Table 1. Risk factors (RFs) used in this study, their derivation, and the motivation for including them.
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| Risk RF |
Name |
Properties |
Description |
| |
| Introduction |
| |
1 |
Immigration |
Dynamic |
Any bird arriving in the ecosystem can potentially carry
a strain of influenza from another ecosystem. We quantified immigration
conservatively, as the difference between the number of birds observed in a
count at time t and a count in the same location at time t-1.
Negative changes (emigration) were entered as zeros. No value for this RF
exists for the first count session by definition. |
| |
2 |
Related AIV Risk |
Non-dynamic |
Birds can introduce different pathogens from different
areas. The local risk (notably for farmers) is therefore related to the type of
strains that are likely to be introduced. We defined four movement patterns and
ranked them according to the associated risk of introducing different strains of
AIV in Chivero-Manyame ecosystem: a) resident species, associated with risk
value of 0; b) species nomadic in Southern Africa, associated with a risk value
of 1 (HPAI H5N1 has not been recorded in African South of the equator -OIE 2009-
but other HP strains have been recorded) or 0 for H5N1 risk; c) Trans-equatorial
migrants, with a risk value of 2 as HPAI H5N1 is now endemic in some African
countries and outbreaks occurred in 11 countries (OIE 2009); and d) paleartic
migrants, associated with a risk value of 3 because of the high number of HPAI
H5N1 outbreaks and reported prevalence of LPAI is higher than in Africa(Olsen et
al. 2006). For species that evidence several different strategies, as with the
wood sandpiper Tringa glareola which has both migratory and resident
populations (Underhill et al. 1999, Hockey et al. 2005), a mean between the two
relevant coefficients was taken. |
|
Maintenance |
|
|
3 |
Abundance |
Dynamic |
Total number of bird observed per species, obtained by
summing numbers seen during the 60 counts. Note that since only 56 counts were
done during the first count session (May 2007), we multiplied the numbers of
birds recorded during this session by 60/56 for full
comparability. |
| |
4 |
Gregariousness |
Dynamic |
The degree of intra-species aggregation. Aggregation
facilitates pathogen transmission and maintenance in the species. For each
species we calculated the average group size observed across all study
sites. |
| |
5 |
Mixing |
Dynamic |
The degree of inter-specific aggregation, which
facilitates pathogen transmission from one species to another. We estimated the
degree of mixing for each species and for each count session as the ratio of the
number of species observed on the same sites and at the same time, divided by
the total number of species counted during the 60 counts of the count session
(total species diversity measured during a count session). |
| |
6 |
Percentage of juveniles in the
population |
Dynamic |
Juveniles are considered to play a role in the
epidemiology of AIV once they have joined the adult population (i.e., after
fledging). Juveniles are also thought to remain epidemiologically naïve in
the population for about 2 months (Stallknecht et al. 1990b). To capture this
risk, we used Roberts’ Birds of Southern Africa (Hockey et al. 2005) to
provide data on: a) clutch size; b) breeding success; and c) laying dates for
the 254 species in the data set. Using a simple population model assuming
constant mortality in adults (4,5% per month) and a decreasing mortality in
juveniles (starting at 40% in month 1 and reaching 4,5% at 6 months), and
integrating the reproductive information, the percentage of juveniles in the
population was estimated by month. Incubation and fledging periods were added to
determine the delay between egg laying and the entry of juveniles into the
population. We considered juveniles for each species to be susceptible to AIV
infection based on their naïve immunological status but despite lack of
information on susceptibility for most African species. |
| |
7 |
Feeding habits |
Non-dynamic |
Transmission of AIV strains in surface water is possible
(Stallknecht et al. 1990a,
Brown et al. 2007b), and we identified four feeding behaviors that were ranked
according to the risk of birds being infected with AI during their feeding
activities. They include: (0) feeding on insects on flight, seeds, nectar or
fruits; (1) feeding on birds, small vertebrates, or insects close to water; (2)
diving or feeding on insects gleaned from open water; and (3) dabbling, gleaning
on or near surface and subsurface vegetation, or probing. |
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