International Journal of Health

Background Vector-borne and zoonotic diseases generally display clear spatial patterns due to different space-dependent factors. Land cover and land use influence disease transmission by controlling both the spatial distribution of vectors or hosts, and the probability of contact with susceptible human populations. The objective of this study was to combine environmental and socio-economic factors to explain the spatial distribution of two emerging human diseases in Belgium, Puumala virus (PUUV) and Lyme borreliosis. Municipalities were taken as units of analysis. Results Negative binomial regressions including a correction for spatial endogeneity show that the spatial distribution of PUUV and Lyme borreliosis infections are associated with a combination of factors linked to the vector and host populations, to human behaviours, and to landscape attributes. Both diseases are associated with the presence of forests, which are the preferred habitat for vector or host populations. The PUUV infection risk is higher in remote forest areas, where the level of urbanisation is low, and among low-income populations. The Lyme borreliosis transmission risk is higher in mixed landscapes with forests and spatially dispersed houses, mostly in wealthy peri-urban areas. The spatial dependence resulting from a combination of endogenous and exogenous processes could be accounted for in the model on PUUV but not for Lyme borreliosis. Conclusion A large part of the spatial variation in disease risk can be explained by environmental and socio-economic factors. The two diseases not only are most prevalent in different regions but also affect different groups of people. Combining these two criteria may increase the efficiency of information campaigns through appropriate targeting.


Background
Although it is well established in Africa, Europe, the Middle East and India, West Nile viral amplification occurs in a bird-mosquitobird cycle before bridge vector mosquitoes (mosquitoes that bite both birds and mammals) infect human populations [4]. Although many bird species become infected with WNv, WNv is particularly fatal to the corvid family of birds (corvid species include crows, ravens, jays, magpies, and nutcrackers). Surveillance in areas experiencing outbreaks found that a dramatic increase in corvid mortality preceded human illness by two to six weeks [5,6]. Their high mortality rate, large size, and distinctive colouring make dead corvid sightings a good indicator for WNv activity in the ecosystem. In addition, corvid carcasses can beeasily tested for WNv infection [7].
In 2004, WNv surveillance in BC involved testing dead corvids, mosquito pools, blood/organ donors, and symptomatic humans for WNv and the public using an internet-based form to report dead corvid sightings [8]. Generally dead corvid sightings reported via the internetbased form are different carcasses than those submitted for testing, with occasional overlap. The methods for collecting carcasses for testing vary regionally, with some regions hiring specific staff to collect carcasses and other regions collaborating with wildlife agencies. No evidence of WNv activity was observed in BC in 2004.
If WNv infection is confirmed in a corvid in BC, resulting public health actions include reinforcing public education around personal protection measures, and possibly heightening mosquito surveillance, initiating larviciding (if not already initiated) and/or considering the use of adulticides (if indicators provide evidence of an imminent outbreak) [9].
The objectives of this evaluation were to determine whether, in the absence of WNv, the numbers of dead corvids sighted and tested for WNv in 2004 were representative of the true corvid mortality. This evaluation examined whether the surveillance indicators demonstrated what was truly happening in the corvid populations, rather than reflecting differences in regional surveillance methods; that is, whether areas of the province that were expected to have larger numbers of dead corvids observed were reporting more dead corvid sightings and submitting more corvids for WNv testing than areas expected to have smaller numbers of dead corvids observed. Corvid surveillance could then be strengthened by addressing differences in regional surveillance systems that cause certain areas to be over-or under-represented.

Results
Surveillance activities in 2004 occurred over a 26 week period (May 1-October 31). The public reported 1,292 dead corvid sightings. The number reported in each Local Health Area (LHA) ranged from 0 to 159 (median = 3) [see Additional file 1]. LHAs submitted 1,437 corvid carcasses for WNv testing. The number submitted by each LHA ranged from 0 to 209 (median = 5). These 1,437 submissions included 1,293 Crows (American or Northwest-ern), 43 Common Ravens, one Gray Jay, 28 Steller's Jays, three Blue Jays, one Clark's Nutcracker and 68 Black-billed Magpies.
The estimates of relative corvid density for each LHA ranged from 0.6 to 61.0. The number of corvid sightings expected in each LHA ranged from 0 to 232 (median = 3).
The expected number of corvids tested in each LHA ranged from 0 to 258 (median = 4).
Twelve LHAs had significantly fewer reports of dead corvid sightings than expected; 21 had significantly more ( Figure 1). Eleven LHAs submitted significantly fewer corvid carcasses for WNv testing than expected; 26 submitted significantly more.
The cross-tabulation of the sighting and submission evaluations is outlined in Table 1.

Discussion
This geography-based evaluation demonstrated that some LHAs were sighting or testing more corvids than expected, and some were sighting or testing fewer than expected. Since WNv was not present in the province, this variation was not the result of differences in corvid mortality due to the virus, but most likely differences in the operation of regional surveillance programs or regional variations in other causes of corvid mortality.
At the time of this evaluation, there were no standards for the number of reports of dead corvid sightings or the number of corvids that should be tested in order to identify WNv in an area. We compared the numbers of corvids sighted and tested in each LHA to an expected number that was based on the proportion of all BC corvids expected in each LHA (assuming constant corvid mortality across LHAs). The absolute number of corvids sighted or tested was, therefore, not evaluated; the proportion of corvids in a particular area relative to sightings or submissions from other parts of the province was. For corvid data to be representative, the proportion sighted or submitted by each LHA should reflect the proportion expected from that LHA.
Sixty-five (78%) LHAs met or exceeded expectations for reports of dead corvid sightings and submissions of corvid carcasses for WNv testing.
Only 5 (6%) LHAs were below expectations for both indicators -Surrey, Vancouver, Cowichan, Greater Victoria, and Sooke. Three of these LHAs (Cowichan, Greater Victoria, and Sooke) were on Vancouver Island. When the two indicators were examined separately, five of the 12 (42%) LHAs reporting fewer dead corvid sightings than expected and five of the 11 (45%) LHAs submitting fewer corvid carcasses for WNv testing than expected were on Vancouver Island. To place this in context, Vancouver Island has 16 LHAs (17% of all LHAs). This lower level of surveillance activity on Vancouver Island may have been a result of lower public health emphasis or low perception of risk. Vancouver Island had been projected to be a low risk area for the initial introduction of WNv into the province.
Surrey and Vancouver, the other two LHAs that were below expectations for both corvid indicators, were both in the Vancouver Lower Mainland. In fact, six of the 11 (55%) LHAs submitting fewer carcasses for WNv testing than expected were in the Vancouver Lower Mainland. The below-expected results for these areas are most likely an artefact of over-estimation of the expected values. The calculation of the expected proportion of corvids in each LHA was based on a number of assumptions and modelling. The number of dead corvids sighted is dependent on the size of the area, the corvid density, and the human population density; however, the exact properties of these relationships are unknown. We assumed a multiplicative relationship between these three factors. As a result, this model may have resulted in erroneous classification of LHAs. The contribution of population density to determining the expected number of corvids for LHAs with high population densities (such as Vancouver and Surrey) may have resulted in over-estimates of expected values. Both Vancouver and Surrey had high raw numbers of reports of dead corvid sightings (139 and 80, respectively) and high raw numbers of corvids tested for WNv (209 and 97, respectively). This equates to more than five corvids submitted for testing per week from each of these LHAs and may have been sufficient to detect WNv activity if Dead corvid sightings and carcasses tested for West Nile virus versus expected, by Local Health Area Figure 1 Dead corvid sightings and carcasses tested for West Nile virus versus expected, by Local Health Area.
present. The threshold value of required corvids is unknown.
The majority of the LHAs testing more corvids than expected were in the eastern and south-eastern parts of the province. WNv was expected to enter the province from these areas since they are adjacent to Alberta, Montana, Idaho, and Washington, which reported WNv activity in 2004 and prior years. Due to low human population and corvid densities in some of these areas, expected corvid sightings and submissions were low (1-5 corvids sighted or tested per year). This small number of corvids may not be sufficient for WNv detection when the virus is introduced. Rural areas with low population and corvid densities may need to focus on other methods of WNv detection.
There is a paucity of data on the distribution of corvids in BC. An examination of the raw North American Breeding Bird Survey (BBS) point data shows that the BBS data have relatively low numbers of observation points and underrepresent the northern parts of province [10]. Therefore, this model was more robust for southerly regions of the province where there was a higher density of observation points.
We used the mean number of total corvids observed in the 1994-2003 BBS bird abundance map data to estimate corvid density in each LHA. Combining the corvid species provided larger, more robust estimates for the model. Similarly, using the mean of a number of years of observations provided more stable numbers. Combining corvid species and using the 10 year bird abundance data may have limited the model's ability to account for the spatial and temporal effects of more recent fluctuations in corvid populations. Furthermore, the assumption of constant corvid mortality across the province may have been erroneous; however, it was not possible to obtain data on local corvid mortality rates.

Conclusion
In conclusion, some LHAs were over-represented and others under-represented in BC's 2004 WNv corvid surveillance data. In addition, some data that were "representative" may not necessarily be useful (e.g., corvid surveillance data in areas with low corvid and human population densities).
To improve the representativeness of corvid surveillance data: 1. LHAs reporting fewer dead corvid sightings than expected should strive to increase reporting by the public by emphasizing this aspect of surveillance in media communications.
2. LHAs testing fewer corvids for WNv than expected should strive to increase the number of corvids submitted for WNv testing relative to other areas of the province, although an absolute number may be adequate to detect WNv presence in an area.
3. Areas with low population and corvid densities may choose to focus surveillance efforts on mosquito and human surveillance or active corvid surveillance rather than passive corvid surveillance. The results of this evaluation and the recommendations were shared with the public health stakeholders in the spring of 2004. During the 2005 WNv surveillance season, notable increases in corvid submissions occurred on Vancouver Island, compared with previous years [11]. In addition, testing of migrating wild birds was conducted in This evaluation demonstrates that geographic analysis can be used to evaluate the representativeness of surveillance systems and result in improvements to surveillance.

Methods
The number of dead corvid sightings reported by the public in each of BC's 83 LHAs and the number of corvid carcasses submitted by each LHA for WNv testing were compared to the numbers expected from each LHA. The expected numbers of corvids sighted and tested from each LHA were projected to be proportional to the geographic size of the LHA, controlling for the relative corvid density and human population density (to account for the chances of a human seeing a dead corvid).
The relative density of corvids in each LHA was estimated using data from the BBS [12]. BBS routes consist of 50 stops spaced 0. 8 (Figure 2), and neighbourhood statistics were used to summarize the mean values of the predicted numbers of corvids sighted for each LHA. This mean corvid count was used as an estimate of relative corvid density in each LHA.
The human population density of each LHA was calculated by dividing the population of the LHA by the LHA's geographic area. Population data were obtained from Population Extrapolation for Organizational Planning with Less Error (P.E.O.P.L.E.) Projection 29 [15]; and geographic data were obtained from the BC Ministry of Health Services.
The numbers of expected dead corvid sightings reported and corvids submitted for WNv testing by each LHA were calculated using the formulas outlined in Figure 3. The numbers of corvids sighted and tested from each LHA were compared to the expected numbers using the exact Poisson distribution and a significance level of 0.05.