cause mortality, with posterior probabilities of 90-99%. For men in Switzerland and Portugal, and both sexes in the Netherlands, France, Sweden, Belgium, Italy, Scotland, Spain and England and Wales, all-cause mortality increased as a result of the pandemic with a posterior probability >99%. After accounting for population size, England and Wales and Spain experienced the highest death toll, nearly 100 deaths per 100,000 people; they also had the largest relative (percent) increase in deaths (37% (95% credible interval 30-44) in England and Wales; 38% (31-44) in Spain). New Zealand, Bulgaria, Hungary, Norway, Denmark and Finland experienced changes in deaths that ranged from possible slight declines to increases of no more than 5%. The large impact in England and Wales stems partly from having experienced (together with Spain) the highest weekly increases in deaths, more than doubling in some weeks, and having had (together with Sweden) the longest duration when deaths exceeded levels that would be expected in the absence of the pandemic. The heterogeneous magnitude and character of the excess deaths due to the Covid-19 pandemic reflect differences in how well countries have managed the pandemic (e.g., timing, extent and adherence to lockdowns and other social distancing measures; effectiveness of test, trace and isolate mechanisms), and the resilience and preparedness of the health and social care system (e.g., effective facility and community care pathways; minimising spread of infection within hospitals and care homes, and between them and the community).
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BackgroundThe risk of severe COVID-19 disease is known to be higher in older individuals and those with underlying health conditions. Understanding the number of individuals at increased risk of severe COVID-19 illness, and how this varies between countries may inform the design of possible strategies to shield those at highest risk. MethodsWe estimated the number of individuals at increased risk of severe COVID-19 disease by age (5-year age groups), sex and country (n=188) based on prevalence data from the Global Burden of Disease (GBD) study for 2017 and United Nations population estimates for 2020. We also calculated the number of individuals without an underlying condition that could be considered at-risk because of their age, using thresholds from 50-70 years. The list of underlying conditions relevant to COVID-19 disease was determined by mapping conditions listed in GBD to the guidelines published by WHO and public health agencies in the UK and US. We analysed data from two large multimorbidity studies to determine appropriate adjustment factors for clustering and multimorbidity. ResultsWe estimate that 1.7 (1.0 - 2.4) billion individuals (22% [15-28%] of the global population) are at increased risk of severe COVID-19 disease. The share of the population at increased risk ranges from 16% in Africa to 31% in Europe. Chronic kidney disease (CKD), cardiovascular disease (CVD), diabetes and chronic respiratory disease (CRD) were the most prevalent conditions in males and females aged 50+ years. African countries with a high prevalence of HIV/AIDS and Island countries with a high prevalence of diabetes, also had a high share of the population at increased risk. The prevalence of multimorbidity (>1 underlying conditions) was three times higher in Europe than in Africa (10% vs 3%). ConclusionBased on current guidelines and prevalence data from GBD, we estimate that one in five individuals worldwide has a condition that is on the list of those at increased risk of severe COVID-19 disease. However, for many of these individuals the underlying condition will be undiagnosed or not severe enough to be captured in health systems, and in some cases the increase in risk may be quite modest. There is an urgent need for robust analyses of the risks associated with different underlying conditions so that countries can identify the highest risk groups and develop targeted shielding policies to mitigate the effects of the COVID-19 pandemic. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSAs the COVID-19 pandemic evolves, countries are considering policies of shielding the most vulnerable, but there is currently very limited evidence on the number of individuals that might need to be shielded. Guidelines on who is currently believed to be at increased risk of severe COVID-19 illness have been published online by the WHO and public health agencies in the UK and US. We searched PubMed ("Risk factors" AND "COVID-19") without language restrictions, from database inception until April 5, 2020, and identified 62 studies published between Feb 15, 2020 and March 20, 2020. Evidence from China, Italy and the USA indicates that older individuals, males and those with underlying conditions, such as CVD, diabetes and CRD, are at greater risk of severe COVID-19 illness and death. Added value of this studyThis study combines evidence from large international databases and new analysis of large multimorbidity studies to inform policymakers about the number of individuals that may be at increased risk of severe COVID-19 illness in different countries. We developed a tool for rapid assessments of the number and percentage of country populations that would need to be targeted under different shielding policies. Implications of all the available evidenceQuantifying how many and who is at increased risk of severe COVID-19 illness is critical to help countries design more effective interventions to protect vulnerable individuals and reduce pressure on health systems. This information can also inform a broader assessment of the health, social and economic implications of shielding various groups.
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“...Member States in the WHO European Region are facing a formidable economic crisis that is also calling into question the sustainability of the European social welfare model as a whole and necessitating even greater cost–effectiveness of health systems. Policy-makers are being called on to account for each and every area of public expenditure and are expected to maximize value for money; indeed, the sizeable share of public money that is devoted to health and the ever-increasing cost pressures and demands to cut public expenditure put health systems at the heart of the policy debate….”
‘….The new policy argues for ‘whole-of-government’ and ‘whole-of-society’ approaches that will consolidate the ideals encompassed in health in all policies.
This concept emphasizes the need to improve the integration of government activities with health and to reach out beyond government to engage patients and citizens, developing a responsive and inclusive approach to governance for health.
The policy will be accompanied by a raft of evidence that underlines its rationale, most particularly around enabling implementation – a lynchpin for policy success. This includes a review of social determinants and the health divide in the European Region, pointing towards successful interventions, and studies on the economics of prevention and on effective tools to improve health governance……..”
Content:
1. Health systems, health, wealth and societal well-being: an introduction;
2. Understanding health systems: scope, functions and objectives;
3. Re-examining the cost pressures on health systems;
4. Economic costs of ill health in the European Region;
5. Saving lives? The contribution of health care to population health;
6. The contribution of public health interventions: an economic perspective;
7. Evidence for strategies to reduce socioeconomic inequalities in health in Europe;
8. Being responsive to citizens’ expectations: the role of health services in responsiveness and satisfaction;
9. Assessing health reform trends in Europe;
10. Performance measurement for health system improvement: experiences, challenges and prospects;
11. Investing in health systems: drawing the lessons
