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Climate change will cause Sub-Saharan tropical countries to experience a disproportionate increase in the number of extremely hot days when compared to Western countries with more temperate climates. We use the High Occupational Temperature Health and Productivity Suppression (HOTHAPS) model to estimate the potential impact of rising temperatures on worker productivity in different climate regions within Ethiopia, Uganda, Rwanda, and Kenya under varying future climate change scenarios. Using population data obtained from the International Labor Organization, we also estimate productivity losses at a country-wide level. We project large inter-country and intra-country disparities in productivity losses due to varying climatic conditions and local geography. Populations living in lower elevations or in more tropical and arid zones will experience higher productivity losses than those at higher elevations with more temperate climates. We estimate that some areas could lose over 12% productivity by 2099. Comparing climate change impacts across cities, Mombasa, Kenya, is projected to suffer most, losing 13% of its labor productivity. Cities above 1500 m in elevation showed almost no productivity loss by the end of the century. Increased heat stress projected from climate change will pose added risk to workers and labor production in lower elevation settings across East Africa. Key words: Climate change, occupational health, Sub-Saharan Africa, health impacts, heat stress, WBGT.

Clean energy policy can provide substantial health benefits through improved air quality. As ambitious clean energy proposals are increasingly considered and adopted across the United States (US), quantifying the benefits of removal of such large air pollution emissions sources is crucial to understanding potential societal impacts of such policy. In this study, we estimate health benefits resulting from the elimination of emissions of fine particulate matter (PM2.5), sulfur dioxide, and nitrogen oxides from the electric power, transportation, building, and industrial sectors in the contiguous US. We use EPA's CO-Benefits Risk Assessment screening tool to estimate health benefits resulting from the removal of PM2.5-related emissions from these energy-related sectors. We find that nationwide efforts to eliminate energy-related emissions could prevent 53,200 (95% CI: 46,900–59,400) premature deaths each year and provide $608 billion ($537–$678 billion) in benefits from avoided PM2.5-related illness and death. We also find that an average of 69% (range: 32%–95%) of the health benefits from emissions removal remain in the emitting region. Our study provides an indication of the potential scale and distribution of public health benefits that could result from ambitious regional and nationwide clean energy and climate mitigation policy.

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.

It is relatively well accepted that climate change can affect human pathogenic diseases; however, the full extent of this risk remains poorly quantified. Here we carried out a systematic search for empirical examples about the impacts of ten climatic hazards sensitive to greenhouse gas (GHG) emissions on each known human pathogenic disease. We found that 58% (that is, 218 out of 375) of infectious diseases confronted by humanity worldwide have been at some point aggravated by climatic hazards; 16% were at times diminished. Empirical cases revealed 1,006 unique pathways in which climatic hazards, via different transmission types, led to pathogenic diseases. The human pathogenic diseases and transmission pathways aggravated by climatic hazards are too numerous for comprehensive societal adaptations, highlighting the urgent need to work at the source of the problem: reducing GHG emissions.

The climate crisis threatens to exacerbate numerous climate-sensitive health risks, including heatwave mortality, malnutrition from reduced crop yields, water- and vector-borne infectious diseases, and respiratory illness from smog, ozone, allergenic pollen, and wildfires. Recent reports from the Intergovernmental Panel on Climate Change stress the urgent need for action to mitigate climate change, underscoring the need for more scientific assessment of the benefits of climate action for health and wellbeing. Project Drawdown has analyzed more than 80 solutions to address climate change, building on existing technologies and practices, that could be scaled to collectively limit warming to between 1.5° and 2 °C above preindustrial levels. The solutions span nine major sectors and are aggregated into three groups: reducing the sources of emissions, maintaining and enhancing carbon sinks, and addressing social inequities. Here we present an overview of how climate solutions in these three areas can benefit human health through improved air quality, increased physical activity, healthier diets, reduced risk of infectious disease, and improved sexual and reproductive health, and universal education. We find that the health benefits of a low-carbon society are more substantial and more numerous than previously realized and should be central to policies addressing climate change. Much of the existing literature focuses on health effects in high-income countries, however, and more research is needed on health and equity implications of climate solutions, especially in the Global South. We conclude that adding the myriad health benefits across multiple climate change solutions can likely add impetus to move climate policies faster and further.

The development of infrastructure, a rapidly increasing population, and urbanization has resulted in increasing air pollution levels in the African city of Addis Ababa. Prior investigations into air pollution have not yet sufficiently addressed the sources of atmospheric particulate matter. This study aims to identify the major sources of fine particulate matter (PM2.5) and its seasonal contribution in Addis Ababa, Ethiopia. Twenty-four-hour average PM2.5 mass samples were collected every 6th day, from November 2015 through November 2016. Chemical species were measured in samples and source apportionment was conducted using a chemical mass balance (CMB) receptor model that uses particle-phase organic tracer concentrations to estimate source contributions to PM2.5 organic carbon (OC) and the overall PM2.5 mass. Vehicular sources (28%), biomass burning (18.3%), plus soil dust (17.4%) comprise about two-thirds of the PM2.5 mass, followed by sulfate (6.5%). The sources of air pollution vary seasonally, particularly during the main wet season (June–September) and short rain season (February–April): From motor vehicles, (31.0 ± 2.6%) vs. (24.7 ± 1.2%), biomass burning, (21.5 ± 5%) vs. (14 ± 2%), and soil dust, (11 ± 6.4%) vs. (22.7 ± 8.4%), respectively, are amongst the three principal sources of ambient PM2.5 mass in the city. We suggest policy measures focusing on transportation, cleaner fuel or energy, waste management, and increasing awareness on the impact of air pollution on the public’s health.

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.

People around the world are increasingly facing the pressing challenges of today's interconnected environmental, social, and health crises. The COVID-19 pandemic has been an important wake-up call reminding us that we need a healthy planet to ensure the health of all people. The emerging field of planetary health is a framework for understanding these interconnections and identifying solutions to the complex challenges confronting our civilization. Building on the unique role and responsibility of education institutions in shaping our futures, embedding planetary health education in curricula is an essential step to achieving the transformative change needed. Planetary health education across all levels and disciplines will equip and enable learners to drive transdisciplinary and mutually reinforcing actions to protect and restore planetary health and achieve the Sustainable Development Goals.

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.

Edible insects offer environmental and nutritional benefits, as they are characteristically nutrient-dense, are efficient biotransformers of organic material, and emit fewer greenhouse gasses than traditional livestock. Cultivating Tenebrio molitor (yellow mealworm) as ‘minilivestock’ is one possible means of increasing access to insect protein for food insecure populations. Tenebrio molitor growth and nutrient content varies with diet and rearing conditions, but little is known about the precise impact of poor quality feedstocks, such as maize crop residue (stover). Stover is widely available across sub-Saharan Africa where maize is a common dietary staple. Early instar larvae were reared under controlled conditions on three feed substrates: a standard control; a mixed soy, maize grain, and stover diet; and a 100% stover diet. Larvae reared for 32 d were analyzed for total amino acid profile, crude protein, and iron content. Larvae fed the three diets contained all essential amino acids for human nutrition and compared favorably to other traditional protein sources. The mixed diet contained 40% stover by weight and yielded amino acid values similar to the control diet, suggesting that some grain feedstock could be replaced with stover without hampering nutrient content. A second experiment demonstrated that T. molitor were able to complete metamorphosis and survive on a 100% stover diet for multiple generations. These results suggest that stover could be a suitable dietary component for T. molitor, which could facilitate the development of low-cost insect farming systems in low-resource settings that stand to benefit from increased access nutrient-dense edible insects.

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 ongoing emission of greenhouse gases (GHGs) is triggering changes in many climate hazards that can impact humanity. We found traceable evidence for 467 pathways by which human health, water, food, economy, infrastructure and security have been recently impacted by climate hazards such as warming, heatwaves, precipitation, drought, floods, fires, storms, sea-level rise and changes in natural land cover and ocean chemistry. By 2100, the world’s population will be exposed concurrently to the equivalent of the largest magnitude in one of these hazards if emmisions are aggressively reduced, or three if they are not, with some tropical coastal areas facing up to six simultaneous hazards. These findings highlight the fact that GHG emissions pose a broad threat to humanity by intensifying multiple hazards to which humanity is vulnerable.

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.

Climatologists now state with a high degree of certainty that global climate change is real, is advancing more rapidly than expected, and is caused by human activities, especially through fossil fuel combustion and deforestation. Environmental public health researchers, in assessing future projections for Earth’s climate, have concluded that, on balance, adverse health outcomes will predominate under these changed conditions. The number of pathways through which climate change can affect the health of populations makes this environmental hazard one of the most perilous and intricate challenges that we face in this century. By contrast, the potential health co-benefits from departing from our current fossil fuel-based economy may offer some of the most beneficial health opportunities in over a century.

Background/Aim: The infrastructure developments, a growing population, and urbanization have led to growing air pollution challenges in Addis Ababa City. Previous investigations into the air pollut...

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

West Nile virus (WNV) is the most important and widespread mosquito-borne virus in the United States (U.S.). WNV has the ability to spread rapidly and effectively, infecting more than 320 bird and mammalian species. An examination of environmental conditions and the health of keystone species may help predict the susceptibility of various habitats to WNV and reveal key risk factors, annual trends, and vulnerable regions. Since 2002, WNV outbreaks in Wisconsin varied by species, place, and time, significantly affected by unique climatic, environmental, and geographical factors. During a 15 year period, WNV was detected in 71 of 72 counties, resulting in 239 human and 1397 wildlife cases. Controlling for population and sampling efforts in Wisconsin, rates of WNV are highest in the western and northwestern rural regions of the state. WNV incidence rates were highest in counties with low human population densities, predominantly wetland, and at elevations greater than 1000 feet. Resources for surveillance, prevention, and detection of WNV were lowest in rural counties, likely resulting in underestimation of cases. Overall, increasing mean temperature and decreasing precipitation showed positive influence on WNV transmission in Wisconsin. This study incorporates the first statewide assessment of WNV in Wisconsin.

Climate change will increase extreme heat related health risks. To quantify the health impacts of mid-century climate change, we assess heat-related excess mortality across the eastern United States. Health risks are estimated using the US Environmental Protection Agency’s Environmental Benefits Mapping and Analysis Program (BenMAP). Mid-century temperature estimates, downscaled using the Weather Research and Forecasting model, are compared to 2007 temperatures at 36 km and 12 km resolutions. Models indicate the average apparent and actual summer temperatures rise by 4.5° and 3.3 °C, respectively. Warmer average apparent temperatures could cause 11,562 additional annual deaths (95% Confidence Interval, CI: 2,641–20,095) due to cardiovascular stress in the population aged 65 years and above, while higher minimum temperatures could cause 8,767 (95% CI: 5,030–12,475) additional deaths each year. Modeled future climate data available at both coarse (36 km) and fine (12 km) resolutions predict significant human health impacts from warmer climates. The findings suggest that currently available information on future climates is sufficient to guide regional planning for the protection of public health. Higher resolution climate and demographic data are still needed to inform more targeted interventions.

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.

Previous studies in Addis Ababa, Ethiopia, focused on PM characteristics and sources, but PM's biological activity in this area has not been adequately investigated. In this study, cellular and acellular ROS activities were measured to assess PM toxicity. PM2.5 samples in Addis Ababa were collected from November 2015 to November 2016 and their chemical composition was analyzed (organic and elemental carbon (OC/EC), ions, elements, and organic molecular markers). PM-induced ROS activity was measured in vitro in alveolar macrophage cells and using the acellular DTT assay. PM2.5 in Addis Ababa primarily consisted of primary pollutants (e.g., EC, water-insoluble OC). Annual average cellular ROS activities (±SD) were 46.5 ± 15.5 μg Zymosan/m3 and 995 ± 403 μg Zymosan/mg PM (normalized to air volume and PM2.5 mass, respectively), with no clear seasonal variations. The annual average DTT consumption rates (±SD) were 2.35 ± 0.83 nmol/min/m3 and 51.9 ± 17.6 nmol/min/mg PM, respectively, and were also similar throughout the year. Only the monthly air volume-based ROS activity had a similar trend to monthly mass concentration. Compared to other major cities worldwide, Addis Ababa PM2.5 had much lower ROS activity with no strong seasonal trends, paralleling the lack of seasonal changes in PM composition and sources. Poor correlations were observed between ROS activity and all components except mobile source tracers. This difference might be due to lower secondary aerosol content in PM2.5 in Addis Ababa than in other cities.

Real-time monitoring of fine particulate matter (PM(2.5)) concentrations and assessing the health impact are limited in Ethiopia. The objective of this study is to describe current levels of PM(2.5) air pollution in Addis Ababa and examine temporal patterns and to consider the health impact of current PM(2.5) exposure levels. METHODS: PM(2.5) concentrations were measured using a centrally-located Beta Attenuator Monitor (BAM-1022) for 3 years (1 April 2017 to 31 March 2020), with data downloaded biweekly. Deaths attributable to current PM(2.5) concentration levels were estimated using the AirQ+ tool. The daily average was estimated using hourly data. RESULTS: The daily mean (SD) PM(2.5) concentration was 42.4 µg/m(3) (15.98). Two daily extremes were observed: morning (high) and afternoon (low). Sundays had the lowest PM(2.5) concentration, while Mondays to Thursdays saw a continuous increase; Fridays showed the highest concentration. Seasons showed marked variation, with the highest values during the wet season. Concentration spikes reflected periods of intensive fuel combustion. A total of 502 deaths (4.44%) were attributable to current air pollution levels referenced to the 35 µg/m(3) WHO interim target annual level and 2,043 (17.7%) at the WHO 10 µg/m(3) annual guideline. CONCLUSION: PM(2.5) daily levels were 1.7 times higher than the WHO-recommended 24-hour guideline. The current annual mean PM(2.5) concentration results in a substantial burden of attributable deaths compared to an annual mean of 10 µg/m(3). The high PM(2.5) level and its variability across days and seasons calls for citywide interventions to promote clean air.

Most global dietary forecasts predict a reduction in nutritional deficiencies over the next several decades driven by significant increases in environmentally unsustainable livestock and animal source food consumption. Here, we explore a more environmentally sensitive alternative to improve global nutrition, consuming insects. Our study focuses on Africa and Asia, two continents with a history of eating insects and high rates of nutritional deficiency. We model the impact of adding modest amounts (2.5, 5 and 10 g per day, dry weight) of regionally appropriate and farmable species on total nutrient intake and population-wide risk of deficiency for specific nutrients of concern: protein, zinc, folate, and vitamin B12. We also estimate the total potential change in dietary iron. Five grams per day of insect consumption could alleviate a considerable amount of risk of nutritional deficiency: 67 million (95% uncertainty interval: 49–84 million) fewer people at risk of protein deficiency, 166 million (120–220 million) fewer people at risk of zinc deficiency, 237 million (120–439 million) fewer people at risk of folate deficiency, and 251 million (28–2271) fewer people at risk for vitamin B12 deficiency. For iron, per capita supplies could increase by 3% (0.8%–6.0%) with insects, and even more so for vulnerable groups in countries currently suffering severe rates of anemia: 4.2% (0.5%–8.8%) for women of childbearing age and 4.1% (0.4%–10.0%) for children under 5. Doubling or halving insect intake per capita causes the benefits for nutritional deficiency risk to roughly double or halve accordingly. Effects are most pronounced in South and Central Asia, though sub-Saharan Africa, East Asia, and Southeast Asia also see considerable reduction in nutritional risk. These results demonstrate the potential for insects to fill a crucial role in providing nutrition for these populous and rapidly developing regions while safeguarding the global environment.

Climate change is causing increases in temperature, changes in precipitation and extreme weather events, sea-level rise, and other environmental impacts. It is also causing or contributing to heat-related disorders, respiratory and allergic disorders, infectious diseases, malnutrition due to food insecurity, and mental health disorders. In addition, increasing evidence indicates that climate change is causally associated with collective violence, generally in combination with other causal factors. Increased temperatures and extremes of precipitation with their associated consequences, including resultant scarcity of cropland and other key environmental resources, are major pathways by which climate change leads to collective violence. Public health professionals can help prevent collective violence due to climate change (a) by supporting mitigation measures to reduce greenhouse gas emissions, (b) by promoting adaptation measures to address the consequences of climate change and to improve community resilience, and (c) by addressing underlying risk factors for collective violence, such as poverty and socioeconomic disparities.

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.

We examine how climate and irrigation conditions are associated with malaria infection from 1986 to 1995 in two climatically dissimilar regions in India. We analyze annually averaged malaria parasite incidence (API) and seasonally averaged climate and irrigation variables in western Rajasthan and Arunachal Pradesh. In arid western Rajasthan, API is significantly positively correlated with summer precipitation and soil moisture, and negatively correlated with summer potential evapotranspiration. Irrigation variables during boreal spring show a significant positive correlation with API in the moisture-limited region. In humid Arunachal Pradesh, API is positively related to summer temperature, but negatively related to summer precipitation and spring irrigation variables, while no statistically significant correlations are observed. During the years of high sea surface temperatures (SSTs) in the tropical western Pacific, increasing precipitation (accompanied by decreasing temperature) in northwestern India appears to promote malaria infection in arid western Rajasthan. However, during the same years, decreasing precipitation and increasing temperature result in increasing malaria incidence in humid Arunachal Pradesh. The statistically significant relationships of climate and irrigation factors with API in western Rajasthan suggest that increasing spring irrigation activity and wetter summer climates related to warmer SST in tropical western Pacific could increase malaria risk in the arid climate region.

Ambient air pollution is a growing public health concern in major African cities, including Addis Ababa (Ethiopia), where little information is available on fine particulate matter (PM2.5, with aerodynamic diameter &lt, 2.5 &micro, m) pollution. This paper aims to characterize annual PM2.5, including bulk composition and seasonal patterns, in Addis Ababa. We collected 24-h PM2.5 samples in the central city every 6 days from November 2015 to November 2016. The mean (&plusmn, SD) daily PM2.5 concentration was 53.8 (&plusmn, 25.0) &micro, g/m3, with 90% of sampled days exceeding the World Health Organization&rsquo, s guidelines. Principal components were organic matter (OM, 44.5%), elemental carbon (EC, 25.4%), soil dust (13.5%), and SNA (sulfate, nitrate, and ammonium ions, 8.2%). Higher PM2.5 concentrations were observed during the heavy rain season, while crustal dust concentrations ranged from 2.9 to 37.6%, with higher levels during dry months. Meteorological variables, vehicle emissions, biomass fuels, unpaved roads, and construction activity contribute to poor air quality. Compared to the Air Quality Index (AQI), 31% and 36% of observed days were unhealthy for everyone and unhealthy for sensitive groups, respectively. We recommend adopting effective prevention strategies and pursuing research on vehicle emissions, biomass burning, and dust control to curb air pollution in the city.