A human disease indicator for the effects of recent global climate change

Spatially-optimized urban greening for reduction of population exposure to land surface temperature extremes

The population experiencing high temperatures in cities is rising due to anthropogenic climate change, settlement expansion, and population growth. Yet, efficient tools to evaluate potential intervention strategies to reduce population exposure to Land Surface Temperature (LST) extremes are still lacking. Here, we implement a spatial regression model based on remote sensing data that is able to assess the population exposure to LST extremes in urban environments across 200 cities based on surface properties like vegetation cover and distance to water bodies. We define exposure as the number of days per year where LST exceeds a given threshold multiplied by the total urban population exposed, in person ⋅ day. Our findings reveal that urban vegetation plays a considerable role in decreasing the exposure of the urban population to LST extremes. We show that targeting high-exposure areas reduces vegetation needed for the same decrease in exposure compared to uniform treatment.

Dairy Cattle Density and Temporal Patterns of Human Campylobacteriosis and Cryptosporidiosis in New Zealand

Public health risks associated with the intensification of dairy farming are an emerging concern. Dairy cattle are a reservoir for a number of pathogens that can cause human illness. This study examined the spatial distribution of dairy cattle density and explored temporal patterns of human campylobacteriosis and cryptosporidiosis notifications in New Zealand from 1997 to 2015. Maps of dairy cattle density were produced, and temporal patterns of disease rates were assessed for urban versus rural areas and for areas with different dairy cattle densities using descriptive temporal analyses. Campylobacteriosis and cryptosporidiosis rates displayed strong seasonal patterns, with highest rates in spring in rural areas and, for campylobacteriosis, summer in urban areas. Increases in rural cases often preceded increases in urban cases. Furthermore, disease rates in areas with higher dairy cattle densities tended to peak before areas with low densities or no dairy cattle. Infected dairy calves may be a direct or indirect source of campylobacteriosis or cryptosporidiosis infection in humans through environmental or occupational exposure routes, including contact with animals or feces, recreational contact with contaminated waterways, and consumption of untreated drinking water. These results have public health implications for populations living, working, or recreating in proximity to dairy farms.

Spatiotemporal variation of the association between climate dynamics and HFRS outbreaks in Eastern China during 2005-2016 and its geographic determinants

Background

Hemorrhagic fever with renal syndrome (HFRS) is a rodent-associated zoonosis caused by hantavirus. The HFRS was initially detected in northeast China in 1931, and since 1955 it has been detected in many regions of the country. Global climate dynamics influences HFRS spread in a complex nonlinear way. The quantitative assessment of the spatiotemporal variation of the “HFRS infections-global climate dynamics” association at a large geographical scale and during a long time period is still lacking.

Methods and findings

This work is the first study of a recently completed dataset of monthly HFRS cases in Eastern China during the period 2005–2016. A methodological synthesis that involves a time-frequency technique, a composite space-time model, hotspot analysis, and machine learning is implemented in the study of (a) the association between HFRS incidence spread and climate dynamics and (b) the geographic factors impacting this association over Eastern China during the period 2005–2016. The results showed that by assimilating core and city-specific knowledge bases the synthesis was able to depict quantitatively the space-time variation of periodic climate-HFRS associations at a large geographic scale and to assess numerically the strength of this association in the area and period of interest. It was found that the HFRS infections in Eastern China has a strong association with global climate dynamics, in particular, the 12, 18 and 36 mos periods were detected as the three main synchronous periods of climate dynamics and HFRS distribution. For the 36 mos period (which is the period with the strongest association), the space-time correlation pattern of the association strength indicated strong temporal but rather weak spatial dependencies. The generated space-time maps of association strength and association hotspots provided a clear picture of the geographic variation of the association strength that often-exhibited cluster characteristics (e.g., the south part of the study area displays a strong climate-HFRS association with non-point effects, whereas the middle-north part displays a weak climate-HFRS association). Another finding of this work is the upward climate-HFRS coherency trend for the past few years (2013–2015) indicating that the climate impacts on HFRS were becoming increasingly sensitive with time. Lastly, another finding of this work is that geographic factors affect the climate-HFRS association in an interrelated manner through local climate or by means of HFRS infections. In particular, location (latitude, distance to coastline and longitude), grassland and woodland are the geographic factors exerting the most noticeable effects on the climate-HFRS association (e.g., low latitude has a strong effect, whereas distance to coastline has a wave-like effect).

Conclusions

The proposed synthetic quantitative approach revealed important aspects of the spatiotemporal variation of the climate-HFRS association in Eastern China during a long time period, and identified the geographic factors having a major impact on this association. Both findings could improve public health policy in an HFRS-torn country like China. Furthermore, the synthetic approach developed in this work can be used to map the space-time variation of different climate-disease associations in other parts of China and the World.

China has the largest number of HFRS infections in the world (9045 cases in 2016). Previous studies have found that HFRS infections are related to climate. However, the spatiotemporal distribution of the association between HFRS outbreaks at a large scale and global climate dynamics (i.e., over Eastern China during the period 2005–2016), as well as the identification of the geographic factors impacting this association have not been studied yet. This is then the dual focus of the present study. Strong synchronicities between global climate change and HFRS infections were detected across the entire study area that were linked to three main time periods (12, 18 and 36 mos). Specifically, strong and weak associations with non-point effects were detected in the south and middle-north parts of the study region, respectively. The climate impacts on HFRS were becoming increasingly sensitive with time. On the other hand, the geographic location (north coordinate, distance to coastline, east coordinate) makes a considerable contribution to the climate-HFRS association. As regards land-use, grassland and woodland were found to play important contributing roles to climate-HFRS association. Certain space-time links between global climate dynamics and HFRS infections were confirmed at a large spatial scale and within a long time period. The above findings could improve both the understanding of the HFRS transmission pattern and the forecasting of HFRS outbreaks.

Intestinal parasites in public transport buses from the city of Diamantina, Minas Gerais, Brazil

Background

Intestinal parasites’ eggs, larvae, or cysts can be carried in public transport buses, and contribute to the increased incidence of diseases. This study aimed to detect biological forms of intestinal parasites in samples from public buses in the town of Diamantina, Minas Gerais, in order to know the local situation and propose interventions to improve public health.

Materials and methods

In November 2014, six samples were obtained in buses of the two stations by using Graham method, in duplicate, by affixing a 6×5 cm clear tape, six times on each collection site of the bus, in an area of ~30 cm². Then, each tape was positioned longitudinally on a slide microscope, and the identification of the biological forms of the parasites was performed with the aid of a 40× objective optical microscope.

Results

A total of 216 slides were analyzed, of which 86 (39.8%) were positive for at least one intestinal parasite. Cysts of Entamoeba coli were the most frequently found in this study (52.1%), followed by Endolimax nana cysts (30.7%), Iodamoeba butschlii (6.5%), helminth larvae (4.7%), Giardia lamblia cysts (3.6%), Hymenolepis nana eggs (1.2%), Enterobius vermicularis eggs (0.6%), and Entamoeba histolytica cysts (0.6%). Top right handrails and right stanchions had the highest occurrence of biological forms, with 18.3% and 14.8%, respectively.

Conclusion

The results indicated the need for better cleaning of the buses and better personal hygiene by users, since pathogenic and non-pathogenic intestinal parasites were found, suggesting fecal contamination of these sites, representing a risk to public health.

Hydrological Regime and Water Shortage as Drivers of the Seasonal Incidence of Diarrheal Diseases in a Tropical Montane Environment

BACKGROUND

The global burden of diarrhea is a leading cause of morbidity and mortality worldwide. In montane areas of South-East Asia such as northern Laos, recent changes in land use have induced increased runoff, soil erosion and in-stream suspended sediment loads, and potential pathogen dissemination. To our knowledge, few studies have related diarrhea incidences to catchment scale hydrological factors such as river discharge, and loads of suspended sediment and of Fecal Indicator Bacteria (FIB) such as Escherichia coli, together with sociological factors such as hygiene practices. We hypothesized that climate factors combined with human behavior control diarrhea incidence, either because higher rainfall, leading to higher stream discharges, suspended sediment loads and FIB counts, are associated with higher numbers of reported diarrhea cases during the rainy season, or because water shortage leads to the use of less safe water sources during the dry season. Using E. coli as a FIB, the objectives of this study were thus (1) to characterize the epidemiological dynamics of diarrhea in Northern Laos, and (2) to identify which hydro-meteorological and sociological risk factors were associated with diarrhea epidemics.

METHODS

Considering two unconnected river catchments of 22 and 7,448 km2, respectively, we conducted a retrospective time series analysis of meteorological variables (rainfall, air temperature), hydrological variables (discharge, suspended sediments, FIB counts, water temperature), and the number of diarrheal disease cases reported at 6 health centers located in the 5 southern districts of the Luang Prabang Province, Lao PDR. We also examined the socio-demographic factors potentially affecting vulnerability to the effect of the climate factors, such as drinking water sources, hygiene habits, and recreational water exposure.

RESULTS

Using thus a mixed methods approach, we found E. coli to be present all year long (100-1,000 Most Probable Number or MPN 100 mL-1) indicating that fecal contamination is ubiquitous and constant. We found that populations switch their water supply from wells to surface water during drought periods, the latter of which appear to be at higher risk of bacterial contamination than municipal water fountains. We thus found that water shortage in the Luang Prabang area triggers diarrhea peaks during the dry and hot season and that rainfall and aquifer refill ends the epidemic during the wet season. The temporal trends of reported daily diarrhea cases were generally bimodal with hospital admissions peaking in February-March and later in May-July. Annual incidence rates were higher in more densely populated areas and mostly concerned the 0-4 age group and male patients.

CONCLUSIONS

We found that anthropogenic drivers, such as hygiene practices, were at least as important as environmental drivers in determining the seasonal pattern of a diarrhea epidemic. For diarrheal disease risk monitoring, discharge or groundwater level can be considered as relevant proxies. These variables should be monitored in the framework of an early warning system provided that a tradeoff is found between the size of the monitored catchment and the frequency of the measurement.

Climate Change and Health: Transcending Silos to Find Solutions

BACKGROUND

Climate change has myriad implications for the health of humans, our ecosystems, and the ecological processes that sustain them. Projections of rising greenhouse gas emissions suggest increasing direct and indirect burden of infectious and noninfectious disease, effects on food and water security, and other societal disruptions. As the effects of climate change cannot be isolated from social and ecological determinants of disease that will mitigate or exacerbate forecasted health outcomes, multidisciplinary collaboration is critically needed.

OBJECTIVES

The aim of this article was to review the links between climate change and its upstream drivers (ie, processes leading to greenhouse gas emissions) and health outcomes, and identify existing opportunities to leverage more integrated global health and climate actions to prevent, prepare for, and respond to anthropogenic pressures.

METHODS

We conducted a literature review of current and projected health outcomes associated with climate change, drawing on findings and our collective expertise to review opportunities for adaptation and mitigation across disciplines.

FINDINGS

Health outcomes related to climate change affect a wide range of stakeholders, providing ready collaborative opportunities for interventions, which can be differentiated by addressing the upstream drivers leading to climate change or the downstream effects of climate change itself.

CONCLUSIONS

Although health professionals are challenged with risks from climate change and its drivers, the adverse health outcomes cannot be resolved by the public health community alone. A phase change in global health is needed to move from a passive responder in partnership with other societal sectors to drive innovative alternatives. It is essential for global health to step outside of its traditional boundaries to engage with other stakeholders to develop policy and practical solutions to mitigate disease burden of climate change and its drivers; this will also yield compound benefits that help address other health, environmental, and societal challenges.

Climate variability, weather and enteric disease incidence in New Zealand: time series analysis

BACKGROUND

Evaluating the influence of climate variability on enteric disease incidence may improve our ability to predict how climate change may affect these diseases.

OBJECTIVES

To examine the associations between regional climate variability and enteric disease incidence in New Zealand.

METHODS

Associations between monthly climate and enteric diseases (campylobacteriosis, salmonellosis, cryptosporidiosis, giardiasis) were investigated using Seasonal Auto Regressive Integrated Moving Average (SARIMA) models.

RESULTS

No climatic factors were significantly associated with campylobacteriosis and giardiasis, with similar predictive power for univariate and multivariate models. Cryptosporidiosis was positively associated with average temperature of the previous month (β =  0.130, SE =  0.060, p <0.01) and inversely related to the Southern Oscillation Index (SOI) two months previously (β =  -0.008, SE =  0.004, p <0.05). By contrast, salmonellosis was positively associated with temperature (β  = 0.110, SE = 0.020, p<0.001) of the current month and SOI of the current (β  = 0.005, SE = 0.002, p<0.050) and previous month (β  = 0.005, SE = 0.002, p<0.05). Forecasting accuracy of the multivariate models for cryptosporidiosis and salmonellosis were significantly higher.

CONCLUSIONS

Although spatial heterogeneity in the observed patterns could not be assessed, these results suggest that temporally lagged relationships between climate variables and national communicable disease incidence data can contribute to disease prediction models and early warning systems.

Intervention-based stochastic disease eradication

Disease control is of paramount importance in public health, with infectious disease extinction as the ultimate goal. Although diseases may go extinct due to random loss of effective contacts where the infection is transmitted to new susceptible individuals, the time to extinction in the absence of control may be prohibitively long. Intervention controls are typically defined on a deterministic schedule. In reality, however, such policies are administered as a random process, while still possessing a mean period. Here, we consider the effect of randomly distributed intervention as disease control on large finite populations. We show explicitly how intervention control, based on mean period and treatment fraction, modulates the average extinction times as a function of population size and rate of infection spread. In particular, our results show an exponential improvement in extinction times even though the controls are implemented using a random Poisson distribution. Finally, we discover those parameter regimes where random treatment yields an exponential improvement in extinction times over the application of strictly periodic intervention. The implication of our results is discussed in light of the availability of limited resources for control.

Assessing seasonal variations and age patterns in mortality during the first year of life in Tanzania

Lack of birth and death registries in most of developing countries, particularly those in sub-Saharan Africa led to the establishment of Demographic Surveillance Systems (DSS) sites which monitor large population cohorts within defined geographical areas. DSS collects longitudinal data on migration, births, deaths and their causes via verbal autopsies. DSS data provide an opportunity to monitor many health indicators including mortality trends. Mortality rates in Sub-Sahara Africa show seasonal patterns due to high infant and child malaria-related mortality which is influenced by seasonal features present in environmental and climatic factors. However, it is unclear whether seasonal patterns differ by age in the first few months of life. This study provides an overview of approaches to assess, capture and detect seasonality peaks and patterns in mortality using the infant mortality data from the Rufiji DSS, Tanzania. Seasonality was best captured using Bayesian negative binomial models with time and cycle dependent seasonal parameters and autoregressive temporal error terms. Seasonal patterns are similar among different age groups during infancy and timing of their mortality peaks do not differ. Seasonality in mortality rates with two peaks per year is pronounced which corresponds to rainy seasons. Understanding of these trends is important for public health preparedness.

Cholera outbreak in Senegal in 2005: was climate a factor?

Cholera is an acute diarrheal illness caused by Vibrio cholerae and occurs as widespread epidemics in Africa. In 2005, there were 31,719 cholera cases, with 458 deaths in the Republic of Senegal. We retrospectively investigated the climate origin of the devastating floods in mid-August 2005, in the Dakar Region of Senegal and the subsequent outbreak of cholera along with the pattern of cholera outbreaks in three other regions of that country. We compared rainfall patterns between 2002 and 2005 and the relationship between the sea surface temperature (SST) gradient in the tropical Atlantic Ocean and precipitation over Senegal for 2005. Results showed a specific pattern of rainfall throughout the Dakar region during August, 2005, and the associated rainfall anomaly coincided with an exacerbation of the cholera epidemic. Comparison of rainfall and epidemiological patterns revealed that the temporal dynamics of precipitation, which was abrupt and heavy, was presumably the determining factor. Analysis of the SST gradient showed that the Atlantic Ocean SST variability in 2005 differed from that of 2002 to 2004, a result of a prominent Atlantic meridional mode. The influence of this intense precipitation on cholera transmission over a densely populated and crowded region was detectable for both Dakar and Thiès, Senegal. Thus, high resolution rainfall forecasts at subseasonal time scales should provide a way forward for an early warning system in Africa for cholera and, thereby, trigger epidemic preparedness. Clearly, attention must be paid to both natural and human induced environmental factors to devise appropriate action to prevent cholera and other waterborne disease epidemics in the region.

A interface da saúde pública com a saúde dos oceanos: produção de doenças, impactos socioeconômicos e relações benéficas

Nas últimas décadas, as atividades humanas têm causado forte impacto sobre o ambiente marinho, provocando alterações no seu processo ecológico. A relação entre a saúde dos oceanos, as atividades antropogênicas e a saúde pública já é consenso, entretanto, seus mecanismos ainda estão sob os olhares da ciência. Essas relações incluem o foco sobre as mudanças climáticas, florações de algas tóxicas, contaminação microbiológica e química nas águas marinhas e bioinvasão de espécies exóticas. Além disso, existe a relação dos valores benéficos que os oceanos proporcionam à saúde e bem-estar da humanidade, tais como produtos naturais relevantes para a alimentação humana, o desenvolvimento da biomedicina, ou simplesmente, a satisfação humana derivada da recreação, esportes e outras interações dos seres humanos com os oceanos. A importância de se conhecer a relação entre saúde pública e a saúde dos oceanos dá-se, principalmente, devido ao crescente número de pessoas vivendo em zonas costeiras, nas regiões tropicais e subtropicais, tendo como pano de fundo as atividades antropogênicas produtoras de risco para a saúde do ambiente marinho, aumento da vulnerabilidade do homem, da biodiversidade e da iniquidade socioambiental.

Uncertainties associated with quantifying climate change impacts on human health: a case study for diarrhea

BACKGROUND

Climate change is expected to have large impacts on health at low latitudes where droughts and malnutrition, diarrhea, and malaria are projected to increase.

OBJECTIVES

The main objective of this study was to indicate a method to assess a range of plausible health impacts of climate change while handling uncertainties in a unambiguous manner. We illustrate this method by quantifying the impacts of projected regional warming on diarrhea in this century.

METHODS

We combined a range of linear regression coefficients to compute projections of future climate change-induced increases in diarrhea using the results from five empirical studies and a 19-member climate model ensemble for which future greenhouse gas emissions were prescribed. Six geographical regions were analyzed.

RESULTS

The model ensemble projected temperature increases of up to 4°C over land in the tropics and subtropics by the end of this century. The associated mean projected increases of relative risk of diarrhea in the six study regions were 8-11% (with SDs of 3-5%) by 2010-2039 and 22-29% (SDs of 9-12%) by 2070-2099.

CONCLUSIONS

Even our most conservative estimates indicate substantial impacts from climate change on the incidence of diarrhea. Nevertheless, our main conclusion is that large uncertainties are associated with future projections of diarrhea and climate change. We believe that these uncertainties can be attributed primarily to the sparsity of empirical climate-health data. Our results therefore highlight the need for empirical data in the cross section between climate and human health.

Potential influence of climate change on vector-borne and zoonotic diseases: a review and proposed research plan

BACKGROUND

Because of complex interactions of climate variables at the levels of the pathogen, vector, and host, the potential influence of climate change on vector-borne and zoonotic diseases (VBZDs) is poorly understood and difficult to predict. Climate effects on the nonvector-borne zoonotic diseases are especially obscure and have received scant treatment.

OBJECTIVE

We described known and potential effects of climate change on VBZDs and proposed specific studies to increase our understanding of these effects. The nonvector-borne zoonotic diseases have received scant treatment and are emphasized in this paper.

DATA SOURCES AND SYNTHESIS

We used a review of the existing literature and extrapolations from observations of short-term climate variation to suggest potential impacts of climate change on VBZDs. Using public health priorities on climate change, published by the Centers for Disease Control and Prevention, we developed six specific goals for increasing understanding of the interaction between climate and VBZDs and for improving capacity for predicting climate change effects on incidence and distribution of VBZDs.

CONCLUSIONS

Climate change may affect the incidence of VBZDs through its effect on four principal characteristics of host and vector populations that relate to pathogen transmission to humans: geographic distribution, population density, prevalence of infection by zoonotic pathogens, and the pathogen load in individual hosts and vectors. These mechanisms may interact with each other and with other factors such as anthropogenic disturbance to produce varying effects on pathogen transmission within host and vector populations and to humans. Because climate change effects on most VBZDs act through wildlife hosts and vectors, understanding these effects will require multidisciplinary teams to conduct and interpret ecosystem-based studies of VBZD pathogens in host and vector populations and to identify the hosts, vectors, and pathogens with the greatest potential to affect human populations under climate change scenarios.

Enhanced vaccine control of epidemics in adaptive networks

We study vaccine control for disease spread on an adaptive network modeling disease avoidance behavior. Control is implemented by adding Poisson-distributed vaccination of susceptibles. We show that vaccine control is much more effective in adaptive networks than in static networks due to feedback interaction between the adaptive network rewiring and the vaccine application. When compared to extinction rates in static social networks, we find that the amount of vaccine resources required to sustain similar rates of extinction are as much as two orders of magnitude lower in adaptive networks.

Climate and vectorborne diseases

Climate change could significantly affect vectorborne disease in humans. Temperature, precipitation, humidity, and other climatic factors are known to affect the reproduction, development, behavior, and population dynamics of the arthropod vectors of these diseases. Climate also can affect the development of pathogens in vectors, as well as the population dynamics and ranges of the nonhuman vertebrate reservoirs of many vectorborne diseases. Whether climate changes increase or decrease the incidence of vectorborne diseases in humans will depend not only on the actual climatic conditions but also on local nonclimatic epidemiologic and ecologic factors. Predicting the relative impact of sustained climate change on vectorborne diseases is difficult and will require long-term studies that look not only at the effects of climate change but also at the contributions of other agents of global change such as increased trade and travel, demographic shifts, civil unrest, changes in land use, water availability, and other issues. Adapting to the effects of climate change will require the development of adequate response plans, enhancement of surveillance systems, and development of effective and locally appropriate strategies to control and prevent vectorborne diseases.

Influence of temperature and rainfall on the evolution of cholera epidemics in Lusaka, Zambia, 2003-2006: analysis of a time series

In this study, we aimed to describe the evolution of three cholera epidemics that occurred in Lusaka, Zambia, between 2003 and 2006 and to analyse the association between the increase in number of cases and climatic factors. A Poisson autoregressive model controlling for seasonality and trend was built to estimate the association between the increase in the weekly number of cases and weekly means of daily maximum temperature and rainfall. All epidemics showed a seasonal trend coinciding with the rainy season (November to March). A 1 degrees C rise in temperature 6 weeks before the onset of the outbreak explained 5.2% [relative risk (RR) 1.05, 95% CI 1.04-1.06] of the increase in the number of cholera cases (2003-2006). In addition, a 50 mm increase in rainfall 3 weeks before explained an increase of 2.5% (RR 1.02, 95% CI 1.01-1.04). The attributable risks were 4.9% for temperature and 2.4% for rainfall. If 6 weeks prior to the beginning of the rainy season an increase in temperature is observed followed by an increase in rainfall 3 weeks later, both exceeding expected levels, an increase in the number of cases of cholera within the following 3 weeks could be expected. Our explicative model could contribute to developing a warning signal to reduce the impact of a presumed cholera epidemic.

Disease extinction in the presence of random vaccination

We investigate disease extinction in an epidemic model described by a birth-death process. We show that, in the absence of vaccination, the effective entropic barrier for extinction displays scaling with the distance to the bifurcation point, with an unusual critical exponent. Even a comparatively weak Poisson-distributed random vaccination leads to an exponential increase in the extinction rate, with the exponent that strongly depends on the vaccination parameters.

Thermal tolerance in a south-east African population of the tsetse fly Glossina pallidipes (Diptera, Glossinidae): implications for forecasting climate change impacts

For tsetse (Glossina spp.), the vectors of human and animal trypanosomiases, the physiological mechanisms linking variation in population dynamics with changing weather conditions have not been well established. Here, we investigate high- and low-temperature tolerance in terms of activity limits and survival in a natural population of adult Glossina pallidipes from eastern Zambia. Due to increased interest in chilling flies for handling and aerial dispersal in sterile insect technique control and eradication programmes, we also provide further detailed investigation of low-temperature responses. In wild-caught G. pallidipes, the probability of survival for 50% of the population at low-temperatures was at 3.7, 8.9 and 9.6 degrees C (95% CIs: +/-1.5 degrees C) for 1, 2 and 3 h treatments, respectively. At high temperatures, it was estimated that treatments at 37.9, 36.2 and 35.6 degrees C (95% CIs: +/-0.5 degrees C) would yield 50% population survival for 1, 2 and 3 h, respectively. Significant effects of time and temperature were detected at both temperature extremes (GLZ, p<0.05 in all cases) although a time-temperature interaction was only detected at high temperatures (p<0.0001). We synthesized data from four other Kenyan populations and found that upper critical thermal limits showed little variation among populations and laboratory treatments (range: 43.9-45.0 degrees C; 0.25 degrees C/min heating rate), although reduction to more ecologically relevant heating rates (0.06 degrees C/min) reduce these values significantly from approximately 44.4 to 40.6 degrees C, thereby providing a causal explanation for why tsetse distribution may be high-temperature limited. By contrast, low-temperature limits showed substantial variation among populations and acclimation treatments (range: 4.5-13.8 degrees C; 0.25 degrees C/min), indicating high levels of inter-population variability. Ecologically relevant cooling rates (0.06 degrees C/min) suggest tsetses are likely to experience chill coma temperatures under natural conditions (approximately 20-21 degrees C). The results from acute hardening experiments in the Zambian population demonstrate limited ability to improve low-temperature tolerance over short (hourly) timescales after non-lethal pre-treatments. In flies which survived chilling, recovery times were non-linear with plateaus between 2-6 and 8-12 degrees C. Survival times ranged between 4 and 36 h and did not vary between flies which had undergone chill coma by comparison with flies which had not, even after factoring body condition into the analyses (p>0.5 in all cases). However, flies with low chill coma values had the highest body water and fat content, indicating that when energy reserves are depleted, low-temperature tolerance may be compromised. Overall, these results suggest that physiological mechanisms may provide insight into tsetse population dynamics, hence distribution and abundance, and support a general prediction for reduced geographic distribution under future climate warming scenarios.

Thermal stress and coral cover as drivers of coral disease outbreaks

Very little is known about how environmental changes such as increasing temperature affect disease dynamics in the ocean, especially at large spatial scales. We asked whether the frequency of warm temperature anomalies is positively related to the frequency of coral disease across 1,500 km of Australia's Great Barrier Reef. We used a new high-resolution satellite dataset of ocean temperature and 6 y of coral disease and coral cover data from annual surveys of 48 reefs to answer this question. We found a highly significant relationship between the frequencies of warm temperature anomalies and of white syndrome, an emergent disease, or potentially, a group of diseases, of Pacific reef-building corals. The effect of temperature was highly dependent on coral cover because white syndrome outbreaks followed warm years, but only on high (>50%) cover reefs, suggesting an important role of host density as a threshold for outbreaks. Our results indicate that the frequency of temperature anomalies, which is predicted to increase in most tropical oceans, can increase the susceptibility of corals to disease, leading to outbreaks where corals are abundant.

Coral reefs have been decimated over the last several decades. The global decline of reef-building corals is of particular concern. Infectious diseases are thought to be key to this mass coral mortality, and many reef ecologists suspect that anomalously high ocean temperatures contribute to the increased incidence and severity of disease outbreaks. This hypothesis is supported by local observations—for example, that some coral diseases become more prevalent in the summertime—but it has never been tested at large spatial scales or over relatively long periods. We tested the temperature–disease hypothesis by combining 6 years of survey data from reefs across 1,500 kilometers of Australia's Great Barrier Reef with a new ocean temperature database derived from satellite measurements. Our results indicate that major outbreaks of the coral disease white syndrome only occurred on reefs with high coral cover after especially warm years. The disease was usually absent on cooler, low-cover reefs. Our results suggest that climate change could be increasing the severity of disease in the ocean, leading to a decline in the health of marine ecosystems and the loss of the resources and services humans derive from them.

High-resolution satellite data of ocean temperature across the Great Barrier Reef reveal that warm temperature anomalies can drive outbreaks of coral disease under conditions of high coral cover.

Ecology of Increasing Diseases: Population Growth and Environmental Degradation

The World Health Organization (WHO) and other organizations report that the prevalence of human diseases during the past decade is rapidly increasing. Population growth and the pollution of water, air, and soil are contributing to the increasing number of human diseases worldwide. Currently an estimated 40% of world deaths are due to environmental degradation. The ecology of increasing diseases has complex factors of environmental degradation, population growth, and the current malnutrition of about 3.7 billion people in the world.

Effect of meteorological factors on clinical malaria risk among children: an assessment using village-based meteorological stations and community-based parasitological survey

Background

Temperature, rainfall and humidity have been widely associated with the dynamics of malaria vector population and, therefore, with spread of the disease. However, at the local scale, there is a lack of a systematic quantification of the effect of these factors on malaria transmission. Further, most attempts to quantify this effect are based on proxy meteorological data acquired from satellites or interpolated from a different scale. This has led to controversies about the contribution of climate change to malaria transmission risk among others. Our study addresses the original question of relating meteorological factors measured at the local scale with malaria infection, using data collected at the same time and scale.

Methods

676 children (6–59 months) were selected randomly from three ecologically different sites (urban and rural). During weekly home visits between December 1, 2003, and November 30, 2004, fieldworkers tested children with fever for clinical malaria. They also collected data on possible confounders monthly. Digital meteorological stations measured ambient temperature, humidity, and rainfall in each site. Logistic regression was used to estimate the risk of clinical malaria given the previous month's meteorological conditions.

Results

The overall incidence of clinical malaria over the study period was 1.07 episodes per child. Meteorological factors were associated with clinical malaria with mean temperature having the largest effect.

Conclusion

Temperature was the best predictor for clinical malaria among children under five. A systematic measurement of local temperature through ground stations and integration of such data in the routine health information system could support assessment of malaria transmission risk at the district level for well-targeted control efforts.

Climate change cannot explain the upsurge of tick-borne encephalitis in the Baltics

Background

Pathogens transmitted by ticks cause human disease on a greater scale than any other vector-borne infections in Europe, and have increased dramatically over the past 2–3 decades. Reliable records of tick-borne encephalitis (TBE) since 1970 show an especially sharp upsurge in cases in Eastern Europe coincident with the end of Soviet rule, including the three Baltic countries, Estonia, Latvia and Lithuania, where national incidence increased from 1992 to 1993 by 64, 175 and 1,065%, respectively. At the county level within each country, however, the timing and degree of increase showed marked heterogeneity. Climate has also changed over this period, prompting an almost universal assumption of causality. For the first time, we analyse climate and TBE epidemiology at sufficiently fine spatial and temporal resolution to question this assumption.

Methodology/Principal Finding

Detailed analysis of instrumental records of climate has revealed a significant step increase in spring-time daily maximum temperatures in 1989. The seasonal timing and precise level of this warming were indeed such as could promote the transmission of TBE virus between larval and nymphal ticks co-feeding on rodents. These changes in climate, however, are virtually uniform across the Baltic region and cannot therefore explain the marked spatio-temporal heterogeneity in TBE epidemiology.

Conclusions/Significance

Instead, it is proposed that climate is just one of many different types of factors, many arising from the socio-economic transition associated with the end of Soviet rule, that have acted synergistically to increase both the abundance of infected ticks and the exposure of humans to these ticks. Understanding the precise differential contribution of each factor as a cause of the observed epidemiological heterogeneity will help direct control strategies.

Climatic, socio-economic, and health factors affecting human vulnerability to cholera in the Lake Victoria basin, East Africa

Cholera epidemics have a recorded history in the eastern Africa region dating to 1836. Cholera is now endemic in the Lake Victoria basin, a region with one of the poorest and fastest growing populations in the world. Analyses of precipitation, temperatures, and hydrological characteristics of selected stations in the Lake Victoria basin show that cholera epidemics are closely associated with El Niño years. Similarly, sustained temperatures high above normal (T(max)) in two consecutive seasons, followed by a slight cooling in the second season, trigger an outbreak of a cholera epidemic. The health and socioeconomic systems that the lake basin communities rely upon are not robust enough to cope with cholera outbreaks, thus rendering them vulnerable to the impact of climate variability and change. Collectively, this report argues that communities living around the Lake Victoria basin are vulnerable to climate-induced cholera that is aggravated by the low socioeconomic status and lack of an adequate health care system. In assessing the communities' adaptive capacity, the report concludes that persistent levels of poverty have made these communities vulnerable to cholera epidemics.

Is the global rise of asthma an early impact of anthropogenic climate change?

The increase in asthma incidence, prevalence, and morbidity over recent decades presents a significant challenge to public health. Pollen is an important trigger of some types of asthma, and both pollen quantity and season depend on climatic and meteorological variables. Over the same period as the global rise in asthma, there have been considerable increases in atmospheric carbon dioxide concentration and global average surface temperature. We hypothesize anthropogenic climate change as a plausible contributor to the rise in asthma. Greater concentrations of carbon dioxide and higher temperatures may increase pollen quantity and induce longer pollen seasons. Pollen allergenicity can also increase as a result of these changes in climate. Exposure in early life to a more allergenic environment may also provoke the development of other atopic conditions, such as eczema and allergic rhinitis. Although the etiology of asthma is complex, the recent global rise in asthma could be an early health effect of anthropogenic climate change.

Global Warming and Infectious Disease

Global warming has serious implications for all aspects of human life, including infectious diseases. The effect of global warming depends on the complex interaction between the human host population and the causative infectious agent. From the human standpoint, changes in the environment may trigger human migration, causing disease patterns to shift. Crop failures and famine may reduce host resistance to infections. Disease transmission may be enhanced through the scarcity and contamination of potable water sources. Importantly, significant economic and political stresses may damage the existing public health infrastructure, leaving mankind poorly prepared for unexpected epidemics. Global warming will certainly affect the abundance and distribution of disease vectors. Altitudes that are currently too cool to sustain vectors will become more conducive to them. Some vector populations may expand into new geographic areas, whereas others may disappear. Malaria, dengue, plague, and viruses causing encephalitic syndromes are among the many vector-borne diseases likely to be affected. Some models suggest that vector-borne diseases will become more common as the earth warms, although caution is needed in interpreting these predictions. Clearly, global warming will cause changes in the epidemiology of infectious diseases. The ability of mankind to react or adapt is dependent upon the magnitude and speed of the change. The outcome will also depend on our ability to recognize epidemics early, to contain them effectively, to provide appropriate treatment, and to commit resources to prevention and research.

Is the global rise of asthma an early impact of anthropogenic climate change?

The increase in asthma incidence, prevalence, and morbidity over recent decades presents a significant challenge to public health. Pollen is an important trigger of some types of asthma, and both pollen quantity and season depend on climatic and meteorologic variables. Over the same period as the global rise in asthma, there have been considerable increases in atmospheric carbon dioxide concentration and global average surface temperature. We hypothesize anthropogenic climate change as a plausible contributor to the rise in asthma. Greater concentrations of carbon dioxide and higher temperatures may increase pollen quantity and induce longer pollen seasons. Pollen allergenicity can also increase as a result of these changes in climate. Exposure in early life to a more allergenic environment may also provoke the development of other atopic conditions, such as eczema and allergic rhinitis. Although the etiology of asthma is complex, the recent global rise in asthma could be an early health effect of anthropogenic climate change.

Climate change and the recent emergence of bluetongue in Europe

Bluetongue, a devastating disease of ruminants, has historically made only brief, sporadic incursions into the fringes of Europe. However, since 1998, six strains of bluetongue virus have spread across 12 countries and 800 km further north in Europe than has previously been reported. We suggest that this spread has been driven by recent changes in European climate that have allowed increased virus persistence during winter, the northward expansion of Culicoides imicola, the main bluetongue virus vector, and, beyond this vector's range, transmission by indigenous European Culicoides species - thereby expanding the risk of transmission over larger geographical regions. Understanding this sequence of events may help us predict the emergence of other vector-borne pathogens.

Dynamical epidemic suppression using stochastic prediction and control

We consider the effects of noise on a model of epidemic outbreaks, where the outbreaks appear randomly. Using a constructive transition approach that predicts large outbreaks prior to their occurrence, we derive an adaptive control scheme that prevents large outbreaks from occurring. The theory is applicable to a wide range of stochastic processes with underlying deterministic structure.

Unhealthy landscapes: Policy recommendations on land use change and infectious disease emergence

Anthropogenic land use changes drive a range of infectious disease outbreaks and emergence events and modify the transmission of endemic infections. 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. The Working Group on Land Use Change and Disease Emergence grew out of a special colloquium that convened international experts in infectious diseases, ecology, and environmental health to assess the current state of knowledge and to develop recommendations for addressing these environmental health challenges. The group established a systems model approach and priority lists of infectious diseases affected by ecologic degradation. Policy-relevant levels of the model include specific health risk factors, landscape or habitat change, and institutional (economic and behavioral) levels. The group recommended creating Centers of Excellence in Ecology and Health Research and Training, based at regional universities and/or research institutes with close links to the surrounding communities. The centers' objectives would be 3-fold: a) to provide information to local communities about the links between environmental change and public health; b) to facilitate fully interdisciplinary research from a variety of natural, social, and health sciences and train professionals who can conduct interdisciplinary research; and c) to engage in science-based communication and assessment for policy making toward sustainable health and ecosystems.

Examining unmet needs in infectious disease

In the past 30 years, more than 30 new aetiological agents of infectious disease have been identified. Some of these are responsible for entirely novel and life-threatening disorders, such as AIDS, Ebola fever, hantavirus pulmonary syndrome and Nipah virus encephalitis. During the same period, some longstanding infectious diseases (such as tuberculosis) have became resurgent, as a result of a combination of complacency, increased travel and social dislocation, and also increasing drug resistance. This review looks at some of the key unmet needs in this therapeutic area and discusses strategies to address them.