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There is widespread debate on the drivers of heterogeneity of adverse COVID-19 pandemic outcomes and, more specifically, on the role played by context-specific factors. We contribute to this literature by testing the role of environmental factors as measured by environmentally protected areas. We test our research hypothesis by showing that the difference between the number of daily deaths per 1,000 inhabitants in 2020 and the 2018-19 average during the pandemic period is significantly lower in Italian municipalities located in environmentally protected areas such as national parks, regional parks, or Environmentally Protected Zones. After controlling for fixed effects and various concurring factors, municipalities with higher share of environmentally protected areas show significantly lower mortality during the pandemic than municipalities that do not benefit from such environmental amenities.

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We investigate the time-varying effect of particulate matter (PM) on COVID-19 deaths in Italian municipalities. We find that the lagged moving averages of PM2.5 and PM10 are significantly related to higher excess deceases during the first wave of the disease, after controlling, among other factors, for time-varying mobility, regional and municipality fixed effects, the nonlinear contagion trend, and lockdown effects. Our findings are confirmed after accounting for potential endogeneity, heterogeneous pandemic dynamics, and spatial correlation through pooled and fixed-effect instrumental variable estimates using municipal and provincial data. In addition, we decompose the overall PM effect and find that both pre-COVID long-term exposure and short-term variation during the pandemic matter. In terms of magnitude, we observe that a 1 µg/m3 increase in PM2.5 can lead to up to 20% more deaths in Italian municipalities, which is equivalent to a 5.9% increase in mortality rate.

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The uneven geographical distribution of the novel coronavirus epidemic (COVID-19) in Italy is a puzzle given the intense flow of movements among the different geographical areas before lockdown decisions. To shed light on it, we test the effect of the quality of air (as measured by particulate matter and nitrogen dioxide) and lockdown restrictions on daily adverse COVID-19 outcomes during the first pandemic wave in the country. We find that air pollution is positively correlated with adverse outcomes of the pandemic, with lockdown being strongly significant and more effective in reducing deceases in more polluted areas. Results are robust to different methods including cross-section, pooled and fixed-effect panel regressions (controlling for spatial correlation), instrumental variable regressions, and difference-in-differences estimates of lockdown decisions through predicted counterfactual trends. They are consistent with the consolidated body of literature in previous medical studies suggesting that poor quality of air creates chronic exposure to adverse outcomes from respiratory diseases. The estimated correlation does not change when accounting for other factors such as temperature, commuting flows, quality of regional health systems, share of public transport users, population density, the presence of Chinese community, and proxies for industry breakdown such as the share of small (artisan) firms. Our findings provide suggestions for investigating uneven geographical distribution patterns in other countries, and have implications for environmental and lockdown policies.

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BACKGROUND: The changing diabetes in children (CDiC) project is a public-private partnership implemented by Novo Nordisk, to improve access to diabetes care for children with type 1 diabetes. This paper outlines the findings from an evaluation of CDiC in Bangladesh and Kenya, assessing whether CDiC has achieved its objectives in each of six core program components. RESEARCH DESIGN AND METHODS: The Rapid Assessment Protocol for Insulin Access (RAPIA) framework was used to analyze the path of insulin provision and the healthcare infrastructure in place for diagnosis and treatment of diabetes. The RAPIA facilitates a mixed-methods approach to multiple levels of data collection and systems analysis. Information is collected through questionnaires, in-depth interviews and focus group discussions, site visits, and document reviews, engaging a wide range of stakeholders (N = 127). All transcripts were analyzed thematically. RESULTS: The CDiC scheme provides a stable supply of free insulin to children in implementing facilities in Kenya and Bangladesh, and offers a comprehensive package of pediatric diabetes care. However, some elements of the CDiC program were not functioning as originally intended. Transitions away from donor funding and toward government ownership are a particular concern, as patients may incur additional treatment costs, while services offered may be reduced. Additionally, despite subsidized treatment costs, indirect costs remain a substantial barrier to care. CONCLUSION: Public-private partnerships such as the CDiC program can improve access to life-saving medicines. However, our analysis found several limitations, including concerns over the sustainability of the project in both countries. Any program reliant on external funding and delivered in a high-turnover staffing environment will be vulnerable to sustainability concerns.

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Focusing only on biomedical targets neglects the important role that psychosocial factors play in effective diabetes self-management. This study aims to understand the lived experiences of children with Type 1 Diabetes (T1DM) in Kenya. Children (n = 15) participated in focus group discussions and photo diary data collection. Focus group discussions and semi-structured interviews were also conducted with caregivers (n = 14). We describe an adaptation to diabetes over time, identifying four overarching themes: knowledge and awareness, economic exclusion, the importance of social support, and striving for normality. Photo diaries are then categorized to explore daily realities of diabetes management. Children with T1DM in Kenya face varied barriers to care but can lead a "normal" and fulfilling life, provided adequate support is in place. To improve the lives of children with diabetes in this context and others like it, stakeholders must take note of children's experiences and recognize their multidimensional needs.

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Policy makers require support in conceptualizing and assessing the impact that vaccination policies can have on the proportion of the population being vaccinated against COVID-19. To this purpose, we propose a behavioural economics-based framework to model vaccination choices. We calibrate our model using up-to-date surveys on people attitudes toward vaccination as well as estimates of COVID-19 infection and mortality rates and vaccine efficacy for the UK population. Our findings show that vaccine campaigns hardly reach herd immunity if the sceptics have real-time information on the proportion of the population being vaccinated and the negationists do not change their attitudes toward vaccination. Based on our results, we discuss the main implications of the model's application in the context of nudging and voluntariness versus mandatory rule-based policies.

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BACKGROUND: The questioned link between air pollution and coronavirus disease 2019 (COVID-19) spreading or related mortality represents a hot topic that has immediately been regarded in the light of divergent views. A first "school of thought" advocates that what matters are only standard epidemiological variables (i.e. frequency of interactions in proportion of the viral charge). A second school of thought argues that co-factors such as quality of air play an important role too. METHODS: We analyzed available literature concerning the link between air quality, as measured by different pollutants and a number of COVID-19 outcomes, such as number of positive cases, deaths, and excess mortality rates. We reviewed several studies conducted worldwide and discussing many different methodological approaches aimed at investigating causality associations. RESULTS: Our paper reviewed the most recent empirical researches documenting the existence of a huge evidence produced worldwide concerning the role played by air pollution on health in general and on COVID-19 outcomes in particular. These results support both research hypotheses, i.e. long-term exposure effects and short-term consequences (including the hypothesis of particulate matter acting as viral "carrier") according to the two schools of thought, respectively. CONCLUSIONS: The link between air pollution and COVID-19 outcomes is strong and robust as resulting from many different research methodologies. Policy implications should be drawn from a "rational" assessment of these findings as "not taking any action" represents an action itself.

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OBJECTIVES: Do people living in more corrupted countries report worse health? We answer this question by investigating the relationship between country-level corruption and the number of chronic diseases for a sample of Europeans aged above 50. METHODS: We link a rich panel dataset on individual health and socio-demographic characteristics with two country-level corruption indices, analyse the overall relationship with pooled ordinary least squares and fixed-effect models, explore heterogeneous effects driven by country and individual factors, and disentangle the effect across different public sectors. RESULTS: Individuals living in more corrupted countries suffer from a higher number of chronic diseases. The heterogeneity analysis shows that (1) health outcomes are worsened especially for respondents living in relatively low-income countries; (2) the health of females and people with poor socio-economic status is more affected by corruption; (3) the corruption-health negative link mainly occurs for cardiovascular diseases and ulcers; (4) only corrupted sectors linked with healthcare are associated with poorer health. CONCLUSIONS: We inform the policy debate with novel results in establishing a nexus between corruption and morbidity indicators.

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We investigate the impact of health expenditure on health outcomes on a large sample of Europeans aged above 50 using individual and regional level data. We find a negative and significant effect of lagged health expenditure on subsequent changes in the number of chronic diseases. This effect varies according to age, health behavior, gender, income, and education. Our empirical findings are confirmed also when health expenditure is instrumented with parliament political composition.

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