Each food security information system has to be methodically analysed and technical improvements proposed. Any help and improvements deemed necessary or useful must not involve changing their structure. Technical assistance will be provided by the members of the corresponding MWGs, whose respective national managers are influential members and often the lead managers. All members of the MWGs, and not only those in charge of the statistics systems, will be involved in the process of technically improving the collection and processing of data, in order to ensure overall cohesion in setting up the system, since each one has to understand the process and participate in it. Moreover, this broader participation of the MWG members is essential from the sustainability point of view, since there can be a rapid change-over rate among national representatives. It is therefore desirable that a large number of managerial staff be involved in this process of technical refinement.
The various existing monitoring systems have been described briefly in Part One (Chapter III, Section 1). Agricultural production monitoring systems are to be found, at different levels of development, in all countries, but a number of them need to be improved so that they can play their part in the collection and processing of data. It should be noted that the monitoring of agricultural production should take into account all basic food products: foodstuffs, products of stock raising or fisheries. In practice, it appears that only food products are monitored, the reasons for which are a combination of convenience and commercial interests.
One of the first things to take into consideration in improving the monitoring of food production is that diversity in agro-climatic environments can lead to very different methods being adopted. While in the semi-arid zones agricultural production is limited to a narrow range of farming systems where the food-crop (and even animal) productivity depends essentially on the water balance, the same cannot be said of the more humid zones where stock farming is much less widespread and agricultural production is dependent on a far greater number of factors:
So the first constraint any analysis of food-production monitoring data encounters is the need to know the environmental conditions in which the food is produced.
Another element of prime importance is, of course, the availability of correct and reliable statistics (also for multiple cropping). Often the published average yields and productions are "administrative" averages calculated for a wide range of production systems and not very representative of food production. National agricultural statistics services often have to overcome technical and financial problems as best they can, and the sample analysed is very often not at all representative of all the agricultural enterprises.
In monitoring food crops production, a distinction should be made between data used for the agro-ecological classifications and those used for crop monitoring during the agricultural season.
A necessary preliminary phase for all environmental conditions consists of dividing the area into agro-ecological zones according to the available resources (soil quality and fertility; temperature, rainfall, water balance and other meteorological data) and the main production systems. This classification is used to varying degrees in different countries according to the availability of information. There may be climatic classifications based on historical series of meteorological data (the most frequent being rainfall), pedological maps, maps of plant cover or grazing areas. The degree of detail in the maps is very variable but they are at times the only source of information for such studies. The classifications are not usually changed unless a new methodology offering a more precise analysis is adopted.
Example
|
|||||
AEZ |
Vegetation |
Altitude |
Rainfall |
No. days rain/year |
No. of months > 100 mm |
High Plains of Adamaoua |
Sudano-guinean savannah |
900-1400 |
Monomodal1500 mm |
110-150 |
7 |
South Cameroon Plain |
Mixed forest & derived savannah |
500-800 |
Bimodal1400-1600 |
125-175 |
7-9 |
Coastal low lands |
Evergreen forest |
0-500 |
Monomodal> 2000 mm |
180-240 |
9-12 |
Western high plains |
High savannah |
750-2000 |
Monomodal> 1750 mm |
175-220 |
7-9 |
More detailed analysis of the AEZs reveals a number of "agricultural production areas" based on specific soil and climatic conditions and the main food and perennial crop systems practised. |
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The map of Benin on the following page further illustrates agro-ecological zones.
Zoning is therefore one of the fundamental preliminary elements of the agricultural production monitoring process. On the other hand, the yields of the principal crops are broadly linked to several factors that can be summarized as follows:
In addition, some socio-economic factors do not have a direct influence on the crop yields but on the behaviour of peasant-farmers, influencing choices in relation to available manpower, the use of fertilizer, multiple cropping methods, etc., which does have an effect on yield and production. Similarly, market access has a strong influence on the planting of vegetable crops, which are difficult to keep fresh, because of the high costs related to losses or investment to avoid such losses. This is also true of continuous cropping plants, the overall yield of which is influenced by the distribution of the harvest over time, but also by whether the produce is traded fresh or dried.
Information on monitoring the crop year is collected and/or produced by the relevant services (statistics, extension, projects etc.) through their field networks, district agents, and decentralized offices. Clearly, the main factors affecting production (and therefore the information needed to monitor production) vary according to the agro-ecological zone. While in the semi-arid zones (rainfall less than 700/800 mm per year) the water balance can give an acceptable estimate of yields for cereals (i.e. sorghum, maize, millet), it only plays a secondary role in determining the yield of main crops in the Sudanian and tropical zones. Indeed in these areas, information on the phytosanitary status of crops is more important than rainfall, an excess of which can have a harmful effect on production. Data on the phenological development of crops provided by agricultural monitoring or extension workers therefore complete the necessary data.
Towards the end of the crop year, the harvest forecasting element, essential for the FSIEWS control panel, takes into account historical statistics, the estimation of yields and cultivated land, and information on production by crop and by administrative district. Although the administrative districts may not be homogeneous areas from the point of view of the above-mentioned zoning criteria, they provide a general reference for assessing harvests since statistics are available and aid requirements are identified at this level.
The approach to monitoring the main food crops and harvest forecasts varies markedly from one country to another but in general it is based on a combination of the following methods:
1. Assessment of cultivated areas for each system of production.
2. Assessment of yields based on:
3. Average production of agricultural households in each production area, based on quantitative (measured locally) and qualitative data.
4. Extrapolation of production at national and provincial levels based on (calculated) extrapolation constants.
In the box below, is a summary of all the factors mentioned and the elements necessary for their characterization.
Factors |
Characterization Elements |
- Total rainfall and distribution, in particular at the beginning and end
of the season, | |
Typical cropping combinations and farming methods: varieties, planting dates, combination and respective density of species, fertilizer, maintenance |
Production methods: |
Incidence of pests and diseases linked to the agro-climatic conditions of the production area, the varieties and production methods (multiple cropping, fertilizer, protection), etc. |
Frequency and incidence of pests and diseases (strongly linked to climatic conditions, varieties, farming practices) |
Priority given to food/cash crops produced by the household or to other activities affecting the availability of the work force at certain times of the year, and priorities of producers according to expected income |
- Presence and areas |
CAMEROON - AN EXAMPLE In the context of harvest forecasting, the mandate of the FSIEWS was limited to the principal food crops having a major impact on food security30. The following products were identified for south Cameroon: Tubers: cassava, new cocoyam/taro, yam + sweet potato, potato; In each agro-ecological zone a group of main food crops is examined according to the following outline: |
Adamaoua |
Southern Plateau |
Coastal Lowlands |
High Plateaus |
|
Main crops |
Cassava |
Plantain/Banana |
Plantain/Banana |
Maize |
|
Secondary crops31 |
YamSweet potato |
Yam |
Yam |
Cassava |
|
Cassava, plantain and banana all have crop cycles of two years or more. Cassava is a continuous cropping plant while plantain/banana is a periodic cropping plant. The other tropical roots and tubers (cocoyam, taro, yam) are annual crops with more limited harvest periods, generally within a single crop season32. All the other crops, including sweet potato and potato, are considered seasonal crops. | |||||
As mentioned above, the agricultural, meteorological, extension, plant protection, water, stock breeding, and other services are normally responsible for providing the data in their own fields. They may also analyse the data since they usually have good background knowledge of the history and local sociology and much experience in the field. The MWG for monitoring agricultural production (APM) is the institutional setting in which these analyses should regularly be carried out as part of the plan to exchange and make information available to all, to coordinate the work of the national services and civil society, and also to prepare bulletins and other methods of disseminating information. The APM/MWG should also be responsible for the harvest forecasts which, in the Sahel, for example, should be effected twice yearly: in November (provisional) and in March (final) for annual crops in the north. The agro-hydro-meteorological tables compiled every ten days are also useful to the APM/MWG.
The principal analytical methods are summarized below.
In climatological analysis, the meteorological conditions of the current year are assessed with the aid of historical series of data. Even when applied in difficult conditions (lack of data, few stations, etc.), the simulation models can project the effects of meteorological conditions on the crop cycles. They can, moreover, be useful in developing "scenarios" for determining yield variability ranges for the current year, with an acceptable degree of probability.
As is the case in most forecasting methods, the approach recommended by FAO is based on the water balance34. Using a series of parameters, the total water requirement is calculated as well as the water deficit or surplus in relation to rainfall and the real evapotranspiration (Etr). The estimated Etr for each year is calibrated using regression analysis and the yields provided by agricultural statistics.
This simplified approach based on rainfall, permits crop yields (of cereals in particular) in semi-arid areas to be estimated. However, the following modifications have been introduced to bring about a steady improvement in the system's performance:
This approach has already been tried experimentally in a number of meteorological services using various programmes. However, many problems were encountered relating to lack of skill in calibrating and refining the regression method for the different crops, taking into account the soil situation and production areas.
Forecasting Harvests
Production is calculated by multiplying the area sown by the estimated yield. The first step, therefore, is to estimate the yields. How reliable the estimate is depends on the care with which the calibration phase is carried out and the experience of the personnel in charge of the analyses. Models sometimes give yield results in the form of indices that have to be transformed into more understandable information (kg per hectare) using historical yield data published by national statistics services for each crop and administrative unit. The reliability of statistical data is of vital importance in that it directly affects the estimation of yields. Reliability, in turn, depends on the number of farms sampled and how representative they are (usually too limited) and on how carefully staff in charge of measurements and surveys in the field carry out their work.
Moreover, for the purposes of forecasting production, the areas sown or planted have to be estimated. This (often inaccurate) information is usually obtained by field agents from the local services of the Ministry of Agriculture, by extrapolating from the whole administrative district. The identification of "proxy" indicators of the area sown is still used in studies and research in several institutes and countries.
Satellite images are widely used in semi-arid areas. They are usually produced through the sensors installed on-board of NOAA35 and Meteosat36 satellites. Professional staff must be trained to analyse these images and in the use of the appropriate hardware and software equipment. The integration of satellite images into the overall analysis depends on the following technical options:
Several institutions have developed methodologies for monitoring the agricultural year in semi-arid areas (in particular the FAO-Agromet Group, the Agrhymet Centre in Niamey, the CSE in Dakar, the JRC of the European Community39). The products most frequently used in monitoring crops are the NDVI (with the option of a time profile for the zones concerned) and the estimated rainfall derived from Meteosat-CCD. Due to lack of resources and information for managerial staff, this work is not usually carried out by national services.
The methodologies described here can typically be applied to zones between the semi-arid and sub-humid regions of Africa, but the analytical principles are also applicable to other tropical regions of Africa, Asia and Latin America. The technical and functional constraints of these regions can be summarized as follows:
As mentioned above, the figures regarding food consumption per inhabitant and the total availability of food often do not take into account food stuffs of animal origin, fish, meat or other livestock products. These elements are sometimes integrated into the definition of basic diets and in the monitoring of vulnerable groups, although in most cases the agricultural production monitoring systems only consider food crops (and often only cereal crops). It is therefore a good idea to make sure that all the products mentioned in the list of staple foods (see the first stage) are included in the agricultural production monitoring system, i.e. for both the collection and analysis of data.
While the monitoring of food crops is often restricted, especially in dry zones, to monitoring the cropping season in order to predict the harvest, the monitoring of animal production (livestock, milk, eggs, chicken, fish, etc.) is more complex because production is continuous and more scattered.
Monitoring the availability of fish is possible when catches are recorded by national authorities (such as the Fisheries Authority) and when aquaculture production, which is quite large in some areas, is known.
Monitoring foodstuff production of animal origin often uses indirect indicators: monitoring grazing, veterinary activities (vaccinations, official slaughtering), and milk production by means of marketing information, etc. The most difficult aspect remains domestic self-sufficiency of these products: indeed it was often thought that nomadic herders in the semi-arid areas suffered chronic hunger as they lived mainly on milk and meat from their own stock (sometimes also dates, which are not monitored either) for much of the year. A few countries have carried out surveys, some of which were country-wide, to estimate animal production, both in sheds and free ranging. Veterinary services that monitor animal production have access to the estimates drawn from these surveys.
Monitoring fish and animal production is an essential part of monitoring agricultural production and the APM/MWG must use every means to set up a database, even if only approximate, for this purpose. This work can only be achieved through regular cooperation with the national and local people in charge of fish or animal production.
As was mentioned in Part 1, Chapter 2, it is possible to predict major variations in animal production using indirect indicators. Indirect indicators must nevertheless be compared with the most accurate data available on animal production and derived products (milk or egg products, for example) in each province.
Populations whose diet depends to a large extent on harvesting wild resources are often (wrongly) considered to be under-nourished, because there is no information on the quantities of products consumed. Even an approximate estimate of food gathered is nevertheless essential for monitoring agricultural production.
FAO has conducted an evaluation of Market Information Systems (MIS) in all FAO member countries on this subject. It revealed that although a large number of countries do have some sort of MIS, the services they offer cannot be considered to provide farmers and traders with commercially useful information. The MIS suffer from inadequate data-gathering, the incompetence of government officials, and general lack of resources. Often set up by donors, they become unsustainable after the donors' departure. There is a tendency when creating an MIS to plan such cumbersome structures that they prove difficult to manage.
In creating an MIS, the first consideration should be its commercial usefulness and viability. A detailed list should be drawn up of the needs of those involved in the marketing system and the MIS tailored to the available resources, only expanding it when additional funds have been acquired on a long-term basis43.
An MIS should be "transparent", providing everyone with a clear picture of the principal trends in markets and prices, in addition to other useful supplementary information on marketing and stocks. Not that information per se can halt price fluctuations or lead to perfect transparency: those involved in marketing will always have to take decisions based on data that is incomplete.
The golden rule is to start with an MIS of modest dimensions that can be expanded later as resources become available. Based on an analysis of the marketing system, it may be appropriate at the outset to have an MIS that only provides the ruling prices in the bigger markets, and to extend it later to cover prices in other wholesale markets and assembly markets. Where donors are involved, perspectives can become skewed and an MIS is likely to be proposed that is too big in relation to the country's capacity to maintain such a system. Beneficiaries find it difficult to refuse offers of aid and tend to focus on the immediate gains, ignoring the question of what will happen in the future, especially if a gradual approach is adopted.
First of all the country's capacity to operate an MIS should be examined from both a technical and financial point of view. The institutional organization needs to be closely examined and the potential for private-sector involvement looked into.
There are a number of possible satisfactory institutional settings for MIS that will vary from one country to another.
The first step is to carry out an in-depth analysis of the marketing system in order to assess the information requirements of each actor in the system (farmers, traders, commission agents, exporters, retailers, consumers, administrators, etc.). Such an analysis provides information on:
Detailed information on marketing channels for products is also necessary:
Monitoring markets
In selecting data for monitoring markets the following principal constraints should be taken into consideration:
Examples The Tanzanian MIS started out collecting prices of 27 products in 45 centres, but most of them were not used. The Ghanaian MIS was based on price-collecting in more than 100 markets but the Agricultural Ministry had to discontinue it due to lack of resources and training for agents in the field, although the MIS still has close to 100 full-time staff. When the MIS has a large number of markets to cover, it runs into the problem of how to manage such large amounts of information. There are not enough resources to pay for salaries, train data-collection agents and maintain the system. |
The storage of products
A good MIS should have precise knowledge of the storage systems throughout the commodity chain and to what extent they are utilized. All stocks (family stocks on the farm, village stocks of cereals, the various commercial stocks, national security stocks etc.) should be analysed and a system of assessing their value and contents be established. In addition, the loss-rate of stored products has to be estimated for each type of storage.
Imports and exports
The MIS needs precise agreements with customs services, ports, and official import and export authorization services for staple food products in order to assess the general status of national supplies and potential short- or medium-term changes in the situation. In some countries, estimates of the flow of food products (including animal products) may be obtained at provincial level from administrative controls carried out for the purpose of applying transport taxes.
The implementation of an MIS should also fulfil the following conditions:
Example of a working MIS A private MIS in South Africa Agritel is a privately run information service providing information on wholesale markets and eleven major abattoirs in South Africa. The markets are computerized and all transactions (price and volume) are recorded. Agritel receives information daily that it then processes and presents in a more user-friendly format. The service covers both price and volume data for all commodities, varieties, categories, sizes and packages. Agritel has about 400 users who pay a monthly fee of between US$28 and US$38 depending on the number of services and markets on which the user requires information. Users include producers, packers, caterers, butchers, wholesalers, market agents and the markets themselves. They can also access the national electronic transmission network (Beltel), either through a terminal hired from Beltel or through the use of a PC and modem. The telephone call to Beltel is free. The service offered by Beltel is menu-driven and easy to use. It provides the following information on the current and previous day's trading for each market: the highest price and volume traded at this price; In addition to trading information for the day, users can consult historical information using a graphics package supplied free of charge by Agritel to its major customers. This information shows trends from the start of the service. Agritel allows market information to be used to its full potential. |
The data processing should be kept simple. A close eye should be kept on computer experts who often tend to design systems that only they can understand. The designs should be flexible enough to provide for future expansion of the MIS but they should avoid being complex at all cost. Users have to be able to use the system easily on a daily basis, and be able to solve any problems that may arise.
The time factor needs to be given careful consideration in the system's design since daily, weekly and monthly reports are required and meaningful comparisons made between the different time periods and markets.
Data security is a major problem. The programmes and databases should be protected and regular checks carried out to make sure they have not been cancelled or accidentally changed. Files can be blocked and passwords used to prevent unauthorized access. But it is difficult to protect information since it is constantly being moved from one sheet to another, or from cell to cell. It is equally difficult to set up automatic checks on the data at the moment when it is being entered.
The media used to disseminate information should be relevant to MIS users. Considerable care should be taken over how the information is presented, and as much use as possible made of graphics. Long lists of prices read out on the radio can make for poor listening: lists should therefore be limited to the most important products, that is, those subject to the greatest price fluctuations. Fuller information can be published in the newspapers. Radio broadcasts should be interspersed with some commentary on market conditions and opportunities, although this lengthens the programme and increases the costs. Finally, and perhaps obviously, prices have to be broadcast in the languages spoken by the people using the MIS.
When an MIS begins radio broadcasting, one or two introductory broadcasts should be devoted to describing the service and providing farmers with the information necessary to be able to understand the prices broadcast. These broadcasts should be repeated periodically. In recent years FAO has developed training materials designed to give extension workers a good background in marketing matters.
Example of an MIS in Zambia Initially, prices and demand in markets was disseminated in three ways (weekly radio broadcasts, weekly market bulletins and price boards) which all suffered various setbacks. When another section of the ministry did not pay its bills, the radio station refused to broadcast any further information; an increase of 400 % in postal charges put an end to the weekly distribution of bulletins; while price boards were not favoured by farmers. These problems were eventually resolved: information is once again broadcast on the radio and published twice a week in a national newspaper, while the bulletin is now distributed thanks to sponsorship from a local bank. Future sustainability will depend on attracting and retaining such sponsorship. |
The FAO-AgriMarket software was developed by FAO to help governments establish agricultural market price lists, called Market Information Systems (MIS), and to improve the operation of existing systems. AgriMarket reduces the time and effort needed to manage large quantities of data and increases the accuracy of such work. The programme permits more information to be transmitted faster to all those involved and should thus help to increase market transparency. It can also be utilized for information regarding prices and quantities of agricultural inputs.
AgriMarket was developed using the database management system "MS ACCESS". It is a simple-to-use menu-driven package. It can monitor up to 891 products in 90 different markets, and the data can be input daily or weekly. The data checking functions enable users to establish price brackets for each product in each market, excluding prices outside these ranges. Conversion from local measurement units into standard units is incorporated into the programme, which saves time and eliminates calculation errors. Reports can be produced daily, weekly, monthly or quarterly, in a variety of ways, enabling users to obtain information on all or some of the markets or products for varying periods.
AgriMarket also has utilities for managing databases, enabling smooth manipulation of disks and files, and data transfer. Database management functions have been included to protect and restore files, index databases or store them. Its data import and export functions make it easy to transfer data between AgriMarket and other databases, spread sheets or graphics programmes. Data can thus be transferred to other programmes for more advanced analysis or to prepare graphs. Moreover, data already stored in computerized market information systems can be imported to AgriMarket without loss of information. The programme also has a simple built-in mailing system that can keep track of all those to whom market information is regularly sent, and create address labels.
Security functions have been built into the programme in order to discourage unauthorized access to the databases and to prevent unsuspecting users from executing potentially damaging commands. The overall programme is protected by passwords, the highest level of access being reserved for the system manager, who allows other users to access the system. The management functions permit users to change their password to obtain a summary of the system's status.
A very useful feature of the programme is the "tutorial" mode, which enables users to access the databases without affecting the real data contained in them. Training sessions can therefore be carried out alongside its use in normal mode and the processing of real data.
A user's guide accompanies the software. It deals principally with setting up a computer information system using AgriMarket in a typical marketing office. The guide gives a step-by-step explanation of how to code data and prepare the screen layouts before going on to explain how to actually use the programme. The case-study approach is effective, new users learning in tutorial mode can use the data contained in the guide for practice.
If AgriMarket is not used as an information management tool, then a commercial relational database management package (such as MS Access or Paradox ) should be used. Direct access to data can be fairly rigidly controlled and data-entry routines can be built in to include error checking features. Reports can also be organized to extract any necessary set of data automatically (any series of products, markets or time periods) with minimum manipulation of the database. Databases do, nevertheless, take more time to set up initially and require more highly trained staff than does a simple spread sheet.
In summary, data processing should follow the principle that the simplest solution is often the best. Allowing computer experts to design systems that they alone can understand is to be avoided at all costs. Moreover, the design should allow for possible future expansion of the MIS, but avoiding complexity as the users have to be able to use it with ease and solve any problems that arise.
The principal constraints that impede the smooth running of an MIS are the following:
Sometimes there is duplication of activities among the services that collect prices nationally and then disseminate them through the various bulletins. This can cause some confusion, particularly when there is no consistency between the data sets. In Cambodia in early 1996, the prices of agricultural products were collected by the ministry of agriculture, the ministry of trade, the statistics service in charge of the retail price index and by a local radio station (the only one to provide the farmers and traders with a useful service).
Forecasting difficulties
Computer problems
According to the FIVIMS44 definition, victims of food insecurity are people whose food consumption falls below the minimum energy requirement, as well as those with the physical symptoms of energy and nutritional deficiencies resulting from an unbalanced or inadequate diet, or from a physiological incapacity to efficiently utilize food because of infection or disease. Groups that are vulnerable to such food insecurity, as mentioned in Part II, Chapter 1, must therefore be identified and monitored carefully.
At institutional level, the MWG monitoring vulnerable groups generally relies on public and private authorities (including NGOs etc) that deal with social problems. But in order to be fully operational it has to work closely with the MWG monitoring nutrition (see next chapter). Indeed in some countries the FSIEWS have chosen, in the interests of efficiency, to have a single FNSS/MVG-MWG that monitors both vulnerable groups and nutrition. In the interests of clarity, however, the two MWGs are described separately here.
The main groups vulnerable to food insecurity can be identified on the basis of the information contained in the synthesis of the basic study for a FSIEWS (Part Two, Chapter I, Section 6), assisted, above all, by a highly (and if possible decentralized) participatory discussion process focussing on this problem and aiming at the gradual definition of these groups. Each representative of an MWG brings to the table one aspect of the situation, depending on the individual experience of food security (production, revenues, health, etc.). No single representative has all the information. Similarly, national social services and NGOs often have different information on the distribution of vulnerable groups, in that the former are centrally based while the latter's expertise relates to the field, just as an economist's perspectives and data will be different from a sociologist's or a technician's.
The table that serves as an example for the participatory synthesis is essential for reaching consensus. Using the table as reference, the MWG monitoring vulnerable groups should collect further information on these groups, particularly in the following areas:
Such an approach, although less common and more difficult to adopt (qualitative methodology, participatory approach), should prove useful for identifying socio-cultural and religious groups and the specific characteristics of their diet.
Data on vulnerable groups is essentially obtained by monitoring vulnerability, that is, the causes of food insecurity: those reflecting the quantities and quality of food available to households, and physical and economic access to foods. The indicators comprise data on household resources, budgets, consumption, etc. These kinds of variables are often dynamic and difficult to measure.
Monitoring population groups involves monitoring several aspects:
Per capita GDP is a general indicator (usually annual) which allows some comparison between countries. It has its limitations, since it ignores the distribution of income within the population, and therefore the extent and degree of poverty, as well as all the other causes of deprivation.
More complex indicators are generally used by the United Nations, such as the HDI45 (human development index) that takes account of income, education and health.
It is not easy to choose poverty indicators, since the data has to be easy to collect, relevant and reliable. Often total revenues (including domestic self-sufficiency), total expenses, and the value of food consumed by households over a given period are used. In general, a minimum total income, below which a household is considered to be in a situation of poverty, is defined. This minimum may be calculated for a region or a village. The same thing applies to total expenses. To calculate the food consumption of a household, the minimum value of a food ration is established, in keeping with the local eating habits, and covering the minimum daily energy requirements of an individual (see Part Two, Chapter I, Section 1, the basic energy requirements). All people whose consumption falls below this minimum level are considered to be under-nourished. Clearly when the data relates to a carefully targeted local population, it is easier to take local factors into account and this reference is therefore more acceptable as a poverty threshold indicator. As each indicator has its own advantages and disadvantages, several indicators are often combined (into a set of indicators), each one marking an aspect of vulnerability. Therefore, if several indicators are in agreement for a given household, there can be no doubt about their poverty.
Nowadays, another dimension of the complex problem of poverty is also taken into account. Studies have effectively demonstrated that, for the same level of economic or social indicators, some families will find a way out of poverty while others get caught up in a downward spiral. This phenomenon can perhaps be explained by the capacity of the former to draw strength from the family or community around them thus rendering their situation more bearable. In other words they have "solidarity assets" that they can draw on, while the others, although characterized by similar economic and social indicators, deprived of such assets are perceived as poorer still and suffer the distress of exclusion. The idea of "social capital" has been proposed by various schools of thought and attempts are currently being made to translate this phenomenon, essentially qualitative in nature, into measurable indicators.
At this stage, and apart from certain partial or combined indicators that have been the subject of large data collections (income, HDI, schooling rate, health cover, etc.) there are more case studies than useable series in the databases. Nevertheless, the large number of examples already gives some countries enough information to work on. Further work can be carried out in the FSIEWS to translate these complex dimensions into useable information.
Some of the indicators for the economic and social monitoring of the most vulnerable groups are also essential for the work of the MWG monitoring nutrition, and, as mentioned above, both MWGs (FNSS and MVG) must agree on how to monitor these variables. This is mainly a question of data regarding:
In this area, the indicators that best seem to reflect the household's energy consumption, in both urban and rural settings, are those for total per capita expenditure or resources, the household dependency ratio, and the number of staple foods used etc.
Monitoring the specific problems groups have in physically accessing food is tied, as was seen above, to criteria such as:
The MWG should therefore take time to examine these criteria for each specific vulnerable group and decide, for each criterion, what data to monitor, usually long-term (annual data may suffice for some indicators). It is often interesting to regularly check for variations in the data when certain conditions appear in the economic or social sector, such as the privatization of transport, changes in the country's social policy, etc.
Familiarity with the coping strategies adopted by families is essential and should be integrated into the basic food security analysis46. Monitoring these strategies gives an insight into how families perceive their own food insecurity. When faced with the risk of not having enough food in the future, they adopt one of these strategies. The indirect indicators that can be derived from these strategies are often more qualitative than quantitative, but they give a fairly clear idea of a foreseeable change in the situation. This, however, requires thorough knowledge of the "vulnerable" groups and what they see as the greatest risks for their families47.
The sequence and nature of coping strategies differ quite a lot from one group to another, depending on the subsistence systems, and within a given subsistence system according to the socio-economic profile, ethnic origin, religion, etc. (see the example of Nigeria below). In countries that regularly face food crises, people adopt complex coping strategies of their own, which can sometimes make the job of forecasting and preventing crises more difficult. Moreover, no two food crises are the same: the underlying causes, the sequence of events, and the conditions in a household facing a crisis are always different. A good understanding of the vulnerabilities of the local subsistence farming systems is therefore fundamental in determining the indicators for monitoring vulnerable groups.
Example: Analysis of coping strategies Time sequence of vulnerable rural household responses to a food crisis in Nigeria Coping strategies in the event of a food crisis in chronological order: Adjustment of food and animal production |
The indicators, direct or indirect, corresponding to these strategies should be identified by the MWG/MVG from the data already available in the existing statistics systems or from other institutions, NGOs or projects.
Monitoring the signs of this behaviour (single indirect indicators or sets of indirect indicators) can give good warning of a probable food crisis. Although they are not usually very expensive to monitor, these indicators do need to be carefully analysed beforehand if they are to be properly adapted to the target populations. They must be developed in cooperation with all the actors working in risk areas since they often function more as "warning signals" than as regular monitoring data. It should also be noted that these indirect indicators should be modified as populations adapt their strategies, and indeed as the ways and means of monitoring evolves, regarding both knowledge of data and ways of measuring the phenomena or transmitting data. The members of the MWG must therefore regularly examine the relevance of the indicators for each group concerned and adapt them as necessary.
When a food crisis occurs, various kinds of information are required at each step, depending on the stage it has reached, who needs information (NGOs, food aid organizations, governments, consumer associations, MCWs, traders etc.) and the decision level concerned. The MVG/MWG should be ready to provide the necessary information from its own database. Food crises are mainly due to failure to access food for various reasons. Depending on their dietary and social customs, their degree of monetarization, etc., households react very differently. A good understanding of the strategies of each of the groups most at risk is very important for decision-makers when crises arise. These can be used both as indicators of the severity of the crisis, and to target aid, favouring, for example, assistance to the most badly affected groups in keeping with their own coping strategies.
People who suffer from malnutrition are those whose food consumption is unsuitable and/or inadequate, or whose biological utilization of nutrients is impeded by a poor state of health, or a combination of both. This corresponds to the "access" and "biological utilization" aspects of food security. Food consumption at household level is a function of available food and how it is distributed within the family itself. Moreover, an unfavourable health environment and poor socio-economic conditions prevent the most deprived households from making optimal use of available food, and are the cause of high levels of infection. Food availability at household level48 is a necessary condition but not sufficient to prevent malnutrition. It is acknowledged that socio-cultural factors play a key role in the utilization of available foodstuffs. The most notable socio-cultural factors (religious, ethnic, etc.) are: different kinds of diet, feeding practices for children (in particular, when they are being weaned), food distribution within the family as well as strategies for coping with food insecurity, etc.
The FNSS have been created mainly for long-term monitoring of food consumption, to check that it is satisfactory, and, should this not be the case, set up programmes to improve the situation. Such programmes may be directly concerned with nutrition (nutritional education, distribution of food supplements in MCWs), or indirectly (prevention of childhood diseases, vaccination programmes). Malnutrition is by definition a dynamic phenomenon, not static. The FNSS should therefore be as flexible as possible in order to "adjust" the monitoring indicators according to the specific context and rapid changes in the food systems. The speed with which urbanization occurs in developing countries brings about changes in consumption patterns and the distribution of food within the family. This specific context is decisive in the choice of FNSS indicators.
Since much of the data for an FNSS relates to health and nutrition, it is often based at the Health Ministry, which gives it access to the decentralized structures of this ministry (MCW49, primary health care staff, etc.) to collect primary data, and statistics services for processing them, and so to obtain health data easily. Some countries, however, have institutes of nutrition, separate from the health ministry, but sometimes attached to the ministry of social affairs or with an autonomous semi-governmental status. Whatever its status, it is always closely linked to health structures, on one hand because data on health and nutrition are often put together, especially in the case of children, and on the other, because doctors and other health workers play an important role in the nutritional education and monitoring of groups.
To set up an FNSS, first of all, a common conceptual basis for existing malnutrition problems and their causes must be worked out in a participatory context involving all the different interested bodies (preferably within the FNSS/MWG). This basis can then be discussed and accepted by all the FNSS participants at all levels. The level can then be set at which the national authorities will act on the causes to modify and/or improve the nutritional situation (and/or food insecurity) through policy decisions, technical intervention and targeted programmes.
The stages in setting up Food and Nutrition Surveillance Systems (FNSS) are as follows:
A system that has been tried and tested in a number of countries is bottom-up monitoring. It relies on specialized teams from non-governmental organizations working in various regions in a country (but using a common methodology so that results can be compared) and on a central system of continuous quality control of data.
The following table illustrates the time sequence of the components of an FNSS in Ethiopia, the aim of which was to obtain information on:
However, such a method has to guarantee the consistency of the methods used, so that reliable comparisons of the various surveys can be made.
To obtain a preliminary framework, all the available information on nutritional problems (extent, geographic and socio-economic distribution, periodicity, as well as the underlying socio-economic factors) must be analysed. Some of this work can be used in the basic studies of the FSIEWS (Part II, Chapter 1) and can be gone into further by the FNSS/MWG together with the MVG/MWG.
National health services usually know what the main deficiencies (chronic or acute) in energy, proteins, and micronutrients are. Malnutrition does not affect all the people in a population to the same degree, or for the same reasons. The most frequent malnutrition problems are to do with protein-energy malnutrition, and deficiencies in micronutrients (mainly vitamin A, iron, and iodine). It also has to be decided if these problems are acute or chronic, as this will influence, among other things, which monitoring indicators (anthropometric in particular) should be used. In the case of acute protein-energy malnutrition, indicators that can monitor changes in people's weight in relation to size are recommended.
Problems have also been noted regarding the biological utilization of foods as a result of cooking methods, ways of consuming food, how it is distributed within the family, and the state of a person's health. These problems depend to a large extent on the socio-cultural environment (dietary habits and taboos), and sanitation (drinking water and state of sanitary installations).
To organize a database for an FNSS, staff have to know what data is already collected regularly on nutritional status, and adapt it as necessary50. This nutritional monitoring work should already have been completed if there is an FNSS in the country: if not, an FNSS/MWG should carry out this task as a priority.
The data regarding malnutrition at household level is generally divided into two categories: causal indicators and status indicators.
Example: FNSS Indicators according to development level
Area |
Indicators |
Level | ||
Demographic and health statistics |
Size of households |
C |
C |
|
Household dependency ratio |
C |
|||
Percentage of low birth-weight breast-fed babies <2500g |
C |
|||
Infant, child and maternal mortality rates |
||||
Morbidity and mortality rate due to the principal infectious diseases |
C |
I |
P | |
Availability and access to health services (%) |
C |
I |
P | |
Vaccination rates (BCG, DCT, oral polio vaccine and measles) among infants under 1 year |
||||
Water and environmental health |
Availability and access to drinking water (%) |
C |
P | |
Availability and access to adequate sanitary installations (%) |
C |
P | ||
Nutritional status |
Weight-age, height-age and weight-height ratio <-2 sd in children under 5 years |
C |
I |
P |
Low height-age ratio in school-age children |
C |
P | ||
Percentage of body mass indices below 18.5 kg/cm2 in adults |
C |
P | ||
Principal deficiencies in micronutrients (iron, iodine and vitamin A) |
C |
P | ||
Food consumption52 |
Quantities of the main groups of foods consumed |
C |
P | |
Level of food expenditure by households and self-produced food consumption |
C |
P | ||
Total expenditure of households per person and number of meals per day |
P | |||
Number of months of household food stocks (depends on food production systems) |
||||
Number of principal foods |
||||
Processing and food practices |
Feeding-practices, breast-feeding |
P | ||
Health and hygiene practices |
P | |||
Food distribution within households |
P | |||
The indicators generally used in Food and Nutrition Surveillance Systems are contained in Table above. The final list of indicators for an FNSS system depends on the specific situation of the country and should be established using a participatory approach involving communities and managers at all levels. These indicators take into consideration the principal foods consumed by households, region, dependency rate and size of households, habitat, morbidity, the vaccination rate, the weaning age, availability of and access to drinking water, and status of sanitary installations. The indicators used should be clearly itemized and presented in a table form for swifter and easier interpretation.
A more reliable monitoring system can be established in areas vulnerable to food insecurity through the combination of different information sources (often called "information providers" in this handbook). For example, it is sometimes useful to combine administrative information (schools, dispensaries) with data from random group samplings among the most vulnerable households. The first source provides a basic time series on nutritional status, while the second is more sensitive to changes in nutritional status, and in particular to the weight-height indicator (emaciation) and the clinical signs of nutritional deficiency. Such surveys of households are not necessary when causal indicators have already raised the alarm for a given area.
In Bangladesh, the nutritional status of children is monitored regularly (every two months, more often during periods of distress) alongside surveillance of the normal health indicators and socio-economic monitoring. This monitoring method, which is carried out at established sites in regions at risk, has proved a valid tool for the forecasting, assessment and coordination of responses to food crises caused by natural disasters53.
The data can be analysed and presented in different ways, in addition to showing the results in table form. The measurement of the rate of change among sensitive indicators can be combined with severity thresholds and so function as an early warning system. In a more complex early warning system in Ethiopia, a drop in the average weight-height ratio (less than 90 per cent that of the reference population) is the warning signal to set in motion the measures to be taken to avert a crisis (tables 3 and 4). Nutritional surveys are also often used to justify or reject aid and nutritional assistance measures. Nevertheless, the threshold values are specific to each country or each homogeneous zone and its prevalent nutritional problems. There is often disagreement over thresholds and they should be studied in more detail. Recent work on data in Ethiopia revealed that children mortality starts rising long before the "average weight-height" ratio reaches the threshold of 90 per cent of the reference population, and therefore action should be taken before the threshold is reached. Data on the nutritional status of young children is not enough on its own and should be completed with the addition of other indicators such as the nutritional status of adults and the sanitary situation of the population.
The media used to disseminate FNSS information and how often it is disseminated is very important. In general, a combination of strategies is recommended (newspapers, video, social mobilization, education and training). In most cases, information appears as periodic bulletins, reports and maps illustrating the geographic distribution of malnutrition in the country. In recent years, there has been a lot of interest in maps, mainly for their usefulness as a didactic tool. More advanced Geographic Information Systems54 (GIS) are currently being examined, but their application in the field of malnutrition is complicated by the particular problems encountered in nutrition and because health officers do not have sufficient training in data processing. Health and malnutrition are dynamic continuous phenomena that do not fit easily into rigid classifications.
In the prevention of food crises, FNSS can be useful in analysing the causes of decreased food consumption or increased malnutrition, and therefore facilitate the setting up of a mechanism or intervention aimed at preventing the occurrence of these problems or lessening their effects on the population.
The use of causal indicators as warning tools is controversial. The use of nutritional indicators in forecasting has also received much criticism. They do, in effect, only reveal an existing nutritional problem. In spite of their poor forecasting powers, such indicators can nonetheless be used in emergency situations to coordinate and assess relief efforts, and to allocate food aid to the most vulnerable groups. In Ethiopia, for example, the nutritional monitoring of children is achieved through random sample surveys restricted to regions where risks have been highlighted by other indicators (agricultural performance, size of herds, etc.). Nutrition data is therefore used to corroborate and fine-tune forecasts.
The usefulness of nutritional data in relief and rehabilitation operations is less controversial than its involvement in early warning and forecasting. Such information can be used to select beneficiaries and estimate the size of the affected population. Not only can priorities then be established among the affected areas but also the type of relief and its required duration. Finally, information on nutritional status is used above all to assess the impact of relief in rehabilitation programmes.
In emergency situations, the relative mortality risk among age groups varies in the same place according to circumstances and the period. Some results show that although infant and child mortality rates may be higher, children over five years and adults are sometimes more seriously affected than the younger children usually monitored. It therefore often becomes necessary to extend nutritional monitoring to all population groups, using anthropometric methods in order to define more precisely how much pressure the population is under. Nomadic populations are another example: when there are severe droughts, these people feed their children to the detriment of the adults. In the case of the children, anthropometry will not reveal the true nature of the crisis. To obtain the nutritional status of the other age groups, random sample surveys including a nutritional element should be adopted. For the anthropometric status of adults, the simplest and most reliable measurement is the Body Mass Index [BMI = weight (kg)/height² (m)].
For prevention and warning, the nutritional indicators must be simple (to avoid errors and to make sure that all the actors involved at all levels of the system can understand them), quickly obtained, adaptable or flexible (as the situations being monitored are dynamic) and involve low costs. Finally, and most importantly, these indicators, whether they are direct or indirect, complex or simple, must be reliable: that is, they should reflect the changing nutritional situation of the groups studied.
Food aid contributes to food security: at household level in the very short-term, through the free distribution or subsidized sale of staple foods in times of crisis; in the longer term, it can bring about an increase in food production, or create production workshops or small industries through food-for-work programmes. It can also encourage schooling (school canteens), training, or improvements in the health of the poorest (hospital meals, for example).
In order to monitor food aid and food assistance, three kinds of information regarding the commodity chain must be identified:
A specific database on food aid often amounts to historic monitoring of the distributed aid, distribution criteria, and products distributed. In theory, data relating to the management of food aid and assistance along the commodity chain, imports or local purchases for distribution to beneficiaries, should be integrated into the MIS. Unfortunately, donors or the government, or both, do not tend to favour transparency where information and its management is concerned, since such information represents power in a country on the verge of a food crisis. Imports should be integrated into the monitoring of all staple food imports, their transport and storage should be known, and distribution criteria decided by the National Food Security Committee (NFSC) (or its equivalent) in all transparency. Distribution of food aid should be monitored by the Provincial Committees (PFSCs) according to the decisions taken by the NFSC.
So far, no precise study has been undertaken of the principal steps to improve the monitoring of food-aid operations, in particular, the selection of key indicators. In some countries, an MWG has been set up specifically for food aid and assistance and a specific database created for monitoring this data (as occurs in Chad). Nevertheless, the establishment of such an MWG and database within the FSIEWS, presupposes that those holding information specific to this commodity chain (donors, WFP and other international agencies, national authorities, private carriers and NGOs chosen to distribute aid etc.) will supply, in good time and without manipulation, accurate information to the MWG. The MWG should then check the information and put it into the FSIEWS database.
The members of the NFSC secretariat (including FSIEWS managers and the lead managers of the MWGs) can easily assess the impact of food-aid operations on the food security of target groups if there is a good database for monitoring aid. It is, however, the case that food aid and assistance can have serious repercussions on production, marketing and consumption, which affect the poorest most. The NFSC and the Provincial Committees should, from time to time, carry out targeted studies of the medium-term effects, in particular the negative ones. It is clear that "triangular" aid, that is, depending on regional (or local) purchases of staple foods, does not distort markets to the same extent, although national agencies or donors tend, for convenience or financial interests, to favour imported aid, often supplied by donor countries.
The development of participatory approaches and the setting up of constructive dialogue with needy populations would, as well as strengthening the links between the various food aid and assistance monitoring systems (WFP's VAM, FEWS, UNICEF's monitoring system, etc.), clearly improve monitoring in this very sensitive field.
It is very difficult to obtain information on the food security of populations in an emergency situation. In particular, in the case of "complex"55 emergencies, which are on the increase, institutional capacities and available expertise are lacking. Often considerable amounts of basic information are missing, although there is an urgent need for information. This information is essential in order to be able to assess:
This information should be supplied to decision-makers (mainly the international community and governments) as quickly as possible. There is, as yet, no clear "model" for a FSIEWS in an emergency situation. A review of the situation is currently being carried out to see what lessons can be drawn from recent experiences. Some simple concrete characteristics of a FSIEWS in an emergency situation can, nonetheless, be outlined.
Information obtained in these conditions may lack accuracy and a scientific approach.
28 These crops are mentioned only as examples.
29 They determine the time to harvest and the quantities, notably for continuous harvest crops (i.e. cassava), and therefore the yield.
30 Forecasts for other crops could be carried out at a later date if required.
31 Once the system is established, the introduction of a "secondary" crop does not involve any further costs.
32 Although aroid plants may be treated as perennial crops in some production systems, it should be noted that the return of the rains stimulates growth in many of the young tubers which therefore become unsuitable for consumption/marketing.
33see "early agrometeorological crop yield forecasting" in FAO Plant production and protection paper N°73
34 Can be calculated using FAOINDEX software.
35 The NOAA satellite produces digital images by means of which the Normalized Difference Vegetation Index (NDVI) can be obtained. This index is broadly correlated with the volume of living vegetation. In arid and semi-arid conditions the state of crops and the surrounding vegetation are closely linked.
36 Meteosat produces digital images that measure the Cold Cloud Duration (CCD - T< -40°C), but this level is then calibrated in keeping with the existing statistical relationship between CCD values and recorded rainfall.
37 See note on the NOAA satellite.
38 See note above on the Meteosat satellite.
39 Apart from the specific products of the institutions mentioned, there has been rapid growth in commercial tools and software for processing satellite images. Several options are available according to the level of expertise of personnel and according to the type of processing to be done. IDRISI, IDA, Addapix, IGT and WinDISP are just some of the programmes. ERDAS is a more advanced programme.
40 These apply mainly to populations in the different zones.
41 In Chad, the extent of cultivated areas in "afub owondo" (in the southern region of Haut-Nyong) is inversely proportional to the "abundance" of wild mangoes (I. gabonensis), which are a substitute crop for groundnuts.
42 The text of this section is based on Market Information Services: Theory and Practice, FAO 1998.
43 A detailed description of how to collect and utilize information in order to forecast cereal market trends was proposed in a handbook presented at an SADC seminar: it is the product of two FAO projects carried out in the field (Helder & Nyhoff, 1994).
44 Food Insecurity and Vulnerability Information and Mapping Systems. FAO document CFS:98/5. See further information in Part Three, Chapter V.
45 See the annual reports of the UNDP for further details.
48 A clear distinction should be made between food availability at household level, a concept used mainly by nutritionists to mean the quantity of each type of food available over a period of time in a household, and the idea of "availability" in the concept of global food security (as used in the FSIEWS), which is defined as the sum of foodstuffs produced in the country, minus losses, plus imports, less exports, from which intermediate consumption is also generally deducted.
49 Maternal and Child Welfare.
50 See above, Part Two, Chapter II, Section Four.
51 MUAC= middle upper arm circumference.
52 Food consumption in economic terms should be monitored by the MVG/MWG
53 Bloem M. et al. (1995) Food and Nutrition Bulletin 16(2):131-138.
54 Part Two, Section 5, Chapter Five: Mapping and Other Software.
55 Accepted definition: A complex emergency can be defined as a disaster with serious humanitarian consequences in a country, region or society where central authority is considerably reduced by an internal or external conflict and which demands the joint intervention of various agencies or ogranizations.
