Am. J. Trop. Med. Hyg., 86(5), 2012, pp. 895–901
Copyright © 2012 by The American Society of Tropical Medicine and Hygiene
Modifiable Risk Factors for West Nile Virus Infection during an Outbreak—Arizona, 2010
Katherine B. Gibney, James Colborn, Steven Baty, Andrean M. Bunko Patterson, Tammy Sylvester,
Graham Briggs, Tasha Stewart, Craig Levy, Ken Komatsu, Katherine MacMillan,
Mark J. Delorey, John-Paul Mutebi, Marc Fischer, and J. Erin Staples*
Division of Vector-borne Diseases, Centers for Disease Control and Prevention (CDC), Fort Collins, Colorado; Epidemic Intelligence
Service Program, CDC, Atlanta, Georgia; Arizona Department of Health Services, Phoenix, Arizona; Maricopa County
Department of Public Health, Phoenix, Arizona; Pinal County Division of Public Health, Florence, Arizona
factors for infection are poorly defined. We performed a case-control study to identify modifiable risk factors for WNV
infection. Case-patients (N = 49) had laboratory evidence of recent WNV infection, whereas control-subjects (N = 74)
had negative WNV serology. We interviewed participants, surveyed households, and assessed environmental data. WNV
infection was associated with living in or near Water District X within Gilbert Township (adjusted odds ratio [aOR] 5.2;
95% confidence interval [95% CI] = 1.5–18.1), having water-holding containers in their yard (aOR 5.0; 95% CI = 1.5–17.3),
and not working or attending school outside the home (aOR 2.4; 95% CI = 1.1–5.5). During this outbreak, WNV infection
was likely primarily acquired peri-domestically with increased risk associated with potential mosquito larval habitats
around the home and neighborhood.
West Nile virus (WNV) is the leading cause of mosquito-borne disease in the United States; however, risk
West Nile virus (WNV) is an arthropod-borne flavivirus
maintained in nature in a bird-mosquito-bird cycle and trans-
mitted to humans primarily through the bites of infective
Culex mosquitoes. Since its introduction into the United
States in 1999, WNV has become the leading cause of neuro-
invasive arboviral disease and is responsible for focal seasonal
outbreaks.1–3Approximately 80% of human WNV infections
are asymptomatic.4Most symptomatic persons develop an
acute undifferentiated febrile illness5–7; < 1% of infected per-
sons develop WNV neuroinvasive disease (e.g., meningitis,
encephalitis, or acute flaccid paralysis), which has a case fatal-
ity rate of ~10%.1,4
Candidate WNV vaccines are being evaluated but none are
licensed for use in humans. In the absence of a vaccine, preven-
tion of WNV disease depends on community- and household-
level mosquito control programs to reduce vector densities,
personal protective behaviors to decrease exposure to mos-
quitoes, and screening of blood donors. Recommended per-
sonal protective behaviors include using mosquito repellents,
wearing protective clothing (long-sleeved shirts and long pants),
and limiting outdoor exposure when mosquitoes are most active.
Applying insecticides, using air-conditioning, installing window
and door screens, and reducing peri-domestic mosquito larval
habitats are other public health actions or messages used to
decrease the risk for WNV exposure.1
Despite annual focal outbreaks, modifiable risk factors for
WNV infection are poorly defined. Only community-level
mosquito control, avoiding outdoor exposure, and using insect
repellent have been associated with reduced WNV disease or
infection risk in the United States.4,8,9Although several eco-
logic studies and geospatial models have been used to identify
environmental risk factors for WNV disease,8,10–14few con-
trolled studies have been performed to look at risk factors for
WNV infection.4,9,15,16We performed a population-based, case-
control study to identify modifiable environmental and behav-
ioral risk factors for WNV infection during an outbreak in the
East Valley of metropolitan Phoenix.
MATERIALS AND METHODS
Setting. In late spring and early Summer 2010, there was an
outbreak of WNV noted in the East Valley of metropolitan
Phoenix, as evidence by trapping of an unusual number of
WNV-infected Culex quinquefasciatus mosquitoes and high
numbers of human WNV disease cases reported to public
health officials.17,18The 2010 WNV activity in this area was
unlike transmission patterns seen from 2005 to 2009, where
the peak number of WNV cases were reported in late August
to September.17The last focal outbreak of WNV disease in
the East Valley of metropolitan Phoenix occurred in 2004.19
Case definitions. We defined a case-patient as an East
Valley resident with laboratory-confirmed WNV infection
diagnosed on a sample collected from May 25 to July 31, 2010.
For the purposes of this investigation, the East Valley of
metropolitan Phoenix was defined as the cities and towns of
Apache Junction, Chandler, Gilbert, Mesa, Queen Creek, Tempe,
Phoenix (zip code 85044 only), San Tan Valley (excluding zip
code 85132), and other unincorporated areas occurring within
the geographic boundaries of these towns and cities. Labora-
tory confirmation of WNV infection required detection of anti-
WNV immunoglobulin (Ig) M antibodies or WNV ribonucleic
acid (RNA) in serum or cerebrospinal fluid (CSF). Case-
patients included symptomatic persons with neuroinvasive (N =
28) and non-neuroinvasive (N = 17) WNV disease, and asymp-
tomatic viremic blood donors (N = 4). Control-subjects were
East Valley residents with a negative result for anti-WNV IgM
and IgG on CSF collected ³ 4 days after symptom onset or
serum collected ³ 7 days after symptom onset. These criteria
were used to prevent persons with either recent or previous
WNV infections from being enrolled as control-subjects.20
Identification and enrollment of study participants. Case-
patients were identified through reports to the state or county
health department of WNV disease cases or viremic blood
donors. In addition, case-patients and control-subjects were
identified through active surveillance for WNV testing
performed at laboratories servicing the East Valley. Persons
who tested negative for anti-WNV IgM and IgG on specimens
*Address correspondence to J. Erin Staples, Division of Vector-borne
Disease, Centers for Disease Control and Prevention, 3150 Rampart
Road, Fort Collins, CO 80521. E-mail: AUV1@cdc.gov
collected too early in the illness to exclude WNV infection (i.e.,
CSF collected < 4 days after symptom onset or serum col-
lected < 7 days after symptom onset) were offered a repeat
blood draw and testing for anti-WNV IgM and were classified
according to that result; persons who declined further testing
were classified as having an indeterminate WNV test result
and were excluded from the study. This investigation was
determined to be part of the emergency public health prac-
tice response to the outbreak and did not require human sub-
Data collection and definition of variables. Variables previ-
ously identified as possible risk factors for WNV or St. Louis
encephalitis virus infection or potentially associated with expo-
sure to larval habitats were collected from a number of sources
(Table 1). After obtaining verbal consent, a standardized tele-
phone questionnaire was administered from July 29–August 18,
2010. Information collected included demographics and per-
sonal protective behaviors. Permission was then sought to
conduct a household visit, during which an entomologist and
an epidemiologist inspected the outside of the house, the
yard, and the neighborhood within 100 m of the property for
mosquito larval habitats and other risk factors that increase
exposure to mosquitoes. To explore additional environmental
features, we retrieved information from county databases,
irrigation maps, and geographic information system (GIS)
maps (Environmental Systems Research Institute [ESRI],
Redlands, CA). To account for the estimated flight distance
of Culex tarsalis and Cx. quinquefasciatus in urban habitats,
these environmental features were evaluated within 500 m of
each participant’s home.21Finally, GIS-based data were used
for 2009 estimates of population density and proportion of
vacant households by census block group.
Data analysis. Data were analyzed using SAS statistical
software version 9.2 (SAS Institute, Cary, NC) and mapped
with ArcMap 10.0 (ESRI). A P < 0.05 was considered signif-
icant. Univariate analysis was performed on collected vari-
ables using c2or Fisher’s exact tests. Persons with missing
data were excluded from the univariate analysis. Missing data
was most often associated with participants who did not con-
sent to a home visit or deceased or debilitated case-patients
for whom surrogates were not able to provide the specific
information. For multivariable analysis, such data were assumed
to be missing at random and were imputed by modeling them
as a function of the observed data for complete cases.22Five
data sets with imputed data were created using SAS PROC MI
and then were analyzed using SAS PROC MIANALYZE.
Variables with a P ³ 0.1 on univariate analysis were entered
into the logistic model in a stepwise manner. A variable must
have had a score c2statistic with P < 0.05 to be retained in the
model. Variables with a Wald P > 0.05 were removed from
We identified 205 East Valley residents who were evalu-
ated for WNV infection using specimens collected between
May 25 and July 31, 2010. Of these, 55 (27%) tested positive
for WNV infection and 150 (73%) tested negative. However,
only 75 of the persons testing negative had enough informa-
tion to exclude recent WNV infection (Figure 1). Forty-nine
case-patients and 74 control-subjects were enrolled and
completed the questionnaire; of these, 41 case-patients and
44 control-subjects agreed to the household assessment.
The median age of the 49 case-patients was 50 years (range:
15–80 years) and of the 74 control-subjects was 44 years
(range: 4–89 years). Case-patients were significantly more likely
than control-subjects to be ³ 60 years of age (odds ratio [OR]
2.5; 95% confidence interval [95% CI] = 1.0–6.1) and to live in
the Town of Gilbert (OR 2.4; 95% CI = 1.1–5.2) (Table 2 and
The only significant behavioral risk factor for WNV infec-
tion was not working or attending school outside the home
(OR 2.6; 95% CI = 1.2–5.4) (Table 3). The majority of both
case-patients and control-subjects did not adhere to WNV
personal protection behaviors; for example, most reported
never wearing long sleeves and pants when outdoors (78%
case-patients and 64% control-subjects) and never wearing
insect repellent when outdoors (86% and 82%). Conversely,
some potentially protective behaviors were common in both
groups, such as air-conditioner use (85% and 91%) and keep-
ing windows closed (73% and 80%).
For environmental risk factors, case-patients were signifi-
cantly more likely than control-subjects to have water-holding
containers in their yard (OR 5.3; 95% CI = 1.4–20.3), live
in or near (within 500 m) of Water District X (OR 2.5; 95%
CI = 1.1–5.9), and have a neglected pool reported within 500 m
of their home (OR 2.2; 95% CI = 1.0–4.7) (Table 3 and Fig-
ure 2). Because of interaction between the variables “lives in
Description of data sources and data collected
Source Data collected
• Behaviors that might affect exposure to mosquitoes such as outdoor activities and working or attending school
outside the home
• Household mosquito prevention measures such as door and window screens
• Potential mosquito larval habitats in the yard such as water-holding containers*
• Potential mosquito larval habitats £ 100 m from residence such as flood irrigation and catch basins†
• Year of house construction
• Neglected pools that are capable of serving as mosquito larval habitats located £ 500 m from residence as
reported to county environmental services, May–June, 2010
• Irrigation service areas (water districts) and open irrigation canals £ 500 m from residence
• Green space £ 500 m from residence such as parks, golf courses, and agricultural land
• 2009 demographic information within census block groups such as population density and percent of houses
that were vacant
*Includes common yard containers and discarded artificial containers such as pots, inflatable pools, and tires.
†Catch basins are defined as man-made depressions in the ground where storm water from roadways and/or residential areas is directed. Large fences or other barriers occasionally limited the
visibility of all areas within 100 m of a residence.
GIBNEY AND OTHERS
(WNV) infection on specimens collected May 25–July 31, 2010.
Enrollment and household visits of residents of the East Valley of metropolitan Phoenix, Arizona evaluated for West Nile virus
Univariate analysis of demographics of West Nile virus case-patients and control-subjects—East Valley of metropolitan Phoenix, Arizona,
May 25–July 31, 2010
Case-patients (N = 49) Control-subjects (N = 74) Univariate analysis
No.(%)No. (%)P value*
Age group 0.04†
< 20 years
³ 60 years
Lives in Town of Gilbert0.02
> High school
High school or less
*Persons with an “unknown” result excluded from univariate analysis.
†Age ³ 60 years compared with age < 60 years for univariate analysis.
‡P value > 0.1.
MODIFIABLE RISK FACTORS FOR WEST NILE VIRUS INFECTION
May 25–July 31, 2010. Based on the estimated population density, 150 m buffer were created around each residence and then a point was randomly
chosen within the buffer to protect individual privacy.
Map of West Nile virus case-patients and control-subjects by place of residence—East Valley of metropolitan Phoenix, Arizona,
Univariate analysis of behavioral and environmental characteristics for West Nile virus case-patients and control-subjects—East Valley of
metropolitan Phoenix, Arizona, May 25–July 31, 2010
Case-patients Control-subjects Univariate analysis
n/N (%)n/N (%)P value
Does not work or attend school outside the home
Never wears long sleeves and pants when outdoors
Never uses insect repellent when outdoors
Spends ³ 1 hour/day outdoors
Always uses air-conditioner
Keeps windows closed
House and yard characteristics
Water-holding containers in yard
House constructed before year 2000
Pool at residence
Deck or unscreened porch
Unscreened doors or windows
Irrigation and other environmental characteristics
Lives within 500 m of Water District X
Neglected pools within 500 m of residence reported to county
Population density ³ 1,000/sq. miles within census block group
³ 25% of houses vacant within census block group
Green area ³ 10% of total area within 500 m of residence
Catch basins within 500 m of residence
Open irrigation canals within 500 m of residence
Flood irrigation observed within 100 m of residence
*P value > 0.10.
n = number affected; N = total number.
GIBNEY AND OTHERS
the Town of Gilbert” and “lives in or near Water District X”,
these two variables were combined for the multivariable
analysis to “lives in or near Water District X within Gilbert.”
The majority of study participants lived in houses that were
constructed > 10 years ago (51% case-patients and 66%
control-subjects) and in settings with a population density
³ 1,000 persons/square mile (94% and 84%).
Logistic regression analysis identified three independent
risk factors for WNV infection: living in or near Water Dis-
trict X within Gilbert (adjusted OR [aOR] 5.2; 95% CI = 1.5–
18.1), having water-holding containers in the yard (aOR 5.0;
95% CI = 1.5–17.3), and not working or attending school
outside the home (aOR 2.4; 95% CI = 1.1–5.5) (Table 4).
Our case-control study identified several unique risk fac-
tors for WNV infection, which suggest that exposures around
the home and in the surrounding neighborhood played an
important role in this outbreak. Water-holding containers
can act as mosquito larval habitats and are a known risk
factor for other mosquito-borne diseases such as dengue.23–25
A number of man-made containers, such as combined sewer
overflow canals and road-side catch basins, have been associ-
ated with Culex spp. breeding and are frequently targeted by
WNV vector control programs.26,27However, to our knowl-
edge, this is the first time common yard or discarded artificial
containers have been identified as a risk for WNV infection
during an outbreak. This finding might have been influenced
by the arid nature of the study area, making artificial water
sources more important as potential larval habitats for Culex
spp. mosquitoes. Culex quinquefasciatus commonly breed
around human homes and in containers with high organic
content water, whereas Cx. tarsalis is usually associated with
irrigation runoffs (clean water) in agricultural fields away
from human settlements.28,29Therefore, the observed associ-
ation between peridomestic water-holding containers and
WNV infection and the high predominance of WNV-infected
Cx. quinquefasciatus in the study area suggest that during this
outbreak Cx. quinquefasciatus was primarily responsible for
transmitting WNV to persons close to their home.18
The incidence of WNV disease has previously been associ-
ated with proximity to irrigated agriculture.11We did not
identify proximity to open irrigation canals or flood irrigation
as risk factors but did identify residence in the area common
to Water District X and the Town of Gilbert as a risk factor
for WNV infection. This might reflect irrigation infrastruc-
ture or irrigation practices that are specific to this area and
impact mosquito breeding.
The association between not working or attending school
outside the home and WNV infection further supports the
premise that WNV was likely acquired peri-domestically dur-
ing this outbreak. However, those who stayed at home tended
to be older and increased age is a known risk factor for WNV
neuroinvasive disease, which affected > 50% of case-patients,1
raising the possibility that not working or attending school
outside the home was a proxy for increased age. Despite this,
not working or attending school outside the home remained a
risk factor across all ages. Further study is warranted to examine
whether staying at home increases the risk of WNV infection
through peri-domestic mosquito exposure or if it is a marker for
age or underlying medical conditions that predispose the house-
hold resident to symptomatic or severe WNV disease.
No modifiable behavioral characteristics were associated
with increased risk of WNV infection in our study. The pos-
sible role of personal protective behaviors in preventing
WNV infection has been examined in a limited number of
serosurveys that were conducted soon after WNV was first
detected in North America.4,9,16Avoiding time outdoors when
mosquitoes are most active, specifically dusk to dawn, has been
identified in three studies as being protective against WNV
infection.4,9,16Use of insect repellent has been associated with
a lower WNV seroprevalence among persons who spent at least
2 hours outdoors from dusk to dawn.4Finally, a serosurvey
from Canada reported persons were at lower risk for WNV
infection if they used at least two of the following personal
protective behaviors: mosquito avoidance, insect repellent,
and protective clothing in the form of long sleeves and long
pants when outdoors.16Human infections with St. Louis
encephalitis virus, a closely related flavivirus also transmitted
by Culex spp. mosquitoes, also have been associated with time
spent outdoors and not wearing long sleeves and long pants.30,31
One possible reason our study did not identify modifiable
behavioral risk factors might be that few study participants
actually adhered to recommended personal protective behav-
iors. For example, > 80% of case-patients and control-subjects
reported never using insect repellent. Possible reasons for
poor adherence to personal protective measures during this
outbreak include: a lack of “nuisance” mosquitoes (e.g., mos-
quitoes that aggressively bite humans but do not transmit WNV),
such as Psorophora columbiae or Aedes vexans, resulting in a
decreased likelihood of using insect repellant; extreme heat
making it impractical to wear long sleeves or pants when
outside; and a belief that WNV no longer poses a threat.
Absence of air-conditioners and window screens has been
associated with increased risk of human St. Louis encephalitis
virus infection, raising the possibility that these could also be
risk factors for WNV infection.31,32However, air-conditioner
use and presence of door and window screens were common
among both case-patients and control-subjects in our study
and did not protect against WNV infection. A finding similar
to ours was obtained during a WNV outbreak in New York in
1999.4In contrast, during a WNV outbreak in Romania, mos-
quitoes in the home and flooded basements in apartment
Multivariable analysis of predictors of West Nile virus infection—East Valley of metropolitan Phoenix, Arizona, May 25–July 31, 2010
Risk factor OR*
[95% CI] aOR[95% CI]
Lives in or near Water District X within Gilbert
Water-holding containers in yard
Does not work or attend school outside the home
*Crude OR for water-holding containers in yard based on 5 complete datasets with imputed data; thus it differs slightly than the ORs that would be generated from the data presented in Table 3
where only observed data are presented.
OR = odds ratio; aOR = adjusted odds ratio; CI = confidence interval.
MODIFIABLE RISK FACTORS FOR WEST NILE VIRUS INFECTION
buildings were associated with infection risk; this study did
not address the presence of air-conditioners or screens.15Over-
all, this suggests that differences in living conditions and set-
tings might influence risk factors for WNV infection and that
public health messages and interventions need to be tailored
for different settings.
Risk of WNV disease has previously been associated with
the presence of neglected pools12,14and we detected this asso-
ciation on univariate but not multivariable analysis. How-
ever, as only a fraction of neglected pools are reported to
the county, we likely underestimated the true density and
potential risk of neglected pools in the study area. In attempts
to improve neglected pool capture, we obtained aerial photo-
graphs taken shortly after the study period but found the
resolution of these images to be inadequate to identify neg-
Our study has certain limitations. Case ascertainment
relied primarily on WNV disease cases reported to public
health authorities that resulted in most case-patients having
severe WNV disease. This likely affected the representa-
tiveness of case-patients compared with all WNV-infected
persons and might explain why case-patients were older
than control-subjects. Incomplete enrollment also might have
affected the representativeness of study participants, particu-
larly control-subjects. Because of concerns about the repre-
sentativeness of study participants, we elected not to calculate
population attributable risk for independent risk factors iden-
tified in this study. Suboptimal data sources might have lim-
ited our ability to detect associations and imputation of
missing data reduced the precision of the estimates. Finally,
particular factors that were unique to the study area, such as
the climate, irrigation methods, and mosquito species respon-
sible for transmitting WNV, might prevent generalizing these
results to other areas.
Our results indicate that WNV infection in this outbreak
was likely acquired peri-domestically and the risk of infection
was increased by the presence of potential mosquito larval
habitats around the home and in the neighborhood. Public
health messages during an outbreak should therefore target
reduction of potential mosquito larval habitats, in particular
elimination of water-holding containers from the yard. Envi-
ronmental factors unique to Water District X within the
Town of Gilbert need further evaluation to define interven-
tions to reduce residents’ WNV infection risk. The infrequent
use of many personal protective behaviors aimed at reducing
mosquito exposure was striking. Ways to improve compliance
with personal protective behaviors should be investigated and
the impact of these measures on prevention of infection with
WNV and other mosquito-borne pathogens should be fur-
Received August 2, 2011. Accepted for publication January 9, 2012.
Acknowledgments: We thank Jamie Feld, Marvin Godsey, Jessica
Mack, Tricia Wadleigh, and Naomi Wheeler for assistance with data
collection and data entry; Peggy Collins for assistance with database
management; Janeen Laven and Amanda Panella for performing
serologic testing; Rebecca Eisen for assistance with analysis of envi-
ronmental data; and Dan Damien, Eric Feldman, Andrea Julius,
Tamra Schuler, Kirk Smith, Don Thomas, and John Townsend for
providing mosquito and environmental data used in this study.
Disclaimer: The findings and conclusions of this report are those of
the authors and do not necessarily represent the views of the Centers
for Disease Control and Prevention.
Authors’ addresses: Katherine B. Gibney, Department of Epidemiology
and Preventive Medicine, Monash University, The Alfred Centre,
Melbourne, Australia, E-mail: Katherine.Gibney@monash.edu. James
Colborn, Division Of Parasitic Diseases And Malaria, Centers for
Disease Control and Prevention, Atlanta, GA, E-mail: firstname.lastname@example.org.
Steven Baty, U.S. Army, Public Health Command and Region-Europe,
Landstuhl, Germany, E-mail: email@example.com. Andrean M. Bunko
Patterson, Tammy Sylvester, and Craig Levy, Maricopa County Depart-
ment of Public Health, Phoenix, AZ, E-mails: AndreanBunkoPatterson@
mail.maricopa.gov, firstname.lastname@example.org, and CraigLevy@
mail.maricopa.gov. Graham Briggs, Pinal County Division of Public Health,
Florence, AZ, E-mail: email@example.com. Tasha Stewart,
Tempe PoliceDepartment, Tempe,AZ,E-mail:firstname.lastname@example.org.
Ken Komatsu, Arizona Department of Health Services, Phoenix, AZ,
E-mail: Ken.Komatsu@azdhs.gov. Katherine MacMillan, Mark J.
Delorey, John-Paul Mutebi, Marc Fischer, and J. Erin Staples, Division
of Vector-borne Disease, Centers for Disease Control and Prevention,
Fort Collins, CO, E-mails: email@example.com, firstname.lastname@example.org, email@example.com,
firstname.lastname@example.org, and email@example.com.
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