Family ideals in an era of low fertility.

Taking stock of individuals' perceived family ideals is particularly important in the current moment given unprecedented fertility declines and the diversification of households in advanced industrial societies. Study participants in urban China, Japan, South Korea, Singapore, the United States, Italy, Spain, and Norway were asked to evaluate vignettes describing families whose characteristics vary on ten dimensions. In contrast to previous studies that focused on a single dimension, such as fertility ideals or gender roles, this holistic vignette approach identifies the relative importance of each dimension. Multilevel regression analysis reveals both expected and unexpected findings. Parenthood remains a positive ideal, but the number of children does not matter once other family dimensions are considered, a potentially important finding in light of conventional wisdom regarding the two-children ideal. When evaluating families with at least one child, respondents tend to positively evaluate more traditional arrangements, including valuing marriage relative to cohabitation and, particularly, divorce. Also, in addition to financial resources, good communication between immediate and extended family members, as well as maintaining respect in the larger community, are highly salient attributes of an ideal family. Notwithstanding some important cross-national differences, egalitarian gender roles and avoiding work-family conflict are also valued positively. Overall, even as the study reveals some notable variations between societies, respondents across countries identify similar components of an ideal family.

Nationwide law enforcement impact on the pet bird trade in China.

Conservation enforcement is a direct strategy to combat illegal wildlife trade in open markets. Yet, its large-scale effectiveness has not been widely assessed due to the lack of extensive market data. Between August 2016 and June 2017, a national coordinated enforcement campaign led by the leading Chinese authority to combat illegal migratory bird trade coincided with the largest-ever pet bird market survey across China by voluntary birdwatchers before and after the enforcement, which served as a unique natural experiment. Across 73 markets from 22 Chinese provinces, the dataset contains 140,723 birds of 346 species from 48 families and recorded a drastic decline in bird abundance traded after enforcement. Notably, species protected under China's Wildlife Protection Law declined significantly, while commercially bred species increased, although responses to enforcement were spatially heterogeneous. Our model showed that the national protection level was the best predictor for the trend of traded species, even after accounting for confounding factors such as regional baseline enforcement pressure and wild native bird populations. However, the widely traded native songbirds were not offered adequate national protection. Future policies should consider the pet bird trade patterns, target key areas of trade, and develop a more systematic market survey design to monitor trade.

Can Generative AI improve social science?

Generative AI that can produce realistic text, images, and other human-like outputs is currently transforming many different industries. Yet it is not yet known how such tools might influence social science research. I argue Generative AI has the potential to improve survey research, online experiments, automated content analyses, agent-based models, and other techniques commonly used to study human behavior. In the second section of this article, I discuss the many limitations of Generative. I examine how bias in the data used to train these tools can negatively impact social science research-as well as a range of other challenges related to ethics, replication, environmental impact, and the proliferation of low-quality research. I conclude by arguing that social scientists can address many of these limitations by creating open-source infrastructure for research on human behavior. Such infrastructure is not only necessary to ensure broad access to high-quality research tools, I argue, but also because the progress of AI will require deeper understanding of the social forces that guide human behavior.

Consistently estimating network statistics using aggregated relational data.

Collecting complete network data is expensive, time-consuming, and often infeasible. Aggregated Relational Data (ARD), which ask respondents questions of the form "How many people with trait X do you know?" provide a low-cost option when collecting complete network data is not possible. Rather than asking about connections between each pair of individuals directly, ARD collect the number of contacts the respondent knows with a given trait. Despite widespread use and a growing literature on ARD methodology, there is still no systematic understanding of when and why ARD should accurately recover features of the unobserved network. This paper provides such a characterization by deriving conditions under which statistics about the unobserved network (or functions of these statistics like regression coefficients) can be consistently estimated using ARD. We first provide consistent estimates of network model parameters for three commonly used probabilistic models: the beta-model with node-specific unobserved effects, the stochastic block model with unobserved community structure, and latent geometric space models with unobserved latent locations. A key observation is that cross-group link probabilities for a collection of (possibly unobserved) groups identify the model parameters, meaning ARD are sufficient for parameter estimation. With these estimated parameters, it is possible to simulate graphs from the fitted distribution and analyze the distribution of network statistics. We can then characterize conditions under which the simulated networks based on ARD will allow for consistent estimation of the unobserved network statistics, such as eigenvector centrality, or response functions by or of the unobserved network, such as regression coefficients.

For living well, behaviors and circumstances matter just as much as psychological traits.

In 2004 through 2016, three studies in the national Midlife in the United States (MIDUS) project asked participants the open-ended question "What do you do to make life go well?". We use verbatim responses to this question to evaluate the relative importance of psychological traits and circumstances for predicting self-reported, subjective well-being. The use of an open-ended question allows us to test the hypothesis that psychological traits are more strongly associated with self-reported well-being than objective circumstances because psychological traits and well-being are similarly self-rated-meaning that they both ask respondents to decide how to place themselves on provided and unfamiliar survey scales. For this, we use automated zero-shot classification to score statements about well-being without training on existing survey measures, and we evaluate this scoring through subsequent hand-labeling. We then assess associations of this measure and closed-ended measures for health behaviors, socioeconomic circumstances, biomarkers for inflammation and glycemic control, and mortality risk over follow-up. Although the closed-ended measures were far more strongly associated with other multiple-choice self-ratings, including Big 5 personality traits, the closed- and open-ended measures were similarly associated with relatively objective indicators of health, wealth, and social connectedness. The findings suggest that psychological traits, when collected through self-ratings, predict subjective reports of well-being so strongly because of a measurement advantage-and that circumstance matters just as much when assessed using a fairer comparison.

Widespread support for a global species list with a formal governance system.

Taxonomic data are a scientific common. Unlike nomenclature, which has strong governance institutions, there are currently no generally accepted governance institutions for the compilation of taxonomic data into an accepted global list. This gap results in challenges for conservation, ecological research, policymaking, international trade, and other areas of scientific and societal importance. Consensus on a global list and its management requires effective governance and standards, including agreed mechanisms for choosing among competing taxonomies and partial lists. However, governance frameworks are currently lacking, and a call for governance in 2017 generated critical responses. Any governance system to which compliance is voluntary requires a high level of legitimacy and credibility among those by and for whom it is created. Legitimacy and credibility, in turn, require adequate and credible consultation. Here, we report on the results of a global survey of taxonomists, scientists from other disciplines, and users of taxonomy designed to assess views and test ideas for a new system of taxonomic list governance. We found a surprisingly high degree of agreement on the need for a global list of accepted species and their names, and consistent views on what such a list should provide to users and how it should be governed. The survey suggests that consensus on a mechanism to create, manage, and govern a single widely accepted list of all the world's species is achievable. This finding was unexpected given past controversies about the merits of list governance.

Uncertainty in boundedly rational household adaptation to environmental shocks.

Despite the growing calls to integrate realistic human behavior in sustainability science models, the representative rational agent prevails. This is especially problematic for climate change adaptation that relies on actions at various scales: from governments to individuals. Empirical evidence on individual adaptation to climate-induced hazards reveals diverse behavioral and social factors affecting economic considerations. Yet, implications of replacing the rational optimizer by realistic human behavior in nature-society systems models are poorly understood. Using an innovative evolutionary economic agent-based model we explore different framings regarding household adaptation behavior to floods, leveraging on behavioral data from a household survey in Miami, USA. We find that a representative rational agent significantly overestimates household adaptation diffusion and underestimates damages compared to boundedly rational behavior revealed from our survey. This "adaptation deficit" exhibited by a population of empirically informed agents is explained primarily by diverse "soft" adaptation constraints-awareness, social influences-rather than heterogeneity in financial constraints. Besides initial inequality disproportionally impacting low/medium adaptive capacity households post-flood, our findings suggest that even under a nearly complete adaptation diffusion, adaptation benefits are uneven, with late or less-efficient actions locking households to a path of higher damages, further exacerbating inequalities. Our exploratory modeling reveals that behavioral assumptions shape the uncertainty of physical factors, like exposure and objective effectiveness of flood-proofing measures, traditionally considered crucial in risk assessments. This unique combination of methods facilitates the assessment of cumulative and distributional effects of boundedly rational behavior essential for designing tailored climate adaptation policies, and for equitable sustainability transitions in general.

The scientific value of numerical measures of human feelings.

Human feelings measured in integers (my happiness is an 8 out of 10, my pain 2 out of 6) have no objective scientific basis. They are "made-up" numbers on a scale that does not exist. Yet such data are extensively collected-despite criticism from, especially, economists-by governments and international organizations. We examine this paradox. We draw upon longitudinal information on the feelings and decisions of tens of thousands of randomly sampled citizens followed through time over four decades in three countries (n = 700,000 approximately). First, we show that a single feelings integer has greater predictive power than does a combined set of economic and social variables. Second, there is a clear inverse relationship between feelings integers and subsequent get-me-out-of-here actions (in the domain of neighborhoods, partners, jobs, and hospital visits). Third, this feelings-to-actions relationship takes a generic form, is consistently replicable, and is fairly close to linear in structure. Therefore, it seems that human beings can successfully operationalize an integer scale for feelings even though there is no true scale. How individuals are able to achieve this is not currently known. The implied scientific puzzle-an inherently cross-disciplinary one-demands attention.

Planning instruments enhance the acceptance of urban densification.

Dense and compact cities yield several benefits for both the population and the environment, including the containment of urban sprawl, reduced carbon emissions, and increased housing supply. Densification of the built environment is thus a key contemporary urban planning paradigm worldwide. However, local residents often oppose urban densification, motivating a need to understand their underlying concerns. In order to do so, we examined different factors driving public acceptance of housing densification projects through a combination of a conjoint survey experiment and different proximity frames among 12,402 participants across Berlin, Chicago, London, Los Angeles, New York, and Paris. Respondents compared housing densification projects with varying attributes, including their geographic proximity, project-related factors, and accompanying planning instruments. The results indicate that the acceptance of such projects decreases with project proximity and that project-related factors, such as the type of investor, usage, and climate goals, impact densification project acceptance. More specifically, we see a negative effect on acceptance levels for projects with for-profit investors and a positive effect when the suggested developments are mixed use or climate neutral. In addition, planning instruments, such as rent control, inclusionary zoning, and participatory planning, appear to positively influence acceptance. Interestingly, a cross-continental comparison shows overall higher acceptance levels of densification by US respondents. These multifaceted results allow us to better understand what drives people's acceptance of housing projects and how projects and planning processes can be designed to increase democratic acceptance of urban densification.

Association of oral microbiome with oral human papillomavirus infection: a population study of the National Health and Nutrition Examination Survey, 2009-2012.

BACKGROUND: Oral human papillomavirus(HPV) infection and the oral microbiome are associated with oropharyngeal cancer. However, population-based data on the association of oral microbiome with oral HPV infection are limited. METHOD: We performed a cross-sectional analysis of 5,496 participants aged 20-59 in National Health and Nutrition Examination Surveys(NHANES):2009-2012. The association between either oral microbiome alpha diversity or beta diversity and oral HPV infection was assessed using multivariable logistic regression or principal coordinate analyses(PCoA) and multivariate analysis of variance(PERMANOVA). RESULTS: For alpha diversity, we found a lower number of observed Amplicon sequence variants(ASVs) (adjusted odds ratio[aOR] = 0.996; 95%CI = 0.992-0.999) and reduced Faith's Phylogenetic Diversity(aOR = 0.95; 95%CI = 0.90-0.99) associated with high-risk oral HPV infection in the overall population. This trend was observed in males for both high-risk and any oral HPV infection. Beta diversity showed differentiation of oral microbiome community by high-risk oral HPV infection as measured by Bray-Curtis dissimilarity (R2 = 0.054%; P = .029) and unweighted UniFrac distance (R2 = 0.046%; P = .045) among the overall population, and associations were driven by males. CONCLUSIONS: Both oral microbiome alpha diversity(within-sample richness and phylogenetic diversity) and beta diversity(heterogeneous dispersion of oral microbiome community) are associated with HPV infection. Longitudinal studies are needed to characterize the role of the microbiome in the natural history of oral HPV infection.

Antibody titers and the risk of infection during the SARS-CoV-2 Omicron phase in Bizen City, Japan.

BACKGROUND: Understanding the association between the immune response and the risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has implications for forthcoming prevention strategies. We evaluated the association between antibody titers and the risk of infection for the general population during the Omicron-dominant phase. METHODS: This was a prospective cohort study of residents or people affiliated with institutions in Bizen City, which included 1,899 participants. We measured the titers of antibodies against SARS-CoV-2 repeatedly every 2 months from June 2022 to March 2023. Infection status was obtained from self-reported questionnaires and the official registry. We estimated risk ratios (RRs) for infection within 2 months of the date of each antibody measurement with 95% confidence intervals (CIs) based on antibody titer categories and spline functions. RESULTS: Compared with the <2,500 arbitrary unit (AU)/mL category, the 2,500-5,000, 5,000-10,000, and ≥10,000 AU/mL categories had adjusted RRs (95% CI) of 0.81 (0.61-1.08), 0.51 (0.36-0.72), and 0.41 (0.31-0.54), respectively. The spline function showed a non-linear relationship between antibody titer and risk. CONCLUSIONS: Higher antibody titers were associated with a lower risk. We demonstrate the usefulness of measuring an antibody titers to determine the appropriate timing for future vaccination.

Description of Cryptococcosis Following SARS-CoV-2 Infection: A Disease Survey Through the Mycosis Study Group Education and Research Consortium (MSG-19).

BACKGROUND: Invasive fungal infections have been described throughout the COVID-19 pandemic. Cryptococcal disease after infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been reported in several isolated case reports and 1 larger case series. We sought to describe cryptococcal infections following SARS-CoV-2 through establishing a database to investigate underlying risk factors, disease manifestations, and outcomes. METHODS: We created a crowdsourced call for cases solicited through the Mycoses Study Group Education and Research Consortium, the Centers for Disease Control and Prevention Emerging Infectious Diseases Network, and infectious diseases Twitter groups. Data were collected in a web-based and secure REDCap survey without personal identifiers. RESULTS: Sixty-nine cases were identified and submitted by 29 separate institutional sites. Cryptococcosis was diagnosed a median of 22 days (interquartile range, 9-42 days) after SARS-CoV-2 infection. Mortality among those with available follow-up was 72% (26/36) for the immunocompetent group and 48% (15/31) for the immunocompromised group (likelihood ratio, 4.01; P = .045). We observed a correlation between disease manifestation (central nervous system infection, proven/probable disseminated disease, and respiratory) and mortality (P = .002). CONCLUSIONS: The mortality rate of 59% for patients with cryptococcosis following SARS-CoV-2 is higher than that of modern Cryptococcus cohorts. There was an association between immunocompromised status and cryptococcal disease manifestations as well as mortality. Moreover, our series emphasizes the need for clinical and laboratory assessment of opportunistic infections beyond 30 days when concerning symptoms develop.

Serologic Immunity to Tetanus in the United States, National Health and Nutrition Examination Survey, 2015-2016.

BACKGROUND: Tetanus, a life-threatening infection, has become rare in the United States since introduction of tetanus toxoid-containing vaccines (TTCVs), recommended as a childhood series followed by decennial boosters beginning at age 11-12 years; vaccination uptake is high in children but suboptimal in adults. The objective of this study was to estimate the prevalence of sero-immunity to tetanus among persons aged ≥6 years in the United States and to identify factors associated with tetanus sero-immunity. Understanding population protection against tetanus informs current and future vaccine recommendations. METHODS: Anti-tetanus toxoid antibody concentrations were measured for participants of the 2015-2016 National Health and Nutrition Examination Survey (NHANES) aged ≥6 years for whom surplus serum samples were available using a microsphere-based multiplex antibody capture assay. Prevalence of sero-immunity, defined as ≥0.10 IU/mL, was estimated overall and by demographic characteristics. Factors associated with tetanus sero-immunity were examined using multivariable regression. RESULTS: Overall, 93.8% of the US population aged ≥6 years had sero-protection against tetanus. Prevalence of sero-immunity was above 90% across racial/ethnic categories, sex, and poverty levels. By age, ≥ 90% had protective sero-immunity through age 69 years, but prevalence of sero-immunity declined thereafter, with 75.8% of those aged ≥80 years having protective sero-immunity. Older age (adjusted prevalence ratio [aPR]: 0.89, 95% confidence interval [CI]: .85-.92) and being born outside the United States (aPR: 0.96, 95% CI: .93-.98) were significantly associated with lower prevalence of sero-immunity. CONCLUSIONS: The majority of the US population has vaccine-induced sero-immunity to tetanus, demonstrating the success of the vaccination program.

Insights into the genome of the 'Loco' Concholepas concholepas (Gastropoda: Muricidae) from low-coverage short-read sequencing: genome size, ploidy, transposable elements, nuclear RNA gene operon, mitochondrial genome, and phylogenetic placement in the family Muricidae.

BACKGROUND: The Peruvian 'chanque' or Chilean 'loco' Concholepas concholepas is an economically, ecologically, and culturally important muricid gastropod heavily exploited by artisanal fisheries in the temperate southeastern Pacific Ocean. In this study, we have profited from a set of bioinformatics tools to recover important biological information of C. concholepas from low-coverage short-read NGS datasets. Specifically, we calculated the size of the nuclear genome, ploidy, and estimated transposable elements content using an in silico k-mer approach, we discovered, annotated, and quantified those transposable elements, we assembled and annotated the 45S rDNA RNA operon and mitochondrial genome, and we confirmed the phylogenetic position of C. concholepas within the muricid subfamily Rapaninae based on translated protein coding genes. RESULTS: Using a k-mer approach, the haploid genome size estimated for the predicted diploid genome of C. concholepas varied between 1.83 Gbp (with kmer = 24) and 2.32 Gbp (with kmer = 36). Between half and two thirds of the nuclear genome of C. concholepas was composed of transposable elements. The most common transposable elements were classified as Long Interspersed Nuclear Elements and Short Interspersed Nuclear Elements, which were more abundant than DNA transposons, simple repeats, and Long Terminal Repeats. Less abundant repeat elements included Helitron mobile elements, 45S rRNA DNA, and Satellite DNA, among a few others.The 45S rRNA DNA operon of C. concholepas that encodes for the ssrRNA, 5.8S rRNA, and lsrRNA genes was assembled into a single contig 8,090 bp long. The assembled mitochondrial genome of C. concholepas is 15,449 bp long and encodes 13 protein coding genes, two ribosomal genes, and 22 transfer RNAs. CONCLUSION: The information gained by this study will inform the assembly of a high quality nuclear genome for C. concholepas and will support bioprospecting and biomonitoring using environmental DNA to advance development of conservation and management plans in this overexploited marine snail.

Risk-management decision-making data from a community-based sample of racially diverse women at high risk of breast cancer: rationale, methods, and sample characteristics of the Daughter Sister Mother Project survey.

BACKGROUND: To understand the dynamics that limit use of risk-management options by women at high risk of breast cancer, there is a critical need for research that focuses on patient perspectives. Prior research has left important gaps: exclusion of high-risk women not in risk-related clinical care, exclusion of non-white populations, and lack of attention to the decision-making processes that underlie risk-management choices. Our objective was to create a more inclusive dataset to facilitate research to address disparities related to decision making for breast cancer risk management. METHODS: The Daughter Sister Mother Project survey collects comprehensive information about the experiences of women at high risk of breast cancer. We collected novel measures of feelings about and reactions to cancer screenings; knowledge, barriers, and facilitators of risk-management options; beliefs related to cancer risk and risk management; and involvement with loved ones who had cancer. Eligible individuals were non-Hispanic white and non-Hispanic Black adult women who self-identified as having high risk of breast cancer and had no personal history of cancer. Between October 2018 and August 2019, 1053 respondents completed the online survey. Of these, 717 were confirmed through risk prediction modeling to have a lifetime breast cancer risk of ≥ 20%. Sociodemographic characteristics of this sample were compared to those of nationally representative samples of the US population: the 2019 Health Information National Trends Survey and the Pew Research Center report: Jewish Americans in 2020. RESULTS: The sample of 717 women at objectively high risk of breast cancer was largely (95%) recruited from non-clinical sources. Of these respondents, only 31% had seen a genetic counselor, 34% had had genetic testing specific to breast cancer risk, and 35% had seen at least one breast or cancer care specialist. The sample includes 35% Black respondents and 8% with Ashkenazi Jewish ancestry. Although encompassing a substantial range of ages, incomes, and education levels, respondents are overall somewhat younger, higher-income, and more educated than the US population as a whole. CONCLUSIONS: The DSM dataset offers comprehensive data from a community-based, diverse sample of women at high risk of breast cancer. The dataset includes substantial proportions of Black and Ashkenazi Jewish women and women who are not already in clinical care related to their breast cancer risk. This sample will facilitate future studies of risk-management behaviors among women who are and are not receiving high-risk care, and of variations in risk-management experiences across race and ethnicity.

Animal Exposure Model for Mapping Crimean-Congo Hemorrhagic Fever Virus Emergence Risk.

To estimate the determinants of spatial variation in Crimean-Congo hemorrhagic fever virus (CCHFV) transmission and to create a risk map as a preventive public health tool, we designed a survey of small domestic ruminants in Andalusia, Spain. To assess CCHFV exposure spatial distribution, we analyzed serum from 2,440 sheep and goats by using a double-antigen ELISA and modeled exposure probability with environmental predictors by using generalized linear mixed models. CCHFV antibodies detected in 84 samples confirmed low CCHFV prevalence in small domestic ruminants in the region. The best-fitted statistical model indicated that the most significant predictors of virus exposure risk were cattle/horse density and the normalized difference vegetation index. Model validation showed 99.7% specificity and 10.2% sensitivity for identifying CCHFV circulation areas. To map CCHFV exposure risk, we projected the model at a 1 × 1-km spatial resolution. Our study provides insight into CCHFV ecology that is useful for preventing virus transmission.

Tick-Borne Encephalitis, Lombardy, Italy.

Tick-borne encephalitis was limited to northeast portions of Italy. We report in Lombardy, a populous region in the northwest, a chamois displaying clinical signs of tickborne encephalitis virus that had multiple virus-positive ticks attached, as well as a symptomatic man. Further, we show serologic evidence of viral circulation in the area.

Third Report of the Japan Diabetes Society/Japanese Cancer Association Joint Committee on Diabetes and Cancer: Summary of the results of a questionnaire survey of oncologists and diabetologists-Secondary publication.

The Japan Diabetes Society and the Japan Cancer Association launched a joint committee and published their "First Joint Committee Report on Diabetes and Cancer" in 2013, compiling recommendations for physicians and health-care providers as well as for the general population. In 2016, the "Second Joint Committee Report on Diabetes and Cancer" summarized the current evidence on glycemic control and cancer risk in patients with diabetes. The current "Third Joint Committee Report on Diabetes and Cancer", for which the joint committee also enlisted the assistance of the Japanese Society of Clinical Oncology and the Japanese Society of Medical Oncology, reports on the results from the questionnaire survey, "Diabetes Management in Patients Receiving Cancer Therapy," which targeted oncologists responsible for cancer management and diabetologists in charge of glycemic control in cancer patients. The results of the current survey indicated that there is a general consensus among oncologists and diabetologists with regard to the need for guidelines on glycemic control goals, the relevance of glycemic control, and glycemic control during cancer therapy in cancer patients.

Patient survey on cancer genomic medicine in Japan under the national health insurance system.

In Japan, comprehensive genomic profiling (CGP) tests have been reimbursed under the national health care system for solid cancer patients who have finished standard treatment. More than 50,000 patients have taken the test since June 2019. We performed a nation-wide questionnaire survey between March 2021 and July 2022. Questionnaires were sent to 80 designated Cancer Genomic Medicine Hospitals. Of the 933 responses received, 370 (39.7%) were web based and 563 (60.3%) were paper based. Most patients (784, 84%) first learned about CGP tests from healthcare professionals, and 775 (83.1%) gave informed consent to their treating physician. At the time of informed consent, they were most worried about test results not leading to novel treatment (536, 57.4%). On a scale of 0-10, 702 respondents (75.2%) felt that the explanations of the test result were easy to understand (7 or higher). Ninety-one patients (9.8%) started their recommended treatment. Many patients could not receive recommended treatment because no approved drugs or clinical trials were available (102/177, 57.6%). Ninety-eight patients (10.5%) did not wish their findings to be disclosed. Overall satisfaction with the CGP test process was high, with 602 respondents (64.5%) giving a score of 7-10. The major reason for choosing 0-6 was that the CGP test result did not lead to new treatment (217/277, 78.3%). In conclusion, satisfaction with the CGP test process was high. Patients and family members need better access to information. More patients need to be treated with genomically matched therapy.

The 2018-2019 FoodNet Population Survey: A tool to estimate risks and behaviors associated with enteric infections.

The FoodNet Population Survey is a periodic survey of randomly selected residents in 10 US sites on exposures and behaviors that may be associated with acute diarrheal infections and the health care sought for those infections. This survey is used to estimate the true disease burden of enteric illness in the United States and to estimate rates of exposure to potential sources of illness. Unlike previous FoodNet Population Surveys, this cycle used multiple sampling frames and administration modes, including cell phone and web-based questionnaires, that allowed for additional question topics and a larger sample size. It also oversampled children to increase representation of this population. Analytic modeling adjusted for mode effects when estimating the prevalence estimates of exposures and behaviors. This report describes the design, methodology, challenges, and descriptive results from the 2018-19 FoodNet Population Survey.