Management information system: the key indicators of progress

in the midst of an outbreak. EDR is a robust and simple measure of the reproductive rate and is adequate for most disease management information systems (see next section).

Where possible, the EDR (and all other date-based indicators) should be calculated using the actual infection date. This is rarely possible, so the next best indicator will be the date of first clinical signs. This should be calculated from the outbreak investigation (see below).

management InformatIon system: the key IndIcators of Progress

Good decision-making has its foundations in a step-wise process, based on information: • Decisions about control policies must be knowledge-based. • Knowledge is built from reliable information. • Information comes from the analysis of data.

find it fast 1. Ratio of positive to negative reports 2. Surveillance methods that are detecting cases 3. Days from onset of first signs to day of reporting

kill it quickly 4. Days from report received to end of culling 5. Days from end of culling to end of disposal 6. Days from end of disposal to end of cleansing and disinfection

stop it spreading 7. Numbers of cases (i.e. outbreak locations) during a given period compared with the number of cases in the previous period (Note: The period most often used for highly infectious diseases is a week). 8. Routes of spread between infected sites

It is important to monitor progress and to make conservative predictions about what is likely to happen in the next period. A key element of resource planning is to have the required resources available before they are needed, not after. This can be done only by close monitoring and interpreting the effectiveness of the current measures. This sort of analysis requires a management information system.

It is important to collect and routinely analyse a standard set of data from all outbreaks in order to create a comprehensive set of indicators. These indicators serve the various phases of a comprehensive response, as follows:

Knowledge comes from the analysis of data. Without data there can be no information, although there is often misinformation. Data that are not analysed are useless. The collection and analysis of disease data is a key function of the epidemiology unit. Others should be collecting and analysing data on how field activities are being implemented. The use of these sets of information will give policy-makers the ability to plan ahead, another key requirement for disease control. The resources required for tomorrow must be sourced today so that they are available when needed.