scholarly journals Seroprevalence of COVID-19 among health workers in the Kathmandu valley, Nepal (SEVID-KaV): a longitudinal cohort study

2021 ◽  
Author(s):  
Kiran Raj Pandey ◽  
Aseem Bhattarai ◽  
Suman Pant ◽  
Rimmy Barakoti ◽  
Janaki Pandey ◽  
...  
Keyword(s):  
Disease Burden ◽  
Health Workers ◽  
Credible Interval ◽  
Longitudinal Survey ◽  
Kathmandu Valley ◽  
Test Accuracy ◽  
Igg Antibodies ◽  
Multilevel Regression ◽  
Occupation Category ◽  
Multilevel Regression Model

Abstract Coronavirus Disease 2019 (COVID-19) burden is often underestimated when relying on case-based incidence reports. Seroprevalence studies accurately estimate infectious disease burden by estimating the population that has developed antibodies following an infection. Sero-Epidemiology of COVID-19 in the Kathmandu valley (SEVID-KaV) is a longitudinal survey of hospital-based health workers in the Kathmandu valley. Between December 3-25, we sampled 800 health workers from 20 hospitals and administered a questionnaire eliciting COVID-19 related history and tested for COVID-19 IgG antibodies. We then used a probabilistic multilevel regression model with post-stratification to correct for test accuracy, the effect of hospital-based clustering, and to establish representativeness. 522 (65.2%) of the participants were female, 372 (46%) were between ages 18-29, and 7 (0.9%) were 60 or above. 287 (36%) of the participants were nurses. About 23% of the participants previously had a PCR positive infection. 321 (40.13%) individuals tested positive for COVID-19 antibodies. Adjusted for test accuracy and weighted by age, gender and occupation category, the seroprevalence was 38.17% (95% Credible Interval (CrI) 29.26%–47.82%). Posterior predictive hospital-wise seroprevalence ranged between 38.1% (95% CrI 30.7.0%– 44.1%) and 40.5% (95% CrI 34.7%–47.0%).

scholarly journals Farm Gate Prices for Non-Varietal Wine in Argentina: A Multilevel Comparison of the Prices Paid by Cooperatives and Investor-Oriented Firms

2017 ◽  
Vol 16 (1) ◽  
Author(s):  
Agustina Malvido Perez Carletti ◽  
Markus Hanisch ◽  
Jens Rommel ◽  
Murray Fulton
Keyword(s):  
Multilevel Regression ◽  
Data Set ◽  
Unique Data ◽  
Market Shares ◽  
Price Effects ◽  
Theoretical Predictions ◽  
The One ◽  
The Cost ◽  
Price Differences ◽  
Multilevel Regression Model

AbstractIn this paper, we use a unique data set of the prices paid to farmers in Argentina for grapes to examine the prices paid by non-varietal wine processing cooperatives and investor-oriented firms (IOFs). Motivated by contrasting theoretical predictions of cooperative price effects generated by the yardstick of competition and property rights theories, we apply a multilevel regression model to identify price differences at the transaction level and the departmental level. On average, farmers selling to cooperatives receive a 3.4 % lower price than farmers selling to IOFs. However, we find cooperatives pay approximately 2.4 % more in departments where cooperatives have larger market shares. We suggest that the inability of cooperatives to pay a price equal to or greater than the one paid by IOFs can be explained by the market structure for non-varietal wine in Argentina. Specifically, there is evidence that cooperative members differ from other farmers in terms of size, assets and the cost of accessing the market. We conclude that the analysis of cooperative pricing cannot solely focus on the price differential between cooperatives and IOFs, but instead must consider other factors that are important to the members.

scholarly journals Seroprevalence of anti-SARS-CoV-2 IgG antibodies, risk factors for infection and associated symptoms in Geneva, Switzerland: a population-based study

2021 ◽  
pp. 140349482110480
Author(s):  
Aude Richard ◽  
Ania Wisniak ◽  
Javier Perez-Saez ◽  
Henri Garrison-Desany ◽  
Dusan Petrovic ◽  
...  
Keyword(s):  
Risk Factors ◽  
Test Performance ◽  
Credible Interval ◽  
The Elderly ◽  
Population Based ◽  
Igg Antibodies ◽  
Population Based Study ◽  
Associated Symptoms ◽  
Household Members ◽  
Occupation Level

Aims: To assess SARS-CoV-2 seroprevalence over the first epidemic wave in the canton of Geneva, Switzerland, as well as risk factors for infection and symptoms associated with IgG seropositivity. Methods: Between April and June 2020, former participants of a representative survey of the 20–74-year-old population of canton Geneva were invited to participate in the study, along with household members aged over 5 years. Blood samples were tested for anti-SARS-CoV-2 immunoglobulin G. Questionnaires were self-administered. We estimated seroprevalence with a Bayesian model accounting for test performance and sampling design. Results: We included 8344 participants, with an overall adjusted seroprevalence of 7.8% (95% credible interval 6.8–8.9). Seroprevalence was highest among 18–49 year-olds (9.5%), and lowest in 5–9-year-old children (4.3%) and individuals >65 years (4.7-5.4%). Odds of seropositivity were significantly reduced for female retirees and unemployed men compared to employed individuals, and smokers compared to non-smokers. We found no significant association between occupation, level of education, neighborhood income and the risk of being seropositive. The symptom most strongly associated with seropositivity was anosmia/dysgeusia. Conclusions: Anti-SARS-CoV-2 population seroprevalence remained low after the first wave in Geneva. Socioeconomic factors were not associated with seropositivity in this sample. The elderly, young children and smokers were less frequently seropositive, although it is not clear how biology and behaviours shape these differences.

scholarly journals Empirical Bayes estimation of farm prevalence adjusting for multistage sampling and uncertainty in test performance: a Brucella cross-sectional serostudy in southern Kazakhstan

2016 ◽  
Vol 144 (16) ◽  
pp. 3531-3539 ◽  
Author(s):  
W. BEAUVAIS ◽  
M. ORYNBAYEV ◽  
J. GUITIAN
Keyword(s):  
Confidence Interval ◽  
Test Performance ◽  
Empirical Bayes ◽  
Small Ruminants ◽  
Credible Interval ◽  
Bayes Estimation ◽  
Test Accuracy ◽  
Endemic Region ◽  
Cross Sectional ◽  
Seropositive Animal

SUMMARYEstimation of farm prevalence is common in veterinary research. Typically, not all animals within the farm are sampled, and imperfect tests are used. Often, assumptions about herd sizes and sampling proportions are made, which may be invalid in smallholder settings. We propose an alternative method for estimating farm prevalence in the context of Brucella seroprevalence estimation in an endemic region of Kazakhstan. We collected 210 milk samples from Otar district, with a population of about 1000 cattle and 16 000 small ruminants, and tested them using an indirect ELISA. Individual-level prevalence and 95% confidence intervals were estimated using Taylor series linearization. A model was developed to estimate the smallholding prevalence, taking into account variable sampling proportions and uncertainty in the test accuracy. We estimate that 73% of households that we sampled had at least one Brucella-seropositive animal (95% credible interval 68–82). We estimate that 58% (95% confidence interval 40–76) of lactating small ruminants and 14% (95% confidence interval 1–28) of lactating cows were seropositive. Our results suggest that brucellosis is highly endemic in the area and conflict with those of the official brucellosis-testing programme, which found that in 2013 0% of cows and 1·7% of small ruminants were seropositive.

scholarly journals Development of a Pressure–Precipitation Transmitter

2019 ◽  
Vol 58 (11) ◽  
pp. 2453-2468
Author(s):  
Masaru Inatsu ◽  
Tamaki Suematsu ◽  
Yuta Tamaki ◽  
Naoto Nakano ◽  
Kao Mizushima ◽  
...  
Keyword(s):  
Regression Model ◽  
Daily Precipitation ◽  
Reanalysis Data ◽  
Precipitation Pattern ◽  
Multilevel Regression ◽  
Extreme Statistics ◽  
Spatial Continuity ◽  
Daily Precipitation Data ◽  
Multilevel Regression Model

AbstractA novel method is proposed to create very long term daily precipitation data for the extreme statistics by computing very long term daily sea level pressure (SLP) with the SLP emulator (a statistical multilevel regression model) and then converting the SLP into precipitation by combining statistical downscaling methods of the analog ensemble and singular value decomposition (SVD). After a review of the SLP emulator, we present a multilevel regression model constructed for each month that is based on a time series of 1000 principal components of SLPs on global reanalysis data. Simple integration of the SLP emulator provides 100-yr daily SLP data, which are temporally interpolated into a 6-h interval. Next, the pressure–precipitation transmitter (PPT) is developed to convert 6-hourly SLP to daily precipitation. The PPT makes its first-guess estimate from a composite of time frames with analogous SLP transition patterns in the learning period. The departure of SLPs from the analog ensemble is then corrected with an SVD relationship between SLPs and precipitation. The final product showed a fairly realistic precipitation pattern, displaying temporal and spatial continuity. The annual-maximum precipitation of the estimated 100-yr data extended the tail of probability distribution of the 8-yr learning data.

scholarly journals A Multilevel Regression Model for Geographical Studies in Sets of Non-Adjacent Cities

PLoS ONE ◽  
2015 ◽  
Vol 10 (8) ◽  
pp. e0133649 ◽  
Author(s):  
Marc Marí-Dell’Olmo ◽  
Miguel Ángel Martínez-Beneito
Keyword(s):  
Regression Model ◽  
Multilevel Regression ◽  
Multilevel Regression Model

scholarly journals Diagnostic Test Accuracy in Childhood Pulmonary Tuberculosis: A Bayesian Latent Class Analysis

2016 ◽  
Vol 184 (9) ◽  
pp. 690-700 ◽  
Author(s):  
Samuel G. Schumacher ◽  
Maarten van Smeden ◽  
Nandini Dendukuri ◽  
Lawrence Joseph ◽  
Mark P. Nicol ◽  
...  
Keyword(s):  
Pulmonary Tuberculosis ◽  
Latent Class Analysis ◽  
Chest Radiography ◽  
Latent Class ◽  
Credible Interval ◽  
Smear Microscopy ◽  
Test Accuracy ◽  
Class Analysis ◽  
Antituberculosis Treatment ◽  
Bayesian Latent Class Analysis

AbstractEvaluation of tests for the diagnosis of childhood pulmonary tuberculosis (CPTB) is complicated by the absence of an accurate reference test. We present a Bayesian latent class analysis in which we evaluated the accuracy of 5 diagnostic tests for CPTB. We used data from a study of 749 hospitalized South African children suspected to have CPTB from 2009 to 2014. The following tests were used: mycobacterial culture, smear microscopy, Xpert MTB/RIF (Cepheid Inc.), tuberculin skin test (TST), and chest radiography. We estimated the prevalence of CPTB to be 27% (95% credible interval (CrI): 21, 35). The sensitivities of culture, Xpert, and smear microscopy were estimated to be 60% (95% CrI: 46, 76), 49% (95% CrI: 38, 62), and 22% (95% CrI: 16, 30), respectively; specificities of these tests were estimated in accordance with prior information and were close to 100%. Chest radiography was estimated to have a sensitivity of 64% (95% CrI: 55, 73) and a specificity of 78% (95% CrI: 73, 83). Sensitivity of the TST was estimated to be 75% (95% CrI: 61, 84), and it decreased substantially among children who were malnourished and infected with human immunodeficiency virus (56%). The specificity of the TST was 69% (95% CrI: 63%, 76%). Furthermore, it was estimated that 46% (95% CrI: 42, 49) of CPTB-negative cases and 93% (95% CrI: 82; 98) of CPTB-positive cases received antituberculosis treatment, which indicates substantial overtreatment and limited undertreatment.

scholarly journals Journey-to-Crime Distances of Residential Burglars in China Disentangled: Origin and Destination Effects

2018 ◽  
Vol 7 (8) ◽  
pp. 325 ◽  
Author(s):  
Luzi Xiao ◽  
Lin Liu ◽  
Guangwen Song ◽  
Stijn Ruiter ◽  
Suhong Zhou
Keyword(s):  
Road Network ◽  
Multilevel Regression ◽  
Individual Level ◽  
Local Residents ◽  
Journey To Crime ◽  
Home Community ◽  
Almost All ◽  
Distinct Features ◽  
Multilevel Regression Model ◽  
Insight Into

Research on journey-to-crime distance has revealed the importance of both the characteristics of the offender as well as those of target communities. However, the effect of the home community has so far been ignored. Besides, almost all journey-to-crime studies were done in Western societies, and little is known about how the distinct features of communities in major Chinese cities shape residential burglars’ travel patterns. To fill this gap, we apply a cross-classified multilevel regression model on data of 3763 burglary trips in ZG City, one of the bustling metropolises in China. This allows us to gain insight into how residential burglars’ journey-to-crime distances are shaped by their individual-level characteristics as well as those of their home and target communities. Results show that the characteristics of the home community have larger effects than those of target communities, while individual-level features are most influential. Older burglars travel over longer distances to commit their burglaries than the younger ones. Offenders who commit their burglaries in groups tend to travel further than solo offenders. Burglars who live in communities with a higher average rent, a denser road network and a higher percentage of local residents commit their burglaries at shorter distances. Communities with a denser road network attract burglars from a longer distance, whereas those with a higher percentage of local residents attract them from shorter by.

scholarly journals High regional variation in prostate surgery for benign prostatic hyperplasia in Switzerland

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254143
Author(s):  
Maria M. Wertli ◽  
Brigitta Zumbrunn ◽  
Pascal Weber ◽  
Alan G. Haynes ◽  
Radoslaw Panczak ◽  
...  
Keyword(s):  
Benign Prostatic Hyperplasia ◽  
Socioeconomic Factors ◽  
Regional Variation ◽  
Disease Burden ◽  
Treatment Options ◽  
Population Based ◽  
Prostatic Hyperplasia ◽  
Multilevel Regression ◽  
Discharge Data ◽  
Swiss German

Background Among various treatment options for benign prostatic hyperplasia (BPH), surgical therapy is the most invasive. As Switzerland has the highest transurethral prostatectomy rate among OECD countries, we assessed the regional variation in prostate surgery for BPH and explored potential determinants of variation. Methods We conducted a population-based analysis using discharge data for men aged ≥40 years with transurethral or simple prostatectomy from all Swiss hospitals during 2013–2018. After excluding patients with genitourinary/prostate cancer, we derived hospital service areas (HSAs) by analyzing patient flows. We calculated age-standardized mean procedure rates and variation indices (extremal quotient [EQ] and systematic component of variation [SCV]). We estimated the reduction in variance across HSAs of prostatectomy rates in multilevel regression models, with incremental adjustment for age, regional cultural and socioeconomic factors, disease burden, density of urologists, and the time since urologists’ graduation. Results Overall, 44,253 prostatectomies (42,710 transurethral and 1543 simple) from 44 HSAs were analyzed. The mean age-standardized prostate surgery rate was 314 (range 166–500) per 100,000 men aged ≥40 years per year. The EQ was 3.01 and the SCV 5.53, indicating a high regional variation. In multivariate models, men aged 75–79 years had an 11.6-fold higher prostatectomy rate than those aged 50–54 years. French/Italian language areas had a 21% lower rate than Swiss German speaking areas. Socioeconomic factors, disease burden, and density of urologist/time since graduation were not associated with prostatectomy rates. After full adjustment, 80% of the variance in prostate surgery across HSAs remained unexplained. Conclusion We found a remarkably high regional variation in prostate surgery rates for BPH within Switzerland.

scholarly journals Trends in SARS-CoV-2 seroprevalence in Massachusetts estimated from newborn screening specimens

2021 ◽  
Author(s):  
Kevin C Ma ◽  
Jaime E Hale ◽  
Yonatan Grad ◽  
Galit Alter ◽  
Katherine Luzuriaga ◽  
...  
Keyword(s):  
Newborn Screening ◽  
Cumulative Incidence ◽  
Diagnostic Testing ◽  
Credible Interval ◽  
Dried Blood Spots ◽  
Multilevel Regression ◽  
Public Health Policies ◽  
Seroprevalence Data ◽  
Test Specificity ◽  
Good Concordance

Background. Estimating the cumulative incidence of SARS-CoV-2 is essential for setting public health policies. We leveraged de-identified Massachusetts newborn screening specimens to generate an accessible, retrospective source of maternal antibodies for estimating statewide SARS-CoV-2 seroprevalence in a non-test-seeking population. Methods. We analyzed 72,117 newborn dried blood spots collected from November 2019 through December 2020, representing 337 towns and cities across Massachusetts. Seroprevalence was estimated for the general Massachusetts population after correcting for imperfect test specificity and nonrepresentative sampling using Bayesian multilevel regression and poststratification. Results. Statewide seroprevalence was estimated to be 0.03% (90% credible interval (CI) [0.00, 0.11]) in November 2019 and rose to 1.47% (90% CI [1.00, 2.13]) by May 2020, following sustained SARS-CoV-2 transmission in the spring. Seroprevalence plateaued from May onwards, reaching 2.15% (90% CI [1.56, 2.98]) in December 2020. Seroprevalence varied substantially by community and was particularly associated with community percent non-Hispanic Black (β = 0.024, 90% CI [0.004, 0.044]); i.e., a 10% increase in community percent non-Hispanic Black was associated with a 27% higher odds of seropositivity. Seroprevalence estimates had good concordance with reported case counts and wastewater surveillance for most of 2020, prior to the resurgence of transmission in winter. Conclusions. Cumulative incidence of SARS-CoV-2 protective antibody in Massachusetts was low as of December 2020, indicating that a substantial fraction of the population was still susceptible. Maternal seroprevalence data from newborn screening can inform longitudinal trends and identify cities and towns at highest risk, particularly in settings where widespread diagnostic testing is unavailable.

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