Estimating least-developed countries' vulnerability to climate-related extreme events over the next 50 years

A framework for managing infectious diseases in rural areas in low- and middle-income countries in the face of climate change-East Africa as a case study

Climate change is having unprecedented impacts on human health, including increasing infectious disease risk. Despite this, health systems across the world are currently not prepared for novel disease scenarios anticipated with climate change. While the need for health systems to develop climate change adaptation strategies has been stressed in the past, there is no clear consensus on how this can be achieved, especially in rural areas in low- and middle-income countries that experience high disease burdens and climate change impacts simultaneously. Here, we highlight the need to put health systems in the context of climate change and demonstrate how this can be achieved by taking into account all aspects of infectious disease risk (i.e., pathogen hazards, and exposure and vulnerability to these pathogen hazards). The framework focuses on rural communities in East Africa since communities in this region experience climate change impacts, present specific vulnerabilities and exposure to climate-related hazards, and have regular exposure to a high burden of infectious diseases. Implementing the outlined approach can help make health systems climate adapted and avoid slowing momentum towards achieving global health grand challenge targets.

Vulnerability and Risk Assessment to Climate Change in Sagar Island, India

Inhabitants of low-lying islands face increased threats due to climate change as a result of their higher exposure and lesser adaptive capacity. Sagar Island, the largest inhabited estuarine island of Sundarbans, is experiencing severe coastal erosion, frequent cyclones, flooding, storm surges, and breaching of embankments, resulting in land, livelihood, and property loss, and the displacement of people at a huge scale. The present study assessed climate change-induced vulnerability and risk for Sagar Island, India, using an integrated geostatistical and geoinformatics-based approach. Based on the IPCC AR5 framework, the proportion of variance of 26 exposure, hazard, sensitivity, and adaptive capacity parameters was measured and analyzed. The results showed that 19.5% of mouzas (administrative units of the island), with 15.33% of the population at the southern part of the island, i.e., Sibpur–Dhablat, Bankimnagar–Sumatinagar, and Beguakhali–Mahismari, are at high risk (0.70–0.80). It has been concluded that the island has undergone tremendous land system transformations and changes in climatic patterns. Therefore, there is a need to formulate comprehensive adaptation strategies at the policy- and decision-making levels to help the communities of this island deal with the adverse impacts of climate change. The findings of this study will help adaptation strategies based on site-specific information and sustainable management for the marginalized populations living in similar islands worldwide.

Human development, greenhouse gas emissions and sub-national mitigation burdens: a Brazilian perspective

International frameworks for greenhouse gas (GHG) mitigation usually disregard country-specific inequalities for the allocation of mitigation burdens. This may hinder low developed regions in a country from achieving development in a socioeconomic perspective, such as the Sustainable Development Goals (SDGs) of eradicating poverty (SDG1) and hunger (SDG2). We use observed data (1991–2010) of carbon dioxide equivalent (CO₂eq) emissions and a sub-national human development index (MicroHDI, range [0, 1]) for Brazilian microregions to design a framework where regional mitigation burdens are proportional to the MicroHDI, without compromising national mitigation pledges. According to our results, the less developed Brazilian regions have not been basing their development in emission-intensive activities; instead, the most developed regions have. Between 2011 and 2050, Brazilian cumulative emissions from the sectors most correlated with MicroHDI are expected to be 325 Gt CO₂eq, of which only 50 Gt are associated with regions of MicroHDI < 0.8. Assuming a national GHG mitigation target of 56.5% in 2050 over 2010 (consistent with limiting global warming to 2 ºC), Brazil would emit 190 Gt CO₂eq instead of 325 Gt and the 135 Gt reduction is only accounted for by regions after reaching MicroHDI ≥ 0.8. Allocating environmental restrictions to the high-developed regions leaves ground for the least developed ones to pursue development with fewer restrictions. Our heterogeneous framework represents a fairer allocation of mitigation burdens which could be implemented under the concepts of green economy. This work could be an international reference for addressing both environmental and socioeconomic development in developing countries at sub-national level as emphasized by the SDGs.

Economic vulnerability to tropical storms on the southeastern coast of Africa

Climate change will hit Africa economically hard, not least Southeast Africa. Understanding the impact of extreme climatic events is important for both economic development and climate change policy. Global climatological summaries reveal high damage potential pathways for developed countries. Will countries in Africa, especially in the southeastern board of the continent, be vulnerable to loss-generating extreme climate events? This study examined for countries in the sub-region, their vulnerability and damage costs, the impact of climate change on tropical storm damage, as well as the differential impacts of storm damages. An approach using a combination of physical and economic reasoning, as well as results of previous studies, reveals that in Southeast Africa, the economic response to the key damage parameters of intensity, size and wind speed is significant for all the countries. Damages in Kenya and Tanzania are sensitive to wind speed. Both vulnerability and adaptation are important for Madagascar and Mozambique - two countries predicted to be persistently damaged by tropical storms. For Mauritius and South Africa, inflictions from extreme events are expected to be impactful, and would require resilient public and private infrastructure. Reducing the physical and socio-economic vulnerability to extreme events will require addressing the underlying socio-economic drivers, as well as developing critical public infrastructure.

Association between temperature changes and uveitis onset in mainland China

BACKGROUND

Some uveitis subtypes show seasonal patterns. Whether these patterns are caused by seasonally varying temperatures or by other climatic factors remains unknown. This ecological research aimed to quantify the association between climate variability and uveitis onset.

METHODS

We combined data from the largest database of uveitis cases with surface climate data to construct panel data. We used choropleth maps to visually assess spatial uveitis variations.

RESULTS

Among 12 721 reports of uveitis originating from 31 provinces of mainland China from 2006 to 2017, we found that a 1°C increase in monthly temperature was associated with a rise in approximately 2 uveitis reports per 1000 individuals (95% CI 0.00059 to 0.0029). This association was present across all provinces, ranging in effect size from 0.0011 to 0.072 (95% CI 0.00037 to 0.10). A clear 0-3 months of cumulative lagging effect was noted across all types of uveitis, with the strongest effect for non-infectious uveitis (0.0067, 95% CI 0.0041 to 0.013). Stratified by age and sex, we found that men and people aged 20-50 years were more affected by temperature variations. Our model predicts that China might experience an increase in uveitis cases due to future global warming.

CONCLUSION

Our study is the largest-ever investigation of the association between uveitis and climate and, for the first time, provides evidence that rising temperature can affect large-scale uveitis onset. These results may help promote and implement policies to mitigate future temperature increases and the burden of disease caused by global warming.

Impact of past and on-going changes on climate and weather on vector-borne diseases transmission: a look at the evidence

Background

The climate variables that directly influence vector-borne diseases’ ecosystems are mainly temperature and rainfall. This is not only because the vectors bionomics are strongly dependent upon these variables, but also because most of the elements of the systems are impacted, such as the host behavior and development and the pathogen amplification. The impact of the climate changes on the transmission patterns of these diseases is not easily understood, since many confounding factors are acting together. Consequently, knowledge of these impacts is often based on hypothesis derived from mathematical models. Nevertheless, some direct evidences can be found for several vector-borne diseases.

Main body

Evidences of the impact of climate change are available for malaria, arbovirus diseases such as dengue, and many other parasitic and viral diseases such as Rift Valley Fever, Japanese encephalitis, human African trypanosomiasis and leishmaniasis. The effect of temperature and rainfall change as well as extreme events, were found to be the main cause for outbreaks and are alarming the global community. Among the main driving factors, climate strongly influences the geographical distribution of insect vectors, which is rapidly changing due to climate change. Further, in both models and direct evidences, climate change is seen to be affecting vector-borne diseases more strikingly in fringe of different climatic areas often in the border of transmission zones, which were once free of these diseases with human populations less immune and more receptive. The impact of climate change is also more devastating because of the unpreparedness of Public Health systems to provide adequate response to the events, even when climatic warning is available. Although evidences are strong at the regional and local levels, the studies on impact of climate change on vector-borne diseases and health are producing contradictory results at the global level.

Conclusions

In this paper we discuss the current state of the results and draw on evidences from malaria, dengue and other vector-borne diseases to illustrate the state of current thinking and outline the need for further research to inform our predictions and response.

Electronic supplementary material

The online version of this article (10.1186/s40249-019-0565-1) contains supplementary material, which is available to authorized users.

Measuring urban vulnerability to climate change using an integrated approach, assessing climate risks in Beijing

This study is responding to the recommendation made by IPCC’s fifth Assessment Report on establishing a standard for measuring and reporting climate risk and vulnerability. It exemplifies the assessment of urban vulnerability to climate change by an integrated approach. The results indicate that Beijing is highly exposed to multiple climate threats in the context of global climate change, specifically urban heat waves, urban drainage floods and drought. Vulnerabilities to the climatic threats of heat waves, drainage floods and droughts have increased by 5%–15% during the period of 2008–2016 in Beijing. High vulnerabilities to both heat waves and drainage floods have been observed in the urban downtown area and high vulnerability to droughts have been observed in the outskirts. This vulnerability assessment, which addressed climatic threats, provides a holistic understanding of the susceptibility to climate change that could facilitate adaptation to climate change in the future. The developments of threats like flooding, heat waves and droughts are analyzed separately for 16 districts and an integrated vulnerability index for all of Beijing is provided as well.

Use of scenario ensembles for deriving seismic risk

High death tolls from recent earthquakes show that seismic risk remains high globally. While there has been much focus on seismic hazard, large uncertainties associated with exposure and vulnerability have led to more limited analyses of the potential impacts of future earthquakes. We argue that as both exposure and vulnerability are reducible factors of risk, assessing their importance and variability allows for prioritization of the most effective disaster risk-reduction (DRR) actions. We address this through earthquake ensemble modeling, using the example of Nepal. We model fatalities from 90 different scenario earthquakes and establish whether impacts are specific to certain scenario earthquakes or occur irrespective of the scenario. Our results show that for most districts in Nepal impacts are not specific to the particular characteristics of a single earthquake, and that total modeled impacts are skewed toward the minimum estimate. These results suggest that planning for the worst-case scenario in Nepal may place an unnecessarily large burden on the limited resources available for DRR. We also show that the most at-risk districts are predominantly in rural western Nepal, with ∼9.5 million Nepalis inhabiting districts with higher seismic risk than Kathmandu. Our proposed approach provides a holistic consideration of seismic risk for informing contingency planning and allows the relative importance of the reducible components of risk (exposure and vulnerability) to be estimated, highlighting factors that can be targeted most effectively. We propose this approach for informing contingency planning, especially in locations where information on the likelihood of future earthquakes is inadequate.

Robust relationship between air quality and infant mortality in Africa

Poor air quality is thought to be an important mortality risk factor globally^1-3, but there is little direct evidence from the developing world on how mortality risk varies with changing exposure to ambient particulate matter. Current global estimates apply exposure-response relationships that have been derived mostly from wealthy, mid-latitude countries to spatial population data⁴, and these estimates remain unvalidated across large portions of the globe. Here we combine household survey-based information on the location and timing of nearly 1 million births across sub-Saharan Africa with satellite-based estimates⁵ of exposure to ambient respirable particulate matter with an aerodynamic diameter less than 2.5 μm (PM_2.5) to estimate the impact of air quality on mortality rates among infants in Africa. We find that a 10 μg m^-3 increase in PM_2.5 concentration is associated with a 9% (95% confidence interval, 4-14%) rise in infant mortality across the dataset. This effect has not declined over the last 15 years and does not diminish with higher levels of household wealth. Our estimates suggest that PM_2.5 concentrations above minimum exposure levels were responsible for 22% (95% confidence interval, 9-35%) of infant deaths in our 30 study countries and led to 449,000 (95% confidence interval, 194,000-709,000) additional deaths of infants in 2015, an estimate that is more than three times higher than existing estimates that attribute death of infants to poor air quality for these countries^2,6. Upward revision of disease-burden estimates in the studied countries in Africa alone would result in a doubling of current estimates of global deaths of infants that are associated with air pollution, and modest reductions in African PM_2.5 exposures are predicted to have health benefits to infants that are larger than most known health interventions.

Assessing urban adaptive capacity to climate change

Despite the growing number of studies focusing on urban vulnerability to climate change, adaptive capacity, which is a key component of the IPCC definition of vulnerability, is rarely assessed quantitatively. We examine the capacity of adaptation in the Concepción Metropolitan Area, Chile. A flexible methodology based on spatial fuzzy modelling was developed to standardise and aggregate, through a stepwise approach, seventeen indicators derived from widely available census statistical data into an adaptive capacity index. The results indicate that all the municipalities in the CMA increased their level of adaptive capacity between 1992 and 2002. However, the relative differences between municipalities did not change significantly over the studied timeframe. Fuzzy overlay allowed us to standardise and to effectively aggregate indicators with differing ranges and granularities of attribute values into an overall index. It also provided a conceptually sound and reproducible means of exploring the interplay of many indicators that individually influence adaptive capacity. Furthermore, it captured the complex, aggregated and continued nature of the adaptive capacity, favouring to deal with gaps of data and knowledge associated with the concept of adaptive capacity. The resulting maps can help identify municipalities where adaptive capacity is weak and identify which components of adaptive capacity need strengthening. Identification of these capacity conditions can stimulate dialogue amongst policymakers and stakeholders regarding how to manage urban areas and how to prioritise resources for urban development in ways that can also improve adaptive capacity and thus reduce vulnerability to climate change.

A Comparative Analysis of Disaster Risk, Vulnerability and Resilience Composite Indicators

Introduction: In the past decade significant attention has been given to the development of tools that attempt to measure the vulnerability, risk or resilience of communities to disasters. Particular attention has been given to the development of composite indices to quantify these concepts mirroring their deployment in other fields such as sustainable development. Whilst some authors have published reviews of disaster vulnerability, risk and resilience composite indicator methodologies, these have been of a limited nature. This paper seeks to dramatically expand these efforts by analysing 106 composite indicator methodologies to understand the breadth and depth of practice.

Methods: An extensive search of the academic and grey literature was undertaken for composite indicator and scorecard methodologies that addressed multiple/all hazards; included social and economic aspects of risk, vulnerability or resilience; were sub-national in scope; explained the method and variables used; focussed on the present-day; and, had been tested or implemented. Information on the index construction, geographic areas of application, variables used and other relevant data was collected and analysed.

Results: Substantial variety in construction practices of composite indicators of risk, vulnerability and resilience were found. Five key approaches were identified in the literature, with the use of hierarchical or deductive indices being the most common. Typically variables were chosen by experts, came from existing statistical datasets and were combined by simple addition with equal weights. A minimum of 2 variables and a maximum of 235 were used, although approximately two thirds of methodologies used less than 40 variables. The 106 methodologies used 2298 unique variables, the most frequently used being common statistical variables such as population density and unemployment rate. Classification of variables found that on average 34% of the variables used in each methodology related to the social environment, 25% to the disaster environment, 20% to the economic environment, 13% to the built environment, 6% to the natural environment and 3% were other indices. However variables specifically measuring action to mitigate or prepare for disasters only comprised 12%, on average, of the total number of variables in each index. Only 19% of methodologies employed any sensitivity or uncertainty analysis and in only a single case was this comprehensive.

Discussion: A number of potential limitations of the present state of practice and how these might impact on decision makers are discussed. In particular the limited deployment of sensitivity and uncertainty analysis and the low use of direct measures of disaster risk, vulnerability and resilience could significantly limit the quality and reliability of existing methodologies. Recommendations for improvements to indicator development and use are made, as well as suggested future research directions to enhance the theoretical and empirical knowledge base for composite indicator development.

Macroeconomics of Natural Disasters: Strengths and Weaknesses of Meta-Analysis Versus Review of Literature

We use the case of the macroeconomic impact of natural disasters to analyze strengths and weaknesses of meta-analysis in an emerging research field. Macroeconomists have published on this issue since 2002 (we identified 60 studies to date). The results of the studies are contradictory and therefore the need to synthesize the available research is evident. Meta-analysis is a useful method in this field. An important aim of our article is to show how one can use the identified methodological characteristics to better understand the robustness and importance of new findings. To provide a comparative perspective, we contrast our meta-analysis and its findings with the major influential research synthesis in the field: the IPCC's 2012 special report Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. We show that the IPCC could have been more confident about the negative economic impact of disasters and more transparent on inclusion and qualification of studies, if it had been complemented by a meta-analysis. Our meta-analysis shows that, controlling for modeling strategies and data set, the impact of disasters is significantly negative. The evidence is strongest for direct costs studies where we see no difference between our larger sample and the studies included in the IPCC report. Direct cost studies and indirect cost studies differ significantly, both in terms of the confidence that can be attached to a negative impact of natural disasters and in terms of the sources of heterogeneity of the findings reported in the primary studies.

Trends in water level and flooding in Dhaka, Bangladesh and their impact on mortality

Climate change is expected to impact flooding in many highly populated coastal regions, including Dhaka (Bangladesh), which is currently among the fastest growing cities in the world. In the past, high mortality counts have been associated with extreme flood events. We first analyzed daily water levels of the past 100 years in order to detect potential shifts in extremes. A distributed lag non-linear model was then used to examine the connection between water levels and mortality. Results indicate that for the period of 2003–2007, which entails two major flood events in 2004 and 2007, high water levels do not lead to a significant increase in relative mortality, which indicates a good level of adaptation and capacity to cope with flooding. However, following low water levels, an increase in mortality could be found. As our trend analysis of past water levels shows that minimum water levels have decreased during the past 100 years, action should be taken to ensure that the exposed population is also well-adapted to drought.

Projected climate impacts to South African maize and wheat production in 2055: a comparison of empirical and mechanistic modeling approaches

Crop model-specific biases are a key uncertainty affecting our understanding of climate change impacts to agriculture. There is increasing research focus on intermodel variation, but comparisons between mechanistic (MMs) and empirical models (EMs) are rare despite both being used widely in this field. We combined MMs and EMs to project future (2055) changes in the potential distribution (suitability) and productivity of maize and spring wheat in South Africa under 18 downscaled climate scenarios (9 models run under 2 emissions scenarios). EMs projected larger yield losses or smaller gains than MMs. The EMs' median-projected maize and wheat yield changes were -3.6% and 6.2%, respectively, compared to 6.5% and 15.2% for the MM. The EM projected a 10% reduction in the potential maize growing area, where the MM projected a 9% gain. Both models showed increases in the potential spring wheat production region (EM = 48%, MM = 20%), but these results were more equivocal because both models (particularly the EM) substantially overestimated the extent of current suitability. The substantial water-use efficiency gains simulated by the MMs under elevated CO2 accounted for much of the EM-MM difference, but EMs may have more accurately represented crop temperature sensitivities. Our results align with earlier studies showing that EMs may show larger climate change losses than MMs. Crop forecasting efforts should expand to include EM-MM comparisons to provide a fuller picture of crop-climate response uncertainties.

Hospital Disaster Preparedness as Measured by Functional Capacity: a Comparison between Iran and Sweden

Introduction

Hospitals are expected to continue to provide medical care during disasters. However, they often fail to function under these circumstances. Vulnerability to disasters has been shown to be related to the socioeconomic level of a country. This study compares hospital preparedness, as measured by functional capacity, between Iran and Sweden.

Methods

Hospital affiliation and size, and type of hazards, were compared between Iran and Sweden. The functional capacity was evaluated and calculated using the Hospital Safety Index (HSI) from the World Health Organization. The level and value of each element was determined, in consensus, by a group of evaluators. The sum of the elements for each sub-module led to a total sum, in turn, categorizing the functional capacity into one of three categories: A) functional; B) at risk; or C) inadequate.

Results

The Swedish hospitals (n = 4) were all level A, while the Iranian hospitals (n = 5) were all categorized as level B, with respect to functional capacity. A lack of contingency plans and the availability of resources were weaknesses of hospital preparedness. There was no association between the level of hospital preparedness and hospital affiliation or size for either country.

Conclusion

The results suggest that the level of hospital preparedness, as measured by functional capacity, is related to the socioeconomic level of the country. The challenge is therefore to enhance hospital preparedness in countries with a weaker economy, since all hospitals need to be prepared for a disaster. There is also room for improvement in more affluent countries.

DjalaliA, CastrenM, KhankehH, GrythD, RadestadM, OhlenG, KurlandL. Hospital disaster preparedness as measured by functional capacity: a comparison between Iran and Sweden. Prehosp Disaster Med.2013;28(5):1-8.

A human development framework for CO2 reductions

Although developing countries are called to participate in CO₂ emission reduction efforts to avoid dangerous climate change, the implications of proposed reduction schemes in human development standards of developing countries remain a matter of debate. We show the existence of a positive and time-dependent correlation between the Human Development Index (HDI) and per capita CO₂ emissions from fossil fuel combustion. Employing this empirical relation, extrapolating the HDI, and using three population scenarios, the cumulative CO₂ emissions necessary for developing countries to achieve particular HDI thresholds are assessed following a Development As Usual approach (DAU). If current demographic and development trends are maintained, we estimate that by 2050 around 85% of the world’s population will live in countries with high HDI (above 0.8). In particular, 300 Gt of cumulative CO₂ emissions between 2000 and 2050 are estimated to be necessary for the development of 104 developing countries in the year 2000. This value represents between 20 % to 30 % of previously calculated CO₂ budgets limiting global warming to 2°C. These constraints and results are incorporated into a CO₂ reduction framework involving four domains of climate action for individual countries. The framework reserves a fair emission path for developing countries to proceed with their development by indexing country-dependent reduction rates proportional to the HDI in order to preserve the 2°C target after a particular development threshold is reached. For example, in each time step of five years, countries with an HDI of 0.85 would need to reduce their per capita emissions by approx. 17% and countries with an HDI of 0.9 by 33 %. Under this approach, global cumulative emissions by 2050 are estimated to range from 850 up to 1100 Gt of CO₂. These values are within the uncertainty range of emissions to limit global temperatures to 2°C.

Assessing the vulnerability of traditional maize seed systems in Mexico to climate change

Climate change is predicted to have major impacts on small-scale farmers in Mexico whose livelihoods depend on rain-fed maize. We examined the capacity of traditional maize seed systems to provide these farmers with appropriate genetic material under predicted agro-ecological conditions associated with climate change. We studied the structure and spatial scope of seed systems of 20 communities in four transects across an altitudinal gradient from 10-2,980 m above sea level in five states of eastern Mexico. Results indicate that 90% of all of the seed lots are obtained within 10 km of a community and 87% within an altitudinal range of ±50 m but with variation across four agro-climate environments: wet lowland, dry lowland, wet upper midlatitude, and highlands. Climate models suggest a drying and warming trend for the entire study area during the main maize season, leading to substantial shifts in the spatial distribution patterns of agro-climate environments. For all communities except those in the highlands, predicted future maize environments already are represented within the 10-km radial zones, indicating that in the future farmers will have easy access to adapted planting material. Farmers in the highlands are the most vulnerable and probably will need to acquire seed from outside their traditional geographical ranges. This change in seed sources probably will entail important information costs and the development of new seed and associated social networks, including improved linkages between traditional and formal seed systems and more effective and efficient seed-supply chains. The study has implications for analogous areas elsewhere in Mexico and around the world.