2294 part 1 final report.pdf - Agra CEAS Consulting

Prevention and control of animal diseases worldwide
Part I: Economic analysis: prevention versus outbreak costs
4.2.1.3. Animal disease surveillance systems
Building and maintaining good (epidemio-)surveillance networks covering the entire national territory
potentially for all animals and for all animal diseases, including zoonoses, is an international obligation of
all OIE member countries (Table 1).
Nonetheless, as demonstrated by the large animal health crises of the last decade including those related to
FMD and HPAI, many countries especially in the developing world fall short of meeting this requirement.
This is due to the lack of significant human resources, as well as of the necessary technical and financial
resources that accompany both the initial investment and its operational maintenance.
The 2006 UNSIC survey (A236) provides a global perspective of the overall surveillance capacity for
animal health. This indicates that overall capacity is perceived to be strong with nearly 84% of the
surveyed countries reporting a strengthened AI surveillance and reporting in birds. Surveillance capacity
appears to be equally strong across all regions.
Delays in reporting the outbreak of a disease to the OIE, the official body for mandatory reporting of listed
animal diseases, can be an indicator of a country’s preparedness to manage outbreaks (A236). A recent
FAO investigation of reporting times for outbreaks of AI in animals, which covered some 2298 disease
outbreak events from 31 countries since 2003, concluded that the average time from outbreak observation
to reporting to the OIE was 12.7 days with a median of 10.8 days (range: 1.2 – 44.5 days). The required
reporting interval from observation of an outbreak to notification of the OIE is immediate or 24 hours.
This disparity may well suggest that significant gaps continue to exist in country-level preparedness 52 .
Looking in more detail at two major components of the animal disease surveillance system, border
controls and diagnostic capacity, according to the 2006 UNSIC survey:
Border controls for AI are also fairly strong, with 80-90% of countries across all regions planning or
implementing such controls. It should be noted, however, that limited information is available on border
control breaches (fraud/illegal imports) which makes it impossible to define the current level of risk from
cross-border activity.
By contrast, laboratory capacity for AI detection is apparently in place for only some 65% of the
countries that responded to the survey. Laboratory detection capacity is particularly low in Africa
(reported in only 6 of the countries), the Middle East/N. Africa (7 countries) and the Americas (7
countries). Although the picture is better in the rest of the world it is still fairly modest in comparison to
the key importance of this component (Asia/Pacific: 11 countries; and Europe/C. Asia: 19 countries).
From the survey results, it seems that around 148 laboratories in the world today have the capacity to
detect AI.
52 This may not necessarily always be the case. Political pressures to under-report exerted by the industry and/or
other interest groups can not be excluded.
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