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in category epidemiology

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5561: Social relationships and patient-reported outcomes in adolescent and young adult cancer survivors
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Posted 04 Nov 2020

Social relationships and patient-reported outcomes in adolescent and young adult cancer survivors
103 downloads medRxiv epidemiology

Pragya G. Poudel, Hailey E. Bauer, Zhaoming Wang, I-Chan Huang

ImportanceNearly 89,000 adolescents and young adults (AYAs) aged 15 to 39 years old are diagnosed with cancer in U.S. annually. Cancer diagnosis in AYAs often alters achievement of age-specific milestones, interferes with interpersonal relations, and disrupts social life. However, social relations in AYA survivors and associations with patient-reported outcomes (PROs) have been understudied. ObjectiveTo investigate the impact of cancer on PROs in AYA survivors and identify social integration mechanisms through which cancer experiences influence PROs. DesignA cross-sectional study. SettingA national Internet survey panel maintained by Opinions 4 Good (Portsmouth, New Hampshire). Participants102 AYA survivors and 102 age/sex/race-matched noncancer controls. ExposureSurvivors were exposed to chemotherapy and/or radiotherapy during AYA. Main outcomes and measuresParticipants identified 25 closest friends/relatives they have contacted in past two years. Their interpersonal connections with each of 25 friends/relatives were used to create a social network index. The Duke-UNC Functional Social Support Questionnaire, UCLA Loneliness Scale, and PROMIS-29 Profile was used to measure social support, loneliness, and PROs (physical functioning, pain interference, fatigue, anxiety, and depression), respectively. ResultsAYA survivors of lymphoma, leukemia, and solid tumor had significantly better social networks than controls (all p-values <0.05). However, solid tumor and central nervous system malignancy survivors experienced higher loneliness than controls. Compared to controls, survivors had significantly poorer PROs in all domains. Cancer experience directly influenced all PRO domains (all p-values <0.05 except fatigue) and indirectly through social network-social support-loneliness pathways (all p-values <0.05). Survivors with high loneliness had lower physical functioning, higher pain interference, fatigue, anxiety, and depression compared with noncancer controls (all p-values <0.05). Conclusions and relevanceAYA survivors were more socially connected, but experienced greater loneliness than controls. The perceived loneliness greatly influenced PROs. Future research should focus on the functional aspects of social relations rather than considering the structural aspects of social integration, which would provide an opportunity for appropriate interventions to improve health outcomes through social integration. KEY POINTSO_ST_ABSQuestionC_ST_ABSHow do social relationships associate with self-reported health outcomes between adolescent and young adult (AYA) cancer survivors and noncancer controls? FindingsThis cross-sectional study revealed that AYA survivors were more socially connected, but perceived greater loneliness compared to noncancer controls. AYA survivors with high loneliness had lower physical functioning, higher pain interference, fatigue, anxiety, and depression compared to noncancer controls. MeaningThe findings of this study suggest that appropriate interventions, focused on improving functional social networks to further meet the needs of AYA cancer survivors, may function as a mean to prevent perceived loneliness and help achieve optimal health outcomes.

5562: A Cross-Sectional Study Evaluating Tick-borne Encephalitis Vaccine Uptake and Timeliness Among Adults in Switzerland
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Posted 08 Feb 2021

A Cross-Sectional Study Evaluating Tick-borne Encephalitis Vaccine Uptake and Timeliness Among Adults in Switzerland
103 downloads medRxiv epidemiology

Kyra D Zens, Vasiliki Baroutsou, Philipp Sinniger, Phung Lang

Objectives The goal of this study was to evaluate timeliness of Tick-borne Encephalitis vaccination uptake among adults in Switzerland. Methods In this cross-sectional survey, we collected vaccination records from randomly selected adults 18-79 throughout Switzerland. Of 4,626 participants, data from individuals receiving at least 1 TBE vaccination (n=1875) were evaluated. We determined year and age of first vaccination and vaccine compliance, evaluating dose timeliness. Participants were considered on time if they received doses according to the recommended schedule plus or minus a 15% tolerance period. Results 45% of participants received their first TBE vaccination between 2006 and 2009. 25% were first vaccinated aged 50 or older (mean age 37). More than 95% of individuals receiving the first dose also received the second; approximately 85% of those receiving the second dose received the third. For individuals completing the primary series, 30% received 3 doses of Encepur, 58% received 3 doses of FSME-Immun, and 12% received a combination. According to conventional schedules, 88% and 79% of individuals received their second and third doses on time, respectively. 20% of individuals receiving Encepur received their third dose too early. Of individuals completing primary vaccination, 19% were overdue for a booster. Among the 31% of subjects receiving a booster, mean time to first booster was 7.1 years. Conclusions We estimate that a quarter of adults in Switzerland were first vaccinated for TBE aged 50 or over. Approximately 80% of participants receiving at least one vaccine dose completed the primary series. We further estimate that 66% of individuals completing the primary series adhered to an ideal TBE vaccination schedule.

5563: Clumpiness: Modeling the Impact of Social Dynamics on COVID-19 Spread
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Posted 16 Apr 2021

Clumpiness: Modeling the Impact of Social Dynamics on COVID-19 Spread
103 downloads medRxiv epidemiology

Ben Goertzel, Cassio Pennachin, Deborah Duong, Matthew Iklé, Michael Duncan, James Boyd, André Senna, Ramon Durães

We present an agent based simulation supplemented with two novel social network interconnectivity measures, `clumpiness' and `hoprank,' that are the same concept defined at global and local levels, respectively. The measures may be computed from samples of readily available demographic data, and are useful for measuring probabilistic packet transmission through social networks. For simplicity, agents in our simulation group together through homophily, the principle of `like attracts like'. In three studies we apply clumpiness to measure the effects, on disease transmission, caused by social networks of both homophilic physical proximity and homophilic information replication. The particular characteristic we are interested in about disease transmission is herd immunity, the percentage of a population that has to be immune in order to prevent infection from spreading to those who are not. Two studies demonstrate innovations measuring herd immunity levels and predicting future outbreak locations, procedures relevant to epidemiological control policy. In the first study, we look at how homophilic physical proximity networks form natural bubbles that act as frictive surfaces that affect the speed of transmission of packets and influence herd immunity levels. In the second study, we test clumpiness in homophilic proximity social networks as a predictor of future infection outbreaks at the level of individual schools, restaurants, and workplaces. Our third study demonstrates that protective social bubbles form naturally from homophilic information replication networks, and enhance the natural bubbles that come from the homophilic physical proximity networks. Accurate description of this information environment lays the foundation for epidemiological messaging policy formation.

5564: Association of cannabis use-related predictor variables and self-reported psychotic disorders: US adults, 2001-2002 and 2012-2013
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Posted 28 Sep 2020

Association of cannabis use-related predictor variables and self-reported psychotic disorders: US adults, 2001-2002 and 2012-2013
103 downloads medRxiv epidemiology

Ofir Livne, Dvora Shmulewitz, Aaron Sarvet, Deborah Hasin

Objective: To determine the association of cannabis use-related variables and self-reported psychotic disorders during two time periods (2001-2002; 2012-2013). Methods: Logistic regression was used to analyze data from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC, 2001-2002; N=43,093) and NESARC-III (2012-2013; N=36,309). Among those with and without cannabis predictors (any and frequent [[&ge;]3 times a week] non-medical use, DSM-IV cannabis use disorders [CUD], cannabis dependence [CD]), standardized prevalence of past-year self-reported psychotic disorders were estimated. Association was indicated by within-survey differences in psychotic disorders by cannabis-related predictor status. Whether associations changed over time was indicated by difference-in-difference tests (contrasts between the surveys). Results: In both surveys, self-reported psychotic disorders were significantly more prevalent in those with than those without any non-medical cannabis use (2001-2002: 1.65% vs 0.27%; 2012-2013: 1.89% vs. 0.68%), with similar associations in both periods. Self-reported psychotic disorders were unrelated to frequent non-medical use in 2001-2002 but were significantly more prevalent in those with than without frequent non-medical use in 2012-2013 (2.68% vs. 0.71%), with no significant difference over time. In both surveys, self-reported psychotic disorders were significantly more prevalent in those with than without CUD (2001-2002: 2.43% vs. 0.30%; 2012-2013: 3.26% vs. 0.72%), with no significant differences in the associations over time. Self-reported psychotic disorders were unrelated to CD in 2001-2002 but were significantly more prevalent in those with than without CD in 2012-2013 (8.54% vs. 0.73%), showing a significantly stronger relationship in 2012-2013; similarly, among past-year non-medical cannabis users, the association was significantly stronger in 2012-2013. Conclusions: Cannabis-related variables, especially cannabis dependence, remain related to self-reported psychotic disorders. Therefore, clinicians should closely monitor cannabis-dependent users and assess the need for preventive and therapeutic interventions for these individuals.

5565: Lack of evidence for interactions between APOE and Klotho genotypes on cognitive, dementia and brain imaging metrics in UK Biobank
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Posted 15 Jan 2021

Lack of evidence for interactions between APOE and Klotho genotypes on cognitive, dementia and brain imaging metrics in UK Biobank
103 downloads medRxiv epidemiology

Rachana Tank, Joey Ward, Daniel J Smith, Kristin Flegal, Donald M. Lyall

Importance: Recent research has suggested that genetic variation in the Klotho (KL) locus may modify the association between apolipoprotein e (APOE) e4 genotype and cognitive impairment. Objective: Large-scale testing for associations and interactions between KL and APOE genotypes vs. risk of dementia (n=1,570 cases), cognitive abilities (n=174,513) and brain structure (n = 13,158) in older (60+ years) participants. Design, setting and participants: Cross-sectional and prospective data (UK Biobank). Main outcomes and measures: KL status was indexed with heterozygosity of the rs9536314 polymorphism (vs. not), in unrelated people with vs. without APOE e4 genotype, using regression and interaction tests. We assessed non-demented cognitive scores (processing speed; reasoning; memory; executive function), multiple structural brain imaging, and clinical dementia outcomes. All tests were corrected for age, sex, assessment centre, eight principal components for population stratification, genotypic array, smoking history, deprivation, and self-reported medication history. Results: APOE e4 presence (vs. not) was associated with increased risk of dementia, worse cognitive abilities and brain structure differences. KL heterozygosity was associated with less frontal lobe grey matter. There were no significant APOE/KL interactions for cognitive, dementia or brain imaging measures (all P>0.05). Conclusions and relevance: We found no evidence of APOE/KL interactions on cognitive, dementia or brain imaging outcomes. This could be due to some degree of cognitive test imprecision, generally preserved participant health potentially due to relatively young age, type-1 error in prior studies, or indicative of a significant age-dependent KL effect only in the context of marked AD pathology.

5566: Long-term Exposures to Air Pollutants Affect FeNO in Children: A Longitudinal Study
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Posted 03 Mar 2021

Long-term Exposures to Air Pollutants Affect FeNO in Children: A Longitudinal Study
103 downloads medRxiv epidemiology

yue zhang, Sandrah Eckel, Kiros Berhane, Erika Garcia, Patrick Muchmore, Noa Ben-Ari Molshatzki, Edward Rappaport, William S.Linn, Rima Habre, Frank Gilliland

Fractional exhaled nitric oxide (FeNO) is a marker of airway inflammation shown to be responsive to short-term air pollution exposures; however, effects of long-term exposures are uncertain. Using longitudinal assessments of FeNO and air pollutant exposures, we aimed to determine whether FeNO is a marker for chronic effects of air pollution exposures after accounting for short-term exposures effects. FeNO was assessed up to six times 2004-2012 in 3607 schoolchildren from 12 communities in the Southern California Children's Health Study. Within-community long-term ambient air pollution exposures (PM2.5, PM10, NO2, O3) were represented by differences between community-specific annual averages and the eight-year average spanning the study period. Linear mixed-effect models estimated within-participant associations of annual average air pollution with current FeNO, controlling for previous FeNO, prior seven-day average pollution, potential confounders, and community-level random intercepts. We considered effect modification by sex, ethnicity, asthma, and allergy at baseline. We found FeNO was positively associated with annual average air pollution, after accounting for short-term exposures. One standard deviation higher annual PM2.5 and NO2 exposures (PM2.5:2.0 g/m3; NO2:2.7 ppb) were associated, respectively, with 4.6% (95%CI:2.3%-6.8%) and 6.5% (95%CI:4.1%-8.9%) higher FeNO. These associations were larger among females. We found little evidence supporting association with PM10 or O3. Annual average PM2.5 and NO2 levels were associated with FeNO in schoolchildren, adding new evidence that long-term exposure affects FeNO beyond the well-documented short-term effects. Longitudinal FeNO measurements may be useful as an early marker of chronic respiratory effects of long-term PM2.5 and NO2 exposures in children.

5567: Risk factors for fecal carriage of multidrug-resistant Escherichia coli in a college community: a penalized regression model
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Posted 18 Nov 2020

Risk factors for fecal carriage of multidrug-resistant Escherichia coli in a college community: a penalized regression model
103 downloads medRxiv epidemiology

Yuan Hu, Julia Rubin, Kaitlyn Mussio, Lee W. Riley

BackgroundBacterial antimicrobial resistance is a serious global public health threat. Intestinal commensal drug-resistant bacteria have been suggested as an important reservoir of antimicrobial resistant genes (ARGs), which may be acquired via food. We aimed to identify risk factors associated with fecal carriage of drug-resistant commensal Escherichia coli (E. coli) among healthy adults focused on their dietary habit. MethodsWe conducted a cross-sectional study targeting healthy adult volunteers in a college community. Fecal samples and questionnaires were obtained from 113 volunteers. We conducted backward elimination logistic regression and least absolute shrinkage and selection (LASSO) methods to identify risk factors. ResultsWe analyzed responses from 81 of 113 volunteers who completed the questionnaire. The logistic regression and LASSO methods identified red meat consumption to be associated with increased risk (OR = 6.13 [1.83-24.2] and 1.82, respectively) and fish consumption with reduced risk (OR = 0.27 [0.08-0.85] and 0.82) for the carriage of multidrug-resistant E. coli, adjusted for gender, employment status, frequently-used supermarket, and previous travel. ConclusionsDietary habits are associated with the risk of fecal carriage of multidrug-resistant E. coli. This study supports the growing evidence that food may be an important source of ARGs present in human commensal E. coli.

5568: Group Testing Large Populations for SARS-CoV-2
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Posted 05 Jun 2021

Group Testing Large Populations for SARS-CoV-2
102 downloads medRxiv epidemiology

Hooman Zabeti, Nick Dexter, Ivan Lau, Leonhardt Unruh, Ben Adcock, Leonid Chindelevitch

Group testing, the testing paradigm which combines multiple samples within a single test, was introduced in 1943 by Robert Dorfman. Since its original proposal for syphilis screening, group testing has been applied in domains such as fault identification in electrical and computer networks, machine learning, data mining, and cryptography. TheSARS-CoV-2 pandemic has led to proposals for using group testing in its original context of identifying infected individuals in a population with few tests. Studies suggest that non-adaptive group testing - in which all the tests are determined in advance - for SARS-CoV-2could help save 20% to 90% of tests depending on the prevalence. However, no systematic approach for comparing different non-adaptive group testing strategies currently exists. In this paper we develop a software platform for evaluating non-adaptive group testing strategies in both a noiseless setting and in the presence of realistic noise sources, modelled on published experimental observations, which makes them applicable to polymerase chain reaction (PCR) tests, the dominant type of tests for SARS-CoV-2. This modular platform can be used with a variety of group testing designs and decoding algorithms. We use it to evaluate the performance of near-doubly-regular designs and a decoding algorithm based on an integer linear programming formulation, both of which are known to be optimal in some regimes. We find savings between 40% and 91% of tests for prevalences up to 10% when a small error (below 5%) is allowed. We also find that the performance degrades gracefully with noise. We expect our modular, user-friendly, publicly available platform to facilitate empirical research into non-adaptive group testing for SARS-CoV-2.

5569: Estimating incidence of infection from diverse data sources: Zika virus in Puerto Rico, 2016
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Posted 16 Oct 2020

Estimating incidence of infection from diverse data sources: Zika virus in Puerto Rico, 2016
102 downloads medRxiv epidemiology

Talia M. Quandelacy, Jessica M. Healy, Bradford Greening, Dania M. Rodriguez, Koo-Whang Chung, Matthew J. Kuehnert, Brad J. Biggerstaff, Emilio Dirlikov, Luis Mier-y-Teran-Romero, Tyler M. Sharp, Stephen Waterman, Michael Johansson

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

5570: Increase in anticholinergic burden in the UK from 1990 to 2015: a UK Biobank study
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Posted 18 Oct 2020

Increase in anticholinergic burden in the UK from 1990 to 2015: a UK Biobank study
102 downloads medRxiv epidemiology

J. Mur, Simon R Cox, Riccardo E. Marioni, Graciela Muniz-Terrera, Tom C Russ

BackgroundThe use of prescription drugs with anticholinergic properties has been associated with multiple negative health outcomes in older people. Moreover, recent evidence suggests that associated adverse effects may occur even decades after stopping anticholinergic use. Despite the implicated importance of examining longitudinal patterns of anticholinergic prescribing for different age groups, few such data are available. MethodsWe performed an age-period-cohort analysis to study trends in anticholinergic burden between the years 1990 and 2015 utilising data from >220,000 UK Biobank participants with linked prescription data from primary care. ResultsAnticholinergic burden in the sample increased between three- and nine-fold over 25 years and was significant for both period/cohort- and age-effects across all models. When adjusted for total number of prescriptions, the effect of age reversed. Anticholinergic burden was also associated with various lifestyle- and demographic factors. ConclusionsThe increase in anticholinergic prescribing is mostly due to an increase in polypharmacy and is attributable to both ageing of participants, as well as period/cohort-related changes in prescribing practices. There is evidence for deprescribing of anticholinergic medications in older age. Further research is needed to clarify the implications of rising anticholinergic use for public health and to contextualise this rise in light of other relevant prescribing practices.

5571: Socioeconomic inequalities in co-morbidity of overweight, obesity and mental ill-health from adolescence to mid-adulthood in two national birth cohort studies
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Posted 28 Oct 2020

Socioeconomic inequalities in co-morbidity of overweight, obesity and mental ill-health from adolescence to mid-adulthood in two national birth cohort studies
102 downloads medRxiv epidemiology

Amal R. Khanolkar, Praveetha Patalay

AimTo examine socioeconomic inequalities in risk of comorbidity between overweight (including obesity) and mental ill-health in two national cohorts. We investigated independent effects of childhood and adulthood socioeconomic disadvantage on comorbidity from childhood to mid-adulthood, and differences by sex and cohort. MethodsData were from 1958 National Child Development Study (NCDS58) and 1970 British Cohort Study (BCS70) [total N=30,868, 51% males] assessed at ages 10, 16, 23, 34 and 42 years. Socioeconomic indicators included childhood and adulthood social class and educational level. Risk for i. having healthy BMI and mental ill-health, ii. overweight and good mental health, and iii. overweight and mental ill-health was analysed using multinomial logistic regression. ResultsSocioeconomic disadvantage was consistently associated with greater risk for overweight-mental ill-health comorbidity at all ages (RRR 1.43, 2.04, 2.38, 1.64 and 1.71 at ages 10, 16, 23, 34 and 42 respectively for unskilled/skilled vs. professional/managerial class). The observed inequalities in co-morbidity were greater than that observed for either condition alone (overweight; RRR 1.39 and 1.25, mental ill-health; 1.36 and 1.22 at ages 16 and 42 respectively, for unskilled/skilled vs. professional/managerial class). In adulthood, childhood and adulthood socioeconomic disadvantage were independently associated with comorbid overweight-mental ill-health, with a clear inverse gradient between educational level and risk for comorbidity; no education, RRR 6.11 (95% CI 4.31-8.65) at age 34 and 4.42 (3.28-5.96) at age 42 compared to university education. There were no differences observed in the extent of inequalities by sex and differences between cohorts were limited. ConclusionsSocioeconomic disadvantage in childhood and adulthood are consistently and independently associated with greater risk for mental ill-health and overweight separately, and even greater inequalities in the risk for comorbidity between both conditions through the lifecourse. These findings are significant given the increasing global prevalence of obesity and mental ill-health, and their implications for lifelong health and mortality.

5572: Forecasting new daily confirmed cases infected by COVID-19 in Italy from April 9th to May 18th 2020
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Posted 04 Nov 2020

Forecasting new daily confirmed cases infected by COVID-19 in Italy from April 9th to May 18th 2020
102 downloads medRxiv epidemiology

Babak Jamshidi, Amir Talaei-Khoei, Shahriar Jamshidi Zargaran, Mansour Rezaei

We aim at forecasting the outbreak of COVID-19 in Italy by using a two-part time series to model the daily relative increments. Our model is based on the data observed from 22 February to 8 April 2020 and its objective is forecasting 40 days from 9 April to 18 May 2020. All the calculations, simulations, and results in the present paper have been done in MatLab R2015b. The average curve and 80% upper and lower bounds are calculated based on 100 simulations of the fitted models. According to our model, it is expected that by May 18th, 2020, the relative increment (RI) falls to the interval of 0.31% to 1.24% (average equal to 0.78%). During the last three days of the studied period, the RI belonged to the interval 2.5% to 3%. Accordingly, It is expected that the new daily confirmed cases face a decreasing to around 1900 on average. Finally, our prediction establishes that the cumulative number of confirmed cases reaches 237635 (with 80% confidence interval equal to [226340 248417] by May 18th, 2020.

5573: Trust boosts recovery of countries from COVID-19
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Posted 07 Apr 2021

Trust boosts recovery of countries from COVID-19
102 downloads medRxiv epidemiology

Timothy Michael Lenton, Chris A Boulton, Marten Scheffer

Why have some countries suppressed waves of the COVID-19 pandemic much more effectively than others? We find that the decay rate of daily cases or deaths from peak levels varies by a factor of ~40 between countries. This measure of country-level resilience to COVID-19 is positively correlated with trust within society, and with the adaptive increase in stringency of government interventions when epidemic waves occur. All countries where >40% agree most people can be trusted achieve a near complete reduction of new cases and deaths. In contrast, countries where governments maintain greater background stringency tend to be less trusting and less resilient. Building trust is therefore critical to resilience, both to epidemics and other unexpected disruptions, of which COVID-19 is unlikely to be the last.

5574: Characterisation, identification, clustering, and classification of disease
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Posted 30 Nov 2020

Characterisation, identification, clustering, and classification of disease
102 downloads medRxiv epidemiology

Anthony J Webster, Kezia Gaitskell, Iain Turnbull, Benjamin J Cairns, Robert Clarke

Data-driven classifications are improving statistical power and refining prognoses for a range of respiratory, infectious, autoimmune, and neurological diseases. Studies have used molecular information, age of disease incidence, and sequences of disease onset ("disease trajectories"). Here we consider whether easily measured risk factors such as height and BMI can usefully characterise diseases in UK Biobank data, combining established statistical methods in new but rigorous ways to provide clinically relevant comparisons and clusters of disease. Over 400 common diseases were selected for study on the basis of clinical and epidemiological criteria, and a conventional proportional hazards model was used to estimate associations with 12 established risk factors. Comparing men and women, several diseases had strongly sex-dependent associations of disease risk with BMI. Despite this, a large proportion of diseases affecting both sexes could be identified by their risk factors, and equivalent diseases tended to cluster adjacently. This included 10 diseases presently classified as "Symptoms, signs, and abnormal clinical and laboratory findings, not elsewhere classified". Many clusters are associated with a shared, known pathogenesis, others suggest likely but presently unconfirmed causes. The specificity of associations and shared pathogenesis of many clustered diseases, provide a new perspective on the interactions between biological pathways, risk factors, and patterns of disease such as multimorbidity.

5575: Improved Prediction of COVID-19 Transmission and Mortality Using Google Search Trends for Symptoms in the United States
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Posted 24 Mar 2021

Improved Prediction of COVID-19 Transmission and Mortality Using Google Search Trends for Symptoms in the United States
102 downloads medRxiv epidemiology

Meshrif Alruily, Mohamed Ezz, Ayman Mohamed Mostafa, Nacim Yanes, Mostafa Abbas, Yasser El-Manzalawy

Accurate forecasting of emerging infectious diseases can guide public health officials in making appropriate decisions related to the allocation of public health resources. Due to the exponential spread of the COVID-19 infection worldwide, several computational models for forecasting the transmission and mortality rates of COVID-19 have been proposed in the literature. To accelerate scientific and public health insights into the spread and impact of COVID-19, Google released the Google COVID-19 search trends symptoms open-access dataset. Our objective is to develop 7 and 14 -day-ahead forecasting models of COVID-19 transmission and mortality in the US using the Google search trends for COVID-19 related symptoms. Specifically, we propose a stacked long short-term memory (SLSTM) architecture for predicting COVID-19 confirmed and death cases using historical time series data combined with auxiliary time series data from the Google COVID-19 search trends symptoms dataset. Considering the SLSTM networks trained using historical data only as the base models, our base models for 7 and 14 -day-ahead forecasting of COVID cases had the mean absolute percentage error (MAPE) values of 6.6% and 8.8%, respectively. On the other side, our proposed models had improved MAPE values of 3.2% and 5.6%, respectively. For 7 and 14 -day-ahead forecasting of COVID-19 deaths, the MAPE values of the base models were 4.8% and 11.4%, while the improved MAPE values of our proposed models were 4.7% and 7.8%, respectively. We found that the Google search trends for "pneumonia," "shortness of breath," and "fever" are the most informative search trends for predicting COVID-19 transmission. We also found that the search trends for "hypoxia" and "fever" were the most informative trends for forecasting COVID-19 mortality.

5576: Non-pharmaceutical interventions and the emergence of pathogen variants
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Posted 28 May 2021

Non-pharmaceutical interventions and the emergence of pathogen variants
102 downloads medRxiv epidemiology

Ben Ashby, Robin N Thompson

Non-pharmaceutical interventions (NPIs), such as social distancing and contact tracing, have been widely implemented during the COVID-19 pandemic. In addition to playing an important role in suppressing transmission, NPIs influence pathogen evolution by mediating mutation supply and altering the strength of selection for novel variants. However, it is unclear how NPIs might affect the emergence of novel variants of concern that are able to escape pre-existing immunity (partially or fully), are more transmissible, or cause greater mortality. Here, we analyse a stochastic two-strain epidemiological model to determine how the strength of NPIs affects the emergence of variants with similar or contrasting life-history characteristics to the wildtype. We show that, while stronger and timelier NPIs generally reduce the likelihood of variant emergence, it is possible for more transmissible variants with high cross immunity to have a greater probability of emerging at intermediate levels of NPIs. However, since one cannot predict the characteristics of a variant, the best strategy to prevent emergence is likely to be implementation of strong, timely NPIs.

5577: A statistical model of COVID-19 testing in populations: effects of sampling bias and testing errors
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Posted 25 May 2021

A statistical model of COVID-19 testing in populations: effects of sampling bias and testing errors
102 downloads medRxiv epidemiology

Lucas Böttcher, Tom Chou, Maria R. D'Orsogna

We develop a statistical model for the testing of disease prevalence in a population. The model assumes a binary test result, positive or negative, but allows for biases in sample selection and both type I (false positive) and type II (false negative) testing errors. Our model also incorporates multiple test types and is able to distinguish between retesting and exclusion after testing. Our quantitative framework allows us to directly interpret testing results as a function of errors and biases. By applying our testing model to COVID-19 testing data and actual case data from specific jurisdictions, we are able to estimate and provide uncertainty quantification of indices that are crucial in a pandemic, such as disease prevalence and fatality ratios.

5578: A Two-Sample Robust Bayesian Mendelian Randomization Method Accounting for Linkage Disequilibrium and Idiosyncratic Pleiotropy With Applications to the COVID-19 Outcome
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Posted 05 Mar 2021

A Two-Sample Robust Bayesian Mendelian Randomization Method Accounting for Linkage Disequilibrium and Idiosyncratic Pleiotropy With Applications to the COVID-19 Outcome
102 downloads medRxiv epidemiology

Anqi Wang, Zhonghua Liu

Mendelian randomization (MR) is a statistical method exploiting genetic variants as instrumental variables to estimate the causal effect of modifiable risk factors on an outcome of interest. Despite wide uses of various popular two-sample MR methods based on genome-wide association study summary level data, however, those methods could suffer from potential power loss or/and biased inference when the chosen genetic variants are in linkage disequilibrium (LD), and have relatively large direct effects on the outcome whose distribution might be heavy-tailed which is commonly referred to as the idiosyncratic pleiotropy. To resolve those two issues, we propose a novel Robust Bayesian Mendelian Randomization (RBMR) model that uses the more robust multivariate generalized t-distribution to model such direct effects in a probabilistic model framework which can also incorporate the LD structure explicitly. The generalized t-distribution can be represented as a Gaussian scaled mixture so that our model parameters can be estimated by the EM-type algorithms. We compute the standard errors by calibrating the evidence lower bound (ELBO) using the likelihood ratio test. Through extensive simulation studies, we show that our RBMR has robust performance compared to other competing methods. We also apply our RBMR method to two benchmark data sets and find that RBMR has smaller bias and standard errors. Using our proposed RBMR method, we find that coronary artery disease is associated with increased risk of critically ill coronavirus disease 2019 (COVID-19). We also develop a user-friendly R package RBMR for public use.

5579: Clinical Risk, Sociodemographic Factors, and SARS-CoV-2 Infection Over Time in Ontario, Canada
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Posted 29 Apr 2021

Clinical Risk, Sociodemographic Factors, and SARS-CoV-2 Infection Over Time in Ontario, Canada
102 downloads medRxiv epidemiology

Jacob Allan Udell, Bahar Behrouzi, Atul Sivaswamy, Anna Chu, Laura E Ferreira-Legere, Jiming Fang, Shaun G Goodman, Justin A Ezekowitz, Kevin R. Bainey, Sean van Diepen, Padma Kaul, Finlay A McAlister, Isaac Bogoch, Cynthia Jackevicius, Husam Abdel-qadir, Harindra C Wijeysundera, Dennis T Ko, Peter C Austin, Douglas S Lee

Background: Sociodemographic and clinical factors are emerging as important predictors for developing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Objective: To determine whether public health interventions that culminated in a stay-at-home lockdown instituted during the first wave of the pandemic in March/April 2020 were effective at mitigating the association of any of these factors with the risk of infection. Design: Population-based cohort study Setting: Ontario, Canada Patients: All adults that underwent testing for SARS-CoV-2 between January 1 and June 12, 2020. Measurements: The outcome of interest was SARS-CoV-2 infection, determined by reverse transcription polymerase chain reaction testing. Adjusted odds ratios (ORs) were determined for sociodemographic and clinical risk factors before and after the peak of the pandemic to assess for changes in effect sizes. Results: Among 578,263 community-dwelling individuals, 20,524 (3.5%) people tested positive. The association between age and SARS-CoV-2 infection risk among tested community-dwelling individuals varied over time (P-interaction <0.0001). Prior to the first-wave peak of the pandemic, the likelihood of SARS-CoV-2 infection increased progressively with age compared with individuals aged 18-45 years (P<0.0001). This association subsequently reversed, with all age groups younger than 85 years at progressively higher risk of infection (P<0.0001) after the peak. Otherwise, risk factors that persisted throughout included male sex, residing in lower income neighborhoods, residing in more racially/ethnically diverse communities, immigration to Canada, and history of hypertension and diabetes. While there was a reduction in infection rates across Ontario after mid-April, there was less impact in regions with higher degrees of racial/ethnic diversity. When considered in an additive risk model, following the initial peak of the pandemic, individuals living in the most racially/ethnically diverse communities with 2, 3, or [&ge;]4 risk factors had ORs of 1.89, 3.07, and 4.73-fold higher for SARS-CoV-2 infection compared to lower risk individuals in their community (all P<0.0001). In contrast, in the least racially/ethnically diverse communities, there was little to no gradient in infection rates across risk strata. Conclusion: After public health interventions in March/April 2020, people with multiple risk factors residing in the most racially diverse communities of Ontario continued to have the highest likelihood of SARS-CoV-2 infection while risk was mitigated for people with multiple risk factors residing in less racially/ethnically diverse communities. Further efforts are necessary to reduce the risk of SARS-CoV-2 infection among the highest risk individuals residing in these communities.

5580: Unmasking the Current Scenario of Indian Biomedical Devices Industry: Ventilators being the Heart of the Discussion
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Posted 02 Mar 2021

Unmasking the Current Scenario of Indian Biomedical Devices Industry: Ventilators being the Heart of the Discussion
101 downloads medRxiv epidemiology

Sheersha Pramanik, Sucheta Karmakar, Shreyas Mukherjee, Indraneel Dhavale, Rohan Shrestha

BackgroundThe Indian Biomedical Device Industry has been growing at an unprecedented rate, but several hindrances need to be acknowledged in offering access to quality, budget-friendly medical devices in India. This article explores the current loopholes of the Indian biomedical device industry along with the proposal of various innovative solutions, with emphasis on ventilators. MethodsAn online survey with the help of Google forms was conducted from 1st November to 25th December 2020, addressing the problems of the Indian medical device industry (MDI) along with probable solutions. The survey also provides a glimpse into the complications aroused from the frequent use of ventilators during COVID-19 outburst, along with possible measures. ResultsAccording to the survey, 51.6%, 46.5%, 55.7%, and 47.5% of respondents have agreed to Stringent laws and implementation, Safety testing and strict regulations, Unfavorable duty structure, and Reducing tax rate on domestic manufacturers, as a possible solution to advance the implementation of ISO 13485 and ISO 10651, implementation of ISO 14971, the probable cause of limitations of Indian MDI, possible measure to overcome limitations of Indian MDI, respectively. 46.7%, 47.5%, 46.2%, and 44.6% of respondents have agreed to Surgical decompression, Nebulized and broad-spectrum antibiotics, PEEP, and Adopting lung protective ventilation strategies as possible solutions to treat various ventilator complications, respectively. ConclusionThe study briefs about the peoples perception of the Indian MDI as well as on the ventilator complications. The results complied with our hypothesis as the majority of the respondents have agreed with almost all the probable solutions in both the sections given by us as options.

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