Climate and Health across Africa

2017 ◽  
Author(s):  
Benjamin F. Zaitchik
Keyword(s):  
Climate Change ◽  
Infectious Disease ◽  
Climate Variability ◽  
Early Warning ◽  
Climate Extremes ◽  
Early Warning Systems ◽  
Climate Impacts ◽  
Temperature Extremes ◽  
Crop Failure ◽  
Weak Institutions

Humans have understood the importance of climate to human health since ancient times. In some cases, the connections appear to be obvious: a flood can cause drownings, a drought can lead to crop failure and hunger, and temperature extremes pose a risk of exposure. In other cases, the connections are veiled by complex or unobserved processes, such that the influence of climate on a disease epidemic or a conflict can be difficult to diagnose. In reality, however, all climate impacts on health are mediated by some combination of natural and human dynamics that cause individuals or populations to be vulnerable to the effects of a variable or changing climate.Understanding and managing negative health impacts of climate is a global challenge. The challenge is greater in regions with high poverty and weak institutions, however, and Africa is a continent where the health burden of climate is particularly acute. Observed climate variability in the modern era has been associated with widespread food insecurity, significant epidemics of infectious disease, and loss of life and livelihoods to climate extremes. Anthropogenic climate change is a further stress that has the potential to increase malnutrition, alter the distribution of diseases, and bring more frequent hydrological and temperature extremes to many regions across the continent.Skillful early warning systems and informed climate change adaptation strategies have the potential to enhance resilience to short-term climate variability and to buffer against negative impacts of climate change. But effective warnings and projections require both scientific and institutional capacity to address complex processes that are mediated by physical, ecological, and societal systems. Here the state of understanding climate impacts on health in Africa is summarized through a selective review that focuses on food security, infectious disease, and extreme events. The potential to apply scientific understanding to early warning and climate change projection is also considered.

scholarly journals Observed Trends in Indices of Daily Temperature Extremes in South America 1960–2000

2005 ◽  
Vol 18 (23) ◽  
pp. 5011-5023 ◽  
Author(s):  
L. A. Vincent ◽  
T. C. Peterson ◽  
V. R. Barros ◽  
M. B. Marino ◽  
M. Rusticucci ◽  
...  
Keyword(s):  
Climate Change ◽  
South America ◽  
Climate Extremes ◽  
Daily Temperature ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Temperature Extremes ◽  
Increasing Trends

Abstract A workshop on enhancing climate change indices in South America was held in Maceió, Brazil, in August 2004. Scientists from eight southern countries brought daily climatological data from their region for a meticulous assessment of data quality and homogeneity, and for the preparation of climate change indices that can be used for analyses of changes in climate extremes. This study presents an examination of the trends over 1960–2000 in the indices of daily temperature extremes. The results indicate no consistent changes in the indices based on daily maximum temperature while significant trends were found in the indices based on daily minimum temperature. Significant increasing trends in the percentage of warm nights and decreasing trends in the percentage of cold nights were observed at many stations. It seems that this warming is mostly due to more warm nights and fewer cold nights during the summer (December–February) and fall (March–May). The stations with significant trends appear to be located closer to the west and east coasts of South America.

scholarly journals Recognizing the Famine Early Warning Systems Network: Over 30 Years of Drought Early Warning Science Advances and Partnerships Promoting Global Food Security

2019 ◽  
Vol 100 (6) ◽  
pp. 1011-1027 ◽  
Author(s):  
Chris Funk ◽  
Shraddhanand Shukla ◽  
Wassila Mamadou Thiaw ◽  
James Rowland ◽  
Andrew Hoell ◽  
...  
Keyword(s):  
Food Security ◽  
Early Warning ◽  
Warning System ◽  
Climate Extremes ◽  
Early Warning Systems ◽  
Food Prices ◽  
Humanitarian Assistance ◽  
Warning Systems ◽  
Recent Climate ◽  
Drought Early Warning

AbstractOn a planet with a population of more than 7 billion, how do we identify the millions of drought-afflicted people who face a real threat of livelihood disruption or death without humanitarian assistance? Typically, these people are poor and heavily dependent on rainfed agriculture and livestock. Most live in Africa, Central America, or Southwest Asia. When the rains fail, incomes diminish while food prices increase, cutting off the poorest (most often women and children) from access to adequate nutrition. As seen in Ethiopia in 1984 and Somalia in 2011, food shortages can lead to famine. Yet these slow-onset disasters also provide opportunities for effective intervention, as seen in Ethiopia in 2015 and Somalia in 2017. Since 1985, the U.S. Agency for International Development’s Famine Early Warning Systems Network (FEWS NET) has been providing evidence-based guidance for effective humanitarian relief efforts. FEWS NET depends on a Drought Early Warning System (DEWS) to help understand, monitor, model, and predict food insecurity. Here we provide an overview of FEWS NET’s DEWS using examples from recent climate extremes. While drought monitoring and prediction provides just one part of FEWS NET’s monitoring system, it draws from many disciplines—remote sensing, climate prediction, agroclimatic monitoring, and hydrologic modeling. Here we describe FEWS NET’s multiagency multidisciplinary DEWS and Food Security Outlooks. This DEWS uses diagnostic analyses to guide predictions. Midseason droughts are monitored using multiple cutting-edge Earth-observing systems. Crop and hydrologic models can translate these observations into impacts. The resulting information feeds into FEWS NET reports, helping to save lives by motivating and targeting timely humanitarian assistance.

Global contribution of climate variability and trends to maize yield change in observations and crop models during 1980-2010

2020 ◽  
Author(s):  
Xiaomeng Yin ◽  
Guoyong Leng
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Statistical Model ◽  
Yield Loss ◽  
Climate Change Impacts ◽  
Maize Yield ◽  
Climate Impacts ◽  
Future Climate Change ◽  
Crop Models ◽  
Process Based Models

<p>Understanding historical crop yield response to climate change is critical for projecting future climate change impacts on yields. Previous assessments rely on statistical or process-based crop models, but each has its own strength and weakness. A comprehensive comparison of climate impacts on yield between the two approaches allows for evaluation of the uncertainties in future yield projections. Here we assess the impacts of historical climate change on global maize yield for the period 1980-2010 using both statistical and process-based models, with a focus on comparing the performances between the two approaches. To allow for reasonable comparability, we develop an emulator which shares the same structure with the statistical model to mimic the behaviors of process-based models. Results show that the simulated maize yields in most of the top 10 producing countries are overestimated, when compared against FAO observations. Overall, GEPIC, EPIC-IIASA and EPIC-Boku show better performance than other models in reproducing the observed yield variations at the global scale. Climate variability explains 42.00% of yield variations in observation-based statistical model, while large discrepancy is found in crop models. Regionally, climate variability is associated with 55.0% and 52.20% of yield variations in Argentina and USA, respectively. Further analysis based on process-based model emulator shows that climate change has led to a yield loss by 1.51%-3.80% during the period 1980-1990, consistent with the estimations using the observation-based statistical model. As for the period 1991-2000, however, the observed yield loss induced by climate change is only captured by GEPIC and pDSSAT. In contrast to the observed positive climate impact for the period 2001-2010, CLM-Crop, EPIC-IIASA, GEPIC, pAPSIM, pDSSAT and PEGASUS simulated negative climate effects. The results point to the discrepancy between process-based and statistical crop models in simulating climate change impacts on maize yield, which depends on not only the regions, but also the specific time period. We suggest that more targeted efforts are required for constraining the uncertainties of both statistical and process-based crop models for future yield predictions. </p>

scholarly journals Influence of ENSO and tropical Atlantic climate variability on flood characteristics in the Amazon basin

2020 ◽  
Author(s):  
Jamie Towner ◽  
Andrea Ficchí ◽  
Hannah L. Cloke ◽  
Juan Bazo ◽  
Erin Coughlan de Perez ◽  
...  
Keyword(s):  
Climate Variability ◽  
Early Warning ◽  
Large Scale ◽  
Amazon Basin ◽  
Early Warning Systems ◽  
Discharge Data ◽  
Flood Magnitude ◽  
Highly Correlated ◽  
The Impact ◽  
Flood Characteristics

Abstract. Flooding in the Amazon basin is frequently attributed to modes of large-scale climate variability, but little attention is paid to how these modes influence the timing and duration of floods despite their importance to early warning systems and the significant impacts that these flood characteristics can have on communities. In this study, river discharge data from the Global Flood Awareness System (GloFAS 2.1) and observed data at 58 gauging stations are used to examine whether positive/negative phases of several Pacific and Atlantic indices significantly alter the characteristics of river flows throughout the Amazon basin (1979–2015). Results show significant changes in both flood magnitude and duration, particularly in the north-eastern Amazon for negative ENSO years when the SST anomaly is positioned in the central tropical Pacific. This response is not identified for the eastern Pacific index, highlighting how the response can differ between ENSO types. Although flood magnitude and duration were found to be highly correlated, the impacts of large-scale climate variability on these characteristics are non-linear; some increases in annual flood maxima coincide with decreases in flood duration. The impact of flood timing however does not follow any notable pattern for all indices analysed. Finally, observed and simulated changes are found to be much more highly correlated for negative ENSO years compared to the positive phase, meaning that GloFAS struggles to accurately simulate the differences in flood characteristics between El Niño and neutral years. These results have important implications for both the social and physical sectors working towards the improvement of early warning action systems for floods.

scholarly journals Ethics, Integrity, and Retributions of Digital Detection Surveillance Systems for Infectious Diseases: Systematic Literature Review (Preprint)

2021 ◽  
Author(s):  
Ivy Y Zhao ◽  
Ye Xuan Ma ◽  
Man Wai Cecilia Yu ◽  
Jia Liu ◽  
Wei Nan Dong ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Infectious Disease ◽  
Civil Rights ◽  
Infectious Diseases ◽  
Early Warning ◽  
Ethical Issues ◽  
Early Warning Systems ◽  
Surveillance Systems ◽  
Warning Systems ◽  
Digital Surveillance

BACKGROUND The COVID-19 pandemic has increased the importance of the deployment of digital detection surveillance systems to support early warning and monitoring of infectious diseases. These opportunities create a “double-edge sword,” as the ethical governance of such approaches often lags behind technological achievements. OBJECTIVE The aim was to investigate ethical issues identified from utilizing artificial intelligence–augmented surveillance or early warning systems to monitor and detect common or novel infectious disease outbreaks. METHODS In a number of databases, we searched relevant articles that addressed ethical issues of using artificial intelligence, digital surveillance systems, early warning systems, and/or big data analytics technology for detecting, monitoring, or tracing infectious diseases according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, and further identified and analyzed them with a theoretical framework. RESULTS This systematic review identified 29 articles presented in 6 major themes clustered under individual, organizational, and societal levels, including awareness of implementing digital surveillance, digital integrity, trust, privacy and confidentiality, civil rights, and governance. While these measures were understandable during a pandemic, the public had concerns about receiving inadequate information; unclear governance frameworks; and lack of privacy protection, data integrity, and autonomy when utilizing infectious disease digital surveillance. The barriers to engagement could widen existing health care disparities or digital divides by underrepresenting vulnerable and at-risk populations, and patients’ highly sensitive data, such as their movements and contacts, could be exposed to outside sources, impinging significantly upon basic human and civil rights. CONCLUSIONS Our findings inform ethical considerations for service delivery models for medical practitioners and policymakers involved in the use of digital surveillance for infectious disease spread, and provide a basis for a global governance structure. CLINICALTRIAL PROSPERO CRD42021259180; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=259180

The Sahel faces complex food and climate challenges

2019 ◽  
Keyword(s):  
Climate Change ◽  
Food Security ◽  
Early Warning ◽  
Early Warning Systems ◽  
Warning Systems ◽  
Content Type ◽  
Good Basis ◽  
Sustained Development ◽  
Full Benefit

Subject Food security and climate change challenges in the Sahel. Significance Despite improved cereal output in 2018-19, many communities have entered the annual ‘lean season’ in a fragile position. Climate change is slowly destabilising the regional balance, while spreading insecurity prevents the region from realising the full benefit of its sustained development efforts. Impacts At 17.7% above the five-year average, the 2018-19 cereal harvest offers a good basis to meet needs during the May-September lean season. Local shortages should be spotted by robust regional early warning systems, with emergency grain stocks and donors ready to step in. Pastoralist populations are in a particularly vulnerable position, as insecurity affects access to many important grazing zones.

scholarly journals Indicators to monitor policy progress in health adaptation to climate change: do they really do the job?

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
G Sanchez Martinez ◽  
MC Tirado von der Pahlen ◽  
V Kendrovski ◽  
C Linares ◽  
J Diaz
Keyword(s):  
Climate Change ◽  
Air Pollution ◽  
Environmental Health ◽  
Social Protection ◽  
Resource Planning ◽  
Early Warning Systems ◽  
Climate Impacts ◽  
Saharan Dust ◽  
Integrative Approach ◽  
Climate Services

Abstract There is a need for urgent adaptive action to protect human health against climate change. Overall assessments based on a selection of indicators suggest that we are unable to cope with current climate impacts on health and unprepared to respond to increased pressures on climate-sensitive exposures and outcomes. The health sector has been addressing climate adaptation to health, through siloed approaches limited to the health system, which reduces their capacity and effectiveness. Successful strategies for addressing climate and environmental degradation challenges to health, and related issues such as environmental health, nutrition or equity, require integrated adaptation approaches among the health systems, social protection systems, water and sanitation systems, urban planning, environmental health and climate services among others. For example, integrated monitoring and surveillance (human-animal-environmental-ecosystems health) is critical for the early identification of emerging risks, diseases or trends, and for resource planning and evaluation of the adaptation and control strategies. In addition, when climate and health indicators are put to use for prevention, and eventually adaptation, they are also frequently used in isolation, disregarding interactions. For example, early warning systems for the prevention of climate-influenced impacts on health, such as Heat Health Action Plans, air pollution warnings or allergenic pollen information systems are usually activated individually commonly fail to address the synergies across various climate-related or climate-aggravated exposures. Since various of those exposures tend to occur concurrently (e.g. heat, anthropogenic air pollution from thermal inversions, and Saharan dust intrusions), failure to integrate them in prevention efforts could affect their effectiveness and reach. Thus, there is a need to carry out an integrative approach for the multiple effects that climate change has on population health.

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