TY - JOUR A1 - Singh, Surya A1 - Shaikh, Mujaheed A1 - Hauck, Katharina A1 - Miraldo, Marisa T1 - Impacts of introducing and lifting nonpharmaceutical interventions on COVID-19 daily growth rate and compliance in the United States JF - PNAS N2 - We evaluate the impacts of implementing and lifting nonpharmaceutical interventions (NPIs) in US counties on the daily growth rate of COVID-19 cases and compliance, measured through the percentage of devices staying home, and evaluate whether introducing and lifting NPIs protecting selective populations is an effective strategy. We use difference-in-differences methods, leveraging on daily county-level data and exploit the staggered introduction and lifting of policies across counties over time. We also assess heterogenous impacts due to counties’ population characteristics, namely ethnicity and household income. Results show that introducing NPIs led to a reduction in cases through the percentage of devices staying home. When counties lifted NPIs, they benefited from reduced mobility outside of the home during the lockdown, but only for a short period. In the long term, counties experienced diminished health and mobility gains accrued from previously implemented policies. Notably, we find heterogenous impacts due to population characteristics implying that measures can mitigate the disproportionate burden of COVID-19 on marginalized populations and find that selectively targeting populations may not be effective. Y1 - 2021 U6 - https://doi.org/10.1073/pnas.2021359118 ER - TY - JOUR A1 - Nicodemo, Catia A1 - Barzin, Samira A1 - Cavalli, Nicolò A1 - Lasserson, Daniel A1 - Moscone, Francesco A1 - Redding, Stuart A1 - Shaikh, Mujaheed T1 - Measuring geographical disparities in England at the time of COVID-19: results using a composite indicator of population vulnerability JF - BMJ Open N2 - Objectives: The growth of COVID-19 infections in England raises questions about system vulnerability. Several factors that vary across geographies, such as age, existing disease prevalence, medical resource availability and deprivation, can trigger adverse effects on the National Health System during a pandemic. In this paper, we present data on these factors and combine them to create an index to show which areas are more exposed. This technique can help policy makers to moderate the impact of similar pandemics. Design: We combine several sources of data, which describe specific risk factors linked with the outbreak of a respiratory pathogen, that could leave local areas vulnerable to the harmful consequences of large-scale outbreaks of contagious diseases. We combine these measures to generate an index of community-level vulnerability. Setting: 91 Clinical Commissioning Groups (CCGs) in England. Main outcome: measures We merge 15 measures spatially to generate an index of community-level vulnerability. These measures cover prevalence rates of high-risk diseases; proxies for the at-risk population density; availability of staff and quality of healthcare facilities. Results: We find that 80% of CCGs that score in the highest quartile of vulnerability are located in the North of England (24 out of 30). Here, vulnerability stems from a faster rate of population ageing and from the widespread presence of underlying at-risk diseases. These same areas, especially the North-East Coast areas of Lancashire, also appear vulnerable to adverse shocks to healthcare supply due to tighter labour markets for healthcare personnel. Importantly, our index correlates with a measure of social deprivation, indicating that these communities suffer from long-standing lack of economic opportunities and are characterised by low public and private resource endowments. Conclusions: Evidence-based policy is crucial to mitigate the health impact of pandemics such as COVID-19. While current attention focuses on curbing rates of contagion, we introduce a vulnerability index combining data that can help policy makers identify the most vulnerable communities. We find that this index is positively correlated with COVID-19 deaths and it can thus be used to guide targeted capacity building. These results suggest that a stronger focus on deprived and vulnerable communities is needed to tackle future threats from emerging and re-emerging infectious disease. Y1 - 2020 U6 - https://doi.org/10.1136/bmjopen-2020-039749 VL - 10 IS - 9 ER - TY - RPRT A1 - Spitzer, Sonja A1 - Shaikh, Mujaheed T1 - Health Misperception and Healthcare Utilisation among Older Europeans N2 - Health perception biases can have serious consequences on health. Despite their relevance,the role of such biases in determining healthcare utilisation is severely underexplored. Herewe study the relationship between health misperception, doctor visits, and concomitant out-of-pocket expenditures for the population 50+ in Europe. We conceptualise health misper-ception as arising from either overconfidence or underconfidence, where overconfidence ismeasured as overestimation of health and underconfidence is measured as underestimationof health. Comparing objective performance measures and their self-reported equivalentsfrom the Survey of Health, Ageing and Retirement in Europe, we find that individuals whooverestimate their health visit the doctor 14% less often than individuals who correctly as-sess their health, which is crucial for preventive care such as screenings. Lower healthcareutilisation is accompanied by lower out-of-pocket spending (38% less). In contrast, indi-viduals who underestimate their health visit the doctor more often (28% more) and havehigher out-of-pocket spending (17% more). We project that underestimating health of thepopulation 50+ will cost the average European country Intl$ 71 million in 2020 and Intl$ 81million by 2060. Country-specific estimates based on population and demographic projec-tions show that countries such as Germany, Denmark and The Netherlands will experiencesignificantly large costs of such misperception. The results are robust to several sensitivitytests and, more important, to various conceptualisations of the misperception measure. Y1 - 2020 UR - https://www.oeaw.ac.at/fileadmin/subsites/Institute/VID/PDF/Publications/Working_Papers/WP2020_01.pdf ER - TY - CHAP A1 - Hurrelmann, Klaus A1 - Shaikh, Mujaheed A1 - Wendt, Claus T1 - Health Policy and Health Governance T2 - The Governance Report 2019 Y1 - 2019 SN - 9780198821502 PB - Oxford University Press ER - TY - RPRT A1 - Shaikh, Mujaheed A1 - Blankart, Katharina T1 - Finanzierung und Ver­gütung eines nachhaltigen Gesundheitssystems – Ansätze und Möglichkeiten Y1 - 2021 UR - https://www.neustart-fuer-gesundheit.de/sites/default/files/documents/2021-05/2020-09_Diskussionspapier_Think%20Lab%205.pdf ER - TY - RPRT A1 - Shaikh, Mujaheed A1 - Haarmann, Alexander T1 - Die Leistungserbringung im Gesundheitssystem der Zukunft Y1 - 2021 UR - https://www.neustart-fuer-gesundheit.de/sites/default/files/documents/2021-05/2020-03_Diskussionspapier_Think%20Lab%204_2.pdf ER - TY - RPRT A1 - Shaikh, Mujaheed A1 - Haarmann, Alexander A1 - Klapper, Bernadette T1 - Patienten-Typologien im Gesundheitssystem von morgen Y1 - 2020 UR - https://www.neustart-fuer-gesundheit.de/sites/default/files/documents/2021-03/2019-11_Diskussionpapier_Think%20Lab%203.pdf ER - TY - RPRT A1 - Shaikh, Mujaheed A1 - Haarmann, Alexander A1 - Klapper, Bernadette T1 - Megatrends – wie sie die Zukunft der Gesundheitsversorgung beeinflussen Y1 - 2020 UR - https://www.neustart-fuer-gesundheit.de/sites/default/files/documents/2021-03/2019-06_Diskussionspapier_Think%20Lab%202.pdf ER - TY - CHAP A1 - Shaikh, Mujaheed A1 - Haarmann, Alexander A1 - Schmitt, Tugce T1 - Die Governance des zukünftigen Gesundheitssystems BT - Impulse von Expertinnen und Experten für die Reformwerkstatt „Neustart!“ (Oktober / November 2020) N2 - Die hier genannten Punkte stellen eine kurze Zusammenfassung an Themen dar, die sich wie rote Fäden in allen unten beschriebenen Feldern der Governance entdecken lassen. Sie können als die Quintessenz, Leitbilder oder Prinzipien der Governance für das Gesundheitssystem der Zukunft angesehen werden. Die einzelnen Felder der Governance werden in den nachfolgenden Kapiteln näher beschrieben und basieren auf den Expertengesprächen im Rahmen der Initiative „Neustart! Reformwerkstatt für unser Gesundheitswesen“ und der existierenden Literatur. • Notwendigkeit erhöhter Transparenz – Transparenz über die Entscheidungen ist das A und O für Governance, wenn gegenseitiges Vertrauen zwischen Stakeholdern und bei Bürgern und Patienten geschaffen werden soll. Transparenz ist Voraussetzung, dass sich letztere ein eigenes Bild machen können und auf die eine oder andere Art sinnvoll an der Governance beteiligt werden können. • Etablierte Standards mit lokaler Ergänzung – Neben der Anpassung der Versorgung an lokal-regionale Bedarfe sollten (Qualitäts-)Standards und (Behandlungs-)Leitlinien auf übergeordneter, nationaler (oder internationaler) Ebene erstellt werden und Anwendung finden, um landesweit einen hohen Qualitätsstandard sicherzustellen. • Governance vom regionalen Bedarf herdenken – Ein Verständnis für den regionalen Bedarf einer Bevölkerung und deren spezifischen Bedürfnisse sollte entwickelt werden als Handlungsorientierung für die Governance vor Ort. Die nationalen Standards können darüber hinaus durch regional entwickelte Praktiken ergänzt werden. Nur auf diese Weise kann die regional beste Passung zwischen angemessener Versorgung und Gesundheitssystem erreicht werden. • Bedarf für geeignete Daten in hoher Qualität – Trotz einer Vielzahl vorhandener Daten fehlt es häufig noch an geeigneten Daten, auf denen Governance-Entscheidungen verlässlich fußen können. Hierzu müssen relevante und geeignete Daten identifiziert werden, die möglichst ohne großen Aufwand im Prozess erhoben werden und dennoch die Realität der Versorgung und der Lebensqualität von Patienten abbilden können. Y1 - 2021 UR - https://www.neustart-fuer-gesundheit.de/sites/default/files/documents/2021-06/2020-11_Diskussionspapier_Think_Lab_6.pdf ET - Diskussionspapier – Think Lab 6 ER - TY - JOUR A1 - Shaikh, Mujaheed A1 - Tymoszuk, Urszula A1 - Williamon, Aaron A1 - Miraldo, Marisa T1 - Socio-economic inequalities in arts engagement and depression among older adults in the United Kingdom: evidence from the English Longitudinal Study of Ageing JF - Public Health N2 - Objectives Arts engagement has been positively linked with mental health and well-being; however, socio-economic inequalities may be prevalent in access to and uptake of arts engagement reflecting on inequalities in mental health. This study estimated socio-economic inequality and horizontal inequity (unfair inequality) in arts engagement and depression symptoms of older adults in England. Trends in inequality and inequity were measured over a period of ten years. Study design This is a repeated cross-sectional study. Methods In this analysis, we used data from six waves (waves 2 to 7) of the nationally representative English Longitudinal Study of Ageing. We estimated socio-economic inequality using concentration curves that plot the distribution of arts engagement and depression symptoms against the distribution of wealth. A concentration index was used to measure the magnitude of the inequality. Unfair inequality was then calculated for need-standardised arts engagement using a horizontal inequity index (HII). Results The study sample included adults aged 50 years and older from waves 2 (2004/2005, n = 6620) to 7 (2014/2015, n = 3329). Engagement with cinema, galleries and theatre was pro-rich unequal, i.e. concentrated among the wealthier, but inequality in depression was pro-poor unequal, i.e. concentrated more among the less wealthy. While pro-rich inequality in arts engagement decreased from wave 2 (conc. index: 0·291, 95% confidence interval 0·27 to 0·31) to wave 7 (conc. index: 0·275, 95% confidence interval 0·24 to 0·30), pro-poor inequality in depression increased from wave 2 (conc. index: −0·164, 95% confidence interval -0·18 to −0·14) to wave 7 (conc. index: −0·189, 95% confidence interval -0·21 to −0·16). Depression-standardised arts engagement showed horizontal inequity that increased from wave 2 (HII: 0·455, 95% confidence interval 0·42 to 0·48) to wave 7 (HII: 0·464, 95% confidence interval 0·42 to 0·50). Conclusions Our findings suggest that while socio-economic inequality in arts engagement might appear to have reduced over time, once arts engagement is standardised for need, inequality has actually worsened over time and can be interpreted as inequitable (unfair). Relying on need-unstandardised estimates of inequality might thus provide a false sense of achievement to policy makers and lead to improper social prescribing interventions being emplaced. Y1 - 2021 U6 - https://doi.org/10.1016/j.puhe.2021.07.044 SN - 0033-3506 VL - 198 SP - 307 EP - 314 ER -