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A new generation of activists is calling for bold responses to the climate crisis. Although young people are motivated to act on climate issues, existing educational frameworks do not adequately prepare them by addressing the scope and complexity of the human health risks associated with climate change. We adapted the US government's climate literacy principles to propose a definition and corresponding set of elements for a concept we term climate and health literacy. We conducted a scoping review to assess how the peer-reviewed literature addresses these elements. Our analysis reveals a focus on training health professionals; more international than US domestic content; and limited information about data and models, fossil fuels, and equity. We propose developing a framework that builds on the elements to support a broader educational agenda that prepares students and future leaders to recognize the complex health ramifications of a changing climate.

Global communities increasingly struggle to provide ample healthful food for growing populations in the face of social and environmental pressures. Insect agriculture is one underexplored and innovative approach. Sustainable cultivation of nutrient-dense edible insects could help boost food access, support human nutrition, and mitigate key drivers of climate change. The edible insects industry is in its nascent stages, as relatively few entities have committed resources towards optimizing farming methods. Nevertheless, insect farming is poised to benefit food insecure populations, and the planet as a whole if more targeted research and conducive policies are implemented. The purpose of this paper is to outline the state of the science regarding edible insects, define a research agenda, and recommend policy action to support the growing industry. Edible insects are not a panacea for current challenges, but they have the potential to confer numerous benefits to people and the environment. Rigorous research is needed to establish optimal farming methods, strengthen food safety, understand health impacts of consumption, explore consumer acceptance, tackle ethical considerations, and investigate economic viability. A clear definition for insects as food, industry guidance support for obtaining generally regarded as safe designation, and collaboration by industry stakeholders to develop production standards will also help move the industry forward. Generating and galvanizing knowledge sharing networks, investing in critical interdisciplinary research, and advocating for conducive policies that support emerging entrepreneurs will be necessary to capitalize on the benefits of edible insects in the future.

The novel coronavirus disease (COVID-19) pandemic is a global threat presenting health, economic and social challenges that continue to escalate. Meta-population epidemic modeling studies in the susceptible-exposed-infectious-removed (SEIR) style have played important roles in informing public health and shaping policy making to mitigate the spread of COVID-19. These models typically rely on a key assumption on the homogeneity of the population. This assumption certainly cannot be expected to hold true in real situations; various geographic, socioeconomic and cultural environments affect the behaviors that drive the spread of COVID-19 in different communities. What’s more, variation of intra-county environments creates spatial heterogeneity of transmission in different sub-regions. To address this issue, we develop a new human mobility flow-augmented stochastic SEIR-style epidemic modeling framework with the ability to distinguish different regions and their corresponding behavior. This new modeling framework is then combined with data assimilation and machine learning techniques to reconstruct the historical growth trajectories of COVID-19 confirmed cases in two counties in Wisconsin. The associations between the spread of COVID-19 and human mobility, business foot-traffic, race & ethnicity, and age-group are then investigated. The results reveal that in a college town (Dane County) the most important heterogeneity is spatial, while in a large city area (Milwaukee County) ethnic heterogeneity becomes more apparent. Scenario studies further indicate a strong response of the spread rate on various reopening policies, which suggests that policymakers may need to take these heterogeneities into account very carefully when designing policies for mitigating the spread of COVID-19 and reopening.

Summary: The rapid global spread and human health impacts of SARS-CoV-2, the virus that causes COVID-19, show humanity's vulnerability to zoonotic disease pandemics. Although anthropogenic land use change is known to be the major driver of zoonotic pathogen spillover from wildlife to human populations, the scientific underpinnings of land use-induced zoonotic spillover have rarely been investigated from the landscape perspective. We call for interdisciplinary collaborations to advance knowledge on land use implications for zoonotic disease emergence with a view toward informing the decisions needed to protect human health. In particular, we urge a mechanistic focus on the zoonotic pathogen infect–shed–spill–spread cascade to enable protection of landscape immunity—the ecological conditions that reduce the risk of pathogen spillover from reservoir hosts—as a conservation and biosecurity priority. Results are urgently needed to formulate an integrated, holistic set of science-based policy and management measures that effectively and cost-efficiently minimise zoonotic disease risk. We consider opportunities to better institute the necessary scientific collaboration, address primary technical challenges, and advance policy and management issues that warrant particular attention to effectively address health security from local to global scales.

In this study, we estimate the health benefits of more stringent alternative energy goals and the costs of reducing coal-fired power plant pollution in China projected in 2030. One of our two overarching alternative energy goals was to estimate the health benefits of complete elimination of coal energy, supplemented by natural gas and renewables. The second was a policy scenario similar to the U.S. 2013 Climate Action Plan (CAP), which played a pivotal role leading up to the 2015 Paris Climate Agreement. We used the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) model created by the International Institute for Applied Systems Analysis for our model simulations. We found that 17,137–24,220 premature deaths can be avoided if coal energy is completely replaced by alternative energy, and 8,693–9,281 premature deaths can be avoided if coal energy is replaced by alternatives in a CAP-like scenario. A CAP-like scenario using emission-controls in coal plants costs $11–18 per person. Reducing coal energy in China under a CAP-like scenario would free up $9.4 billion in the annual energy budget to spend on alternatives, whereas eliminating the cost of coal energy frees up $32 billion. This study's estimates show that more stringent alternative energy targets in China are worth the investment in terms of health.

Floods are the most common and damaging natural disaster in Bangladesh, and the effects of floods on public health have increased significantly in recent decades, particularly among lower socio-economic populations. Assessments of social vulnerability on flood-induced health outcomes typically focus on local to regional scales; a notable gap remains in comprehensive, large-scale assessments that may foster disaster management practices. In this study, socio-economic, health, and coping capacity vulnerability and composite social-health vulnerability are assessed using both equal-weight and principal component approaches using 26 indicators across Bangladesh. Results indicate that vulnerable zones exist in the northwest riverine areas, northeast floodplains, and southwest region, potentially affecting 42 million people (26 % of total population). Subsequently, the vulnerability measures are linked to flood forecast and satellite inundation information to evaluate their potential for predicting actual flood impact indices (distress, damage, disruption, and health) based on the immense August 2017 flood event. Overall, the forecast-based equally weighted vulnerability measures perform best. Specifically, socio-economic and coping capacity vulnerability measures strongly align with the distress, disruption, and health impacts records observed. Additionally, the forecast-based composite social-health vulnerability index also correlates well with the impact indices, illustrating its utility in identifying predominantly vulnerable regions. These findings suggest the benefits and practicality of this approach to assess both thematic and comprehensive spatial vulnerabilities, with the potential to support targeted and coordinated public disaster management and health practices.

Key Points Question Did human mobility patterns change during stay-at-home orders and were the mobility changes associated with the coronavirus disease 2019 (COVID-19) curve? Findings This cross-sectional study using anonymous location data from more than 45 million mobile phones found that median travel distance decreased and stay-at-home time increased across the nation, although there was geographic variation. State-specific empirical doubling time of total COVID-19 cases increased (ie, the spread reduced) significantly after stay-at-home orders were put in place. Meaning These findings suggest that stay-at-home social distancing mandates were associated with the reduced spread of COVID-19 when they were followed., This cross-sectional study uses anonymous mobile phone location data to examine travel and home dwell time patterns before and after enactment of stay-at-home orders in US states during the coronavirus disease 2019 (COVID-19) pandemic., Importance A stay-at-home social distancing mandate is a key nonpharmacological measure to reduce the transmission rate of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), but a high rate of adherence is needed. Objective To examine the association between the rate of human mobility changes and the rate of confirmed cases of SARS-CoV-2 infection. Design, Setting, and Participants This cross-sectional study used daily travel distance and home dwell time derived from millions of anonymous mobile phone location data from March 11 to April 10, 2020, provided by the Descartes Labs and SafeGraph to quantify the degree to which social distancing mandates were followed in the 50 US states and District of Columbia and the association of mobility changes with rates of coronavirus disease 2019 (COVID-19) cases. Exposure State-level stay-at-home orders during the COVID-19 pandemic. Main Outcomes and Measures The main outcome was the association of state-specific rates of COVID-19 confirmed cases with the change rates of median travel distance and median home dwell time of anonymous mobile phone users. The increase rates are measured by the exponent in curve fitting of the COVID-19 cumulative confirmed cases, while the mobility change (increase or decrease) rates were measured by the slope coefficient in curve fitting of median travel distance and median home dwell time for each state. Results Data from more than 45 million anonymous mobile phone devices were analyzed. The correlation between the COVID-19 increase rate and travel distance decrease rate was –0.586 (95% CI, –0.742 to –0.370) and the correlation between COVID-19 increase rate and home dwell time increase rate was 0.526 (95% CI, 0.293 to 0.700). Increases in state-specific doubling time of total cases ranged from 1.0 to 6.9 days (median [interquartile range], 2.7 [2.3-3.3] days) before stay-at-home orders were enacted to 3.7 to 30.3 days (median [interquartile range], 6.0 [4.8-7.1] days) after stay-at-home social distancing orders were put in place, consistent with pandemic modeling results. Conclusions and Relevance These findings suggest that stay-at-home social distancing mandates, when they were followed by measurable mobility changes, were associated with reduction in COVID-19 spread. These results come at a particularly critical period when US states are beginning to relax social distancing policies and reopen their economies. These findings support the efficacy of social distancing and could help inform future implementation of social distancing policies should they need to be reinstated during later periods of COVID-19 reemergence.

The 2018 NASA Health and Air Quality Applied Science Team (HAQAST) “Indicators” Tiger Team collaboration between NASA‐supported scientists and civil society stakeholders aimed to develop satellite‐derived global air pollution and climate indicators. This Commentary shares our experience and lessons learned. Together, the team developed methods to track wildfires, dust storms, pollen counts, urban green space, nitrogen dioxide concentrations and asthma burdens, tropospheric ozone concentrations, and urban particulate matter mortality. Participatory knowledge production can lead to more actionable information but requires time, flexibility, and continuous engagement. Ground measurements are still needed for ground truthing, and sustained collaboration over time remains a challenge., Key Points The NASA Health and Air Quality Applied Science Team “Indicators” Tiger Team developed satellite‐based air quality and climate indicatorsParticipatory knowledge production can lead to more useful information for stakeholders but requires continuous engagement and flexibilityGround measurements are still needed, and sustained collaboration between the researchers and stakeholders over time remains a challenge

Health professionals are in a unique position to accelerate the creation of policies to mitigate and adapt to the public health emergency that is the climate crisis. At the forefront of the burgeoning climate and health movement are state and national health professional networks that are educating their colleagues and the lay public about the gravity of this threat and advocating for equitable solutions. Here we present a case of one such group, Wisconsin Health Professionals for Climate Action (WHPCA), highlighting its organizational structure and path to success. We also present a logic map to help understand the primary leverage points for health professional advocacy.

Introduction Overdependence on gasoline-powered personal automobiles in industrialized urban settings has resulted in transportation behaviour that is detrimental to public health. Risk not only stems from an increase in air pollution, but also, and more significantly for wealthy nations, from a reduction in physical activity. Tools and models that demonstrate the magnitude of the health benefits of physical activity are needed to inform policies addressing the epidemic of physical inactivity and to help promote environmentally sustainable cities. Methods The Health-Oriented Transportation (HOT) model is a transparent and easily accessible tool that allows users to assess the current and potential health benefits of active transportation (walking or cycling) using data from a one-day travel survey. As a case-study, we apply the HOT model to the population of London, England, using the London Travel Demand Survey. Results We estimate that in the 2016 adult population of London, 1,618 and 2,720 deaths were averted in the inner and outer boroughs, respectively, due to transportation-related physical activity; an additional 364 and 946 deaths are potentially averted if the proportion of the adult population that walked or cycled at least weekly from 80% and 73% to 100% in the inner and outer boroughs, respectively. A 50% increase in walking/cycling mode share among active travellers would result in a 2.5% reduction in premature deaths in the adult population of London. Conclusions Estimating the potentially large health benefits arising from active transportation in an urban setting can provide key public health information for urban planners and local officials, informing investments in infrastructure and critical public health programs.

Season is a major determinant of infectious disease rates, including arboviruses spread by mosquitoes, such as dengue, chikungunya, and Zika. Seasonal patterns of disease are driven by a combination of climatic or environmental factors, such as temperature or rainfall, and human behavioral time trends, such as school year schedules, holidays, and weekday-weekend patterns. These factors affect both disease rates and healthcare-seeking behavior. Seasonality of dengue fever has been studied in the context of climatic factors, but short- and long-term time trends are less well-understood. With 2009—2016 medical record data from patients diagnosed with dengue fever at two hospitals in rural Ecuador, we used Poisson generalized linear modeling to determine short- and long-term seasonal patterns of dengue fever, as well as the effect of day of the week and public holidays. In a subset analysis, we determined the impact of school schedules on school-aged children. With a separate model, we examined the effect of climate on diagnosis patterns. In the first model, the most important predictors of dengue fever were annual sinusoidal fluctuations in disease, long-term trends (as represented by a spline for the full study duration), day of the week, and hospital. Seasonal trends showed single peaks in case diagnoses, during mid-March. Compared to the average of all days, cases were more likely to be diagnosed on Tuesdays (risk ratio (RR): 1.26, 95% confidence interval (CI) 1.05—1.51) and Thursdays (RR: 1.25, 95% CI 1.02—1.53), and less likely to be diagnosed on Saturdays (RR: 0.81, 95% CI 0.65—1.01) and Sundays (RR: 0.74, 95% CI 0.58—0.95). Public holidays were not significant predictors of dengue fever diagnoses, except for an increase in diagnoses on the day after Christmas (RR: 2.77, 95% CI 1.46—5.24). School schedules did not impact dengue diagnoses in school-aged children. In the climate model, important climate variables included the monthly total precipitation, an interaction between total precipitation and monthly absolute minimum temperature, an interaction between total precipitation and monthly precipitation days, and a three-way interaction between minimum temperature, total precipitation, and precipitation days. This is the first report of long-term dengue fever seasonality in Ecuador, one of few reports from rural patients, and one of very few studies utilizing daily disease reports. These results can inform local disease prevention efforts, public health planning, as well as global and regional models of dengue fever trends.Author summaryDengue fever exhibits a seasonal pattern in many parts of the world, much of which has been attributed to climate and weather. However, additional factors may contribute to dengue seasonality. With 2009— 2016 medical record data from rural Ecuador, we studied the short- and long-term seasonal patterns of dengue fever, as well as the effect of school schedules and public holidays. We also examined the effect of climate on dengue. We found that dengue diagnoses peak once per year in mid-March, but that diagnoses are also affected by day of the week. Dengue was also impacted by regional climate and complex interactions between local weather variables. This is the first report of long-term dengue fever seasonality in Ecuador, one of few reports from rural patients, and one of very few studies utilizing daily disease reports. This is the first report on the impacts of school schedules, holidays, and weekday-weekend patterns on dengue diagnoses. These results suggest a potential impact of human behaviors on dengue exposure risk. More broadly, these results can inform local disease prevention efforts and public health planning, as well as global and regional models of dengue fever trends.

Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, 4002 Basel, Switzerland University of Basel, Petersplatz 1, 4003 Basel, Switzerland Faculty of Health Sciences, Curtin University, P.O. Box U1987, Perth, WA 6845, Australia The Burnet Institute, Melbourne, VIC 3004, Australia Australian Animal Health Laboratory, P.O. Box 100, Geelong, VIC, Australia Centre on Global Health Security, Chatham House, London, UK Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK Global Health Institute, University of Wisconsin, 1710 University Avenue, Madison, WI 53726 EcoHealth Alliance, 460 West 34th Street, 17th Floor, New York, NY 10001

Occupational health risks posed by climate change have focused on heat-related illness and mortality, and a growing body of evidence shows substantial risks to health and economic productivity for many countries. Since the 2015 Paris Agreement on climate change, the shift away from fossil fuel-based economies has accelerated. Potential population health benefits from improved air quality, more physically active urban communitng and reduced future heating of the planet are substantial. However, unquantified is the extent that technologies in renewable energy sources pose risks to workers. A comparision between fossil fuel-related job risks and those stemming from renewable energy-related jobs will be presented. Gaps in knowledge will be identified to help guide the safest path for workers in our evolving low-carbon society. Note this abstract is part of the Mini-Symposium, Climate Change impacts on Occupational Health via workplace heat (Tord Kjellstrom, organiser). p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 16.0px ‘Courier New’; -webkit-text-stroke: #000000} span.s1 {font-kerning: none}

Land use and cover change drive a range of infectious disease outbreaks or disease emergences. These drivers include agricultural encroachment, deforestation, road construction, dam building, irrigation, wetland modification, mining, the concentration or expansion of urban environments, coastal zone degradation, and other activities. These changes in turn cause a cascade of factors that exacerbate infectious disease emergence, such as forest fragmentation, disease introduction, pollution, poverty, and human migration. Such changes can subsequently affect biological mechanisms of disease emergence including: altered vector breeding sites or reservoir host distribution; niche invasions or interspecies host transfers; changes in biodiversity (including loss of predator species and changes in host population density); human-induced genetic changes of disease vectors or pathogens (such as mosquito resistance to pesticides or the emergence of antibiotic-resistant bacteria); and environmental contamination of infectious disease agents.

Background: The accelerating accumulation of greenhouse gases in the Earth’s atmosphere is changing global environmental conditions in unprecedented and potentially irreversible ways. Climate change poses a host of challenges to the health of populations through complex direct and indirect mechanisms. The direct effects include an increased frequency of heat waves, rising sea levels that threaten low-lying communities, anticipated extremes in the global hydrologic cycle (droughts, floods, and intense storms), and adverse effects on agricultural production and fisheries due to environmental stressors and changes in land use. Indirectly, climate change is anticipated to threaten health by worsening urban air pollution and increasing rates of infectious (particularly waterborne and vector-borne) disease transmission. Objective: To provide a state-of-the-science review on the health consequences of a changing climate. Findings: Environmental public health researchers have concluded that, on balance, adverse health outcomes will dominate under these changed climatic conditions. The number of pathways through which climate change can affect the health of populations makes this environmental health threat one of the largest and most formidable of the new century. Geographic location plays an influential role the potential for adverse health effects caused by climate change, and certain regions and populations are more vulnerable than others to expected health effects. Two kinds of strategies are available for responding to climate change: mitigation policies (which aim to reduce greenhouse gas emissions) and adaptation measures (relating to preparedness for anticipated impacts). Conclusions: To better understand and address the complex nature of health risks posed by climate change, interdisciplinary collaboration is critical. Efforts to move beyond our current reliance on fossil fuels to cleaner, more sustainable energy sources may offer some of the greatest health opportunities in more than a century and cobenefits beyond the health sector. Because the nations least responsible for climate change are most vulnerable to its effects, the challenge to reduce greenhouse gas emissions is not merely technical, but also moral.

Objectives. This study investigated if the type of drinking water source (treated municipal, untreated municipal, and private well water) modifies the effect of hydrology on childhood (aged Methods. We conducted a time series study to assess the relationship between hydrologic and weather conditions with childhood gastrointestinal illness from 1991 to 2010. The Central and Northern Wisconsin study area includes households using all 3 types of drinking water systems. Separate time series models were created for each system and half-year period (winter/spring, summer/fall). Results. More precipitation (summer/fall) systematically increased childhood gastrointestinal illness in municipalities accessing untreated water. The relative risk of contracting gastrointestinal illness was 1.4 in weeks with 3 centimeters of precipitation and 2.4 in very wet weeks with 12 centimeters of precipitation. By contrast, gastrointestinal illness in private well and treated municipal areas was not influenced by hydrologic conditions, although warmer winter temperatures slightly increased incidence. Conclusions. Our study suggests that improved drinking water protection, treatment, and delivery infrastructure may improve public health by specifically identifying municipal water systems lacking water treatment that may transmit waterborne disease.

Today’s substantial global health gains are being undermined by the threat of climate change. Ironically, the actions required to confront the climate crisis represent possibly the largest public health opportunity in more than a century. Health benefits from improved air quality may far outweigh the cost of clean energy investments. Upward trends in chronic diseases are now occurring throughout the world. Herein lies even more golden opportunities for public health through the following: first, adopting more alternative modes of transportation, especially those that promote “active transport” by foot or by bicycle, in combination with effective public transportation; and second, by reducing meat in the diet. In essence, there is no better time to focus on health as central in the climate negotiations; and in so doing, may we move faster and further with effective actions on climate change and the subsequent health benefits that will arise from a low-carbon society.

Climate change leads to increasing temperatures, shifting rainfall patterns and more extreme weather events, which affect occupational health in many ways. Heat stress at work poses health risks and reduced work capacity, presenting a new and widespread occupational health challenge due to climate change. Human physiology limits to coping with heat stress are well known, but the links to climate change need further analysis. Occupational health effects include heat exhaustion (reducing work capacity), serious heat stroke (including deaths), dehydration effects on the kidneys, and exacerbation of chronic diseases. Cognitive performance is also affected by heat stress. Physical work significantly adds to heat stress because of internal heat production from muscles. Working people slow down or take frequent breaks (self-pacing) to compensate. As a result, reduced productivity creates economic losses. We compared population based estimates of health impacts of heat stress for selected climate models applied to the four different “Representative Concentration Pathways” of greenhouse gases established by the UN Intergovernmental Panel on Climate Change (IPCC). Serious ambient heat stress conditions currently occur 1–2% of annual daylight hours in hot tropical low altitude countries (e.„g. Nicaragua or Bangladesh), while higher altitude countries (e.„g. Ethiopia) or less hot sub-tropical countries (e.g. Greece) have less than 0.2% hours affected. The “business as usual” pathway creates heat stress risks for 10–20% of annual daylight hours in 2085 in the tropics. The climate change mitigation programs offered at the recent UN Framework Convention on Climate Change (UNFCCC) Paris summit may only halve these risks. In many low income countries the loss of work hours will create substantial reductions of annual GDP. Stricter global climate policies are needed, and occupational epidemiology research is essential to develop health impact assessments essential for decision-making to protect millions of working people in vulnerable countries.

Background: Automobile exhaust contains precursors to ozone and fine particulate matter (PM ≤ 2.5 µm in aerodynamic diameter; PM2.5), posing health risks. Dependency on car commuting also reduces physical fitness opportunities. Objective: In this study we sought to quantify benefits from reducing automobile usage for short urban and suburban trips. Methods: We simulated census-tract level changes in hourly pollutant concentrations from the elimination of automobile round trips ≤ 8 km in 11 metropolitan areas in the upper midwestern United States using the Community Multiscale Air Quality (CMAQ) model. Next, we estimated annual changes in health outcomes and monetary costs expected from pollution changes using the U.S. Environmental Protection Agency Benefits Mapping Analysis Program (BenMAP). In addition, we used the World Health Organization Health Economic Assessment Tool (HEAT) to calculate benefits of increased physical activity if 50% of short trips were made by bicycle. Results: We estimate that, by eliminating these short automobile trips, annual average urban PM2.5 would decline by 0.1 µg/m3 and that summer ozone (O3) would increase slightly in cities but decline regionally, resulting in net health bene-fits of $4.94 billion/year [95% confidence interval (CI): $0.2 billion, $13.5 billion), with 25% of PM2.5 and most O3 bene-fits to populations outside metropolitan areas. Across the study region of approximately 31.3 million people and 37,000 total square miles, mortality would decline by approximately 1,295 deaths/year (95% CI: 912, 1,636) because of improved air quality and increased exercise. Making 50% of short trips by bicycle would yield savings of approximately $3.8 billion/year from avoided mortality and reduced health care costs (95% CI: $2.7 billion, $5.0 billion]. We estimate that the combined benefits of improved air quality and physical fitness would exceed $8 billion/year. Conclusion: Our findings suggest that significant health and economic benefits are possible if bicycling replaces short car trips. Less dependence on automobiles in urban areas would also improve health in downwind rural settings.

Background The Integrated Transport and Health Impacts Modelling (ITHIM) Tool has been used in data-rich environments of the UK, select US metros, and even Sao Paulo, Brazil. Its use has been limited, in part, because of its data requirements, format, and complexity. This work makes improvements to the US version of ITHIM, in particular to its module for estimating chronic disease burden reduction through change in population-level physical activity, to address these limitations. Methods Using the R software and language, we have updated and improved the US implementation of ITHIM. The revised model includes improved discretization of the attributable fraction as well as clearer documentation of model runs, changes, and results. Results These improvements have produced results that were more stable in the face of variability of existing input parameters, particularly population-level non-travel active times. Conclusions The resulting package for R is freely available software for modeling the health impacts of transportation planning scenarios. We believe these improvements will appeal to a larger user base through its ease of use, improved documentation, and more powerful capabilities.

UNLABELLED Indoor air pollution (IAP) from domestic biomass combustion is an important health risk factor, yet direct measurements of personal IAP exposure are scarce. We measured 24-h integrated gravimetric exposure to particles < 2.5 μm in aerodynamic diameter (particulate matter, PM₂.₅) in 280 adult women and 240 children in rural Yunnan, China. We also measured indoor PM₂.₅ concentrations in a random sample of 44 kitchens. The geometric mean winter PM₂.₅ exposure among adult women was twice that of summer exposure [117 μg/m³ (95% CI: 107, 128) vs. 55 μg/m³ (95% CI: 49, 62)]. Children's geometric mean exposure in summer was 53 μg/m³ (95% CI: 46, 61). Indoor PM₂.₅ concentrations were moderately correlated with women's personal exposure (r=0.58), but not for children. Ventilation during cooking, cookstove maintenance, and kitchen structure were significant predictors of personal PM₂.₅ exposure among women primarily cooking with biomass. These findings can be used to develop exposure assessment models for future epidemiologic research and inform interventions and policies aimed at reducing IAP exposure. PRACTICAL IMPLICATIONS Our results suggest that reducing overall PM pollution exposure in this population may be best achieved by reducing winter exposure. Behavioral interventions such as increasing ventilation during cooking or encouraging stove cleaning and maintenance may help achieve these reductions.

Given predictions of increased intensity and frequency of heat waves, it is important to study the effect of high temperatures on human mortality and morbidity. Many studies focus on heat wave-related mortality; however, heat-related morbidity is often overlooked. The goals of this study are to examine the historical observed relationship between temperature and morbidity (illness), and explore the extent to which observed historical relationships could be used to generate future projections of morbidity under climate change. We collected meteorological, air pollution, and hospital admissions data in Milwaukee, Wisconsin, for the years 1989–2005, and employed a generalized additive model (GAM) to quantify the relationship between morbidity (as measured by hospital admissions) and high temperatures with adjustment for the effects of potential confounders. We also estimated temperature threshold values for different causes of hospital admissions and then quantified the associated percent increase of admissions per degree above the threshold. Finally, the future impact of higher temperatures on admissions for the years 2059–2075 was examined. Our results show that five causes of admission (endocrine, genitourinary, renal, accidental, and self-harm) and three age groups (15–64, 75–84, >85 years) were affected by high temperatures. Future projections indicate a larger number of days above the current temperature threshold leading to an increase in admissions. Our results indicate that climate change may increase heat-related hospital admissions in the US urban mid-West and that health systems should include heat wave planning.

Large-scale anthropogenic changes to the natural environment, including land-use change, climate change, and the deterioration of ecosystem services, are all accelerating. These changes are interacting to generate five major emerging public health threats that endanger the health and well-being of hundreds of millions of people. These threats include increasing exposure to infectious disease, water scarcity, food scarcity, natural disasters, and population displacement. Taken together, they may represent the greatest public health challenge humanity has faced. There is an urgent need to improve our understanding of the dynamics of each of these threats: the complex interplay of factors that generate them, the characteristics of populations that make them particularly vulnerable, and the identification of which populations are at greatest risk from each of these threats. Such improved understanding would be the basis for stepped-up efforts at modeling and mapping global vulnerability to each of these threats. It would also help natural resource managers and policy makers to estimate the health impacts associated with their decisions and would allow aid organizations to target their resources more effectively.

Kawasaki disease exhibits a distinct seasonality, and short-term changes in weather may affect its occurrence.: To investigate the effects of weather variability on the occurrence of this syndrome, we conducted a time-between-events analysis of consecutive admissions for Kawasaki disease to a large pediatric hospital in Chicago. We used gamma regression to model the times between admissions. This is a novel application of gamma regression to model the time between admissions as a function of subject-specific covariates.: We recorded 723 admissions in the 18-year (1986-2003) study period, of which 700 had complete data for analysis. Admissions for Kawasaki disease in Chicago were seasonal: The mean time between admissions was 34% shorter (relative time = 0.66, 95% confidence interval 0.54-0.81) from January-March than from July-September. In 1998, we recorded a larger number of admissions for Kawasaki disease (n = 65) than in other years (mean n = 37). January-March months of 1998 were warmer by a mean of 3 degrees C (1.5 degrees C-4.4 degrees C) and the mean time between admissions was 48% shorter (relative time = 0.52, 0.36-0.75) than in equivalent periods of other study years.: Our findings show that atypical changes in weather affect the occurrence of Kawasaki disease and are compatible with a link to an infectious trigger. The analysis of interevent times using gamma regression is an alternative to Poisson regression in modeling a time series of sparse daily counts.

Introduction: E nvironmental factors contribute with 16% of the burden of disease in Colombia. A main obstacle in implementing national and regional environmental and occupational health policies is the limited knowledge on the local ability to study and control the impact of harmful exposures on health. Objective: To identify needs for research and training in environmental and occupational health in Colombia. Materials and methods: We conducted a three-round hybrid Delphi study. A group of environmental and occupational health Colombian experts (n=16) from government agencies, universities, and research centers was recruited to participate in the study. Expert´s opinions on research and training needs were gathered through online questionnaires, followed by an in-person meeting. The percentage of agreement and the coefficient of variation were used to measure consensus. Results: Air pollution and chemical products were considered the most important environmental and occupational exposures, due to their significant impact on chronic non-communicable diseases, such as respiratory diseases, cardiovascular diseases, and cancer. Research on the effects of outdoor air pollution on cardiovascular and respiratory diseases was considered of the greatest importance. Priority training areas included environmental and occupational health risk assessment, exposure modeling, advanced statistical methods, urban planning, occupational safety and hygiene, and epidemiology and toxicology. Conclusions: These findings provide a valuable input for the definition and implementation of national environmental and occupational health policies and for the development of a regional hub aimed at strengthening the capacity for research and training in Colombia. Introducción. Los factores ambientales contribuyen con el 16 % de la carga de enfermedad en Colombia. Un obstáculo importante para la implementación de políticas en salud ambiental y ocupacional es el conocimiento limitado sobre la capacidad local para estudiar y controlar el impacto de exposiciones ambientales y ocupacionales. Objetivo. Identificar necesidades de investigación y formación en salud ambiental y ocupacional en Colombia. Materiales y métodos. Se hizo un estudio Delphi híbrido en tres rondas. Se reclutó a un grupo de expertos en salud ambiental y ocupacional (n=16) de instituciones gubernamentales, universidades y centros de investigación. Las opiniones de los expertos sobre necesidades de investigación y formación se recolectaron mediante cuestionarios electrónicos, seguidos de una reunión presencial. El porcentaje de acuerdo y el coeficiente de variación se usaron para cuantificar el consenso del grupo. Resultados. La contaminación del aire y los productos químicos fueron considerados por los expertos como las exposiciones más importantes, dado su gran efecto en las enfermedades crónicas no transmisibles. La investigación de los efectos de la contaminación del aire ambiental sobre las enfermedades cardiovasculares y respiratorias, se consideró de importancia máxima. Las áreas prioritarias de formación fueron la evaluación del riesgo, el modelado de la exposición, los métodos estadísticos avanzados, la planeación urbana, la higiene y la seguridad industrial, y la epidemiología y la toxicología aplicadas a la salud ambiental y ocupacional. Conclusiones. Estos resultados son un insumo importante para la implementación de políticas nacionales en salud ambiental y ocupacional, y para el desarrollo de un nodo regional que fortalezca la capacidad de investigación y formación en Colombia.

This report assesses the impact of the variability in environmental and vector factors on the transmission of Ross River virus (RRV) in Brisbane, Australia. Poisson time series regression analyses were conducted using monthly data on the counts of RRV cases, climate variables (Southern Oscillation Index and rainfall), high tides and mosquito density for the period of 1998-2001. The results indicate that increases in the high tide (relative risk (RR): 1.65; 95% confidence interval (CI): 1.20-2.26), rainfall (RR: 1.45; 95% CI: 1.21-1.73), mosquito density (RR: 1.17; 95% CI: 1.09-1.27), the density of Culex annulirostris (RR: 1.25; 95% CI: 1.13-1.37) and the density of Ochlerotatus vigilax (RR: 2.39; 95% CI: 2.30-2.48), each at a lag of 1 month, were statistically significantly associated with the rise of monthly RRV incidence. The results of the present study might facilitate the development of early warning systems for reducing the incidence of this wide-spread disease in Australia and other Pacific island nations.

The increasing burden of emerging infectious diseases worldwide confronts us with numerous chal- lenges, including the imperative to design research and responses that are commensurate to understanding the complex social and ecological contexts in which infectious diseases occur. A diverse group of scientists met in Hawaii in March 2005 to discuss the linked social and ecological contexts in which infectious diseases emerge. A subset of the meeting was a group that focused on ''transdisciplinary approaches'' to integrating knowledge across and beyond academic disciplines in order to improve prevention and control of emerging infections. This article is based on the discussions of that group. Here, we outline the epidemiological legacy that has dominated infectious disease research and control up until now, and introduce the role of new, transdisciplinary and systems-based approaches to emerging infectious diseases. We describe four cases of transboundary health issues and use them to discuss the potential benefits, as well as the inherent difficulties, in understanding the social-ecological contexts in which infectious diseases occur and of using transdisciplinary approaches to deal with them.

We estimated the effects of temperature and humidity on hospital admissions for heart disease (International Classification of Diseases, 9th revision [ICD-9] codes 390-429) and myocardial infarction (ICD-9 code 410) of persons age 65 and older in 12 U.S. cities with a wide range of climates. To account for possible delayed effects and harvesting, we examined the impact of weather up to 20 days before each admission.Poisson regression models were fitted in each city, with regression splines used to control for season and barometric pressure. We also controlled day of the week. We estimated the effect and the lag structure of both temperature and humidity based on a distributed lag model.For cities in both hot and cold climates, we found that hospital admissions for all heart disease increased monotonically with average temperature on the same day as and the day before admission. The effect of very high temperatures had a temporal pattern consistent with harvesting: several days after an episode of high temperature, there were fewer admissions. In contrast, a protective effect of cold temperature persisted without rebound. The effects of either hot or cold temperature disappeared within 10 days of exposure. There was no evidence for a humidity effect. Similar but smaller effects of temperature were seen for admissions for myocardial infarction specifically.The effects of temperature on hospital admissions predominantly occur within a few days after exposure, and much of the effect of hot temperatures is short-term displacement of events.

This comparative review of three assessment reports, the Intergovernmental Panel on Climate Change, (IPCC), The National Research Council (NRC), and United States Global Change Research Program (USGCRP), respectively is presented in response to comments in the press suggesting that the three reports varied substantially in their assessments of associations between global climate and infectious disease in humans. Comparisons of the assessment teams, approach, reports' findings, views on predictive modeling, recommendations to policymakers and future research are presented. All teams were interdisciplinary, two international, one US-based. Although their approaches differed somewhat, all addressed the role of climate change, El Nino and climate variability, and ultimately, human health, especially infectious disease. The panels agreed that a paucity of long-term data and complexity of relationships among factors affecting climate variability and change and human health rendered projections of current predictive models inadequate as the basis for policy decisions. Each team suggested further study of associations among climate variability/climate change and human infectious disease and downscaled models to project regional and subregional outcomes. Each added additional areas for investigation, e.g., mathematical modeling, effects of socioeconomic factors, emergence of zoonotic disease in humans, transmission dynamics of disease agents. Rather than disagreements, there were differences in emphasis on known components and on hypothesized additional contributing factors and relationships among climate and human infectious disease variables.

Most US energy consumption occurs in buildings, with cooling demands anticipated to increase net building electricity use under warmer conditions. The electricity generation units that respond to this demand are major contributors to sulfur dioxide (SO2) and nitrogen oxides (NOx), both of which have direct impacts on public health, and contribute to the formation of secondary pollutants including ozone and fine particulate matter. This study quantifies temperature-driven changes in power plant emissions due to increased use of building air conditioning. We compare an ambient temperature baseline for the Eastern US to a model-calculated mid-century scenario with summer-average temperature increases ranging from 1 C to 5 C across the domain. We find a 7% increase in summer electricity demand and a 32% increase in non-coincident peak demand. Power sector modeling, assuming only limited changes to current generation resources, calculated a 16% increase in emissions of NOx and an 18% increase in emissions of SO2. There is a high level of regional variance in the response of building energy use to climate, and the response of emissions to associated demand. The East North Central census region exhibited the greatest sensitivity of energy demand and associated emissions to climate.

Exposure to waterborne and foodborne pathogens can occur via drinking water (associated with fecal contamination), seafood (due to natural microbial hazards, toxins, or wastewater disposal) or fresh produce (irrigated or processed with contaminated water). Weather influences the transport and dissemination of these microbial agents via rainfall and runoff and the survival and/or growth through such factors as temperature. Federal and state laws and regulatory programs protect much of the U.S. population from waterborne disease; however, if climate variability increases, current and future deficiencies in areas such as watershed protection, infrastructure, and storm drainage systems will probably increase the risk of contamination events. Knowledge about transport processes and the fate of microbial pollutants associated with rainfall and snowmelt is key to predicting risks from a change in weather variability. Although recent studies identified links between climate variability and occurrence of microbial agents in water, the relationships need further quantification in the context of other stresses. In the marine environment as well, there are few studies that adequately address the potential health effects of climate variability in combination with other stresses such as overfishing, introduced species, and rise in sea level. Advances in monitoring are necessary to enhance early-warning and prevention capabilities. Application of existing technologies, such as molecular fingerprinting to track contaminant sources or satellite remote sensing to detect coastal algal blooms, could be expanded. This assessment recommends incorporating a range of future scenarios of improvement plans for current deficiencies in the public health infrastructure to achieve more realistic risk assessments.

Summary Introduction To investigate whether the EI Nino phenomenon and ambient temperature had an effect on the epidemiology of childhood diarrhoea, we analysed data on daily number of admissions of children with diarrhoea to the Oral Rehydration Unit of the Instituto de Salud del Nino in Lima, Peru, between January, 1993, and November, 1998. Methods We obtained daily data on hospital admissions from the Oral Rehydration Unit, and meteororological data from the Peruvian Weather Service, and used time-series linear regression models to assess the effects of the 1997–98 EI Nino event on admissions for diarrhoea. Findings 57 331 children under 10 years old were admitted to the unit during the study. During the 1997–98 EI Nino episode, mean ambient temperature in Lima increased up to 5°C above normal, and the number of daily admissions for diarrhoea increased to 200% of the previous rate. 6225 excess admissions were attributable to EI Nino , and these cost US$277 000. During the period before the EI Nino episode, admissions for diarrhoea increased by 8% per 1°C increase in mean ambient temperature. The effects of EI Nino and ambient temperature on the number of admissions for diarrhoea were greatest during the winter months. Interpretatlon EI Nino had an effect on hospital admissions greater than that explained by the regular seasonal variability in ambient temperature. The excess increase in ambient temperature was the main environmental variable affecting admissions. If our findings are reproducible in other regions, diarrhoeal diseases may increase by millions of cases worldwide with each degree of increase in ambient temperature above normal.

The United Nation's Intergovernmental Panel on Climate Change estimates an unprecedented global rise of 2.0°C by the year 2100. Such change can affect serious infectious diseases, including dengue fever and malaria. Both large-scale iterative modeling and site-specific microclimatic analysis of disease ecology are needed in tandem to address health effects of climate change scenarios. In two separate studies of dengue and malaria transmission, both General Circulation Models (GCMs) of global climate change and site-specific climate analysis are used respectively to investigated climate change impacts on dengue fever and malaria transmission risk. For the first study, analysis was conducted using the integrated MIASMA model to link GCM projections of climate with a vectorial capacity model of transmission. Preliminary results indicate climate conditions being more suitable to dengue transmission, given viral introduction. An expansion of potential epidemic risk both geographically and temporally is inferred from this study. In the malaria study, preliminary results from regression analysis show mosquito biting rates to correlate to ambient temperature and rainfall. Parasite development was also shown to relate to temperature and humidity. Further interdisciplinary cooperation and multi-scaled analytical approaches will be required to better assess the potential effect of climate change on malaria and dengue. J Epidemiol, 1996 ; 6 : S145-S148.

Background: Almost half of the world’s population uses coal and biomass fuels for domestic energy. Limited evidence suggests that exposure to air pollutants from indoor biomass combustion may be associated with elevated blood pressure (BP). Objective: Our aim was to assess the relationship between air pollution exposure from indoor biomass combustion and BP in women in rural China. Methods: We measured 24-hr personal integrated gravimetric exposure to fine particles < 2.5 µm in aerodynamic diameter (PM2.5) and systolic BP (SBP) and diastolic BP (DBP) in the winter and summer among 280 women ≥ 25 years of age living in rural households using biomass fuels in Yunnan, China. We investigated the association between PM2.5 exposure and SBP and DBP using mixed-effects models with random intercepts to account for correlation among repeated measures. Results: Personal average 24-hr exposure to PM2.5 ranged from 22 to 634 µg/m3 in winter and from 9 to 492 µg/m3 in summer. A 1-log-µg/m3 increase in PM2.5 exposure was associated with 2.2 mm Hg higher SBP [95% confidence interval (CI), 0.8 to 3.7; p = 0.003] and 0.5 mm Hg higher DBP (95% CI, –0.4 to 1.3; p = 0.31) among all women; estimated effects varied by age group. Among women > 50 years of age, a 1-log-µg/m3 increase in PM2.5 exposure was associated with 4.1 mm Hg higher SBP (95% CI, 1.5 to 6.6; p = 0.002) and 1.8 mm Hg higher DBP (95% CI, 0.4 to 3.2; p = 0.01). PM2.5 exposure was positively associated with SBP among younger women, but the association was not statistically significant. Conclusion: PM2.5 exposure from biomass combustion may be a risk factor for elevated BP and hence for cardiovascular events. Our findings should be corroborated in longitudinal studies.

Climate change is projected to have adverse impacts on public health. Cobenefits may be possible from more upstream mitigation of greenhouse gases causing climate change. To help measure such cobenefits alongside averted disease-specific risks, a health impact assessment ( HIA ) framework can more comprehensively serve as a decision support tool. HIA also considers health equity, clearly part of the climate change problem. New choices for energy must be made carefully considering such effects as additional pressure on the world's forests through large-scale expansion of soybean and oil palm plantations, leading to forest clearing, biodiversity loss and disease emergence, expulsion of subsistence farmers, and potential increases in food prices and emissions of carbon dioxide to the atmosphere. Investigators must consider the full range of policy options, supported by more comprehensive, flexible, and transparent assessment methods.

The environmental and health consequences of climate change, which disproportionately affect low-income countries and poor people in high-income countries, profoundly affect human rights and social justice. Environmental consequences include increased temperature, excess precipitation in some areas and droughts in others, extreme weather events, and increased sea level. These consequences adversely affect agricultural production, access to safe water, and worker productivity, and, by inundating land or making land uninhabitable and uncultivatable, will force many people to become environmental refugees. Adverse health effects caused by climate change include heat-related disorders, vector-borne diseases, foodborne and waterborne diseases, respiratory and allergic disorders, malnutrition, collective violence, and mental health problems.These environmental and health consequences threaten civil and political rights and economic, social, and cultural rights, including rights to life, access to safe food and water, health, security, shelter, and culture. On a national or local level, those people who are most vulnerable to the adverse environmental and health consequences of climate change include poor people, members of minority groups, women, children, older people, people with chronic diseases and disabilities, those residing in areas with a high prevalence of climate-related diseases, and workers exposed to extreme heat or increased weather variability. On a global level, there is much inequity, with low-income countries, which produce the least greenhouse gases (GHGs), being more adversely affected by climate change than high-income countries, which produce substantially higher amounts of GHGs yet are less immediately affected. In addition, low-income countries have far less capability to adapt to climate change than high-income countries.Adaptation and mitigation measures to address climate change needed to protect human society must also be planned to protect human rights, promote social justice, and avoid creating new problems or exacerbating existing problems for vulnerable populations.

The World Health Organization has concluded that the climatic changes that have occurred since the mid 1970s could already be causing annually over 150,000 deaths and five million disability-adjusted life-years (DALY), mainly in developing countries. The less developed countries are, ironically, those least responsible for causing global warming. Many health outcomes and diseases are sensitive to climate, including: heat-related mortality or morbidity; air pollution-related illnesses; infectious diseases, particularly those transmitted, indirectly, via water or by insect or rodent vectors; and refugee health issues linked to forced population migration. Yet, changing landscapes can significantly affect local weather more acutely than long-term climate change. Land-cover change can influence micro-climatic conditions, including temperature, evapo-transpiration and surface run-off, that are key determinants in the emergence of many infectious diseases. To improve risk assessment and risk management of these synergistic processes (climate and land-use change), more collaborative efforts in research, training and policy-decision support, across the fields of health, environment, sociology and economics, are required.

Land use has generally been considered a local environmental issue, but it is becoming a force of global importance. Worldwide changes to forests, farmlands, waterways, and air are being driven by the need to provide food, fiber, water, and shelter to more than six billion people. Global croplands, pastures, plantations, and urban areas have expanded in recent decades, accompanied by large increases in energy, water, and fertilizer consumption, along with considerable losses of biodiversity. Such changes in land use have enabled humans to appropriate an increasing share of the planet's resources, but they also potentially undermine the capacity of ecosystems to sustain food production, maintain freshwater and forest resources, regulate climate and air quality, and ameliorate infectious diseases. We face the challenge of managing trade-offs between immediate human needs and maintaining the capacity of the biosphere to provide goods and services in the long term.