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3.1 Literature review: Legionnaires' disease outbreak response
Fredrikstad and Sarpsborg, Norway, May 2005 (Nygard et. al, 2008)[1]
On the 21 st May 2005, health authorities were alerted to an outbreak of
Legionnaires' disease (Legionnaires' disease) in the neighbouring municipalities of Fredrikstad
and Sarpsborg, Norway. The resulting outbreak investigation utilised GIS to identify a commercial air scrubber as the source
of the outbreak. The information collected as part of the investigation included mapping each
surviving patient's home location and movements over the 12 days prior to the onset of
symptoms. The locations of the potential sources of infection (including 23 businesses with
cooling towers) were also mapped and attack rates and risk ratios were calculated for the
populations living within various radii of each potential source. Although those infected lived
up to 20 km apart, results of the analyses revealed that those people living within 1 km of a
particular air scrubber were most at risk, and only for this source did that risk decrease as
the radius increased. Climatic data were also incorporated into a Gaussian puff model to
describe the dispersal of aerosols from a number of potential sources. Analyses revealed that
the plume modelled for the responsible air scrubber had the best fit with the distribution of
cases.
Murcia, Spain, July 2001 (Garcia-Fulgueiras et. al, 2003)[2]
In July 2001 the world's largest Legionnaires' disease outbreak to date occurred in Murcia,
Spain. More than 800 suspected cases were reported with 449 confirmed. In conjunction with
traditional statistical analyses, GIS-based analyses formed part of the outbreak investigation
that identified cooling towers at a city hospital as the source. A standardised questionnaire
with a strong focus on 'urban mobility' was administered to 662 suspected patients collecting
information for the 14 days prior to the patients' onset of symptoms. From this questionnaire a
variety of data-types were mapped including home and work addresses, travel movements and
method of transport. Thirty 'zones' were also mapped around potential sources for the dispersal
of contaminated aerosols (such as cooling towers). The case-control study conducted by the
authors' analysed movements through each of these zones and revealed a strong association
between passing through the zone surrounding the hospital cooling tower and being ill with
Legionnaires' disease (in all 8 multivariate analyses described in the paper). In fact,
Legionnaires' disease was 4.8-11.4 times more likely to be developed in those who passed
through the zone surrounding the hospital during the identified 'risk period' than persons who
did not travel through this zone.
Pas-de-Calais, France, November 2003 (Nguyen et. al, 2006)[3]
Between November 2003 and January 2004 Pas-de-Calais, France experienced a community wide
Legionnaires' disease outbreak with 86 laboratory confirmed cases. A cooling tower was
identified as the likely source of the outbreak with the authors suggesting from their
investigation that the distance of airborne transmission of L. pneumophila could be
greater than previous studies had reported. A standardised questionnaire was completed as part
of a matched case-control study collecting information about medical history and personal
characteristics; housing and living conditions; and daily outdoor activities and exposures for
the 10 days before the onset of illness. Data were gathered on each location visited, the time
spent at each location and also the type of transportation used to travel to each location. The
data collected revealed that all cases lived or visited an area within a 12 km radius of the
responsible plant but did not frequent any places in common. Although some cases were
identified within a 12 km radius the majority of cases resided within 6 km of the responsible
outbreak source with the highest attack rates identified among residents of the commune in
which the responsible source was located. A Gaussian dispersion model (which took into
consideration hourly meteorological data on temperature, humidity, nebulosity and wind speed
and direction) was used to simulate the dispersion of aerosols from cooling towers. Analyses
revealed a good fit between the dispersal of the plumes simulated by the model and the spatial
distribution of cases. Temporal alignments were also identified between cooling tower
operations and the various 'waves' of the outbreak.
Hereford, England 2003 (Kirrage et. al, 2007)[4]
In October and November 2003 Hereford, England experienced a Legionnaires' disease outbreak
with 28 identified cases. The investigation involved interviewing all cases (or a proxy) using
an adaption of the Health Protection Agency's standard Legionella Questionnaire.
Information was collected on predisposing risk factors, demographic factors, recent movements
within and outside Hereford, and specific visits or proximity to an aerosol-generating system,
such as a cooling tower, within a 14 day period prior to the onset of symptoms. Information
gathered on the place of residence and the daily movements of each case were entered into a
GIS were the locations of
cooling towers in the area, with 250 m, 500 m, and 1000 m radii plotted around each of them.
Wind direction and velocity data for half hour periods were also obtained from a local schools
weather station and incorporated into the analyses. A 'composite score' methodology was
employed to quantify the risk of exposure and therefore identify the likely source of
contamination amongst a large number of potential sources in and around the city centre. The
composite score was calculated for each potential source by allocating one point to each source
for each of the cases that had either been (a) within 500m of the source or (b) within 1 km
downwind of the source at any time during the incubation period. The maximum score was
therefore 56 points from the 28 cases. When reviewing the composite scores 3 potential sources
were identified as having significantly more cases residing or travelling within 500 m, and who
had been downwind of them, than all other sources. Additional epidemiological and
microbiological investigation then enabled the rapid identification of a single cooling tower
as the source of the outbreak.
North Shropshire, England 2006 (Carr et. al , 2010)[5]
Between August and September 2006, in North Shropshire 6 cases of Legionnaires' disease were
reported over a 19 day period (3 times as many cases as had been reported for the same time of
the previous 3 years). The initial hypothesis was that this 'cluster' had arisen due to
exposure to a contaminated aerosol producing device in the community. GIS was used as part of the outbreak
response and helped target the environmental investigation. A GIS database was created consisting of potential sources
of aerosol exposure, residential locations of cases, workplace locations, daily travel
movements and wind direction. Visualisation of laboratory confirmed Legionnaires' disease cases
and their movements revealed that they were scattered over a wide area with no significant
clustering. Two mile radii were established around each cases place of residence, their
workplace and any other locations visited socially. Two sites with four registered cooling
towers that were within a 2 mile radius of the residences or workplaces of four of the cases
were identified and visited. Environmental health officers, who also identified other potential
sources of contamination such as unregistered cooling towers and car washes within that area,
took samples from the identified facilities - they were all culture negative for
Legionella species. Despite a detailed investigation into the occurrence of the
Legionnaires' disease cluster it was not possible to identify a common source as being
responsible for the outbreak. From the available epidemiological, environmental and
microbiological information it was concluded that the cluster of Legionnaires' disease cases
identified constituted a pseudo-outbreak. Indeed the author makes comment that at the same time
other parts of England and parts of Europe were experiencing large increases of cases of
Legionnaires' disease.
Barcelona, Spain 2000 ( Jansà et.al , 2002)[6]
During October and November 2000 an outbreak of Legionnaires' disease was investigated in an
inner city district of Barcelona. 54 patients related to the outbreak were identified with a
case fatality rate of 5.5%. In association with epidemiological and environmental
investigation, spatial analysis was employed to assist in the identification of the outbreak
source. Case data was collected from each patient using a structured case questionnaire and in
addition each case was presented with a map of the district and asked to identify the locations
in space they had occupied during the 48 hours prior to their admission to hospital. In the
absence of a register of cooling tower locations an identification exercise was carried out
through visual reconnaissance and also a number of inquiries being made at various public
buildings in the area. Although the map-based element of the case questionnaire did not
identify any patterns that helped to establish the source of the outbreak an examination of
incidence rates proved more revealing. Incidence rates were calculated using census tracts -
each containing approximately 400 people. The incidence rate for the affected area as a whole
was calculated as 4.61 cases per 1000 population, however, breaking down the incidence rates by
census tract revealed that the northern part of the district was more heavily affected
(6.40/1000) than the southern area (2.23/1000). This area was subsequently shown to be in the
closest proximity to the cooling towers responsible for the outbreak, as identified through
further environmental and microbiological investigation.
South Wales, 2010 (Unpublished and Keramarou & Evans, 2010)[7]
Between August and September 2010, an outbreak of Legionnaires' disease occurred in South East
Wales with 22 cases identified. In conjunction with an epidemiological investigation carried
out by Public Health Wales (PHW) the Health Protection Agency (HPA) utilised a number of
mathematical, statistical and GIS based analytical methods to assist with the identification
of a potential outbreak source(s). Although no definitive source(s) was established the
epidemiological investigation conducted by PHW (see Keramarou & Evans , 2010) identified 2
space-time clusters centred on the upper Rhymney Valley and the lower Cynon Valley, with both
areas in close proximity to cooling towers. GIS-based analyses conducted by the HPA
corroborated the findings of the PHW epidemiological investigation with regard to the Rhymney
Valley area, identifying 2 cooling towers (within close spatial proximity to each other) as the
most likely outbreak sources. Although some of the statistical techniques employed by the HPA
provided supporting evidence for a second cluster in the Cynon Valley the GIS-based techniques
did not identify this area as a likely source of the outbreak.
As part of the GIS-based outbreak investigation home locations and other visited locations were
mapped for each case for the 14 days prior to the onset of symptoms. Travel routes between
those locations were inferred using a GIS-based road network analysis and cooling tower
locations were obtained from PHW Communicable Disease Surveillance Centre (CDSC) and mapped. Using the residential
address of each case and population data from the HSE National Population Database, attack rates were calculated
within 1 km of each cooling tower at 200 m intervals, under the assumption that for the
responsible cooling tower the attack rate would decrease with distance. The results, however,
revealed that no cooling tower displayed the expected radial attack rate profile. By altering
the methodology to incorporate each point along a cases travel history as a potential location
of infection and thereby artificially boosting the number of 'cases' within the analysis, the
results yielded two cooling tower locations showing a decreasing attack rate with distance -
both in the Rhymney Valley area. A raster based kernel density analysis was also utilised that
incorporated each location visited by each case and the inferred travel routes taken between
them. The purpose of the kernel density analysis was to identify those areas in space within
close proximity to the locations visited or the routes travelled, that are common between
cases. The analysis again revealed an area in the Rhymney Valley that reflected a high
incidence of cases coming within relatively close spatial proximity, and therefore suggested an
area where a common source of infection could potentially be located. Within the area
identified two cooling towers were in operation. Weighting locations and travel routes based on
the expected incubation period and re-running the kernel density analysis revealed similarly
high values in the Rhymney Valley area.
Alcoi, Spain 1999-2000 (Martínez-Beneito et al., 2006)[8]
Three consecutive outbreaks of Legionnaires' disease occurred in the industrial city of Alcoi
in east Spain between September 1999 and December 2000. 36 cases were identified in the first
outbreak; 11 in the second outbreak; and 97 in the third outbreak. Industrial cooling towers
belonging to Alcoi's textile factories discharge aerosols into the city atmosphere and it was
suspected that the source of the outbreaks could have been one or more of these towers.
Martínez-Beneito et al. (2006) identified a group of controls who had an
admission to hospital in the same period as cases in the first outbreak and who were of the
same gender and roughly the same age. Residential postcodes were obtained and a spatial point
process model was constructed with the aim of identifying whether the geographical distribution
of the cases could be considered to be random within space.
Ripley's K function was estimated for cases and controls (Ripley, 1981). A difference between
these measures was then calculated and tested for statistical significance. Results of the
significance tests confirmed higher aggregation of cases than of controls in all outbreaks.
Risk surface maps were also estimated for each outbreak. These were given by the difference
between the observed probability of being a case at a particular location and the expected
probability of being a case within the city. Thus areas of high risk were highlighted and
suggested areas to focus on in attempts to find a source for each outbreak.
One of the strengths of this approach is that it uses neither administrative geography nor a
network of points; the only locations are the (x,y) coordinates of the cases and controls. This
minimises computing overhead and also gives results in a continuous domain. However only home
locations were considered and it would be desirable to incorporate workplace locations in
future.
Delaware, United States of America 1994 (Brown et al., 1999)[9]
29 cases of community-acquired Legionnaires' disease were reported in Delaware, United States,
between July and September 1994. A hospital cooling tower was implicated as a likely source of
the outbreak and Brown et al. (1999) describe a case-control study designed to
investigate the importance of distance from the cooling tower and duration of exposure. They
interviewed participants about potential areas of exposure by using maps divided into a grid.
Concentric square blocks were marked on the grid at distances of 0.125, 0.25, 0.5, 0.75 and 1
mile around the hospital. Each case patient and matched control was then asked about possible
sites of exposure in the two weeks before the date of onset of illness of the case, and about
the number of visits made and the length of time spent in each block. Separate regression
models were used to determine the change in risk associated with a change in frequency and
duration of exposure in each block. A further regression model assessed the change in risk
associated with a change in distance from the cooling tower.
Risk of illness was found to decrease by 20% for each 0.1 mile increase in distance from the
hospital, up to one mile from the hospital, but increased by 8% for each hour spent in blocks
within 0.125 miles of the hospital. The median dose of modelled exposure was higher for cases
than controls.
- NYGARD K., WERNER-JOHANSEN O., RONSEN S., CAUGANT D. A., SIMONSEN O., KANESTROM A., ASK E.,
RINGSTAD J., ODEGARD R., JENSEN T., KROGH T., HOIBY E. A., RAGNHILDSTVEIT E., AABERGE I. S.
& AAVITSLAND P. (2008) An outbreak of Legionnaires' disease caused by long-distance spread
from an industrial air scrubber in Sarpsborg, Norway Clinical Infectious Diseases 46(1),
pp.61-69 http
- GARCIA-FULGUEIRAS A., NAVARRO C., FENOLL D., GARCIA J., GONZALEZ-DIEGO P., JIMENEZ-BUNUALES
T., RODRIGUEZ M., LOPEZ R., PACHECO F., RUIZ J., SEGOVIA M., BALADRON B. & PELAZ C. (2003)
Legionnaires' disease outbreak in Murcia, Spain Emerging Infectious Diseases 9(8),
pp.915 - 921 http pdf
- NGUYEN T. M. N., ILEF D., JARRAUD S., ROUIL L., CAMPESE C., CHE D., HAEGHEBAERT S.,
GANIAYRE F., MARCEL F., ETIENNE J. & DESENCLOS J.C. (2006) A community-wide outbreak of
Legionnaires' disease linked to industrial cooling towers: How far can contaminated aerosols
spread? Journal of Infectious Diseases 193, pp.102-111 http
- KIRRAGE D., REYNOLDS G., SMITH G.E. & OLOWOKURE B; HEREFORD LEGIONNAIRES' OUTBREAK
CONTROL TEAM (2007) Investigation of an outbreak of Legionnaires' disease: Hereford, UK 2003
Respiratory Medicine 101(8), pp.1639-1644 http
- CARR R., WARREN R., TOWERS L., BARTHOLOMEW A., DUGGAL H.V., REHMAN Y., HARRISON T.G. &
OLOWOKURE B (2010) Investigating a cluster of Legionnaires' cases: public health implications
Public Health 124 (6), pp. 326-331. http
- JANSÀ, J.M., CAYLÀ, J.A., FERRER D., GRACIA J., PELAZ C., SALVADOR M.,
BENAVIDES A., PELLICER T., RODRIGUEZ P., GARCÉS, J.MA., SEGURA A., GUIX J., PLASENCIA
A., ARMENGOU J.MA., BOTIA A., MORENO B., FERRER A., GARCÍA DE OLALLA P., GUIX J.,
PAÑELLA H., PEDRO R., SANZ M., VILLALBÍ RAMÓN, J., DÍEZ A.,
GARCÍA-CARASUSAN M., MANZANERA R., BENEYTO V., MASDÉU, J., GARRIGA R.,
DOMÍNGUEZ A., SALLERAS L., ALVAREZ J., BRAVO C., FLORES J., GUDIOL F., GRAU R., MATIA
L., MONTERDE R., MORELL F., OROMÍ, J., SABRIÀ, M., TRILLA A. & VAQUÉ,
J (2002) An outbreak of Legionnaires' disease in an inner city district: Importance of the
first 24 hours in the investigation International Journal of Tuberculosis and Lung
Disease 6(9), pp.831-838 http pdf
- KERAMAROU M. & EVANS M.R (2010) A community outbreak of Legionnaires' disease in South
Wales, August-September 2010 Eurosurveillance 15 (42), pp.1-4. http pdf
- MARTÍNEZ-BENEITO M. A., ABELLÁN, J. J., LÓPEZ-QUÍLEZ A.,
VANACLOCHA H., ZURRIAGA O., JORQUES G. & FENOLLAR J. (2006) Source detection in an outbreak
of Legionnaires' disease Lecture Notes in Statistics 185(3), pp.162-182 http
- BROWN C. M., NUORTI P. J., BREIMAN R. F., HATHCOCK A. L., FIELDS B. S., LIPMAN H. B.,
LLEWELLYN G. C., HOFMANN J. & CETRON M. (1999) A community outbreak of Legionnaires'
disease linked to hospital cooling towers: An epidemiological method to calculate dose of
exposure International Journal of Epidemiology 28, pp.353-359 http pdf
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