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SARS-CoV-2 has caused over 6.9 million deaths and continues to produce lasting health consequences. COVID-19 manifests broadly from no symptoms to death. In a retrospective cross-sectional study, we developed personalized risk assessment models that predict clinical outcomes for individuals with COVID-19 and inform targeted interventions. We sequenced viruses from SARS-CoV-2-positive nasopharyngeal swab samples between July 2020 and July 2022 from 4450 individuals in Missouri and retrieved associated disease courses, clinical history, and urban-rural classification. We integrated this data to develop machine learning-based predictive models to predict hospitalization, ICU admission, and long COVID.The mean age was 38.3 years (standard deviation = 21.4) with 55.2% (N = 2453) females and 44.8% (N = 1994) males (not reported, N = 4). Our analyses revealed a comprehensive set of predictors for each outcome, encompassing human, environment, and virus genome-wide genetic markers. Immunosuppression, cardiovascular disease, older age, cardiac, gastrointestinal, and constitutional symptoms, rural residence, and specific amino acid substitutions were associated with hospitalization. ICU admission was associated with acute respiratory distress syndrome, ventilation, bacterial co-infection, rural residence, and non-wild type SARS-CoV-2 variants. Finally, long COVID was associated with hospital admission, ventilation, and female sex.Overall, we developed risk assessment models that offer the capability to identify patients with COVID-19 necessitating enhanced monitoring or early interventions. Of importance, we demonstrate the value of including key elements of virus, host, and environmental factors to predict patient outcomes, serving as a valuable platform in the field of personalized medicine with the potential for adaptation to other infectious diseases.Model summary and motivation. Individuals infected with SARS-CoV-2 experience a wide spectrum of clinical manifestations ranging from no symptoms to death. Using the Virus-Human Outcomes Prediction (ViHOP) algorithm, we aim to utilize the individual’s clinical characteristics, the individual’s location, and the infecting SARS-CoV-2 virus characteristics obtained by whole genome sequencing to determine their likelihood of admission to the hospital, admission to the intensive care unit (ICU), or experiencing long COVID. This model allows clinicians to identify at-risk patients for further monitoring and/or early treatment.

This study compares pandemic experiences of Missouri’s 115 counties based on rurality and sociodemographic characteristics during the 1918–20 influenza and 2020–21 COVID-19 pandemics. The state’s counties and overall population distribution have remained relatively stable over the last century, which enables identification of long-lasting pandemic attributes. Sociodemographic data available at the county level for both time periods were taken from U.S. census data and used to create clusters of similar counties. Counties were also grouped by rural status (RSU), including fully (100%) rural, semirural (1–49% living in urban areas), and urban (>50% of the population living in urban areas). Deaths from 1918 through 1920 were collated from the Missouri Digital Heritage database and COVID-19 cases and deaths were downloaded from the Missouri COVID-19 dashboard. Results from sociodemographic analyses indicate that, during both time periods, average farm value, proportion White, and literacy were the most important determinants of sociodemographic clusters. Furthermore, the Urban/Central and Southeastern regions experienced higher mortality during both pandemics than did the North and South. Analyses comparing county groups by rurality indicated that throughout the 1918–20 influenza pandemic, urban counties had the highest and rural had the lowest mortality rates. Early in the 2020–21 COVID-19 pandemic, urban counties saw the most extensive epidemic spread and highest mortality, but as the epidemic progressed, cumulative mortality became highest in semirural counties. Additional results highlight the greater effects both pandemics had on county groups with lower rates of education and a lower proportion of Whites in the population. This was especially true for the far southeastern counties of Missouri (“the Bootheel”) during the COVID-19 pandemic. These results indicate that rural-urban and socioeconomic differences in health outcomes are long-standing problems that continue to be of significant importance, even though the overall quality of health care is substantially better in the 21st century.

Objectives We compared HPV vaccine initiation and completion of heterosexual with lesbian and bisexual (LB) women. Methods We aggregated National Health and Nutrition Examination Survey data from 2009 to 2016 for 3,017 women aged 18 to 34 y in the United States. HPV vaccine initiation was defined as reported receipt of ≥1 dose of the vaccine and completion as receipt of the three recommended doses. Weighted percentages and multivariable logistic regression models were used to examine differences in HPV vaccine initiation and completion between heterosexual and LB women. Results Approximately 12% of respondents self-identified as LB women. Overall, a higher percentage of respondents (26%) had initiated the HPV vaccine than completed the three vaccine doses (17%). In the bivariate analysis, LB women had higher initiation ([35% of LB women versus 25% heterosexual]; p = .0012) and completion rates ([24% of LB women versus 17% heterosexual]; p = .0052) than heterosexual women. After adjusting for covariates, compared to heterosexual women, LB women were 60% (aOR = 1.60, 95% CI: 1.16–2.19) more likely to initiate and 63% (aOR = 1.63, 95% CI: 1.12–2.37) more likely to complete the HPV vaccine. Conclusions Although LB women had higher likelihood of HPV vaccine initiation and completion compared with heterosexual women, their HPV vaccine uptake was well below the Healthy People 2020 target (80%). Understanding differences in the drivers of vaccine uptake in the LB population may inform strategies that would further increase HPV vaccine uptake toward achieving the 80% completion target.

After the COVID-19 pandemic reached Missouri, the Show-Me ECHO (Extension for Community Healthcare Outcomes) project initiated COVID-19 ECHO virtual knowledge-sharing networking sessions. These live-interactive weekly sessions inform participants about up-to-date evidence-based recommendations and guidelines through expert didactic lectures followed by real-life case discussions. We conducted a qualitative analysis of pre-session surveys and questions asked during sessions to learn about information needs of community members during first months of public health emergency. This was a pilot project using qualitative analysis of registration questions regarding anticipated COVID-19 community information needs, and participants' questions asked during sessions collected from March 23 until May 4, 2020. We also analyzed participants' satisfaction surveys collected in December 2020. A total of 761 unique participants attended COVID-19 ECHO during the study period. Survey was completed by 692 respondents. Participants asked 315 questions resulting in 797 identified community information needs. Five thematic categories were recognized: patient care, information seeking, minimizing exposure, financial themes, and general comments. Most attendees rated content quality, logistics, and technical operations as good or excellent on a five-point Likert scale. The COVID-19 ECHO model was responsive to the needs of participants by sharing and discussing up-to-date recommendations and guidelines regarding COVID-19. Sessions were well-attended, and the didactic presenters were invited to deliver same or similar presentations at Boone County Medical Society (BCMS) weekly seminars, suggesting the value of the project to healthcare providers and other community members caring for or working with the most vulnerable populations.

Influenza B viruses (IBVs) are causing an increasing burden of morbidity and mortality, yet the prevalence of culture-adapted mutations in human seasonal IBVs are unclear. We collected 368 clinical samples from patients with influenza-like illness in Missouri during the 2019–2020 influenza season and recovered 146 influenza isolates including 38 IBV isolates. Of MDCK-CCL34, MDCK-Siat1, and humanized MDCK (hCK), hCK showed the highest virus recovery efficiency. All Missourian IBVs belonged to the Victoria V1A.3 lineage, all of which contained a three-amino acid deletion on the HA protein and were antigenically distant from the Victoria lineage IBV vaccine strain used during that season. By comparing genomic sequences of these IBVs in 31 paired samples, eight cell-adapted nonsynonymous mutations were identified, with the majority in the RNA polymerase. Analyses of IBV clinical sample–isolate pairs from public databases further showed that cell- and egg-adapted mutations occurred more widely in viral proteins, including the receptor and antibody binding sites on HA. Our study suggests that hCK is an effective platform for IBV isolation and that culture-adapted mutations may occur during IBV isolation. As culture-adapted mutations may affect subsequent virus studies and vaccine development, the knowledge from this study may help optimize strategies for influenza surveillance, vaccine strain selection, and vaccine development.

The purpose of this study was to evaluate the influence of a student-run clinic on the diversification of a medical student class. We distributed a two-page, 20-item, paper survey to students of the University of Missouri School of Medicine (MU SOM) class of 2015 in July of 2011. The survey gathered information on general demographics, opinions on the importance of medical education opportunities, and opinions on the importance of medical school characteristics in applying to and attending MU SOM. A total of 104 students responded to the survey. A majority of the students identified the MedZou Community Health Clinic, a student-run, free health clinic affiliated with MU SOM, and simulated-patient encounters as important educational experiences (81% and 94%, respectively). More than half of the self-identified “non-white” students reported MedZou as an important factor in their choice to apply to (60%; 95% confidence interval [CI], 32 to 88) and attend (71%; 95% CI, 44 to 98) MU SOM, over half of the females reported MedZou as important in their choice to apply (59%; 95% CI, 43 to 76) and attend (57%; 95% CI, 40 to 74), and over half of non-Missouri residents reported MedZou as important in their choice to apply (64%; 95% CI, 36 to 93) and attend (71%; 95% CI, 44 to 98). According to the above results, it can be said that students clearly value both MedZou and simulated-patient encounters as important educational experiences. Women, minorities, and non-Missouri residents value MedZou more highly than their peers who are First Year Medical Students who are Missouri residents, suggesting that MedZou may provide a promising opportunity to advance diversity within MU SOM. These results highlight the need for additional research to further explore MedZou’s potential to enhance the recruitment of a diverse medical student class.

IntroductionIdentifying communities with lower rates of mammography screening is a critical step to providing targeted screening programs; however, population-based data necessary for identifying these geographic areas are limited. This study presents methods to identify geographic disparities in the early detection of breast cancer.MethodsData for all women residing in Dane County, Wisconsin, at the time of their breast cancer diagnosis from 1981 through 2000 (N = 4769) were obtained from the Wisconsin Cancer Reporting System (Wisconsin’s tumor registry) by ZIP code of residence. Hierarchical logistic regression models for disease mapping were used to identify geographic differences in the early detection of breast cancer.ResultsThe percentage of breast cancer cases diagnosed in situ (excluding lobular carcinoma in situ) increased from 1.3% in 1981 to 11.9% in 2000. This increase, reflecting increasing mammography use, occurred sooner in Dane County than in Wisconsin as a whole. From 1981 through 1985, the proportion of breast cancer diagnosed in situ in Dane county was universally low (2%–3%). From 1986 through 1990, urban and suburban ZIP codes had significantly higher rates (10%) compared with rural ZIP codes (5%). From 1991 through 1995, mammography screening had increased in rural ZIP codes (7% of breast cancer diagnosed in situ). From 1996 through 2000, mammography use was fairly homogeneous across the entire county (13%–14% of breast cancer diagnosed in situ).ConclusionThe percentage of breast cancer cases diagnosed in situ increased in the state and in all areas of Dane County from 1981 through 2000. Visual display of the geographic differences in the early detection of breast cancer demonstrates the diffusion of mammography use across the county over the 20-year period.

BACKGROUND Geographic information systems (GIS) and spatial statistics are useful for exploring the relation between geographic location and health. The ultimate usefulness of GIS depends on both completeness and accuracy of geocoding (the process of assigning study participants' residences latitude/longitude coordinates that closely approximate their true locations, also known as address matching). The goal of this project was to develop an iterative geocoding process that would achieve a high match rate in a large population-based health study.METHODS Data were from a study conducted in Wisconsin using mailing addresses of participants who were interviewed by telephone from 1988 to 1995. We standardized the addresses according to US Postal Service guidelines, used desktop GIS geocoding software and two versions of the Topologically Integrated Geographic Encoding and Referencing street maps, accessed Internet mapping engines for problematic addresses, and recontacted a small number of study participants' households. We also tabulated the project's cost, time commitment, software requirements, and brief notes for each step and their alternatives.RESULTS Of the 14,804 participants, 97% were ultimately assigned latitude/longitude coordinates corresponding to their respective residences. The remaining 3% were geocoded to their zip code centroid.CONCLUSION The multiple methods described in this work provide practical information for investigators who are considering the use of GIS in their population health research. [ABSTRACT FROM AUTHOR]

Estrogen-mimicking chemicals, such as cadmium, may be associated with increased susceptibility to hormone-dependent cancers, though supporting data are sparse, particularly for endometrial cancer. The Health and Environmental Exposure Research (HEER) study worked with the Arkansas Central Cancer Registry, Iowa Cancer Registry and Missouri Cancer Registry to obtain names of women diagnosed with endometrial cancer who were willing to be contacted for participation in our case control study. Voter registration lists from Iowa and Missouri were used to randomly select similarly aged women as represented in the case population. Participants were interviewed by telephone to obtain information on known or suspected endometrial risk factors. Urine kits were sent to participants for home collection and returned for analysis. Our case-control study consisted of 631 incident cases of endometrial cancer diagnosed from January 2010 to October 2012 and 879 age-matched population-based controls, ages 18-81 years (mean age 65 years). We quantified cadmium amounts in urine and standardized these values through creatinine adjustment. Using data from all survey completers, we developed a multivariable model for endometrial cancer. Creatinine-adjusted cadmium concentration was added to this model. Odds ratio (OR) and 95% confidence intervals (CIs) for endometrial cancer were calculated. After multivariable adjustment, higher creatinine-adjusted cadmium exposure was associated with a statistically significant increase of endometrial cancer risk (OR: 1.22; 95% CI: 1.03-1.44). Our results provide evidence that cadmium may increase the risk of endometrial cancer, possibly through estrogenic effects.

Cadmium is a human lung carcinogen and possesses estrogen-like activity. This combination of carcinogenic and estrogenic activity makes cadmium a contaminant of high concern for hormone-related cancers. Diet and smoking are the main sources of cadmium exposure. The aim of this study was to investigate the association between dietary cadmium intake and risk of breast, endometrial and ovarian cancer in Danish postmenopausal woman.We estimated dietary cadmium intake in the Diet, Cancer and Health cohort at enrolment 1993-97. The estimates were based on food frequency questionnaires and cadmium contents in all foods. Among 23,815 postmenopausal women we identified 1390 breast, 192 endometrial, and 146 ovarian cancer cases from enrolment through December 31, 2010 using the Danish Cancer Registry. Cox regression was used to analyse the association between dietary cadmium intake and cancer risk.Mean dietary cadmium intake was 14 µg/day. Cadmium was not associated with breast cancer, incidence rate ratio (IRR) = 0.99, 95% confidence interval (CI): 0.87-1.13 per 10 µg higher dietary cadmium intake/day; endometrial cancer, IRR = 1.08, 95% CI: 0.76-1.53; or ovarian cancer, IRR = 1.15, 95% CI: 0.78-1.70. We found a positive association between cadmium and endometrial cancer for the women with BMI