The MEWS framework as set out by WHO consists of four components: 1) vulnerability monitoring; 2) seasonal climate forecasting; 3) environmental monitoring; and 4) sentinel case surveillance. This framework is illustrated in Figure 1.
Vulnerability monitoring
There are many factors that increase the vulnerability of a population to malaria epidemics [6, 7] and increase the severity of disease outcome should a malaria epidemic occur. Co-infection with other diseases such as HIV-AIDS is a major consideration for Southern African countries. Resistance to therapeutic drugs and insecticides has also been a recent problem throughout much of the region. Drought, food insecurity and associated population movements between areas of differing endemicity combine to make certain populations more vulnerable to epidemics. These factors and consideration of the where and how to get appropriate information were discussed and countries were encouraged to identify measurable indicators and key informants.
Seasonal climate forecasting
In recent years there have been significant scientific advances in our ability to predict climate on the seasonal timescale [8]. The skill associated with these predictions varies from region to region, but is generally higher within the tropics. Scientists from the SADC Drought Monitoring Centre and the International Research Institute for Climate Prediction (IRI) joined with meteorologists from Democratic Republic of Congo, Malawi, Namibia, Zimbabwe and the World Meteorological Organization (WMO) to deliver the climate forecast for the forthcoming 2004–2005 season. An overview of climate variability in the SADC region was presented. The inherent issues of probability and uncertainty in climate forecasting were discussed with participants from the malaria control services. A number of myths were exploded and the variables that could or could not be skilfully forecast were reviewed. The malaria control participants gave their views on how communication of the forecast should be improved and made more understandable to the non-climate-specialist. Following a subsequent working session by the climate and meteorological specialists, an outline of additional or alternative forecast indicators was provided.
Environmental monitoring
The availability of environmental variables pertinent to malaria transmission, such as rainfall, temperatures, humidity, and flooding, were discussed and information on where they could be obtained was provided. The two basic sources of such information are periodic summaries (usually satellite-derived and interpolated estimates) available through the internet from the SADC DMC, the Famine Early Warning Systems Network (FEWS-NET) or the International Research Institute for Climate Prediction, Columbia University (IRI) websites; or directly from national meteorological services' ground-based weather observations. Generally, summary products are available free of charge, whereas the meteorological services may need to charge for raw data. Countries were encouraged to begin dialogue with their national meteorological services and discuss the more specific information requirements and support they may need.
Sentinel case surveillance
The paramount importance of developing good health information and sentinel surveillance systems was acknowledged. The process of MEWS development is seen as offering opportunities for strengthening integrated health systems surveillance. It is in itself dependent on good epidemiological data for testing and validating the relationships between the component parts. Methods of using indicators for epidemic early detection were discussed. Various indicators such as the mean × 2 standard deviations, the 'normal channel', cumulative-sum and weekly case thresholds have been tried, tested and used in a number of Southern Africa countries, and countries are encouraged to develop and use what is most appropriate and effective for their purposes. However, a number of the countries acknowledged having a poor statistical basis on which to develop and test early warning and detection indicators.
Following the formal presentations setting out the MEWS components and epidemiological trends, the discussions centred around the countries' perceived control needs over the coming season and the information requirements for developing appropriate plans of action for epidemic preparedness and response. The countries represented varied markedly in their current levels of endemicity/epidemicity, surveillance and control coverage. Tanzania is for the most part a highly endemic country with an estimated 16–19 million cases per year. Botswana and Swaziland, by contrast, are currently recording cases in the low thousands and hundreds respectively. Zimbabwe's economic situation has recently compromised its control programme, and two of the countries, Mozambique and Angola, are in process of reconstructing their control programmes after recently emerging from major disruption due to long-term conflict situations. However, all of the countries did acknowledge the integrated MEWS approach as offering a useful framework for improving their epidemic planning, preparedness and response capabilities.
Based on the the climate forecast for October, November, December, and the extended forecast for January, February, March, which are posted on the DMC website http://www.dmc.co.zw/SeasonalForecasts/SARCOF_2004_STATEMENT.pdf. The participants discussed the difficulties in access to and interpretation of meteorological data. The representatives from the meteorological services expressed a willingness to engage in closer collaboration to address these issues. The participants voiced a clear need to improve the availability of the seasonal climate forecast to the epidemic prone districts. They also highlighted the need for better communication of the forecast to non-climate users. Requests were specifically made for forecasts that are more 'meaningful' to the health sector. In response, the meteorological sector pointed at the necessity to know more specifically what information the health sector requires in order to then meet this need. Forecasts could, for example, be expressed simply as the probability of the coming season being wetter or drier than the previous season, or two, or three, or n seasons; or compared to that of the last epidemic season; or as probabilities of exceeding a given threshold for the season. However, it was stressed that forecasts will always be probabilistic and not deterministic. Moreover, countries were encouraged to refer to forecast updates as the season progresses. The issues of how to communicate better the probabilities and uncertainties associated with seasonal climate forecasts were addressed more closely. While many activities in malaria control are based on probabilistic, uncertain premises (clinical diagnosis and presumptive treatment, for instance), public health professionals are well aware of the limitations of their own indicators. While recognizing the potential value of advance lead-times for planning, they are understandably cautious in basing critical decisions on uncertain information from others, and the health and meteorological sectors probably need to work this through in more local collaborative settings.
One additional issue that came out strongly during the meeting was the need for broader cross-border collaboration on epidemic prevention and control as 'true epidemic' prone areas are often based on particular environmental zones rather than administrative boundaries. For example, high rainfall anomalies in Angola may ultimately find their way as increased stream-flow into Botswana and Namibia, and create extensive breeding sites for vectors. Drought, food security, or a range of other factors, may lead to migrations of people across borders from one level of endemicity to another and pose a significant increase in epidemic risk. Development of national epidemic risk maps therefore ought to reflect the situation in neighbouring countries. There are a few examples of cross-border initiatives in the region: Republic of South Africa, Swaziland and Mozambique; Republic of South Africa and Zimbabwe. Both are showing promising results.