Our ability to forecast epidemics far into the future is constrained by the many complexities of disease systems. Realistic longer-term projections may, however, be possible under well-defined scenarios that specify the future state of critical epidemic drivers. Since December 2020, the U.S. COVID-19 Scenario Modeling Hub (SMH) has convened multiple modeling teams to make months ahead projections of SARS-CoV-2 burden, totaling nearly 1.8 million national and state-level projections. Here, we find SMH performance varied widely as a function of both scenario validity and model calibration. We show scenarios remained close to reality for 22 weeks on average before the arrival of unanticipated SARS-CoV-2 variants invalidated key assumptions. An ensemble of participating models that preserved variation between models (using the linear opinion pool method) was consistently more reliable than any single model in periods of valid scenario assumptions, while projection interval coverage was near target levels. SMH projections were used to guide pandemic response, illustrating the value of collaborative hubs for longer-term scenario projections.

BACKGROUND: Culture-independent diagnostic testing (CIDT) provides rapid results to clinicians and is quickly displacing traditional detection methods. Increased CIDT use and sensitivity likely result in higher case detection but might also obscure infection trends. Severe illness outcomes, such as hospitalization and death, are likely less affected by changes in testing practices and can be used as indicators of the expected case incidence trend had testing methods not changed. METHODS: Using US Foodborne Diseases Active Surveillance Network data during 1996-2019 and mixed effects quasi-Poisson regression, we estimated the expected yearly incidence for nine enteric pathogens. RESULTS: Removing the effect of CIDT use, CIDT panel testing and culture-confirmation of CIDT testing, the modelled incidence in all but three pathogens (Salmonella, Shigella, STEC O157) was significantly lower than the observed and the upward trend in Campylobacter was reversed from an observed 2.8% yearly increase to a modelled -2.8% yearly decrease (95% credible interval: -4.0, -1.4). CONCLUSIONS: Severe outcomes may be useful indicators in evaluating trends in surveillance systems that have undergone a marked change.

Beginning in December 2020, the COVID-19 Scenario Modeling Hub has provided quantitative scenario-based projections for cases, hospitalizations, and deaths, aggregated across up to nine modeling groups. Projections spanned multiple months into the future and provided timely information on potential impacts of epidemiological uncertainties and interventions. Projections results were shared with the public, public health partners, and the Centers for Disease Control COVID-19 Response Team. The projections provided insights on situational awareness and informed decision-making to mitigate COVID-19 disease burden (e.g., vaccination strategies). By aggregating projections from multiple modeling teams, the Scenario Modeling Hub provided rapidly synthesized information in times of great uncertainty and conveyed possible trajectories in the presence of emerging variants. Here we detail several use cases of these projections in public health practice and communication, including assessments of whether modeling results directly or indirectly informed public health communication or guidance. These include multiple examples where comparisons of projected COVID-19 disease outcomes under different vaccination scenarios were used to inform Advisory Committee for Immunization Practices recommendations. We also describe challenges and lessons learned during this highly beneficial collaboration.

BACKGROUND: Campylobacter is the most common cause of bacterial diarrhea in the United States; resistance to macrolides and fluoroquinolones limits treatment options. We examined the epidemiology of US Campylobacter infections and changes in resistance over time. METHODS: The Foodborne Diseases Active Surveillance Network receives information on laboratory-confirmed Campylobacter cases from 10 US sites, and the National Antimicrobial Resistance Monitoring System receives a subset of isolates from these cases for antimicrobial susceptibility testing. We estimated trends in incidence of Campylobacter infection, adjusting for sex, age, and surveillance changes attributable to culture-independent diagnostic tests. We compared percentages of isolates resistant to erythromycin or ciprofloxacin during 2005-2016 with 2017-2018 and used multivariable logistic regression to examine the association of international travel with resistance. RESULTS: Adjusted Campylobacter incidence remained stable or decreased for all groups analyzed since 2012. Among 2449 linked records in 2017-2018, the median patient age was 40.2 years (interquartile range, 21.6-57.8 years), 54.8% of patients were male, 17.2% were hospitalized, and 0.2% died. The percentage of resistant infections increased from 24.5% in 2005-2016 to 29.7% in 2017-2018 for ciprofloxacin (P < .001) and from 2.6% to 3.3% for erythromycin (P = .04). Persons with recent international travel had higher odds than nontravelers of having isolates resistant to ciprofloxacin (adjusted odds ratio [aOR] varied from 1.7 to 10.6 by race/ethnicity) and erythromycin (aOR = 1.7; 95% confidence interval, 1.3-2.1). CONCLUSIONS: Campylobacter incidence has remained stable or decreased, whereas resistance to antimicrobials recommended for treatment has increased. Recent international travel increased the risk of resistance.

As of March 2021, three COVID-19 vaccines have been authorized by the U.S. Food and Drug Administration (FDA) for use in the United States. Each has substantial efficacy in preventing COVID-19. However, as efficacy from trials was &lt;100% for all three vaccines, disease in vaccinated people is expected to occur. We created a spreadsheet-based tool to estimate the number of symptomatic vaccine breakthrough infections based on published vaccine efficacy (VE) data, percent of the population that has been fully vaccinated, and average number of COVID-19 cases reported per day. We estimate that approximately 51,000 symptomatic vaccine breakthrough infections (95% CI: ∼48,000–55,000 cases) occurred in the United States during January–April 2021 among &gt;77 million fully vaccinated people, reflecting &lt;0.5% of COVID-19 cases that occurred during that time. With ongoing SARS-CoV-2 transmission and increasing numbers of people vaccinated in the United States, vaccine breakthrough infections will continue to accumulate before population immunity is sufficient to interrupt transmission. Understanding expectations regarding number of vaccine breakthrough infections enables accurate public health messaging to help ensure that the occurrence of such cases does not negatively affect vaccine perceptions, confidence, and uptake.Competing Interest StatementThe authors have declared no competing interest.Funding StatementNo external funding was received.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:This activity was conducted consistent with applicable federal policy.All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll input data are publicly available

Emerging epidemics are challenging to track. Only a subset of cases is recognized and reported, as seen with the Zika virus (ZIKV) epidemic where large proportions of infection were asymptomatic. However, multiple imperfect indicators of infection provide an opportunity to estimate the underlying incidence of infection. We developed a modeling approach that integrates a generic Time-series Susceptible-Infected-Recovered epidemic model with assumptions about reporting biases in a Bayesian framework and applied it to the 2016 Zika epidemic in Puerto Rico using three indicators: suspected arboviral cases, suspected Zika-associated Guillain-Barré Syndrome cases, and blood bank data. Using this combination of surveillance data, we estimated the peak of the epidemic occurred during the week of August 15, 2016 (the 33rd week of year), and 120 to 140 (50% credible interval [CrI], 95% CrI: 97 to 170) weekly infections per 10,000 population occurred at the peak. By the end of 2016, we estimated that approximately 890,000 (95% CrI: 660,000 to 1,100,000) individuals were infected in 2016 (26%, 95% CrI: 19% to 33%, of the population infected). Utilizing multiple indicators offers the opportunity for real-time and retrospective situational awareness to support epidemic preparedness and response.Competing Interest StatementThe authors have declared no competing interest.Funding StatementThe author(s) received no specific funding for this work.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:Exemption was obtained from the CDC Human Subjects Research Office as the data were collected as part of regular surveillance activities.All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll relevant data are within the manuscript and its Supporting Information files.

WHAT IS ALREADY KNOWN ABOUT THIS TOPIC? The highly transmissible SARS-CoV-2 Delta variant has begun to cause increases in cases, hospitalizations, and deaths in parts of the United States. With slowed vaccination uptake, this novel variant is expected to increase the risk of pandemic resurgence in the US in July-December 2021. WHAT IS ADDED BY THIS REPORT? Data from nine mechanistic models project substantial resurgences of COVID-19 across the US resulting from the more transmissible Delta variant. These resurgences, which have now been observed in most states, were projected to occur across most of the US, coinciding with school and business reopening. Reaching higher vaccine coverage in July-December 2021 reduces the size and duration of the projected resurgence substantially. The expected impact of the outbreak is largely concentrated in a subset of states with lower vaccination coverage. WHAT ARE THE IMPLICATIONS FOR PUBLIC HEALTH PRACTICE? Renewed efforts to increase vaccination uptake are critical to limiting transmission and disease, particularly in states with lower current vaccination coverage. Reaching higher vaccination goals in the coming months can potentially avert 1.5 million cases and 21,000 deaths and improve the ability to safely resume social contacts, and educational and business activities. Continued or renewed non-pharmaceutical interventions, including masking, can also help limit transmission, particularly as schools and businesses reopen.

Background SARS-CoV-2 vaccination of persons aged 12 years and older has reduced disease burden in the United States. The COVID-19 Scenario Modeling Hub convened multiple modeling teams in September 2021 to project the impact of expanding vaccine administration to children 5-11 years old on anticipated COVID-19 burden and resilience against variant strains. Methods Nine modeling teams contributed state- and national-level projections for weekly counts of cases, hospitalizations, and deaths in the United States for the period September 12, 2021 to March 12, 2022. Four scenarios covered all combinations of: 1) presence vs. absence of vaccination of children ages 5-11 years starting on November 1, 2021; and 2) continued dominance of the Delta variant vs. emergence of a hypothetical more transmissible variant on November 15, 2021. Individual team projections were combined using linear pooling. The effect of childhood vaccination on overall and age-specific outcomes was estimated by meta-analysis approaches. Findings Absent a new variant, COVID-19 cases, hospitalizations, and deaths among all ages were projected to decrease nationally through mid-March 2022. Under a set of specific assumptions, models projected that vaccination of children 5-11 years old was associated with reductions in all-age cumulative cases (7.2%, mean incidence ratio [IR] 0.928, 95% confidence interval [CI] 0.880-0.977), hospitalizations (8.7%, mean IR 0.913, 95% CI 0.834-0.992), and deaths (9.2%, mean IR 0.908, 95% CI 0.797-1.020) compared with scenarios where children were not vaccinated. This projected effect of vaccinating children 5-11 years old increased in the presence of a more transmissible variant, assuming no change in vaccine effectiveness by variant. Larger relative reductions in cumulative cases, hospitalizations, and deaths were observed for children than for the entire U.S. population. Substantial state-level variation was projected in epidemic trajectories, vaccine benefits, and variant impacts. Conclusions Results from this multi-model aggregation study suggest that, under a specific set of scenario assumptions, expanding vaccination to children 5-11 years old would provide measurable direct benefits to this age group and indirect benefits to the all-age U.S. population, including resilience to more transmissible variants. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.

Reconstructing the incidence of SARS-CoV-2 infection is central to understanding the state of the pandemic. Seroprevalence studies are often used to assess cumulative infections as they can identify asymptomatic infection. Since July 2020, commercial laboratories have conducted nationwide serosurveys for the U.S. CDC. They employed three assays, with different sensitivities and specificities, potentially introducing biases in seroprevalence estimates. Using models, we show that accounting for assays explains some of the observed state-to-state variation in seroprevalence, and when integrating case and death surveillance data, we show that when using the Abbott assay, estimates of proportions infected can differ substantially from seroprevalence estimates. We also found that states with higher proportions infected (before or after vaccination) had lower vaccination coverages, a pattern corroborated using a separate dataset. Finally, to understand vaccination rates relative to the increase in cases, we estimated the proportions of the population that received a vaccine prior to infection.

BACKGROUND: The COVID-19 Scenario Modeling Hub convened nine modeling teams to project the impact of expanding SARS-CoV-2 vaccination to children aged 5-11 years on COVID-19 burden and resilience against variant strains. METHODS: Teams contributed state- and national-level weekly projections of cases, hospitalizations, and deaths in the United States from September 12, 2021 to March 12, 2022. Four scenarios covered all combinations of 1) vaccination (or not) of children aged 5-11 years (starting November 1, 2021), and 2) emergence (or not) of a variant more transmissible than the Delta variant (emerging November 15, 2021). Individual team projections were linearly pooled. The effect of childhood vaccination on overall and age-specific outcomes was estimated using meta-analyses. FINDINGS: Assuming that a new variant would not emerge, all-age COVID-19 outcomes were projected to decrease nationally through mid-March 2022. In this setting, vaccination of children 5-11 years old was associated with reductions in projections for all-age cumulative cases (7.2%, mean incidence ratio [IR] 0.928, 95% confidence interval [CI] 0.880-0.977), hospitalizations (8.7%, mean IR 0.913, 95% CI 0.834-0.992), and deaths (9.2%, mean IR 0.908, 95% CI 0.797-1.020) compared with scenarios without childhood vaccination. Vaccine benefits increased for scenarios including a hypothesized more transmissible variant, assuming similar vaccine effectiveness. Projected relative reductions in cumulative outcomes were larger for children than for the entire population. State-level variation was observed. INTERPRETATION: Given the scenario assumptions (defined before the emergence of Omicron), expanding vaccination to children 5-11 years old would provide measurable direct benefits, as well as indirect benefits to the all-age U.S. population, including resilience to more transmissible variants. FUNDING: Various (see acknowledgments).

In Spring 2021, the highly transmissible SARS-CoV-2 Delta variant began to cause increases in cases, hospitalizations, and deaths in parts of the United States. At the time, with slowed vaccination uptake, this novel variant was expected to increase the risk of pandemic resurgence in the US in summer and fall 2021. As part of the COVID-10 Scenario Modeling Hub, an ensemble of nine mechanistic models produced six-month scenario projections for July-December 2021 for the United States. These projections estimated substantial resurgences of COVID-19 across the US resulting from the more transmissible Delta variant, projected to occur across most of the US, coinciding with school and business reopening. The scenarios revealed that reaching higher vaccine coverage in July-December 2021 reduced the size and duration of the projected resurgence substantially, with the expected impacts was largely concentrated in a subset of states with lower vaccination coverage. Despite accurate projection of COVID-19 surges occurring and timing, the magnitude was substantially underestimated 2021 by the models compared with the of the reported cases, hospitalizations, and deaths occurring during July-December, highlighting the continued challenges to predict the evolving COVID-19 pandemic. Vaccination uptake remains critical to limiting transmission and disease, particularly in states with lower vaccination coverage. Higher vaccination goals at the onset of the surge of the new variant were estimated to avert over 1.5 million cases and 21,000 deaths, though may have had even greater impacts, considering the underestimated resurgence magnitude from the model.

As of March 2021, three COVID-19 vaccines had been authorized by the U.S. Food and Drug Administration (FDA) for use in the United States. Each has substantial efficacy in preventing COVID-19. However, as efficacy from trials was <100% for all three vaccines, disease in vaccinated people is expected to occur. We created a spreadsheet-based tool to estimate the number of symptomatic COVID-19 cases among vaccinated people (vaccine breakthrough infections) based on published vaccine efficacy (VE) data, percent of the population that has been fully vaccinated, and average number of COVID-19 cases reported per day. We estimate that approximately 199,000 symptomatic vaccine breakthrough infections (95% CI: ~183,000-214,000 cases) occurred in the United States during January-July 2021 among >156 million fully vaccinated people. With high SARS-CoV-2 transmission and increasing numbers of people vaccinated in the United States, vaccine breakthrough infections will continue to accumulate. Understanding expectations regarding number of vaccine breakthrough infections enables accurate public health messaging to help ensure that the occurrence of such cases does not negatively affect vaccine perceptions, confidence, and uptake.

After a period of rapidly declining U.S. COVID-19 incidence during January-March 2021, increases occurred in several jurisdictions (1,2) despite the rapid rollout of a large-scale vaccination program. This increase coincided with the spread of more transmissible variants of SARS-CoV-2, the virus that causes COVID-19, including B.1.1.7 (1,3) and relaxation of COVID-19 prevention strategies such as those for businesses, large-scale gatherings, and educational activities. To provide long-term projections of potential trends in COVID-19 cases, hospitalizations, and deaths, COVID-19 Scenario Modeling Hub teams used a multiple-model approach comprising six models to assess the potential course of COVID-19 in the United States across four scenarios with different vaccination coverage rates and effectiveness estimates and strength and implementation of nonpharmaceutical interventions (NPIs) (public health policies, such as physical distancing and masking) over a 6-month period (April-September 2021) using data available through March 27, 2021 (4). Among the four scenarios, an accelerated decline in NPI adherence (which encapsulates NPI mandates and population behavior) was shown to undermine vaccination-related gains over the subsequent 2-3 months and, in combination with increased transmissibility of new variants, could lead to surges in cases, hospitalizations, and deaths. A sharp decline in cases was projected by July 2021, with a faster decline in the high-vaccination scenarios. High vaccination rates and compliance with public health prevention measures are essential to control the COVID-19 pandemic and to prevent surges in hospitalizations and deaths in the coming months.

Emerging epidemics are challenging to track. Only a subset of cases is recognized and reported, as seen with the Zika virus (ZIKV) epidemic where large proportions of infection were asymptomatic. However, multiple imperfect indicators of infection provide an opportunity to estimate the underlying incidence of infection. We developed a modeling approach that integrates a generic Time-series Susceptible-Infected-Recovered epidemic model with assumptions about reporting biases in a Bayesian framework and applied it to the 2016 Zika epidemic in Puerto Rico using three indicators: suspected arboviral cases, suspected Zika-associated Guillain-Barré Syndrome cases, and blood bank data. Using this combination of surveillance data, we estimated the peak of the epidemic occurred during the week of August 15, 2016 (the 33rd week of year), and 120 to 140 (50% credible interval [CrI], 95% CrI: 97 to 170) weekly infections per 10,000 population occurred at the peak. By the end of 2016, we estimated that approximately 890,000 (95% CrI: 660,000 to 1,100,000) individuals were infected in 2016 (26%, 95% CrI: 19% to 33%, of the population infected). Utilizing multiple indicators offers the opportunity for real-time and retrospective situational awareness to support epidemic preparedness and response.

Most nontyphoidal Salmonella (NTS) illnesses in the United States are thought to be foodborne. However, transmission routes likely vary among the different serotypes. We developed a relative ranking of NTS serotypes according to the strength of their association with foodborne transmission. We used Laboratory-based Enteric Disease Surveillance data to estimate the proportion of infections for each Salmonella serotype reported from 1998 to 2015 and Foodborne Disease Outbreak Surveillance System data to calculate the proportion of foodborne outbreak-associated Salmonella illnesses caused by each serotype. We calculated the ratios of these proportions to create a foodborne relatedness (FBR) measure for each serotype. Of the top 20 serotypes, Saintpaul (2.14), Heidelberg (1.61), and Berta (1.48) had the highest FBR measures; Mississippi (0.01), Bareilly (0.13), and Paratyphi B variant L(+) tartrate(+) (0.20) had the lowest. The FBRs for the three most prevalent serotypes were 1.22 for Enteritidis, 0.77 for Typhimurium, and 1.16 for Newport. This method provides a quantitative approach to estimating the relative differences in the likelihood that an illness caused by a particular serotype was transmitted by food, which may aid in tailoring strategies to prevent Salmonella illnesses and guide future research into serotype-specific source attribution.

BACKGROUND: Hepatitis A is a vaccine-preventable viral disease transmitted by the fecal-oral route. During 2016-2018, the County of San Diego investigated an outbreak of hepatitis A infections primarily among people experiencing homelessness (PEH) to identify risk factors and support control measures. At the time of the outbreak, homelessness was not recognized as an independent risk factor for the disease. METHODS: We tested the association between homelessness and infection with hepatitis A virus (HAV) using a test-negative study design comparing patients with laboratory-confirmed hepatitis A with control subjects who tested negative for HAV infection. We assessed risk factors for severe hepatitis A disease outcomes, including hospitalization and death, using multivariable logistic regression. We measured the frequency of indications for hepatitis A vaccination according to Advisory Committee on Immunization Practice (ACIP) guidelines. RESULTS: Among 589 outbreak-associated cases reported, 291 (49%) occurred among PEH. Compared with those who were not homeless, PEH were at 3.3 (95% CI: 1.5-7.9) times higher odds of HAV infection, 2.5 (95% CI: 1.7-3.9) times higher odds of hospitalization, and 3.9 (95% CI: 1.1-16.9) times higher odds of death associated with hepatitis A. Among PEH, 212 (73%) patients recorded other ACIP indications for hepatitis A vaccination. CONCLUSIONS: PEH were at higher risk for infection with HAV and higher risk for severe hepatitis A disease outcomes compared with those not experiencing homelessness. Approximately one-fourth of PEH had no other ACIP indication for hepatitis A vaccination. These findings support the recent ACIP recommendation to add homelessness as an indication for hepatitis A vaccination.

Listeria monocytogenes is a foodborne pathogen that disproportionally affects pregnant females, older adults, and immunocompromised individuals. Using U.S. Foodborne Diseases Active Surveillance Network (FoodNet) surveillance data, we examined listeriosis incidence rates and rate ratios (RRs) by age, sex, race/ethnicity, and pregnancy status across three periods from 2008 to 2016, as recent incidence trends in U.S. subgroups had not been evaluated. The invasive listeriosis annual incidence rate per 100,000 for 2008-2016 was 0.28 cases among the general population (excluding pregnant females), and 3.73 cases among pregnant females. For adults >/=70 years, the annual incidence rate per 100,000 was 1.33 cases. No significant change in estimated listeriosis incidence was found over the 2008-2016 period, except for a small, but significantly lower pregnancy-associated rate in 2011-2013 when compared with 2008-2010. Among the nonpregnancy-associated cases, RRs increased with age from 0.43 (95% confidence interval: 0.25-0.73) for 0- to 14-year olds to 44.9 (33.5-60.0) for >/=85-year olds, compared with 15- to 44-year olds. Males had an incidence of 1.28 (1.12-1.45) times that of females. Compared with non-Hispanic whites, the incidence was 1.57 (1.18-1.20) times higher among non-Hispanic Asians, 1.49 (1.22-1.83) among non-Hispanic blacks, and 1.73 (1.15-2.62) among Hispanics. Among females of childbearing age, non-Hispanic Asian females had 2.72 (1.51-4.89) and Hispanic females 3.13 (2.12-4.89) times higher incidence than non-Hispanic whites. We observed a higher percentage of deaths among older patient groups compared with 15- to 44-year olds. This study is the first characterizing higher RRs for listeriosis in the United States among non-Hispanic blacks and Asians compared with non-Hispanic whites. This information for public health risk managers may spur further research to understand if differences in listeriosis rates relate to differences in consumption patterns of foods with higher contamination levels, food handling practices, comorbidities, immunodeficiencies, health care access, or other factors.

In 2014, an acute respiratory illness outbreak affected unaccompanied children from Central America entering the US; 9% of 774 surveyed children were colonized with Streptococcus pneumoniae serotype 5. In our 2015 follow-up survey of 475 children, serotype 5 was not detected, and an interim recommendation to administer 13-valent pneumococcal conjugate vaccine to all unaccompanied children was discontinued.

Surveillance systems for West Nile virus (WNV) combine several methods to determine the location and timing of viral amplification. The value of each surveillance method must be measured against its efficiency and costs to optimize integrated vector management and suppress WNV transmission to the human population. Here we extend previous comparisons of WNV surveillance methods by equitably comparing the most common methods after standardization on the basis of spatial sampling density and costs, and by estimating optimal levels of sampling effort for mosquito traps and sentinel chicken flocks. In general, testing for evidence of viral RNA in mosquitoes and public-reported dead birds resulted in detection of WNV approximately 2-5 weeks earlier than serological monitoring of sentinel chickens at equal spatial sampling density. For a fixed cost, testing of dead birds reported by the public was found to be the most cost effective of the methods, yielding the highest number of positive results per $1000. Increased spatial density of mosquito trapping was associated with more precise estimates of WNV infection prevalence in mosquitoes. Our findings also suggested that the most common chicken flock size of 10 birds could be reduced to six to seven without substantial reductions in timeliness or sensitivity. We conclude that a surveillance system that uses the testing of dead birds reported by the public complemented by strategically timed mosquito and chicken sampling as agency resources allow would detect viral activity efficiently in terms of effort and costs, so long as susceptible bird species that experience a high mortality rate from infection with WNV, such as corvids, are present in the area.