Acute febrile illness (AFI) is a broad clinical syndrome with a wide range of potential infectious etiologies. The lack of accessible, standardized approaches to conducting AFI etiologic investigations has contributed to significant global gaps in data on the epidemiology of AFI. Based on lessons learned from years of supporting AFI sentinel surveillance worldwide, the U.S. Centers for Disease Control and Prevention developed the toolkit for planning and implementing AFI surveillance, described here. This toolkit provides a comprehensive yet flexible framework to guide researchers, public health officials, and other implementers in developing a strategy to identify and/or monitor the potential causes of AFI. The toolkit comprises a cohesive set of planning aids and supporting materials, including an implementation framework, generic protocol, several generic forms (including screening, case report, specimen collection and testing, and informed consent and assent), and a generic data dictionary. These materials incorporate key elements intended to harmonize approaches for AFI surveillance, as well as setting-specific components and considerations for adaptation based on local surveillance objectives and limitations. Appropriate adaptation and implementation of this toolkit may generate data that expand the global AFI knowledge base, strengthen countries' surveillance and laboratory capacity, and enhance outbreak detection and response efforts.

Diagnostic limitations challenge management of clinically indistinguishable acute infectious illness globally. Gene expression classification models show great promise distinguishing causes of fever. We generated transcriptional data for a 294-participant (USA, Sri Lanka) discovery cohort with adjudicated viral or bacterial infections of diverse etiology or non-infectious disease mimics. We then derived and cross-validated gene expression classifiers including: 1) a single model to distinguish bacterial vs. viral (Global Fever-Bacterial/Viral [GF-B/V]) and 2) a two-model system to discriminate bacterial and viral in the context of noninfection (Global Fever-Bacterial/Viral/Non-infectious [GF-B/V/N]). We then translated to a multiplex RT-PCR assay and independent validation involved 101 participants (USA, Sri Lanka, Australia, Cambodia, Tanzania). The GF-B/V model discriminated bacterial from viral infection in the discovery cohort an area under the receiver operator curve (AUROC) of 0.93. Validation in an independent cohort demonstrated the GF-B/V model had an AUROC of 0.84 (95% CI 0.76-0.90) with overall accuracy of 81.6% (95% CI 72.7-88.5). Performance did not vary with age, demographics, or site. Host transcriptional response diagnostics distinguish bacterial and viral illness across global sites with diverse endemic pathogens.

The SARS-CoV-2 Delta variant, first identified in October 2020, quickly became the dominant variant worldwide. We used publicly available data to explore the relationship between illness and death (peak case rates, death rates, case-fatality rates) and selected predictors (percentage vaccinated, percentage of the population >65 years, population density, testing volume, index of mitigation policies) in 45 high-income countries during the Delta wave using rank-order correlation and ordinal regression. During the Delta-dominant period, most countries reported higher peak case rates (57%) and lower peak case-fatality rates (98%). Higher vaccination coverage was protective against peak case rates (odds ratio 0.95, 95% CI 0.91-0.99) and against peak death rates (odds ratio 0.96, 95% CI 0.91-0.99). Vaccination coverage was vital to preventing infection and death from COVID-19 during the Delta wave. As new variants emerge, public health authorities should encourage the uptake of COVID-19 vaccination and boosters.

The design and execution of rigorous, fast, and ethical vaccine efficacy trials can be challenging during epidemics of emerging pathogens, such as the 2014-2016 Ebola virus and 2015-2016 Zika virus epidemics. Response to an urgent public health crisis requires accelerated research even as emerging epidemics themselves change rapidly and are inherently less well understood than well-established diseases. As part of the World Health Organization Research and Development Blueprint, we designed a web-based interactive decision support system (InterVax-Tool) to help diverse stakeholders navigate the epidemiological, logistical, and ethical decisions involved in designing a vaccine efficacy trial during a public health emergency. In contrast to existing literature on trial design, InterVax-Tool offers high-level visual and interactive assistance through a set of four decision trees, guiding users through selection of 1) the Primary Endpoint, (2) the Target Population, (3) Randomization, and (4) the Comparator. Guidance is provided on how each of fourteen key considerations–grouped as Epidemiological, Vaccine-related, Infrastructural, or Sociocultural–should be used to inform each decision in the trial design process. The tool is not intended to provide a black box decision framework for identifying an optimal trial design, but rather to facilitate transparent, collaborative and comprehensive discussion of the relevant decisions, while recording the decision process. The tool can also assist capacity building by providing a cross-disciplinary picture of trial design using concepts from epidemiology, study design, vaccinology, biostatistics, mathematical modeling and clinical research ethics. Here, we describe the goals and features of InterVax-Tool as well as its application to the design of a Zika vaccine efficacy trial.One Sentence Summary An interactive web-based decision support tool was developed to assist in the design of vaccine efficacy trials during emerging outbreaks.

SARS-CoV-2 seroprevalence surveys provide critical information to assess the burden of COVID-19, describe population immunity, and guide public health strategies. Early in the pandemic, most of these surveys were conducted within high-income countries, leaving significant knowledge gaps in low-and middle-income (LMI) countries. To address this gap, the U.S. Centers for Disease Control and Prevention (CDC) is supporting serosurveys internationally. We conducted a descriptive analysis of international serosurveys supported by CDC during May 12, 2020-February 28, 2022, using an internal tracker including data on the type of assistance provided, study design, population surveyed, laboratory testing performed, and status of implementation. Since the beginning of the pandemic, CDC has supported 72 serosurveys (77 serosurvey rounds) in 35 LMI countries by providing technical assistance (TA) on epidemiologic, statistical, and laboratory methods, financial assistance (FA), or both. Among these serosurvey rounds, the majority (61%) received both TA and FA from CDC, 30% received TA only, 3% received only FA, and 5% were part of informal reviews. Fifty-four percent of these serosurveys target the general population, 13% sample pregnant women, 7% sample healthcare workers, 7% sample other special populations (internally displaced persons, patients, students, and people living with HIV), and 18% assess multiple or other populations. These studies are in different stages of implementation, ranging from protocol development to dissemination of results. They are conducted under the leadership of local governments, who have ownership over the data, in collaboration with international partners. Thirty-four surveys rounds have completed data collection. CDC TA and FA of SARS-CoV-2 seroprevalence surveys will enhance the knowledge of the COVID-19 pandemic in almost three dozen LMI countries. Support for these surveys should account for current limitations with interpreting results, focusing efforts on prospective cohorts, identifying, and forecasting disease patterns over time, and helping understand antibody kinetics and correlates of protection. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license.

BACKGROUND: The study of the etiology of acute febrile illness (AFI) has historically been designed as a prevalence of pathogens detected from a case series. This strategy has an inherent unrealistic assumption that all pathogen detection allows for causal attribution, despite known asymptomatic carriage of the principal causes of acute febrile illness in most low- and middle-income countries (LMICs). We designed a semi-quantitative PCR in a modular format to detect bloodborne agents of acute febrile illness that encompassed common etiologies of AFI in the region, etiologies of recent epidemics, etiologies that require an immediate public health response and additional pathogens of unknown endemicity. We then designed a study that would delineate background levels of transmission in the community in the absence of symptoms to provide corrected estimates of attribution for the principal determinants of AFI. METHODS: A case-control study of acute febrile illness in patients ten years or older seeking health care in Iquitos, Loreto, Peru, was planned. Upon enrollment, we will obtain blood, saliva, and mid-turbinate nasal swabs at enrollment with a follow-up visit on day 21-28 following enrollment to attain vital status and convalescent saliva and blood samples, as well as a questionnaire including clinical, socio-demographic, occupational, travel, and animal contact information for each participant. Whole blood samples are to be simultaneously tested for 32 pathogens using TaqMan array cards. Mid-turbinate samples will be tested for SARS-CoV-2, Influenza A and Influenza B. Conditional logistic regression models will be fitted treating case/control status as the outcome and with pathogen-specific sample positivity as predictors to attain estimates of attributable pathogen fractions for AFI. DISCUSSION: The modular PCR platforms will allow for reporting of all primary results of respiratory samples within 72 h and blood samples within one week, allowing for results to influence local medical practice and enable timely public health responses. The inclusion of controls will allow for a more accurate estimate of the importance of specific prevalent pathogens as a cause of acute illness. STUDY REGISTRATION: Project 1791, Registro de Proyectos de Investigación en Salud Pública (PRISA), Instituto Nacional de Salud, Perú.

The global COVID-19 response focused heavily on nonpharmaceutical interventions (NPIs) until vaccines became available. Even where vaccination coverage is low, over time governments have become increasingly reluctant to use NPIs. Inequities in vaccine and treatment accessibility and coverage, differences in vaccine effectiveness, waning immunity, and immune-escape variants of concern of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reinforce the long-term need for mitigation. Initially, the concept of NPIs, and mitigation more broadly, was focused on prevention of SARS-CoV-2 transmission; however, mitigation can and has done more than prevent transmission. It has been used to address the clinical dimensions of the pandemic as well. The authors propose an expanded conceptualization of mitigation that encompasses a continuum of community and clinical mitigation measures that can help reduce infection, illness, and death from COVID-19. It can further help governments balance these efforts and address the disruptions in essential health services, increased violence, adverse mental health outcomes, and orphanhood precipitated by the pandemic and by NPIs themselves. The COVID-19 pandemic response revealed the benefits of a holistic and layered mitigation approach to public health emergencies from the outset. Lessons learned can inform the next phases of the current pandemic response and planning for future public health emergencies.

Confronted with a novel coronavirus, countries worldwide were forced to rapidly adjust their public health systems, platforms, and tools to respond to COVID-19. The US Centers for Disease Control and Prevention (CDC) and its global partners adapted health systems and programs originally developed for other purposes, such as controlling the HIV/AIDS pandemic through the US President’s Emergency Plan for AIDS Relief (PEPFAR), Global Health Security Agenda implementation, influenza surveillance, and vaccine-preventable disease elimination and eradication. This special supplement of Emerging Infectious Diseases highlights responses to the early phases of the COVID-19 pandemic from >80 countries, spanning 6 continents and representing >130 organizations. This article summarizes global adaptations of core public health functions during COVID-19: surveillance, information, and laboratory systems; workforce, institutional, and public health capacity; and clinical and health services delivery.

Existing acute febrile illness (AFI) surveillance systems can be leveraged to identify and characterize emerging pathogens, such as SARS-CoV-2, which causes COVID-19. The US Centers for Disease Control and Prevention collaborated with ministries of health and implementing partners in Belize, Ethiopia, Kenya, Liberia, and Peru to adapt AFI surveillance systems to generate COVID-19 response information. Staff at sentinel sites collected epidemiologic data from persons meeting AFI criteria and specimens for SARS-CoV-2 testing. A total of 5,501 patients with AFI were enrolled during March 2020-October 2021; >69% underwent SARS-CoV-2 testing. Percentage positivity for SARS-CoV-2 ranged from 4% (87/2,151, Kenya) to 19% (22/115, Ethiopia). We show SARS-CoV-2 testing was successfully integrated into AFI surveillance in 5 low- to middle-income countries to detect COVID-19 within AFI care-seeking populations. AFI surveillance systems can be used to build capacity to detect and respond to both emerging and endemic infectious disease threats.

The emergence of Marburg virus (MARV) in Guinea and Ghana triggered the assembly of the MARV vaccine "MARVAC" consortium representing leaders in the field of vaccine research and development aiming to facilitate a rapid response to this infectious disease threat. Here, we discuss current progress, challenges, and future directions for MARV vaccines.

SARS-CoV-2 seroprevalence surveys provide critical information to assess the burden of COVID-19, describe population immunity, and guide public health strategies. Early in the pandemic, most of these surveys were conducted within high-income countries, leaving significant knowledge gaps in low-and middle-income (LMI) countries. To address this gap, the U.S. Centers for Disease Control and Prevention (CDC) is supporting serosurveys internationally. We conducted a descriptive analysis of international serosurveys supported by CDC during May 12, 2020-February 28, 2022, using an internal tracker including data on the type of assistance provided, study design, population surveyed, laboratory testing performed, and status of implementation. Since the beginning of the pandemic, CDC has supported 72 serosurveys (77 serosurvey rounds) in 35 LMI countries by providing technical assistance (TA) on epidemiologic, statistical, and laboratory methods, financial assistance (FA), or both. Among these serosurvey rounds, the majority (61%) received both TA and FA from CDC, 30% received TA only, 3% received only FA, and 5% were part of informal reviews. Fifty-four percent of these serosurveys target the general population, 13% sample pregnant women, 7% sample healthcare workers, 7% sample other special populations (internally displaced persons, patients, students, and people living with HIV), and 18% assess multiple or other populations. These studies are in different stages of implementation, ranging from protocol development to dissemination of results. They are conducted under the leadership of local governments, who have ownership over the data, in collaboration with international partners. Thirty-four surveys rounds have completed data collection. CDC TA and FA of SARS-CoV-2 seroprevalence surveys will enhance the knowledge of the COVID-19 pandemic in almost three dozen LMI countries. Support for these surveys should account for current limitations with interpreting results, focusing efforts on prospective cohorts, identifying, and forecasting disease patterns over time, and helping understand antibody kinetics and correlates of protection.

INTRODUCTION: The metabolomics quality assurance and quality control consortium (mQACC) is enabling the identification, development, prioritization, and promotion of suitable reference materials (RMs) to be used in quality assurance (QA) and quality control (QC) for untargeted metabolomics research. OBJECTIVES: This review aims to highlight current RMs, and methodologies used within untargeted metabolomics and lipidomics communities to ensure standardization of results obtained from data analysis, interpretation and cross-study, and cross-laboratory comparisons. The essence of the aims is also applicable to other 'omics areas that generate high dimensional data. RESULTS: The potential for game-changing biochemical discoveries through mass spectrometry-based (MS) untargeted metabolomics and lipidomics are predicated on the evolution of more confident qualitative (and eventually quantitative) results from research laboratories. RMs are thus critical QC tools to be able to assure standardization, comparability, repeatability and reproducibility for untargeted data analysis, interpretation, to compare data within and across studies and across multiple laboratories. Standard operating procedures (SOPs) that promote, describe and exemplify the use of RMs will also improve QC for the metabolomics and lipidomics communities. CONCLUSIONS: The application of RMs described in this review may significantly improve data quality to support metabolomics and lipidomics research. The continued development and deployment of new RMs, together with interlaboratory studies and educational outreach and training, will further promote sound QA practices in the community.

BACKGROUND: The collaborative integrated surveillance system known as Vigilancia Integrada Comunitaria (ViCo) was implemented in 2007 to better understand and characterize the burden of diarrheal, respiratory and febrile illnesses in Guatemala. METHODS: To evaluate the usefulness of ViCo and inform a redesign of the system and new surveillance activities in the Central American region, personnel from the United States Centers for Disease Control and Prevention (CDC) conducted thirty-nine in-depth interviews from June-December 2018 with key stakeholders responsible for the design and implementation of ViCo in Guatemala. A semi-structured questionnaire adapted from the Updated CDC Guidelines for Evaluating Public Health Surveillance Systems was used for data collection. We used a grounded theory approach to explore stakeholder perceptions of ViCo and generate recommendations for improvement. Primary qualitative findings were organized based on thematic areas using ATLAS.ti version 8 software. RESULTS: Emergent themes relevant to the usefulness of ViCo were organized across strengths, weaknesses, and recommendations pertaining to the: (1) Size and Complexity of ViCo, (2) Stakeholder Expectations About the Objectives of ViCo, (3) Data Management and Structure of the Information System, (4) Local Control of Data, (5) Integration of ViCo within the Ministry of Health, and, (6) Improvement of the Operational and Design Aspects of ViCo across System, Process, and Output levels. CONCLUSIONS: Stakeholders perceived ViCo to be useful. They recommended measures to improve system performance and quality, including simplifying the surveillance system, routine data analysis and feedback, and channeling efforts towards integrating surveillance data into the national health information system. To create a well-performing surveillance system and achieve the intended objective of surveillance for public health action, ongoing evaluation and assessment of surveillance activities are necessary.

As cases and deaths from coronavirus disease 2019 (COVID-19) in Europe rose sharply in late March, most European countries implemented strict mitigation policies, including closure of nonessential businesses and mandatory stay-at-home orders. These policies were largely successful at curbing transmission of SARS-CoV-2, the virus that causes COVID-19 (1), but they came with social and economic costs, including increases in unemployment, interrupted education, social isolation, and related psychosocial outcomes (2,3). A better understanding of when and how these policies were effective is needed. Using data from 37 European countries, the impact of the timing of these mitigation policies on mortality from COVID-19 was evaluated. Linear regression was used to assess the association between policy stringency at an early time point and cumulative mortality per 100,000 persons on June 30. Implementation of policies earlier in the course of the outbreak was associated with lower COVID-19-associated mortality during the subsequent months. An increase by one standard deviation in policy stringency at an early timepoint was associated with 12.5 cumulative fewer deaths per 100,000 on June 30. Countries that implemented stringent policies earlier might have saved several thousand lives relative to those countries that implemented similar policies, but later. Earlier implementation of mitigation policies, even by just a few weeks, might be an important strategy to reduce the number of deaths from COVID-19.

Lipidomics is a rapidly growing field, fueled by developments in analytical instrumentation and bioinformatics. To date, most researchers and industries have employed their own lipidomics workflows without a consensus on best practices. Without a community-wide consensus on best practices for the prevention of lipid degradation and transformations through sample collection and analysis, it is difficult to assess the quality of lipidomics data and hence trust results. Clinical studies often rely on samples being stored for weeks or months until they are analyzed, but inappropriate sampling techniques, storage temperatures, and analytical protocols can result in the degradation of complex lipids and the generation of oxidized or hydrolyzed metabolite artifacts. While best practices for lipid stability are sample dependent, it is generally recommended that strategies during sample preparation capable of quenching enzymatic activity and preventing oxidation should be considered. In addition, after sample preparation, lipid extracts should be stored in organic solvents with antioxidants at -20 degrees C or lower in an airtight container without exposure to light or oxygen. This will reduce or eliminate sublimation, and chemically and physically induced molecular transformations such as oxidation, enzymatic transformation, and photon/heat-induced degradation. This review explores the available literature on lipid stability, with a particular focus on human health and/or clinical lipidomic applications. Specifically, this includes a description of known mechanisms of lipid degradation, strategies, and considerations for lipid storage, as well as current efforts for standardization and quality insurance of protocols.

BACKGROUND: Diarrhea is a major cause of morbidity and mortality, yet incidence and etiology data are limited. We conducted laboratory-based diarrhea surveillance in Guatemala. METHODS: A diarrhea case was defined as >/=3 loose stools in a 24-h period in a person presenting to the surveillance facilities. Epidemiologic data and stool specimens were collected. Specimens were tested for bacterial, parasitic, and viral pathogens. Yearly incidence was adjusted for healthcare seeking behaviors determined from a household survey conducted in the surveillance catchment area. RESULTS: From November 2008 to December 2012, the surveillance system captured 5331 diarrhea cases; among these 1381 (26%) had specimens tested for all enteric pathogens of interest. The adjusted incidence averaged 659 diarrhea cases per 10,000 persons per year, and was highest among children aged < 5 years, averaging 1584 cases per 10,000 children per year. Among 1381 (26%) specimens tested for all the pathogens of interest, 235 (17%) had a viral etiology, 275 (20%) had a bacterial, 50 (4%) had parasites, and 86 (6%) had co-infections. Among 827 (60%) specimens from children aged < 5 years, a virus was identified in 196 (23%) patients; 165 (20%) had norovirus and 99 (12%) rotavirus, including co-infections. Among 554 patients aged >/=5 years, 103 (19%) had a bacterial etiology, including diarrheagenic Escherichia coli in 94 (17%) cases, Shigella spp. in 31 (6%), Campylobacter spp. in 5 (1%), and Salmonella spp. in 4 (1%) cases. Detection of Giardia and Cryptosporidium was infrequent (73 cases; 5%). CONCLUSIONS: There was a substantial burden of viral and bacterial diarrheal diseases in Guatemala, highlighting the importance of strengthening laboratory capacity for rapid detection and control and for evaluation of public health interventions.

BACKGROUND: Licensed vaccines are urgently needed for emerging infectious diseases, but the nature of these epidemics causes challenges for the design of phase III trials to evaluate vaccine efficacy. Designing and executing rigorous, fast, and ethical, vaccine efficacy trials is difficult, and the decisions and limitations in the design of these trials encompass epidemiological, logistical, regulatory, statistical, and ethical dimensions. RESULTS: Trial design decisions are complex and interrelated, but current guidance documents do not lend themselves to efficient decision-making. We created InterVax-Tool (http://vaxeval.com), an online, interactive decision-support tool, to help diverse stakeholders navigate the decisions in the design of phase III vaccine trials. InterVax-Tool offers high-level visual and interactive assistance through a set of four decision trees, guiding users through selection of the: (1) Primary Endpoint, (2) Target Population, (3) Randomization Scheme, and, (4) Comparator. We provide guidance on how key considerations - grouped as Epidemiological, Vaccine-related, Infrastructural, or Sociocultural - inform each decision in the trial design process. CONCLUSIONS: InterVax-Tool facilitates structured, transparent, and collaborative discussion of trial design, while recording the decision-making process. Users can save and share their decisions, which is useful both for comparing proposed trial designs, and for justifying particular design choices. Here, we describe the goals and features of InterVax-Tool as well as its application to the design of a Zika vaccine efficacy trial.

Worldwide, infectious diseases continue to emerge at an alarming pace, due to numerous factors including microbial adaptation, increasing human population migration, urbanization, conflict and instability, intensified animal-human interface, and habitat perturbation [1,2,3,4,5,6]. The litmus test for an effective national public health program is its ability to be ready to initiate an effective response for an unknown emerging or re-emerging infectious disease or public health event. The most impactful global health programs are built with the understanding that they must be able to help countries strengthen core public health capacity so that new threats can be detected and contained before they become international crises that increase morbidity and mortality, adversely impact the health and livelihoods of individuals and populations, disrupt travel, interfere with global trade and economies, or even lead to political destabilization [6, 7].

We sought datasets with granular age distributions of rotavirus-positive presentations among children <5 years of age, before the introduction of rotavirus vaccines. We identified 117 datasets and fit parametric age distributions to each country dataset and mortality stratum and calculated the median age, and cumulative proportion of rotavirus gastroenteritis events expected to occur at ages between birth and 5.0 years. The median age of rotavirus-positive hospital admissions was 38 weeks (inter-quartile range IQR: 25-58) in countries with very high child mortality and 65 weeks (IQR: 40-107) in countries with very low/low child mortality. In countries with very high child mortality 69% of rotavirus-positive admissions <5 years were in the first year of life, with 3% by 10 weeks, 8% by 15 weeks and 27% by 26 weeks. This information is critical for assessing the potential benefits of alternative rotavirus vaccination schedules in different countries, and for monitoring programme impact.

Background: Culture-independent diagnostic tests (CIDTs) are increasingly used to diagnose Campylobacter infection in the Foodborne Diseases Active Surveillance Network (FoodNet). Because CIDTs have different performance characteristics compared with culture, which has been used historically and is still used to diagnose campylobacteriosis, adjustment of cases diagnosed by CIDT is needed to compare with culture-confirmed cases for monitoring incidence trends. Methods: We identified the necessary parameters for CIDT adjustment using culture as the gold standard, and derived formulas to calculate positive predictive values (PPVs). We conducted a literature review and meta-analysis to examine the variability in CIDT performance and Campylobacter prevalence applicable to FoodNet sites. We then developed a Monte Carlo method to estimate test-type and site-specific PPVs with their associated uncertainties. Results: The uncertainty in our estimated PPVs was largely derived from uncertainty about the specificity of CIDTs and low prevalence of Campylobacter in tested samples. Stable CIDT-adjusted incidences of Campylobacter cases from 2012 to 2015 were observed compared with a decline in culture-confirmed incidence. Conclusions: We highlight the lack of data on the total numbers of tested samples as one of main limitations for CIDT adjustment. Our results demonstrate the importance of adjusting CIDTs for understanding trends in Campylobacter incidence in FoodNet.

The Centers for Disease Control and Prevention has established 10 Global Disease Detection (GDD) Program regional centers around the world that serve as centers of excellence for public health research on emerging and reemerging infectious diseases. The core activities of the GDD Program focus on applied public health research, surveillance, laboratory, public health informatics, and technical capacity building. During 2015-2016, program staff conducted 205 discrete projects on a range of topics, including acute respiratory illnesses, health systems strengthening, infectious diseases at the human-animal interface, and emerging infectious diseases. Projects incorporated multiple core activities, with technical capacity building being most prevalent. Collaborating with host countries to implement such projects promotes public health diplomacy. The GDD Program continues to work with countries to strengthen core capacities so that emerging diseases can be detected and stopped faster and closer to the source, thereby enhancing global health security.

The Foodborne Diseases Active Surveillance Network (FoodNet) conducts population-based surveillance for Campylobacter infection. For 2010 through 2015, we compared patients with Campylobacter jejuni with patients with infections caused by other Campylobacter species. Campylobacter coli patients were more often >40 years of age (OR = 1.4), Asian (OR = 2.3), or Black (OR = 1.7), and more likely to live in an urban area (OR = 1.2), report international travel (OR = 1.5), and have infection in autumn or winter (OR = 1.2). Campylobacter upsaliensis patients were more likely female (OR = 1.6), Hispanic (OR = 1.6), have a blood isolate (OR = 2.8), and have an infection in autumn or winter (OR = 1.7). Campylobacter lari patients were more likely to be >40 years of age (OR = 2.9) and have an infection in autumn or winter (OR = 1.7). Campylobacter fetus patients were more likely male (OR = 3.1), hospitalized (OR = 3.5), and have a blood isolate (OR = 44.1). International travel was associated with antimicrobial-resistant C. jejuni (OR = 12.5) and C. coli (OR = 12) infections. Species-level data are useful in understanding epidemiology, sources, and resistance of infections.

Salmonella causes an estimated 1.2 million illnesses annually in the USA. Salmonella enterica serotype Javiana (serotype Javiana) is the fourth most common serotype isolated from humans, with the majority of illnesses occurring in southeastern states. The percentage of wetland cover by wetland type and the average incidence rates of serotype Javiana infection in selected counties of the Foodborne Disease Active Surveillance Network (FoodNet) were examined. This analysis explored the relationship between wetland environments and incidence in order to assess whether regional differences in environmental habitats may be associated with observed variations in incidence. Findings suggest that environmental habitats may support reservoirs or contribute to the persistence of serotype Javiana, and may frequently contribute to the transmission of infection compared with other Salmonella serotypes.

The Foodborne Diseases Active Surveillance Network (FoodNet) is currently using a negative binomial (NB) regression model to estimate temporal changes in the incidence of Campylobacter infection. FoodNet active surveillance in 483 counties collected data on 40,212 Campylobacter cases between years 2004 and 2011. We explored models that disaggregated these data to allow us to account for demographic, geographic, and seasonal factors when examining changes in incidence of Campylobacter infection. We hypothesized that modeling structural zeros and including demographic variables would increase the fit of FoodNet's Campylobacter incidence regression models. Five different models were compared: NB without demographic covariates, NB with demographic covariates, hurdle NB with covariates in the count component only, hurdle NB with covariates in both zero and count components, and zero-inflated NB with covariates in the count component only. Of the models evaluated, the nonzero-augmented NB model with demographic variables provided the best fit. Results suggest that even though zero inflation was not present at this level, individualizing the level of aggregation and using different model structures and predictors per site might be required to correctly distinguish between structural and observational zeros and account for risk factors that vary geographically.

Developing a surveillance system during a public health emergency is always challenging but is especially so in countries with limited public health infrastructure. Surveillance for Ebola virus disease (Ebola) in the West African countries heavily affected by Ebola (Guinea, Liberia, and Sierra Leone) faced numerous impediments, including insufficient numbers of trained staff, community reticence to report cases and contacts, limited information technology resources, limited telephone and Internet service, and overwhelming numbers of infected persons. Through the work of CDC and numerous partners, including the countries' ministries of health, the World Health Organization, and other government and nongovernment organizations, functional Ebola surveillance was established and maintained in these countries. CDC staff were heavily involved in implementing case-based surveillance systems, sustaining case surveillance and contact tracing, and interpreting surveillance data. In addition to helping the ministries of health and other partners understand and manage the epidemic, CDC's activities strengthened epidemiologic and data management capacity to improve routine surveillance in the countries affected, even after the Ebola epidemic ended, and enhanced local capacity to respond quickly to future public health emergencies. However, the many obstacles overcome during development of these Ebola surveillance systems highlight the need to have strong public health, surveillance, and information technology infrastructure in place before a public health emergency occurs. Intense, long-term focus on strengthening public health surveillance systems in developing countries, as described in the Global Health Security Agenda, is needed.The activities summarized in this report would not have been possible without collaboration with many U.S and international partners (http://www.cdc.gov/vhf/ebola/outbreaks/2014-west-africa/partners.html).

To evaluate progress toward prevention of enteric and foodborne illnesses in the United States, the Foodborne Diseases Active Surveillance Network (FoodNet) monitors the incidence of laboratory-confirmed infections caused by nine pathogens transmitted commonly through food in 10 U.S. sites.* This report summarizes preliminary 2015 data and describes trends since 2012. In 2015, FoodNet reported 20,107 confirmed cases (defined as culture-confirmed bacterial infections and laboratory-confirmed parasitic infections), 4,531 hospitalizations, and 77 deaths. FoodNet also received reports of 3,112 positive culture-independent diagnostic tests (CIDTs) without culture-confirmation, a number that has markedly increased since 2012 (1). Diagnostic testing practices for enteric pathogens are rapidly moving away from culture-based methods. The continued shift from culture-based methods to CIDTs that do not produce the isolates needed to distinguish between strains and subtypes affects the interpretation of public health surveillance data and ability to monitor progress toward prevention efforts. Expanded case definitions and strategies for obtaining bacterial isolates are crucial during this transition period.

The Foodborne Diseases Active Surveillance Network (FoodNet) provides a foundation for food safety policy and illness prevention in the United States. FoodNet conducts active, population-based surveillance at 10 US sites for laboratory-confirmed infections of 9 bacterial and parasitic pathogens transmitted commonly through food and for hemolytic uremic syndrome. Through FoodNet, state and federal scientists collaborate to monitor trends in enteric illnesses, identify their sources, and implement special studies. FoodNet's major contributions include establishment of reliable, active population-based surveillance of enteric diseases; development and implementation of epidemiologic studies to determine risk and protective factors for sporadic enteric infections; population and laboratory surveys that describe the features of gastrointestinal illnesses, medical care-seeking behavior, frequency of eating various foods, and laboratory practices; and development of a surveillance and research platform that can be adapted to address emerging issues. The importance of FoodNet's ongoing contributions probably will grow as clinical, laboratory, and informatics technologies continue changing rapidly.

BACKGROUND: A growing segment of the population-adults aged ≥65 years-is more susceptible than younger adults to certain enteric (including foodborne) infections and experience more severe disease. MATERIALS AND METHODS: Using data on laboratory-confirmed infections from the Foodborne Diseases Active Surveillance Network (FoodNet), we describe trends in the incidence of Campylobacter spp., Escherichia coli O157, Listeria monocytogenes, and nontyphoidal Salmonella infections in adults aged ≥65 years over time and by age group and sex. We used data from FoodNet and other sources to estimate the total number of illnesses, hospitalizations, and deaths in the United States caused by these infections each year using a statistical model to adjust for underdiagnosis (taking into account medical care-seeking, stool sample submission, laboratory practices, and test sensitivity). RESULTS: From 1996 to 2012, 4 pathogens caused 21,405 laboratory-confirmed infections among older adults residing in the FoodNet surveillance area; 49.3% were hospitalized, and 2.6% died. The average annual rate of infection was highest for Salmonella (12.8/100,000) and Campylobacter (12.1/100,000). Salmonella and Listeria led as causes of death. Among older adults, rates of laboratory-confirmed infection and the percentage of patients who were hospitalized and who died generally increased with age. A notable exception was the rate of Campylobacter infections, which decreased with increasing age. Adjusting for underdiagnosis, we estimated that these pathogens caused about 226,000 illnesses ( approximately 600/100,000) annually among U.S. adults aged ≥65 years, resulting in approximately 9700 hospitalizations and approximately 500 deaths. CONCLUSIONS: Campylobacter, E. coli O157, Listeria, and Salmonella are major contributors to illness in older adults, highlighting the value of effective and targeted intervention.

Foodborne illnesses represent a substantial, yet largely preventable, health burden in the United States. In 10 U.S. geographic areas, the Foodborne Diseases Active Surveillance Network* (FoodNet) monitors the incidence of laboratory-confirmed infections caused by nine pathogens transmitted commonly through food. This report summarizes preliminary 2014 data and describes changes in incidence compared with 2006-2008 and 2011-2013. In 2014, FoodNet reported 19,542 infections, 4,445 hospitalizations, and 71 deaths. The incidence of Shiga toxin-producing Escherichia coli (STEC) O157 and Salmonella enterica serotype Typhimurium infections declined in 2014 compared with 2006-2008, and the incidence of infection with Campylobacter, Vibrio, and Salmonella serotypes Infantis and Javiana was higher. Compared with 2011-2013, the incidence of STEC O157 and Salmonella Typhimurium infections was lower, and the incidence of STEC non-O157 and Salmonella serotype Infantis infections was higher in 2014. Despite ongoing food safety efforts, the incidence of many infections remains high, indicating that further prevention measures are needed to make food safer and achieve national health objectives.

The increased availability and rapid adoption of culture-independent diagnostic tests (CIDTs) is moving clinical detection of bacterial enteric infections away from culture-based methods. These new tests do not yield isolates that are currently needed for further tests to distinguish among strains or subtypes of Salmonella, Campylobacter, Shiga toxin-producing Escherichia coli, and other organisms. Public health surveillance relies on this detailed characterization of isolates to monitor trends and rapidly detect outbreaks; consequently, the increased use of CIDTs makes prevention and control of these infections more difficult. During 2012-2013, the Foodborne Diseases Active Surveillance Network (FoodNet*) identified a total of 38,666 culture-confirmed cases and positive CIDT reports of Campylobacter, Salmonella, Shigella, Shiga toxin-producing E. coli, Vibrio, and Yersinia. Among the 5,614 positive CIDT reports, 2,595 (46%) were not confirmed by culture. In addition, a 2014 survey of clinical laboratories serving the FoodNet surveillance area indicated that use of CIDTs by the laboratories varied by pathogen; only CIDT methods were used most often for detection of Campylobacter (10%) and STEC (19%). Maintaining surveillance of bacterial enteric infections in this period of transition will require enhanced surveillance methods and strategies for obtaining bacterial isolates.