scholarly journals Early warning systems for food security in West Africa: evolution, achievements and challenges

2011 ◽  
Vol 12 (1) ◽  
pp. 142-148 ◽  
Author(s):  
L. Genesio ◽  
M. Bacci ◽  
C. Baron ◽  
B. Diarra ◽  
A. Di Vecchia ◽  
...  
Keyword(s):  
Food Security ◽  
West Africa ◽  
Early Warning ◽  
Early Warning Systems ◽  
Warning Systems

Assessment of Food Security Early Warning Systems for East and Southern Africa

10.1596/29269 ◽  
2018 ◽  
Author(s):  
Ademola Braimoh ◽  
Bernard Manyena ◽  
Grace Obuya ◽  
Francis Muraya
Keyword(s):  
Food Security ◽  
Southern Africa ◽  
Early Warning ◽  
Early Warning Systems ◽  
Warning Systems

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.

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.

Systematic User Feedback to Co-develop a Flood Early Warning System in West Africa

2021 ◽  
Author(s):  
Martijn Kuller ◽  
Jafet Andersson ◽  
Judit Lienert
Keyword(s):  
West Africa ◽  
Early Warning ◽  
Rainy Season ◽  
Emergency Services ◽  
Early Warning Systems ◽  
End Users ◽  
General Assembly ◽  
Warning Systems ◽  
System Components ◽  
Hydrological Services

<p><strong>Introduction</strong></p><p>The Horizon 2020 project FANFAR (www.fanfar.eu) aims to develop a Flood Early Warning Systems (FEWS) for West Africa. Prospective end-users of the FANFAR system include the hydrological services and emergency services of 17 countries in West Africa. Close involvement of end-users during the development phase can enhance effectiveness and usefulness of early warning systems (Reid, 2006). Therefore, FANFAR took a co-development approach between the consortium of developers and the end-users (Andersson, Ali, et al., 2020). Important vehicle for co-development are three workshops, organised over three years by the development consortium. Workshops were attended by one representative from hydrological services and one from emergency services from each country. The objectives of co-development included: tailoring to user- and context specific preferences and requirements, acquiring technical feedback on system components, enhancing user skills and capacity, building trust and ownership, enabling performance testing and enhancing system uptake.</p><p><strong>Approach</strong></p><p>Several strategies and interventions have been deployed to meet the objectives. Firstly, a Multi-Criteria Decision Analysis was conducted to establish the end-users’ primary objectives and system configurations to best meet these (Lienert, Andersson, & Silva Pinto, 2020). Furthermore, including the execution of regular surveys to explore user experiences with the system and receive technical feedback. Two different pen-and-paper surveys were taken during the both the second and third workshop sessions: (1) a survey exploring long-term and detailed information on usage, performance, preferences, obstacles and experience of using FANFAR and (2) a survey eliciting detailed technical feedback on separate system components. A third, shorter survey was conducted online on a monthly basis during the rainy season (May-October 2020) focussing on day-to-day operational usage and performance. Here, we summarise some main insights from these three types of surveys.</p><p><strong>Outcomes</strong></p><p>The data on user experience with the FANFAR system gathered during these interventions enabled the development team to improve the forecast system. For example, accuracy was identified as critical issue to improve. In response, the development team initiated several activities aimed at improving accuracy, including model calibration, catchment re-delineation, assimilation of local streamflow observations and EO data, and utilising alternative meteorological data (Andersson, Santos, et al., 2020).</p><p>There was an important discrepancy between the reported overwhelming intention to use FANFAR (82-93%) and the actual usage (28-46%). One reason could be related to the reported barrier posed by the initial state of the system, and the lack of accuracy mentioned above. Furthermore, priorities and resources might partly explain these numbers. However, these finding could be skewed by the changing composition of respondents between surveys, compromising their representativeness. Indeed, the user statistics of the online platform show a rise in visits. Finally, users seem to prioritise a functional system delivering daily predictions over a complex system with broad functionality.</p><p>Overall, our co-development has been a positive one. Participation has been strong and continuous, with an increasing number of organisations and their representatives partaking in workshops. In addition, participation outside the workshops (during the rainy season) was encouraging, particularly in the light of its voluntary nature.</p><p><strong>References</strong><br>Andersson, J., Ali, A., Arheimer, B., Crochemore, L., Gbobaniyi, B., Gustafsson, D., . . . Machefer, M. (2020). Flood forecasting and alerts in West Africa-experiences from co-developing a pre-operational system at regional scale. Paper presented at the EGU General Assembly Conference Abstracts.<br>Andersson, J., Santos, L., Isberg, K., Gustafsson, D., Musuuza, J., Minoungou, B., & Crochemore, L. (2020). Deliverable: D3.2 Report documenting and explaining the hydrological models. Retrieved from available at: https://fanfar.eu/resources/:<br>Lienert, J., Andersson, J., & Silva Pinto, F. (2020). Co-designing a flood forecasting and alert system in West Africa with decision-making methods: the transdisciplinary project FANFAR. Paper presented at the EGU General Assembly Conference Abstracts.<br>Reid, B. (2006). Global early warning systems for natural hazards: systematic and people-centred. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 364(1845), 2167-2182. doi:doi:10.1098/rsta.2006.1819</p>

The CARE Telematics Network for the Surveillance of Influenza in Europe

1995 ◽  
Vol 34 (05) ◽  
pp. 518-522 ◽  
Author(s):  
M. Bensadon ◽  
A. Strauss ◽  
R. Snacken
Keyword(s):  
Public Health ◽  
Early Warning ◽  
Early Warning Systems ◽  
Warning Systems ◽  
Surveillance Networks ◽  
Spanish Flu ◽  
The 1950S ◽  
National Networks ◽  
First Time

Abstract:Since the 1950s, national networks for the surveillance of influenza have been progressively implemented in several countries. New epidemiological arguments have triggered changes in order to increase the sensitivity of existent early warning systems and to strengthen the communications between European networks. The WHO project CARE Telematics, which collects clinical and virological data of nine national networks and sends useful information to public health administrations, is presented. From the results of the 1993-94 season, the benefits of the system are discussed. Though other telematics networks in this field already exist, it is the first time that virological data, absolutely essential for characterizing the type of an outbreak, are timely available by other countries. This argument will be decisive in case of occurrence of a new strain of virus (shift), such as the Spanish flu in 1918. Priorities are now to include other existing European surveillance networks.

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