Susceptibility and vulnerability to health effects of air pollution: The case of nitrogen dioxide

Epidemiological and toxicological studies have reported adverse health effects in response to exposure to air pollution including nitrogen dioxide (NO2). Some of these studies have indicated that specific populations may be at different risk of NO2 related health effects that others. Adverse health effects from air pollution are not equally distributed among populations and individuals. Differences in vulnerability and susceptibility may affect the risk of developing a health effect and its severity. A description and characterization of factors associated with vulnerability and susceptibility to health effects of ambient air pollution with a focus on NO2 exposure, a common air pollutant which has been associated with human morbidity and mortality, is presented based on a scoping review for the period 2011-2015. We identified epidemiological studies of factors that may play the role of effect modifiers of the association between exposure to NO2 and related health effects. Studies that may influence risk were critically reviewed. Population groups and characteristics were identified and health effects described and put into the context of risk assessment of air pollution. Population characteristics that can modify the health effects related to NO2 and confer susceptibility are predominantly age, underlying disease, and potentially genetics and gender. These population characteristics don’t differ from those identified for other air pollutants. Understanding about the latter two characteristics has been limited also in association with other air pollutants. Differential vulnerability has been shown due to socioeconomic factors. Insufficient attention in terms of exploration has been paid to the effects of other vulnerability factors. Understanding how NO2 may differently affect individuals or population subgroups is of major relevance for evidence-based policy making in emission reduction strategies and in health protection of those populations most vulnerable and susceptible.JRC.H.2-Air and Climat

Risk Mapping and Mathematical Modelling:Assessment Tools for the Impact of Climate Change on Infectious Diseases

There is now near undisputed scientific consensus that the rise in atmospheric concentration of greenhouse gases causes warming at the Earth¿s surface. Global warming will also have impacts on human health. We focus here on vector-borne infectious diseases because climatic variables are major determinants of the geographical distribution of the cold-blooded insect and tick species that can transmit viruses, bacteria and other microparasites to humans. The distribution of vectors is thus one important component of infection risk. We review the methods that have been developed in the past few years to determine and to model the distribution of species under actual and hypothetical environmental conditions and show how mathematical models have been used in this context. Remote sensing technology offers progressively better environmental and climatic data which can be employed in conjunction with Geographic Information Systems (GIS) and spatial statistical techniques to determine the distribution of vector species under different scenarios. Mathematical models can help to elucidate many aspects of infectious disease dynamics. The available studies lead to the expectation that climate change affects the transmission dynamics of vector-borne infectious diseases. However, the details and the degree of these effects are very uncertain. In order to predict more reliably the effects of extreme climate variability or climate change on infectious disease dynamics more data on the interaction between ecological, epidemiological, economical and social processes are needed.JRC.G.2-Support to external securit

Operations research in disaster preparedness and response: The public health perspective

Operations research is the scientific study of operations for the purpose of better decision making and management. Disasters are defined as events whose consequences exceed the capability of civil protection and public health systems to provide necessary responses in a timely manner. Public health science is applied to the design of operations of public health services and therefore operations research principles and techniques can be applied in public health. Disaster response quantitative methods such as operations research addressing public health are important tools for planning effective responses to disasters. Models address a variety of decision makers (e.g. first responders, public health officials), geographic settings, strategies modelled (e.g. dispensing, supply chain network design, prevention or mitigation of disaster effects, treatment) and outcomes evaluated (costs, morbidity, mortality, logistical outcomes) and use a range of modelling methodologies. Regarding natural disasters the modelling approaches have been rather limited. Response logistics related to public health impact of disasters have been modelled more intensively since decisions about procurement, transport, stockpiling, and maintenance of needed supplies but also mass vaccination, prophylaxis, and treatment are essential in the emergency management. Major issues at all levels of disaster response decision making, including long-range strategic planning, tactical response planning, and real-time operational support are still unresolved and operations research can provide useful techniques for decision management.-JRC.G.2-Global security and crisis managemen

On modeling airborne infection risk

Airborne infection risk analysis is usually performed for enclosed spaces where susceptible individuals are exposed to infectious airborne respiratory droplets by inhalation. It is usually based on exponential, dose-response models of which a widely used variant is the Wells-Riley (WR) model. We employ a population-based Susceptible-Exposed-Droplet-Infected-Recovered (SEDIR) model to revisit the infection-risk estimate at the population level during an epidemic. We demonstrate the link between epidemiological models and the WR model, including its Gammaitoni-Nucci (GN) generalization. This connection shows how infection quanta are related to the number of infectious airborne droplets. For long latent periods, the SEDIR model reduces to the GN model with parameters that depend on biological properties of the pathogen (size-dependent pathogen droplet concentration, infection probability of a deposited infectious droplet), physical droplet properties (lung-deposition probability), and individual behavioral properties (exposure time). In two scenarios we calculate the probability of infection during the epidemic. The WR and GN limits of the SEDIR model reproduce accurately the SEDIR-calculated infection risk.Comment: 14 pages, 3 figure

Migratory birds, the H5N1 influenza virus and the scientific method

<p>Abstract</p> <p>Background</p> <p>The role of migratory birds and of poultry trade in the dispersal of highly pathogenic H5N1 is still the topic of intense and controversial debate. In a recent contribution to this journal, Flint argues that the strict application of the scientific method can help to resolve this issue.</p> <p>Discussion</p> <p>We argue that Flint's identification of the scientific method with null hypothesis testing is misleading and counterproductive. There is far more to science than the testing of hypotheses; not only the justification, bur also the discovery of hypotheses belong to science. We also show why null hypothesis testing is weak and that Bayesian methods are a preferable approach to statistical inference. Furthermore, we criticize the analogy put forward by Flint between involuntary transport of poultry and long-distance migration.</p> <p>Summary</p> <p>To expect ultimate answers and unequivocal policy guidance from null hypothesis testing puts unrealistic expectations on a flawed approach to statistical inference and on science in general.</p

The H1N1 (2009) influenza pandemic: insights into its dynamics from different types of epidemiological data

For the assessment of the transmission potential and the severity of the recent H1N1 (2009) influenza pandemic, a series of different types of epidemiological data were used. We describe the way these data have been employed to estimate some key epidemiological parameters of the pandemic. A preliminary statistical analysis of European data related to Severe Acute Respiratory Infections (SARI) provided interesting insights into the severity of the pandemic as this was manifested in Europe.JRC.G.2-Global security and crisis managemen

Modelling the 2007 Chikungunya Outbreak in Italy

The report describes the modelling analysis performed by JRC on request of the DG-SANCO related to the Chickungunya Outbreak occurred in Italy in the summer of 2007. The analysis reports the calculations performed using global models and agent based models.JRC.G.2-Support to external securit

Demographic and Human Capital Scenarios for the 21st Century: 2018 assessment for 201 countries

This volume presents different scenarios of future population and human capital trends in 201 countries of the world to the end of this century to inform the assessment of possible future migration patterns into the EU, as currently carried out by the Centre of Expertise on Population and Migration (CEPAM) Project (collaboration between JRC and IIASA). The study also goes beyond the conventional population projections, which only consider age and sex structures, by taking a multi-dimensional approach through adding educational attainment for all countries and also labour force participation for EU member states. The definition of scenarios in this study follows the narratives of the SSPs (Shared Socioeconomic Pathways) which are widely used in the global change research community

Demographic and Human Capital Scenarios for the 21st Century: 2018 assessment for 201 countries

This volume presents different scenarios of future population and human capital trends in 201 countries of the world to the end of this century to inform the assessment of possible future migration patterns into the EU as currently carried out by the Centre of Expertise on Population and Migration (CEPAM) Project (collaboration between JRC and IIASA). The study also goes beyond the conventional population projections which only consider the age and sex structures by taking a multi-dimensional approach through adding educational attainment for all countries and also labor force participation for EU member states. The definition of scenarios in this study follows the narratives of the SSPs (Shared Socioeconomic Pathways) which are widely used in the global change research community. The Medium scenario (SSP2) foresees that fertility and mortality follow a medium pathway that can be seen as most likely from today’s perspective. The scenario of Rapid Development (SSP1) assumes rapid increases in life expectancy, a faster fertility decline in high fertility countries and an education expansion path that follows the education goals as given by the SDGs (Sustainable Development Goals). The Stalled Development scenario (SSP3) presents divided world foreseeing a stall in educational expansion in developing countries as well as continued high fertility and high mortality. Moreover, these scenarios also serve policy considerations in many other fields ranging from the economic consequences of population ageing to development priorities in Africa, global population and environment interactions. This volume also serves as an update of the scenarios presented in the 2014 Oxford University Press book entitled “World Population and Human Capital in the 21st Century” (Lutz et al 2014), which includes the most comprehensive summary of different possible scientific arguments underlying the assumptions of future fertility, mortality, migration and education trends in different parts of the world with input from over 550 population experts. This new 2018 assessment also has a new 2015 baseline and adjusts the near term (up to 2030) fertility and mortality assumptions accordingly while maintaining the long term assumptions as justified in the 2014 book. In terms of migration, it combines three rough migration assumptions – zero migration, constant rates as observed over the past 60 years and double those rates – with medium fertility and mortality trends to illustrate the sensitivity of longer term population trends to alternative migration intensities. In terms of global level results, in the Medium scenario, world population would continue to increase until around 2070-80 when it would reach a maximum level of around 9.8 billion before starting a slow decline, reaching about 9.5 billion by the end of the century. This projected increase is lower than the recent United Nations projections based on a different model and higher than in the above mentioned 2014 book which uses the same long term assumptions. An important reason for increase in the outlook lies in the fact that child mortality, particularly in Africa, declined more rapidly than was previously assumed by all international projections. In demographic terms, a decline in child mortality has the same effect on the number of surviving children as an increase in fertility. Hence, already the population baseline of 2015 was markedly higher than had been projected on the basis of the 2010 baseline, which was used in the previous assessment. However, in the long run demography is not destiny and alternative scenarios show a broad range of possible futures. Assuming rapid social development (SSP1), in particular a rapid expansion of education following the Sustainable Development Goals, world population would after a further increase start to decrease, showing a peak population of around 8.9 billion in 2055-60 and a decline to 7.8 billion by the end of the century. Assuming on the other hand stalled social development (SSP3) and thus lower female education and higher fertility rates for each education group, world population already reaches the 10 billion mark around 2045 and then continues to grow over the rest of the century reaching 13.4 billion in 2100. This scenario is also likely to be associated with wide-spread poverty and weak resilience to already unavoidable environmental change. As to the European Union, projected population size under the Medium scenario of EU28 in 2060 is very close to the current baseline of 2015, namely around 507 million inhabitants. However, the trajectory of change would have a convex shape reaching a maximum 512 million people around the year 2035. While the initial increase is mostly a consequence of assumed immigration to the EU the following decline results from persistent sub-replacement fertility levels which will have developed a negative growth momentum through an age structure with fewer young people. Under the scenario of Zero Migration the population of the EU-28 would decline to around 460 million by 2060, while under the Double Migration scenario it would increase to 550 million. Under all scenarios the population of the EU28 shows significant ageing, which is more pronounced under low fertility and low immigration assumptions. However, the scenarios that explicitly consider education and labor force participation also show that the total labor force in Europe does not necessarily shrink, if labor force participation around the EU would approach that of Sweden today and that the future labor force could also be more productive. The population of Sub-Saharan Africa, on the other hand, is likely to more than double by 2060 from currently around 1 billion to 2.2 billion under the Medium scenario and even 2.7 billion under the stalled development SSP3 scenario. Hence, with the demographic transition in Asia well advanced, the future of world population growth will largely be decided in Africa with the future education of women as a main determinant of fertility playing a key role. There has been recent moderate progress in education expansion but continued progress is not guaranteed, despite the fact that today in virtually all countries the young generations are better educated than the older ones. But as shown by the stalled development (SSP3) scenario the combination of high population growth with no further schooling expansion can actually result in an increase of the proportion without any formal education even at the global level from 10 to 22 percent by the end of the century. This possible stall in education will not only accelerate population growth but also likely be associated with widespread poverty and high vulnerability to already unavoidable climate change. The combined trends of decreasing fertility and increasing life expectancy would lead to continued population ageing in the world in the future. The world will be significantly older. In all scenarios presented in the report, as well as those used by United Nations, the share of older people increases over time. For example, in our Medium scenario the percentage of those aged 65 and more increases from around 8% in 2015 to 20% by 2060. In the European Union, the share of older people will grow from around 20% in 2015 to 32% in 2060 according to medium scenario. In 2060 half of the population in this region will be at an age of at least 50 years. A particularly dynamic process would be observed in Eastern European member states where lower fertility and high life expectancy is accompanied with high volume of emigration accelerating ageing if the current trends continue. These structural changes would lead to significant socio-economic challenges for societies in the future.JRC.A.5-Scientific Developmen