The association between ambient temperature and mortality in South Africa: A time-series analysis

Short-term effects of diurnal temperature range on hospital admission in Bangkok, Thailand

Diurnal temperature range (DTR) is a key indicator reflecting climate stability. Many previous studies have examined the effects of ambient temperature, both hot and cold, on human morbidity and mortality, but few studies have evaluated health effects of DTR, especially those in developing countries. This study aimed to investigate the association between short-term exposure to DTR and hospital admissions for cardiovascular and respiratory diseases in Bangkok, Thailand. We obtained daily meteorological variables from the Thai Meteorological Department from January 2006 through December 2014 and daily hospital admissions from the National Health Security Office during the same period. Quasi-Poisson generalized linear regression model combined with distributed lag non-linear model was used to examine the association between DTR and cardiovascular and respiratory hospital admissions controlling for daily average temperature, relative humidity, day of the week, public holiday, and seasonal and long-term trend. A J-shape relationship between DTR and hospital admissions was observed. With 7.8 °C DTR as a reference value, the relative risks for cardiovascular and respiratory hospital admission associated with extremely high DTR (11.6 °C) at cumulative lag 0-21 (21-day cumulative effects) were 1.206 (95% CI: 1.002-1.452) and 1.021 (95% CI: 0.856-1.218), respectively. The effects of extremely high DTR relative to a reference value did not significantly differ between males and females, as well as between young people (<65 years) and the elderly (≥65 years) for both cardiovascular and respiratory admission. When stratifying the effects by season, the effect of extremely high DTR in winter was greater than that in summer and rainy season. This study showed that short-term exposure to extremely high DTR was significantly associated with increased risk of hospital admissions for cardiovascular disease in Bangkok, especially during winter. Results from this study could provide important scientific evidence for policy decision making to protect populations from adverse health effects of DTR.

Heat-health vulnerability in temperate climates: lessons and response options from Ireland

Background

In Ireland, rising temperatures remains the climate projection that national climate scientists associate with the highest degree of confidence. However, the health challenge of heat has been largely absent from Ireland’s public health sector. This is epitomised by the lack of a comprehensive public health-focused heat-health action plan or country-specific codes of practice for heat-health when working outdoors. Our objective is to highlight the anticipated heat-health challenges in Ireland, and other temperate regions, through analysing vulnerable groups and systems, reinforcing the need to respond.

Methods

A scoping literature review was conducted to determine how heat affects health of the vulnerable in temperate climatic regions, with a focus on Ireland. Additionally, national Google Trends data was coarsely analysed to determine whether heat is a growing societal concern.

Results and discussion

The heat-vulnerable include: older people; chronically ill; infants, pregnant women, children; outdoor workers; socio-economically disadvantaged; urban dwellers; food systems and the health sector. Google Trends data suggest an increase in heat-related health searches over time, demonstrating rising levels of concern to temperature increases, reinforcing a gap in national policy associated with communication of, and response to, the heat-health challenge. Specific, actionable recommendations for adaptation and mitigation strategies are proposed.

Conclusion

Heat poses a public and occupational health challenge, receiving limited attention in Ireland. Lack of a co-ordinated effort, places vulnerable populations at risk. Our recommendations, with reference to vulnerable groups and acknowledging the multi-sectoral nature of heat-health and climate change, advocate for the adoption of a “health and climate change in all policies” approach and the development of a public health-focused heat-health action plan.

Impact of extreme temperatures on ambulance dispatches in London, UK

BACKGROUND

Associations between extreme temperatures and health outcomes, such as mortality and morbidity, are often observed. However, relatively little research has investigated the role of extreme temperatures upon ambulance dispatches.

METHODS

A time series analysis using London Ambulance Service (LAS) incident data (2010-2014), consisting of 5,252,375 dispatches was conducted. A generalized linear model (GLM) with a quasi-likelihood Poisson regression was applied to analyse the associations between ambulance dispatches and temperature. The 99^th (22.8°C) and 1^st (0.0°C) percentiles of temperature were defined as extreme high and low temperature. Fourteen categories of ambulance dispatches were investigated, grouped into 'respiratory' (asthma, dyspnoea, respiratory chest infection, respiratory arrest and chronic obstructive pulmonary disease), 'cardiovascular' (cardiac arrest, chest pain, cardiac chest pain RCI, cardiac arrhythmia and other cardiac problems) and 'other' non-cardiorespiratory (dizzy, alcohol related, vomiting and 'generally unwell') categories. The effects of long-term trends, seasonality, day of the week, public holidays and air pollution were controlled for in the GLM. The lag effect of temperature was also investigated. The threshold temperatures for each category were identified and a distributed lag non-linear model (DLNM) was reported using relative risk (RR) values at 95% confidence intervals.

RESULTS

Many dispatch categories show significant associations with extreme temperature. Total calls from 999 dispatches and 'generally unwell' dispatch category show significant RRs at both low and high temperatures. Most respiratory categories (asthma, dyspnoea and RCI) have significant RRs at low temperatures represented by with estimated RRs ranging from 1.392 (95%CI: 1.161-1.699) for asthma to 2.075 (95%CI: 1.673-2.574) for RCI. The RRs for all other non-cardiorespiratory dispatches were often significant for high temperatures ranging from 1.280 (95% CI: 1.128-1.454) for 'generally unwell' to 1.985 (95%CI: 1.422-2.773) for alcohol-related. For the cardiovascular group, only chest pain dispatches reported a significant RR at high temperatures.

CONCLUSIONS

Ambulance dispatches can be associated with extreme temperatures, dependent on the dispatch category. It is recommended that meteorological factors are factored into ambulance forecast models and warning systems, allowing for improvements in ambulance and general health service efficiency.

The role of cities in reducing the cardiovascular impacts of environmental pollution in low- and middle-income countries

BACKGROUND

As low- and middle-income countries urbanize and industrialize, they must also cope with pollution emitted from diverse sources.

MAIN TEXT

Strong and consistent evidence associates exposure to air pollution and lead with increased risk of cardiovascular disease occurrence and death. Further, increasing evidence, mostly from high-income countries, indicates that exposure to noise and to both high and low temperatures may also increase cardiovascular risk. There is considerably less research on the cardiovascular impacts of environmental conditions in low- and middle-income countries (LMICs), where the levels of pollution are often higher and the types and sources of pollution markedly different from those in higher-income settings. However, as such evidence gathers, actions to reduce exposures to pollution in low- and middle-income countries are warranted, not least because such exposures are very high. Cities, where pollution, populations, and other cardiovascular risk factors are most concentrated, may be best suited to reduce the cardiovascular burden in LMICs by applying environmental standards and policies to mitigate pollution and by implementing interventions that target the most vulnerable. The physical environment of cities can be improved though municipal processes, including infrastructure development, energy and transportation planning, and public health actions. Local regulations can incentivize or inhibit the polluting behaviors of industries and individuals. Environmental monitoring can be combined with public health warning systems and publicly available exposure maps to inform residents of environmental hazards and encourage the adoption of pollution-avoiding behaviors. Targeted individual or neighborhood interventions that identify and treat high-risk populations (e.g., lead mitigation, portable air cleaners, and preventative medications) can also be leveraged in the very near term. Research will play a key role in evaluating whether these approaches achieve their intended benefits, and whether these benefits reach the most vulnerable.

CONCLUSION

Cities in LMICs can play a defining role in global health and cardiovascular disease prevention in the next several decades, as they are well poised to develop innovative, multisectoral approaches to pollution mitigation, while also protecting the most vulnerable.

Influence of temperature on prevalence of health and welfare conditions in pigs: time-series analysis of pig abattoir inspection data in England and Wales

The prevalence of many diseases in pigs displays seasonal distributions. Despite growing concerns about the impacts of climate change, we do not yet have a good understanding of the role that weather factors play in explaining such seasonal patterns. In this study, national and county-level aggregated abattoir inspection data were assessed for England and Wales during 2010–2015. Seasonally-adjusted relationships were characterised between weekly ambient maximum temperature and the prevalence of both respiratory conditions and tail biting detected at slaughter. The prevalence of respiratory conditions showed cyclical annual patterns with peaks in the summer months and troughs in the winter months each year. However, there were no obvious associations with either high or low temperatures. The prevalence of tail biting generally increased as temperatures decreased, but associations were not supported by statistical evidence: across all counties there was a relative risk of 1.028 (95% CI 0.776–1.363) for every 1 °C fall in temperature. Whilst the seasonal patterns observed in this study are similar to those reported in previous studies, the lack of statistical evidence for an explicit association with ambient temperature may possibly be explained by the lack of information on date of disease onset. There is also the possibility that other time-varying factors not investigated here may be driving some of the seasonal patterns.

The effects of climate change on human health in Africa, a dermatologic perspective: a report from the International Society of Dermatology Climate Change Committee

Throughout much of the African continent, healthcare systems are already strained in their efforts to meet the needs of a growing population using limited resources. Climate change threatens to undermine many of the public health gains that have been made in this region in the last several decades via multiple mechanisms, including malnutrition secondary to drought-induced food insecurity, mass human displacement from newly uninhabitable areas, exacerbation of environmentally sensitive chronic diseases, and enhanced viability of pathogenic microbes and their vectors. We reviewed the literature describing the various direct and indirect effects of climate change on diseases with cutaneous manifestations in Africa. We included non-communicable diseases such as malignancies (non-melanoma skin cancers), inflammatory dermatoses (i.e. photosensitive dermatoses, atopic dermatitis), and trauma (skin injury), as well as communicable diseases and neglected tropical diseases. Physicians should be aware of the ways in which climate change threatens human health in low- and middle-income countries in general, and particularly in countries throughout Africa, the world's lowest-income and second most populous continent.

The Association between Air Temperature and Mortality in Two Brazilian Health Regions

Air temperature, both cold and hot, has impacts on mortality and morbidities, which are exacerbated by poor health service and protection responses, particularly in under-developed countries. This study was designed to analyze the effects of air temperature on the risk of deaths for all and specific causes in two regions of Brazil (Florianopolis and Recife), between 2005 and 2014. The association between temperature and mortality was performed through the fitting of a quasi-Poisson non-linear lag distributed model. The association between air temperature and mortality was identified for both regions. The results showed that temperature exerted influence on both general mortality indicators and specific causes, with hot and cold temperatures bringing different impacts to the studied regions. Cerebrovascular and cardiovascular deaths were more sensitive to cold temperatures for Florianopolis and Recife, respectively. Based on the application of the very-well documented state-of-the-art methodology, it was possible to conclude that there was evidence that extreme air temperature influenced general and specific deaths. These results highlighted the importance of consolidating evidence and research in tropical countries such as Brazil as a way of understanding climate change and its impacts on health indicators.

Short-term association between ambient temperature and homicide in South Africa: a case-crossover study

BACKGROUND

Criminology research has traditionally investigated sociodemographic predictors of crime, such as sex, race, age, and socioeconomic status. However, evidence suggests that short-term fluctuations in crime often vary more than long-term trends, which sociodemographic factors cannot explain. This has redirected researchers to explore how environmental factors, such as meteorological variables, influence criminal behavior. In this study we investigate the association between daily ambient temperature and homicide incidence in South Africa, a country with one of the highest homicide rates in the world.

METHODS

Mortality data was from South Africa's civil registration system and includes all recorded deaths in the country from 1997 to 2013 (17 years). Daily temperature was from the National Oceanographic and Atmospheric Association of the United States and South Africa's Agricultural Research Council. Data were analyzed using a time-stratified case-crossover design with conditional logistic regression. We delineated cases as either "definite" (ICD-10 codes X85-Y09, n = 68,356) or "probable" homicides (ICD-10 codes W25-W26, W32-W34, W50, Y22-Y24, Y28-Y29, n = 177,873). Case periods were defined as the day on which a death occurred. Control periods were selected using a day-of-week match within the same month and district. Analyses investigated same-day and lagged effects of maximum, mean and minimum temperature.

RESULTS

A one-degree Celsius increase in same-day maximum temperature - our a priori metric of choice - was associated with a 1.5% (1.3-1.8%) increase in definite homicides and a 1.2% (1.1-1.3%) increase in total (definite + probable) homicides. Significant (p < 0.05) positive associations were also observed when applying other temperature metrics (mean, minimum) and lags (1, 0-1). The shape of the association did not display any clear non-linearities. There was no evidence of confounding by public holidays or air pollution.

CONCLUSIONS

This study suggests a positive association between daily ambient temperature and homicide in South Africa. This temperature-health relationship may be of particular concern in the context of climate change. The ability to include meteorological variables as a predictor of criminal activity and violent behavior could prove valuable in resource allocation for crime prevention efforts.

Countrywide climate features during recorded climate-related disasters

Climate-related disasters cause substantial disruptions to human societies. With climate change, many extreme weather and climate events are expected to become more severe and more frequent. The International Disaster Database (EM-DAT) records climate-related disasters associated with observed impacts such as affected people and economic damage on a country basis. Although disasters are classified into different meteorological categories, they are usually not linked to observed climate anomalies. Here, we investigate countrywide climate features associated with disasters that have occurred between 1950 and 2015 and have been classified as droughts, floods, heat waves, and cold waves using superposed epoch analysis. We find that disasters classified as heat waves are associated with significant countrywide increases in annual mean temperature of on average 0.13 ^∘C and a significant decrease in annual precipitation of 3.2%. Drought disasters show positive temperature anomalies of 0.08 ^∘C and a 4.8 % precipitation decrease. Disasters classified as droughts and heat waves are thus associated with significant annual countrywide anomalies in both temperature and precipitation. During years of flood disasters, precipitation is increased by 2.8 %. Cold wave disasters show no significant signal for either temperature or precipitation. We further find that climate anomalies tend to be larger in smaller countries, an expected behavior when computing countrywide averages. In addition, our results suggest that extreme weather disasters in developed countries are typically associated with larger climate anomalies compared to developing countries. This effect could be due to different levels of vulnerability, as a climate anomaly needs to be larger in a developed country to cause a societal disruption. Our analysis provides a first link between recorded climate-related disasters and observed climate data, which is an important step towards linking climate and impact communities and ultimately better constraining future disaster risk.

Projections of Temperature-Attributable Deaths in Portuguese Metropolitan Areas: A Time-Series Modelling Approach

Climate change is now widely recognised as the greatest global threat over the coming decades. This study aimed to quantify and project the effects of climate change on future temperature-attributable mortality due to circulatory system diseases (CSD) in Lisbon metropolitan area (LMA) and in Porto metropolitan area (PMA). The future time slices of Representative Concentration Pathway (RCP 8.5), mid-term (2046–2065) and long-term (2080–2099) were compared with the reference period (1986–2005). There is a significant decreasing trend in proportion to the overall extreme cold temperature-attributable mortality due to CSD in the future periods (2045–2065 and 2081–2099) in LMA, −0.63% and −0.73%, respectively, and in PMA, −0.62% for 2045–2065 and −0.69% for 2081–2099, compared to the historical period. The fraction attributable to extreme hot temperature in the summer months increased by 0.08% and 0.23%, from 0.04% in the historical period to 0.11% during 2046–2065, and to 0.27% during 2081–2099 in LMA. While there were no noticeable changes due to extreme hot temperature during the summer in PMA, significant increases were observed with warmer winter temperatures: 1.27% and 2.80%. The projections of future temperature-attributable mortality may provide valuable information to support climate policy decision making and temperature-related risk management.

Mapping the increased minimum mortality temperatures in the context of global climate change

Minimum mortality temperature (MMT) is an important indicator to assess the temperature–mortality relationship. It reflects human adaptability to local climate. The existing MMT estimates were usually based on case studies in data rich regions, and limited evidence about MMT was available at a global scale. It is still unclear what the most significant driver of MMT is and how MMT will change under global climate change. Here, by analysing MMTs in 420 locations covering six continents (Antarctica was excluded) in the world, we found that although the MMT changes geographically, it is very close to the local most frequent temperature (MFT) in the same period. The association between MFT and MMT is not changed when we adjust for latitude and study year. Based on the MFT~MMT association, we estimate and map the global distribution of MMTs in the present (2010s) and the future (2050s) for the first time.

Minimum mortality temperature (MMT) changes geographically and over time. Here, by analysing MMTs in 420 global locations during 1984-2018, the authors found that MMT is very close to the local most frequent temperature (MFT) in the same period, and the association between MFT and MMT is not changed when adjusted for lattitude and study year.

The effects of temperature on human mortality in a Chinese city: burden of disease calculation, attributable risk exploration, and vulnerability identification

Few studies have examined the attributable fraction (AF) of temperature to mortality and Years of Life Lost (YLL), especially in developing countries. This study aims to explore the short-term effect of the cold and hot temperatures on the cause-specific YLL and mortality, discover the attributable contributions from the temperature variations, and identify the vulnerable populations in Weifang, China. Daily registered death information and meteorological data over the period 2010-2016 were obtained in Weifang, a northern Chinese city. Generalized additive Poisson and Gaussian regression models were used to assess the impacts of temperatures on both mortality and YLL, explore the AF of the temperature variations on mortality, after adjusting for other covariates. Both hot and cold temperatures have had significant negative impacts on cause-specific mortality counts and YLL, with heat presented an acute and short effect and the cold temperatures had delayed effects and lasted for several days. In terms of the attributable fraction calculations, the contributions from cold effects was higher than that of hot effects on non-accidental, cardiovascular, and respiratory deaths (YLL 10.88 vs. 1.23%, 19.58 vs. 1.71%, and 14.47 vs. 3.05%; mortality 13.97 vs. 1.65%, 19.20 vs. 1.59%, and 14.89 vs. 3.09%), respectively. The elderly and women and people with low education level were the most vulnerable. The findings will provide important scientific evidences and policy implications for developing adaptation strategies to reduce the adverse effect of cold and hot exposure in Weifang, in terms of resource allocation, healthcare workforce capacity building, and community health education, especially for the vulnerable groups.

Cardiorespiratory effects of heatwaves: A systematic review and meta-analysis of global epidemiological evidence

BACKGROUND

Heatwaves affect human health and global heatwave-related disease burden will continue to rise as climate change proceeds, but the effects of heatwaves on cardiovascular and respiratory diseases have not yet been investigated globally and nationally.

OBJECTIVES

This systematic review and meta-analysis aim to quantify heatwave effects on four major health outcomes: cardiovascular and respiratory morbidity and mortality.

METHODS

We searched PubMed, Scopus, Embase, and Web of Science for relevant studies from database inception to November 2018. Categories of morbidity included hospital admissions, emergency department visits, and ambulance attendances/call-outs. A random-effects meta-analysis model was used to pool previous estimates of heatwave effects on mortality and morbidity due to cardiovascular and respiratory diseases. Subgroup analyses by gender, age, and disease cause were conducted. Sensitivity analyses were performed by the categories of morbidity, heatwave definitions, study design, and using a leave-one-out cross validation approach. This study is registered with PROSPERO (number: CRD42018101964).

RESULTS

We identified 54 studies conducted in 20 countries. In total, there were significant associations between heatwaves and cardiovascular mortality (risk estimates (RE): 1.149, 95% confidence interval (CI): 1.090, 1.210) and respiratory mortality (RE: 1.183, 95%CI: 1.092, 1.282), but the magnitude of these associations varied across countries and studies. Heatwaves appeared to be marginally associated with cardiovascular and respiratory morbidities (RE: 0.999, 95%CI: 0.996, 1.002, p-value = 0.61 for cardiovascular morbidity; RE: 1.043, 95%CI: 0.995, 1.093; p-value = 0.08 for respiratory morbidity). For mortality, significant associations were observed for the elderly, ischemic heart disease, stroke, heart failure, and chronic obstructive pulmonary disease. Sensitivity analyses suggested that these findings were robust.

CONCLUSION

Mortality of cardiovascular and respiratory diseases appeared to be more vulnerable to heatwaves in comparison to morbidity. Considering high heterogeneity detected between studies and limited investigations into subpopulations, more research are required to provide a clearer picture of how heatwaves affect cardiovascular and respiratory diseases in different settings.

Dynamic Bayesian network in infectious diseases surveillance: a simulation study

The surveillance of infectious diseases relies on the identification of dynamic relations between the infectious diseases and corresponding influencing factors. However, the identification task confronts with two practical challenges: small sample size and delayed effect. To overcome both challenges to imporve the identification results, this study evaluated the performance of dynamic Bayesian network(DBN) in infectious diseases surveillance. Specifically, the evaluation was conducted by two simulations. The first simulation was to evaluate the performance of DBN by comparing it with the Granger causality test and the least absolute shrinkage and selection operator (LASSO) method; and the second simulation was to assess how the DBN could improve the forecasting ability of infectious diseases. In order to make both simulations close to the real-world situation as much as possible, their simulation scenarios were adapted from real-world studies, and practical issues such as nonlinearity and nuisance variables were also considered. The main simulation results were: ① When the sample size was large (n = 340), the true positive rates (TPRs) of DBN (≥98%) were slightly higher than those of the Granger causality method and approximately the same as those of the LASSO method; the false positive rates (FPRs) of DBN were averagely 46% less than those of the Granger causality test, and 22% less than those of the LASSO method. ② When the sample size was small, the main problem was low TPR, which would be further aggravated by the issues of nonlinearity and nuisance variables. In the worst situation (i.e., small sample size, nonlinearity and existence of nuisance variables), the TPR of DBN declined to 43.30%. However, it was worth noting that such decline could also be found in the corresponding results of Granger causality test and LASSO method. ③ Sample size was important for identifying the dynamic relations among multiple variables, in this case, at least three years of weekly historical data were needed to guarantee the quality of infectious diseases surveillance. ④ DBN could improve the foresting results through reducing forecasting errors by 7%. According to the above results, DBN is recommended to improve the quality of infectious diseases surveillance.

Socio-economic and environmental factors influenced the United Nations healthcare sustainable agenda: evidence from a panel of selected Asian and African countries

The objective of the study is to evaluate socio-economic and environmental factors that influenced the United Nations healthcare sustainable agenda in a panel of 21 Asian and African countries. The results show that changes in price level (0.0062, p < 0.000), life risks of maternal death (4.579, p < 0.000), and under-5 mortality rate (0.374, p < 0.000) substantially increases out-of-pocket health expenditures, while CO₂ emissions (5.681, p < 0.003), prevalence of undernourishment (15.184, p < 0.000), PM_2.5 particulate emission (1557, p < 0.000), unemployment, and private health expenditures (30.729, p < 0000) are associated with high mortality rate across countries. Healthcare reforms affected by low healthcare spending, unsustainable environment, and ease of environmental regulations that ultimately increases mortality rate across countries. The Granger causality estimates confirmed the different causal mechanisms between socio-economic and environmental factors, which is directly linked with the country's healthcare agenda, i.e., the causality running from (i) CO₂ emissions to life risks of maternal death and under-5 mortality rate, (ii) from depth of food deficit to incidence of tuberculosis and unemployment, (iii) from PM_2.5 emissions to infant mortality rate, (iv) from foreign direct investment (FDI) inflows to PM_2.5 emissions, (v) from trade openness to greenhouse gas (GHG) emissions, and (vi) from mortality indicators to per capita income, while there is a feedback relationship between health expenditures and per capita income across countries. The variance decomposition analysis shows that (i) under-5 mortality rate will increase out-of-pocket health expenditures, (ii) unemployment rate will increase mortality indicators, and (iii) health expenditures will increase economic well-being in a panel of selected countries, for the next 10 years.

Complex effects of atmospheric parameters on acute cardiovascular diseases and major cardiovascular risk factors: data from the CardiometeorologySM study

Several studies have examined the cardiovascular effects of atmospheric parameters as separate factors; however, few have investigated atmospheric parameters’ joint effects. We aim to explore the joint effects of atmospheric parameters on acute cardiovascular diseases (ACVDs) and on major cardiovascular risk factors (CRFs). We correlated all ACVD admissions with major CRFs and local atmospheric conditions during a 5-year study period. A seasonal variation was detected in a higher incidence rate during cold atmospheric conditions. There were significant incidence relative ratios, including: 1.140 (95% CI [1.020, 1.283]) for daily temperature change (≥5 °C); 0.991 (95% CI [0.988, 0.994]) for average daily temperature; and 1.290 (95% CI [1.090, 1.599]) for the interaction of daily temperature change (≥5 °C) with humidity change (≥40%). We observed a significant association between the atmospheric parameters’ joint effects and hyperlipidaemia, diabetes, and previous ACVDs. Patients with diabetes had the highest significant incidence relative ratio at 2.429 (95% CI [1.088, 5.424]) for humidity-temperature interactions. Thus, the atmospheric parameters’ joint effects play an important role as minor CRFs. These unfavourable atmospheric situations are predicted to increase the number of ACVDs mainly. Our study may help to organize prevention strategies more effectively and to reduce cardiovascular risks.

A Bayesian Kriging Regression Method to Estimate Air Temperature Using Remote Sensing Data

Surface air temperature (Ta) is an important physical quantity, usually measured at ground weather station networks. Measured Ta data is inadequate to characterize the complex spatial patterns of Ta field due to low density and unevenness of the networks. Remote sensing can provide satellite imagery with large scale spatial coverage and fine resolution. Estimating spatially continuous Ta by integrating ground measurements and satellite data is an active research area. A variety of methods have been proposed and applied in this area. However, the existing studies primarily focused on daily Ta and failed to quantify uncertainties in model parameter and estimated results. In this paper, a Bayesian Kriging regression (BKR) method is proposed to model and estimate monthly Ta using satellite-derived land surface temperature (LST) as the only input. The BKR is a spatial statistical model with the capacity to quantify uncertainties via Bayesian inference. The BKR method was applied to estimate monthly maximum air temperature (Tmax) and minimum air temperature (Tmin) over the conterminous United States in 2015. An exploratory analysis shows a strong relationship between LST and Ta at the monthly scale, indicating LST has the great potential to estimate monthly Ta. 10-fold cross-validation approach was adopted to compare the predictive performance of the BKR method with the linear regression method over the whole region and the urban areas of the contiguous United States. For the whole region, the results show that the BKR method achieves a competitively better performance with averaged RMSE values 1 . 23 K for Tmax and 1 . 20 K for Tmin, which are also lower than previous studies on estimation of monthly Ta. In the urban areas, the cross-validation demonstrates similar results with averaged RMSE values 1 . 21 K for Tmax and 1 . 27 K for Tmin. Posterior samples for model parameters and estimated Ta were obtained and used to analyze uncertainties in the model parameters and estimated Ta. The BKR method provides a promising way to estimate Ta with competitively predictive performance and to quantify model uncertainties at the same time.

Climate change adaptation in South Africa: a case study on the role of the health sector

BACKGROUND

Globally, the response to climate change is gradually gaining momentum as the impacts of climate change unfold. In South Africa, it is increasingly apparent that delays in responding to climate change over the past decades have jeopardized human life and livelihoods. While slow progress with mitigation, especially in the energy sector, has garnered much attention, focus is now shifting to developing plans and systems to adapt to the impacts of climate change.

METHODS

We applied systematic review methods to assess progress with climate change adaptation in the health sector in South Africa. This case study provides useful lessons which could be applied in other countries in the African region, or globally. We reviewed the literature indexed in PubMed and Web of Science, together with relevant grey literature. We included articles describing adaptation interventions to reduce the impact of climate change on health in South Africa. All study designs were eligible. Data from included articles and grey literature were summed thematically.

RESULTS

Of the 820 publications screened, 21 were included, together with an additional xx papers. Very few studies presented findings of an intervention or used high-quality research designs. Several policy frameworks for climate change have been developed at national and local government levels. These, however, pay little attention to health concerns and the specific needs of vulnerable groups. Systems for forecasting extreme weather, and tracking malaria and other infections appear well established. Yet, there is little evidence about the country's preparedness for extreme weather events, or the ability of the already strained health system to respond to these events. Seemingly, few adaptation measures have taken place in occupational and other settings. To date, little attention has been given to climate change in training curricula for health workers.

CONCLUSIONS

Overall, the volume and quality of research is disappointing, and disproportionate to the threat posed by climate change in South Africa. This is surprising given that the requisite expertise for policy advocacy, identifying effective interventions and implementing systems-based approaches rests within the health sector. More effective use of data, a traditional strength of health professionals, could support adaptation and promote accountability of the state. With increased health-sector leadership, climate change could be reframed as predominately a health issue, one necessitating an urgent, adequately-resourced response. Such a shift in South Africa, but also beyond the country, may play a key role in accelerating climate change adaptation and mitigation.

Mortality and morbidity associated with ambient temperatures in Taiwan

BACKGROUND

This study evaluated integrated risks of all-cause mortality, emergency room visits (ERVs), and outpatient visits associated with ambient temperature in all cities and counties of Taiwan. In addition, the modifying effects of socio-economic and environmental factors on temperature-health associations were also evaluated.

METHODS

A distributed lag non-linear model was applied to estimate the cumulative relative risks (RRs) with confidence intervals of all-cause mortality, ERVs, and outpatient visits associated with extreme temperature events. Random-effect meta-analysis was used to estimate the pooled RR of all-cause mortality, ERVs, and outpatient visits influenced by socio-economic and environmental factors.

RESULTS

Temperature-related risks varied with study area and health outcome. Meta-analysis showed greater all-cause mortality risk occurred in low temperatures than in high temperatures. Integrated RR of all-cause mortality was 1.71 (95% confidence interval [CI]:1.43-2.04) in the 5th percentile temperature and 1.10 (95% CI: 1.05-1.15) in the 95th percentile temperature, while the lowest mortality risk was in the 60th percentile temperature (22.2 °C). Risk for ERVs increased when temperature increased (RR was 1.21 [95% CI: 1.17-1.26] in 95th percentile temperature), but risk of outpatient visits increased at low temperatures (RR was 1.06 [95% CI: 1.01-1.12] in the 5th percentile temperature). Certain socio-economic factors significantly modified low-temperature-related mortality risks, including number of employed populations, elders living alone from lower-income families, and public and medical services.

CONCLUSIONS

This study found that mortality and outpatient visits were higher at low temperature, while ERVs risk was higher at high temperature. Future plans for public health and emerging medical services responding to extreme temperatures should consider regional and integrated evaluations of temperature-related health risks and modifying factors.

Socio-geographic disparity in cardiorespiratory mortality burden attributable to ambient temperature in the United States

Compared with relative risk, attributable fraction (AF) is more informative when assessing the mortality burden due to some environmental exposures (e.g., ambient temperature). Up to date, however, available AF-based evidence linking temperature with mortality has been very sparse regionally and nationally, even for the leading mortality types such as cardiorespiratory deaths. This study aimed to quantify national and regional burden of cardiorespiratory mortality (CRM) attributable to ambient temperature in the USA, and to explore potential socioeconomic and demographic sources of spatial heterogeneity between communities. Daily CRM and weather data during 1987-2000 for 106 urban communities across the mainland of USA were acquired from the publicly available National Morbidity, Mortality and Air Pollution Study (NMMAPS). We did the data analysis using a three-stage analytic approach. We first applied quasi-Poisson regression incorporated with distributed lag nonlinear model to estimate community-specific temperature-CRM associations, then pooled these associations at the regional and national level through a multivariate meta-analysis, and finally estimated the temperature-AF of CRM and performed subgroup analyses stratified by community-level characteristics. Both low and high temperatures increased short-term CRM risk, while temperature-CRM associations varied by regions. Nationally, the fraction of cardiorespiratory deaths caused by the total non-optimum, low, and high temperatures was 7.58% (95% empirical confidence interval, 6.68-8.31%), 7.15% (6.31-7.85%), and 0.43% (0.37-0.46%), respectively. Greater temperature-AF was identified in two northern regions (i.e., Industrial Midwest and North East) and communities with lower temperature and longitude, higher latitude, and moderate humidity. Additionally, higher vulnerability appeared in locations with higher urbanization level, more aging population, less White race, and lower socioeconomic status. Ambient temperature may be responsible for a large fraction of cardiorespiratory deaths. Also, temperature-AF of CRM varied considerably by geographical and climatological factors, as well as community-level disparity in socioeconomic status.

Priority focus areas for a sub-national response to climate change and health: A South African provincial case study

INTRODUCTION

The intersection of health and climate change is often absent or under-represented in sub-national government strategies. This analysis of the literature, using a new methodological framework, highlights priority focus areas for a sub-national government response to health and climate change, using the Western Cape (WC) province of South Africa as a case study.

METHODS

A methodological framework was created to conduct a review of priority focus areas relevant for sub-national governments. The framework encompassed the establishment of a Project Steering Group consisting of relevant, sub-national stakeholders (e.g. provincial officials, public and environmental health specialists and academics); an analysis of local climatic projections as well as an analysis of global, national and sub-national health risk factors and impacts.

RESULTS

Globally, the discussion of health and climate change adaptation strategies in sub-national, or provincial government is often limited. For the case study presented, multiple health risk factors were identified. WC climatic projections include a warmer and potentially drier future with an increased frequency and intensity of extreme weather events. WC government priority focus areas requiring further research on health risk factors include: population migration and environmental refugees, land use change, violence and human conflict and vulnerable groups. WC government priority focus areas for further research on health impacts include: mental ill-health, non-communicable diseases, injuries, poisonings (e.g. pesticides), food and nutrition insecurity-related diseases, water- and food-borne diseases and reproductive health. These areas are currently under-addressed, or not addressed at all, in the current provincial climate change strategy.

CONCLUSIONS

Sub-national government adaptation strategies often display limited discussion on the health and climate change intersect. The methodological framework presented in this case study can be globally utilized by other sub-national governments for decision-making and development of climate change and health adaptation strategies. Additionally, due to the broad range of sectoral issues identified, a primary recommendation from this study is that sub-national governments internationally should consider a "health and climate change in all policies" approach when developing adaptation and mitigation strategies to address climate change.

Effects of ambient temperature on ambulance emergency call-outs in the subtropical city of Shenzhen, China

The associations between meteorological factors and mortality have been well documented worldwide, but limited evidence is available for the non-fatal health impacts of ambient temperature, particularly there are few population-based investigations on the impacts of emergency ambulance dispatches in Asia. In this study, based on 809,906 ambulance emergency call-outs (AECOs) for the total population from 2010-2016 in the subtropical city of Shenzhen, China, a Poisson regression combined with a distributed lag nonlinear model was used to simultaneously assess the nonlinear and lag effects of daily mean temperature on AECOs. Stratified analyses by age and sex were performed to identify vulnerable subpopulations. A U-shaped relationship was found between temperature and AECOs. Cold effects were delayed and persisted for 3-4 weeks, with a cumulative relative risk (RR) and 95% confidence interval (CI) of 1.23 (1.10-1.38) and 1.25 (1.16-1.35) over lag 0-28 when comparing the 1st and 5th percentile of the temperature distribution to the optimal (i.e. minimum AECOs) temperature, respectively. Hot effects were immediate and diminished quickly in 5 days, with an increase of 19% (RR = 1.19, 95%CI: 1.14-1.23) and 21% (RR = 1.21, 95%CI: 1.16-1.26) in AECOs over lag 0-5 when comparing the 95th and 99th percentile of temperature to the optimal temperature. Children and the elderly were more vulnerable to cold effects. The youth and middle-aged people suffered more from high temperature. The effects of temperature were similar between males and females. In summary, significant increases were observed in the frequency of AECOs during cold and hot days, and the weather-associated increases in AECOs are different among age groups. This information has valuable implications in ambulance demand prediction and service provision planning.

Impacts of Climate Change on Health and Wellbeing in South Africa

Given its associated burden of disease, climate change in South Africa could be reframed as predominately a health issue, one necessitating an urgent health-sector response. The growing impact of climate change has major implications for South Africa, especially for the numerous vulnerable groups in the country. We systematically reviewed the literature by searching PubMed and Web of Science. Of the 820 papers screened, 34 were identified that assessed the impacts of climate change on health in the country. Most papers covered effects of heat on health or on infectious diseases (20/34; 59%). We found that extreme weather events are the most noticeable effects to date, especially droughts in the Western Cape, but rises in vector-borne diseases are gaining prominence. Climate aberration is also linked in myriad ways with outbreaks of food and waterborne diseases, and possibly with the recent Listeria epidemic. The potential impacts of climate change on mental health may compound the multiple social stressors that already beset the populace. Climate change heightens the pre-existing vulnerabilities of women, fishing communities, rural subsistence farmers and those living in informal settlements. Further gender disparities, eco-migration and social disruptions may undermine the prevention-but also treatment-of HIV. Our findings suggest that focused research and effective use of surveillance data are required to monitor climate change's impacts; traditional strengths of the country's health sector. The health sector, hitherto a fringe player, should assume a greater leadership role in promoting policies that protect the public's health, address inequities and advance the country's commitments to climate change accords.

Temporal and seasonal variations of mortality burden associated with hourly temperature variability: A nationwide investigation in England and Wales

BACKGROUND

Sudden temperature change may elevate short-term mortality and remains an important global health threat in the context of climate change. To date, however, little available temperature-mortality evidence has taken into account both intra- and inter-day temperature variability (TV), thus largely limiting the comprehensive understanding of mortality burden due to unstable weather. Moreover, seasonal and temporal patterns in TV-mortality associations were sparsely discussed, nationally and regionally.

OBJECTIVES

We aimed to assess the nationwide association of all-cause mortality with hourly temperature variability (HTV), quantify HTV-attributable mortality, and further explore the temporal and seasonal variations of mortality burden due to HTV in United Kingdom.

METHODS

Fourteen-year time-series data on temperature and mortality were collected from 10 regions in England and Wales during 1993-2006, totally including 7,573,716 all-cause deaths. HTV was calculated from the standard deviation of hourly temperature records within two neighboring days. A three-stage analytic approach was adopted to assess HTV-associated mortality burden. We first applied a time-series quasi-Poisson regression to estimate region-specific HTV-mortality associations, then pooled these associations at the national level using a multivariate meta-analysis, and finally estimated the HTV-attributable mortality fraction and illustrated its seasonal and temporal variations by conducting season- and period-specific analyses based on time-varying distributed lag models.

RESULTS

We found strong evidence that large HTV exposure elevated short-term mortality risk in England and Wales, with a pooled estimate of 1.13% (95% confidence interval (CI): 0.88, 1.39) associated with a 1-°C increase in HTV. During the whole study period, HTV accounted for a national average attributable fraction of 2.52% (95% empirical confidence interval (eCI): 2.27, 2.76) of the total deaths. This HTV-attributable mortality estimate showed a significant temporal decrease (p < 0.001) from 2.72% (95% eCI: 2.58, 2.87) in 1993-99 to 2.28% (95% eCI: 2.13, 2.43) in 2000-06. Additionally, clear seasonal variations were observed for HTV-attributable mortality burden, with the largest estimate of 3.08% (95% eCI: 2.80, 3.38) in summer, followed by 2.71% (95% eCI: 2.44, 2.98) in spring, 2.40% (95% eCI: 2.16, 2.63) in autumn, and 2.00% (95% eCI: 1.81, 2.20) in winter.

CONCLUSIONS

Despite clear evidence observed for the reduction, mortality burden caused by temperature variability remained a great public health threat, especially in warm seasons. It highlighted the importance of specific interventions targeted to unstable weather as well as temperature extremes, so as to reduce climate-related mortality burden.

Current and Potential Future Seasonal Trends of Indoor Dwelling Temperature and Likely Health Risks in Rural Southern Africa

Climate change has resulted in rising temperature trends which have been associated with changes in temperature extremes globally. Attendees of Conference of the Parties (COP) 21 agreed to strive to limit the rise in global average temperatures to below 2 °C compared to industrial conditions, the target being 1.5 °C. However, current research suggests that the African region will be subjected to more intense heat extremes over a shorter time period, with projections predicting increases of 4–6 °C for the period 2071–2100, in annual average maximum temperatures for southern Africa. Increased temperatures may exacerbate existing chronic ill health conditions such as cardiovascular disease, respiratory disease, cerebrovascular disease, and diabetes-related conditions. Exposure to extreme temperatures has also been associated with mortality. This study aimed to consider the relationship between temperatures in indoor and outdoor environments in a rural residential setting in a current climate and warmer predicted future climate. Temperature and humidity measurements were collected hourly in 406 homes in summer and spring and at two-hour intervals in 98 homes in winter. Ambient temperature, humidity and windspeed were obtained from the nearest weather station. Regression models were used to identify predictors of indoor apparent temperature (AT) and to estimate future indoor AT using projected ambient temperatures. Ambient temperatures will increase by a mean of 4.6 °C for the period 2088–2099. Warming in winter was projected to be greater than warming in summer and spring. The number of days during which indoor AT will be categorized as potentially harmful will increase in the future. Understanding current and future heat-related health effects is key in developing an effective surveillance system. The observations of this study can be used to inform the development and implementation of policies and practices around heat and health especially in rural areas of South Africa.

Commonalities between Disaster and Climate Change Risks for Health: A Theoretical Framework

Disasters and climate change have significant implications for human health worldwide. Both climate change and the climate-sensitive hazards that result in disasters, are discussed in terms of direct and indirect impacts on health. A growing body of literature has argued for the need to link disaster risk reduction and climate change adaptation. However, there is limited articulation of the commonalities between these health impacts. Understanding the shared risk pathways is an important starting point for developing joint strategies for adapting to, and reducing, health risks. Therefore, this article discusses the common aspects of direct and indirect health risks of climate change and climate-sensitive disasters. Based on this discussion a theoretical framework is presented for understanding these commonalities. As such, this article hopes to extend the current health impact frameworks and provide a platform for further research exploring opportunities for linked adaptation and risk reduction strategies.