scholarly journals Impact of community piped water coverage on re-infection with urogenital schistosomiasis in rural South Africa

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Polycarp Mogeni ◽  
Alain Vandormael ◽  
Diego Cuadros ◽  
Christopher Appleton ◽  
Frank Tanser
Keyword(s):  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Primary School Children ◽  
Effective Control ◽  
Urogenital Schistosomiasis ◽  
Percentage Point Increase ◽  
Piped Water ◽  
Point Increase ◽  
Binomial Regression

Previously, we demonstrated that coverage of piped water in the seven years preceding a parasitological survey was strongly predictive of Schistosomiasis haematobium infection in a nested cohort of 1976 primary school children (Tanser, 2018). Here, we report on the prospective follow up of infected members of this nested cohort (N = 333) for two successive rounds following treatment. Using a negative binomial regression fitted to egg count data, we found that every percentage point increase in piped water coverage was associated with 4.4% decline in intensity of re-infection (incidence rate ratio = 0.96, 95% CI: 0.93–0.98, p=0.004) among the treated children. We therefore provide further compelling evidence in support of the scaleup of piped water as an effective control strategy against Schistosoma haematobium transmission.

Abstract 16807: Burden and Timing of Hospitalizations in Heart Failure: A Community Study

Circulation ◽  
2014 ◽  
Vol 130 (suppl_2) ◽  
Author(s):  
Alanna M Chamberlain ◽  
Yariv Gerber ◽  
Shannon M Dunlay ◽  
Sheila M Manemann ◽  
Susan A Weston ◽  
...  
Keyword(s):  
Heart Failure ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Community Study ◽  
Olmsted County ◽  
Comorbid Conditions ◽  
Binomial Regression ◽  
Time Periods ◽  
Patients Experience

Background: Heart failure (HF) patients are experiencing an epidemic of hospitalizations. Nevertheless, data on the frequency and distribution of hospitalizations over the course of the disease are lacking. Methods: We determined the rates of hospitalizations during periods of follow-up in Olmsted County, MN residents with incident HF from 2000-2010. HF was identified using ICD-9 code 428 and validated by the Framingham criteria. All hospitalizations were obtained for the 2 years following incident HF and each was categorized as due to HF, other cardiovascular (ICD-9 codes 390-427, 429-459), or non-cardiovascular causes. Follow-up was divided into discrete time periods (epochs): 0-30, 31-182, 183-365, and 366-730 days. Negative binomial regression examined associations between epochs of follow-up time and hospitalizations. Results: Among 1702 incident HF patients (mean age 76, 44% male), 1143 (67%) were hospitalized at index. Over the 2 year follow-up, 3008 hospitalizations were observed among 1136 patients, and 351 patients were hospitalized within 30 days of incident HF (median time from HF to hospitalization: 11 days). The majority of hospitalizations were due to non-cardiovascular causes (63% vs. 14% HF, 23% other cardiovascular); however, a larger proportion of HF and other cardiovascular hospitalizations were observed within the first 30 days (52% non-cardiovascular, 18% HF, 30% other cardiovascular) compared to the other time periods. The rate of hospitalization was highest within the first 30 days and was similar across sex, presentation of incident HF (inpatient, outpatient), and type of HF (preserved (≥50%), reduced (<50%) ejection fraction) (Table). Conclusions: HF patients experience high rates of hospitalizations, particularly within the first 30 days, and the majority of hospitalizations are for non-cardiovascular causes. Continued efforts to manage comorbid conditions and reduce hospitalizations in HF patients are needed.

scholarly journals Inequalities in COVID19 mortality related to ethnicity and socioeconomic deprivation

2020 ◽  
Author(s):  
Tanith C. Rose ◽  
Kate Mason ◽  
Andy Pennington ◽  
Philip McHale ◽  
Iain Buchan ◽  
...  
Keyword(s):  
Mortality Rate ◽  
Low Income ◽  
Negative Binomial ◽  
Mortality Rates ◽  
Ethnic Composition ◽  
Effective Control ◽  
Local Authorities ◽  
Cross Sectional ◽  
Percentage Point Increase ◽  
Point Increase

AbstractBackgroundInitial reports suggest that ethnic minorities may be experiencing more severe coronavirus disease 2019 (COVID19) outcomes. We therefore assessed the association between ethnic composition, income deprivation and COVID19 mortality rates in England.MethodsWe performed a cross-sectional ecological analysis across England’s upper-tier local authorities. We assessed the association between the proportion of the population from Black, Asian and Minority Ethnic (BAME) backgrounds, income deprivation and COVID19 mortality rates using multivariable negative binomial regression, adjusting for population density, proportion of the population aged 50–79 and 80+ years, and the duration of the epidemic in each area.FindingsLocal authorities with a greater proportion of residents from ethnic minority backgrounds had statistically significantly higher COVID19 mortality rates, as did local authorities with a greater proportion of residents experiencing deprivation relating to low income. After adjusting for income deprivation and other covariates, each percentage point increase in the proportion of the population from BAME backgrounds was associated with a 1% increase in the COVID19 mortality rate [IRR=1.01, 95%CI 1.01–1.02]. Each percentage point increase in the proportion of the population experiencing income deprivation was associated with a 2% increase in the COVID19 mortality rate [IRR=1.02, 95%CI 1.01–1.04].InterpretationThis study provides evidence that both income deprivation and ethnicity are associated with greater COVID19 mortality. To reduce these inequalities, Government needs to target effective control and recovery measures at these disadvantaged communities, proportionate to their greater needs and vulnerabilities, during and following the pandemic.FundingNational Institute of Health Research; Medical Research Council

Burden and trajectory of multimorbidity in rheumatoid arthritis: a matched cohort study from 2006 to 2015

2020 ◽  
pp. annrheumdis-2020-218282 ◽  
Author(s):  
Bryant R England ◽  
Punyasha Roul ◽  
Yangyuna Yang ◽  
Harlan Sayles ◽  
Fang Yu ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Cohort Study ◽  
Chronic Conditions ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Sensitivity Analyses ◽  
Cross Sectional ◽  
Diagnostic Codes ◽  
Binomial Regression

ObjectivesTo compare the onset and trajectory of multimorbidity between individuals with and without rheumatoid arthritis (RA).MethodsA matched, retrospective cohort study was completed in a large, US commercial insurance database (MarketScan) from 2006 to 2015. Using validated algorithms, patients with RA (overall and incident) were age-matched and sex-matched to patients without RA. Diagnostic codes for 44 preidentified chronic conditions were selected to determine the presence (≥2 conditions) and burden (count) of multimorbidity. Cross-sectional comparisons were completed using the overall RA cohort and conditional logistic and negative binomial regression models. Trajectories of multimorbidity were assessed within the incident RA subcohort using generalised estimating equations.ResultsThe overall cohort (n=277 782) and incident subcohort (n=61 124) were female predominant (76.5%, 74.1%) with a mean age of 55.6 years and 54.5 years, respectively. The cross-sectional prevalence (OR 2.29, 95% CI 2.25 to 2.34) and burden (ratio of conditions 1.68, 95% CI 1.66 to 1.70) of multimorbidity were significantly higher in RA than non-RA in the overall cohort. Within the incident RA cohort, patients with RA had more chronic conditions than non-RA (β 1.13, 95% CI 1.10 to 1.17), and the rate of accruing chronic conditions was significantly higher in RA compared with non-RA (RA × follow-up year, β 0.21, 95% CI 0.20 to 0.21, p<0.001). Results were similar when including the pre-RA period and in several sensitivity analyses.ConclusionsMultimorbidity is highly prevalent in RA and progresses more rapidly in patients with RA than in patients without RA during and immediately following RA onset. Therefore, multimorbidity should be aggressively identified and targeted early in the RA disease course.

P3543Rehospitalization burden in heart failure with mid-range ejection fraction and morbidity burden. Is it a distinct phenotype?

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
E Santas Olmeda ◽  
R De La Espriella ◽  
G Minana ◽  
E Valero ◽  
P Palau ◽  
...  
Keyword(s):  
Heart Failure ◽  
Confidence Interval ◽  
Ejection Fraction ◽  
Recurrent Events ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Morbidity Burden ◽  
Binomial Regression ◽  
Similar Risk

Abstract Heart failure with mid-range ejection fraction (HFmrEF) has been recognized as a distinct HF phenotype, but wether patients on this category fare worse, similarly, or better than those with HF with reduced EF (HFrEF) or preserved EF (HFpEF) in terms of rehospitalization risk over time remains unclear. We therefore sought to characterize the mordibity burden of HFmrEF patients by evaluating the risk of recurrent hospitalizations following an admission for acute HF. Methods We prospectively included 2,961 consecutive patients discharged for acute HF in our institution from 2004 to 2017. Patients were categorized according to their ejection fraction (EF) obtained by an echocardiography during the index admission: HFmrEF (EF 41–49%), HFrEF (EF≤40%) and HFpEF (EF≥50%). Negative binomial regression method was used to evaluate the association between EF status and recurrent all-cause and HF-related admissions. Risk estimates were expressed as incidence ratio ratios (IRR). Results Mean age of the cohort was 73.9±11.1 years, 49% were women, and 46.0% had suffered from previous HF admissions. 472 patients (15.9%) had HFmrEF, 956 (32.3%) had HFrEF, and 1,533 (51.8%) had HFpEF. At a median (interquartile range) follow-up of 2.4 (4.4) years, 1,821 (61.5%) patients died and 6,035 all-cause readmissions were registered in 2,026 patients (68.4%), being 2,163 of them HF-related. Rates of all-cause readmission per 100 patients-years of follow-up were 43.4, 47.1 and 50.1 per HFrEF, HFmrEF and HFpEF categories, respectively. After multivariable adjustment, and compared to patients with HFrEF, HFmrEF status was not associated with a higher risk of all-cause or HF-related recurrent admissions (IRR=1.06; 95% confidence interval (CI), 0.93–1.20; p=0.89), and IRR=1.07; 95% CI, 0.91–1.26; p=0.389, respectively), whereas HFpEF status was associated with a non-significant increase in the risk of all-cause recurrent admissions but a similar risk of HF-related readmissions (IRR=1.10; 95% confidence interval (CI), 0.99–1.22; p=0.06, and IRR=1.01; 95% CI, 0.88–1.16; p=0.900, respectively) Conclusion Following an admission for acute HF, patients with HFmrEF have a similar all-cause and HF-related rehospitalization burden when compared to patients with HFrEF, by means of recurrent events analysis.

scholarly journals Is area deprivation associated with greater impacts of COVID-19 in care homes across England? A preliminary analysis of COVID-19 outbreaks and deaths

2021 ◽  
pp. jech-2020-215039 ◽  
Author(s):  
Anders Malthe Bach-Mortensen ◽  
Michelle Degli Esposti
Keyword(s):  
Negative Binomial ◽  
Care Home ◽  
Negative Binomial Regression ◽  
Population Characteristics ◽  
Care Homes ◽  
Future Research ◽  
Area Deprivation ◽  
Binomial Regression ◽  
Index Of Multiple Deprivation

IntroductionThe COVID-19 pandemic has disproportionately impacted care homes and vulnerable populations, exacerbating existing health inequalities. However, the role of area deprivation in shaping the impacts of COVID-19 in care homes is poorly understood. We examine whether area deprivation is linked to higher rates of COVID-19 outbreaks and deaths among care home residents across upper tier local authorities in England (n=149).MethodsWe constructed a novel dataset from publicly available data. Using negative binomial regression models, we analysed the associations between area deprivation (Income Deprivation Affecting Older People Index (IDAOPI) and Index of Multiple Deprivation (IMD) extent) as the exposure and COVID-19 outbreaks, COVID-19-related deaths and all-cause deaths among care home residents as three separate outcomes—adjusting for population characteristics (size, age composition, ethnicity).ResultsCOVID-19 outbreaks in care homes did not vary by area deprivation. However, COVID-19-related deaths were more common in the most deprived quartiles of IDAOPI (incidence rate ratio (IRR): 1.23, 95% CI 1.04 to 1.47) and IMD extent (IRR: 1.16, 95% CI 1.00 to 1.34), compared with the least deprived quartiles.DiscussionThese findings suggest that area deprivation is a key risk factor in COVID-19 deaths among care home residents. Future research should look to replicate these results when more complete data become available.

scholarly journals Association between fatality rate of COVID-19 and selenium deficiency in China

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hai-Yang Zhang ◽  
An-Ran Zhang ◽  
Qing-Bin Lu ◽  
Xiao-Ai Zhang ◽  
Zhi-Jie Zhang ◽  
...  
Keyword(s):  
Negative Binomial ◽  
Viral Infections ◽  
Case Fatality ◽  
Selenium Deficiency ◽  
Negative Binomial Regression ◽  
Negative Binomial Regression Model ◽  
Fatality Rate ◽  
Selenium Content ◽  
Individual Level ◽  
Binomial Regression

Abstract Background COVID-19 has impacted populations around the world, with the fatality rate varying dramatically across countries. Selenium, as one of the important micronutrients implicated in viral infections, was suggested to play roles. Methods An ecological study was performed to assess the association between the COVID-19 related fatality and the selenium content both from crops and topsoil, in China. Results Totally, 14,045 COVID-19 cases were reported from 147 cities during 8 December 2019–13 December 2020 were included. Based on selenium content in crops, the case fatality rates (CFRs) gradually increased from 1.17% in non-selenium-deficient areas, to 1.28% in moderate-selenium-deficient areas, and further to 3.16% in severe-selenium-deficient areas (P = 0.002). Based on selenium content in topsoil, the CFRs gradually increased from 0.76% in non-selenium-deficient areas, to 1.70% in moderate-selenium-deficient areas, and further to 1.85% in severe-selenium-deficient areas (P < 0.001). The zero-inflated negative binomial regression model showed a significantly higher fatality risk in cities with severe-selenium-deficient selenium content in crops than non-selenium-deficient cities, with incidence rate ratio (IRR) of 3.88 (95% CIs: 1.21–12.52), which was further confirmed by regression fitting the association between CFR of COVID-19 and selenium content in topsoil, with the IRR of 2.38 (95% CIs: 1.14–4.98) for moderate-selenium-deficient cities and 3.06 (1.49–6.27) for severe-selenium-deficient cities. Conclusions Regional selenium deficiency might be related to an increased CFR of COVID-19. Future studies are needed to explore the associations between selenium status and disease outcome at individual-level.

scholarly journals Statistical models for analyzing count data: predictors of length of stay among HIV patients in Portugal using a multilevel model

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ahmed Nabil Shaaban ◽  
Bárbara Peleteiro ◽  
Maria Rosario O. Martins
Keyword(s):  
Length Of Stay ◽  
Regression Model ◽  
Random Effects ◽  
Count Data ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Comprehensive Approach ◽  
Negative Binomial Regression Model ◽  
Hiv Patients ◽  
Binomial Regression

Abstract Background This study offers a comprehensive approach to precisely analyze the complexly distributed length of stay among HIV admissions in Portugal. Objective To provide an illustration of statistical techniques for analysing count data using longitudinal predictors of length of stay among HIV hospitalizations in Portugal. Method Registered discharges in the Portuguese National Health Service (NHS) facilities Between January 2009 and December 2017, a total of 26,505 classified under Major Diagnostic Category (MDC) created for patients with HIV infection, with HIV/AIDS as a main or secondary cause of admission, were used to predict length of stay among HIV hospitalizations in Portugal. Several strategies were applied to select the best count fit model that includes the Poisson regression model, zero-inflated Poisson, the negative binomial regression model, and zero-inflated negative binomial regression model. A random hospital effects term has been incorporated into the negative binomial model to examine the dependence between observations within the same hospital. A multivariable analysis has been performed to assess the effect of covariates on length of stay. Results The median length of stay in our study was 11 days (interquartile range: 6–22). Statistical comparisons among the count models revealed that the random-effects negative binomial models provided the best fit with observed data. Admissions among males or admissions associated with TB infection, pneumocystis, cytomegalovirus, candidiasis, toxoplasmosis, or mycobacterium disease exhibit a highly significant increase in length of stay. Perfect trends were observed in which a higher number of diagnoses or procedures lead to significantly higher length of stay. The random-effects term included in our model and refers to unexplained factors specific to each hospital revealed obvious differences in quality among the hospitals included in our study. Conclusions This study provides a comprehensive approach to address unique problems associated with the prediction of length of stay among HIV patients in Portugal.

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