We used two different algorithms to calculate the transgressor indices [TI] and detector indices [DI]: i) Google's PageRank algorithm 
and ii) the HITS algorithm of Kleinberg 
. Both measures are normalized so the sum of all TI and all DI separately is always equal to 1 at any given time as described under Methods
. Our analytical tool is on open access via the Internet [http://staffnet.kingston.ac.uk/~ku36087/foodalert/
]. Its interactive visualization application enables users to rapidly access information about the patterns of reports over a wide range of parameters using user selected durations. These include: reporting countries, reported countries, extent of reporting activity and networks in reporting at the country level. Our results are visualized in an interactive graph that makes all food report connections transparent at once while allowing the user to focus on a selected country at any given time. As shown in , the levels of reports against a country can be instantly plotted from the first alert against the given country to the selected end period.
Transgressor and detector indices over time and network representations for selected countries.
The growth and changes in global food alerts, as reported from an EU perspective, are illustrated in . Food alert reports adopt an ‘infringement’ approach, focusing on the frequency and trends in reasons for food alert. Network analysis highlighted differences in the underlying structures of food alerts that otherwise would have remained hidden. As seen in [and ], the number of alerts for each country frequently do not correspond to the impact on other countries as shown by the TI indices. For example, comparing China to Iran, the latter has the highest number of alerts but has a lower impact relative to the total transgressions over a given period. On the other hand, China has a major increase in alerts against its produce over the period as shown by annual sampling in . The impact of transgressor countries is further highlighted when limiting the weight of edges taken into consideration from below . Although several transgressor countries have impact on some 25 detector countries with no cutoff, only China impacts on above ten detector countries when only edges with weight >5 are taken into account.
Snapshots of growth and changes in the network structures of the RASFF between 2003–2008, taken on the 1st of July each year, focusing on China (in the center of the layout).
The cumulative number of food alerts and transgressor indices (TI) indices for the countries listed among the first 30 in their category.
Change in the number of transgressor and detector countries over the six-year period.
Impact on countries by selected transgressors at edge-weight cut-off value of 0 and 5.
Although countries' ranks on the three lists [ and ] showed significant correlation (Kendall tau
; 0.66, p
; and 0.64, p
for pairs of Alerts – HITS
, Alerts – PageRank
and HITS - PageRank
, respectively for the top 30 countries), there was a notable difference between volume (number of alerts) and impact (quantified by the TI indices and the number of countries involved) for some food producer countries. Whilst the number of food alerts appears to level off after 2006 with no significant seasonal variation, the number of countries involved in the food alert system has grown from 94 to 151. Although, based on the TI/DI values, the new countries appear to be insignificant transgressors, their appearance has contributed to the complexity of global food alerts. Thus, whilst the numbers of alerts are relatively easy to compare, obtaining information on impact requires a network approach. The importance of having information on the latter aspect is underscored by highly concerning incidents, such as the recently discovered melamine contamination in Chinese milk and milk-based products; or the Salmonella
contamination of peanut butter and related products in multiple countries in 2009. The latter incidents have resulted in a critical evaluation of the currently disjoint US food safety system. In keeping with the increasing complexity, the intention is to modernise the system by adding the ability to handle complex information from multiple sources and implement preventive measures 
Comparison of the accumulated number of food alerts and the transgressor indices.