Beyond Reassurance: The Reputational Effect of Cultural Reforms in Peace Agreements

We explore whether including cultural reforms in an intra-state peace accord facilitates its success. We distinguish between accommodationist and integrationist cultural provisions and employ a mixed research method combining negative binomial regression on a data set of all intra-state political agreements concluded between 1989 and 2017, and an in-depth analysis of the 1998 Good Friday Agreement for Northern Ireland. We recognize the important reassuring effect of accommodationist cultural reforms in separatist conflicts. However, we also find that they have an important and hitherto overlooked reputational effect across all conflict types. By enhancing the reputation of negotiating leaders, accommodationist cultural provisions contribute to ending violence by preventing leadership challenges, rebel fragmentation and remobilization across all civil conflicts. By the same logic, and despite the overwhelming emphasis of peace agreements on integrationist cultural initiatives, integrationist cultural reforms problematize leaders' ability to commit to pacts and to ensure compliance among their rank and file.

Quality of work community and workers’ intention to retire

Purpose To study the workers’ perception of the quality of work community and its association with intention to retire early, separately among women and men working in Finnish postal service. Methods A questionnaire survey was sent to all Finnish postal services employees aged ≥ 50 years in 2016 and 44% (n = 2096) replied to the survey (mean age 56.3, 40% women). Employee’s intention to retire before statutory retirement was measured on a scale of 1–5 and dichotomized. The quality of work community was defined by four composite variables: equality at work, flexibility at work, supportive work environment and health or other reason and trichotomized by their tercile values. Odds ratio (ORs) and their 95% confidence intervals (CIs) for associations of quality of work community with intention to retire were calculated separately for men and women using log binomial regression models adjusted for potential confounders. Results About one-third of respondents intended to retire early with no significant gender difference in retirement intention. Low equality at work (women OR 2.77, 95% CI 1.60–4.81; men 2.84, 1.80–4.48) and low flexibility at work (women 3.30, 1.94–5.60; men 2.91, 1.88–4.50) was associated with higher likelihood of intention to retire. Among women intention to retire was found less likely due to low supportive work environment (0.52, 0.31–0.89) and among men due to intermediate health or other reason (0.65, 043–0.98). Conclusion The results highlight the importance of the quality of work community as well as the promotion of work-related health in order to encourage employees to remain at workforce for longer.

Characteristics of severely malnourished under-five children immunized with Bacillus Calmette-Guérin following Expanded Programme on Immunization schedule and their outcomes during hospitalization at an urban diarrheal treatment centre, Bangladesh

Background Bacillus Calmette-Guérin (BCG) vaccination has recently been found to have beneficial effects among children infected other than Mycobacterium tuberculosis. Due to the paucity of data on the outcomes of children who had successful BCG vaccination following Expanded Programme on Immunization (EPI) schedule, we aimed to investigate the characteristics of such children and their outcomes who were hospitalized for severe malnutrition. Methods A prospective observational study was conducted to determine the viral etiology of pneumonia in severely malnourished children those were admitted to the Dhaka Hospital of International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b) between April 2015 and December 2017, constituted the study population. Using a case-control design for the analysis, children having BCG vaccination prior hospital admission were treated as cases (n = 611) and those without vaccination, constituted as controls (n = 83). Bi-variate analysis was conducted using socio-demographic, clinical, laboratory, and treatment characteristics on admission and outcomes during hospitalization. Finally, log-linear binomial regression analysis was done to identify independent impact of BCG vaccination. Results The cases more often presented with older age, have had lower proportion of maternal illiteracy, higher rate of breastfeeding, severe wasting and lower rate of hypoglycemia, compared to the controls. The cases were also found to have lower risk of severe sepsis and deaths, compared to the controls (for all, p<0.05). However, in log-linear binomial regression analysis, after adjusting for potential confounders, BCG vaccination following EPI schedule (RR:0.54; 95%CI = 0.33–0.89; p = 0.015) and breastfeeding (RR:0.53; 95%CI = 0.35–0.81; p = 0.003) were found to be protective for the development of severe sepsis. Conclusion BCG vaccination and breastfeeding were found to be protective for the development of severe sepsis in hospitalized severely malnourished under-five children which underscores the importance of continuation of BCG vaccination at birth and breastfeeding up to two years of age.

Association between vaccination status and reported incidence of post-acute COVID-19 symptoms in Israel: a cross-sectional study of patients infected between March 2020 and November 2021

Background: Long COVID is a post-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection syndrome characterised by not recovering for several weeks or months following the acute episode. The effectiveness of COVID-19 vaccines against long-term symptoms of COVID19 is not well understood. We determined whether vaccination was associated with reporting long-term symptoms post-SARS-CoV-2 infection by comparing, among individuals previously infected with SARS-CoV-2, those who were vaccinated to those who were not, in terms of self-reported long-term symptoms. Methods: We invited individuals who were PCR tested for SARS-CoV-2 infection at participating hospitals between March 2020-June 2021 to fill an online questionnaire that included baseline demographics, details of their acute episode and information about symptoms they were currently experiencing. Using binomial regression, we compared vaccinated individuals with those unvaccinated in terms of self-reported symptoms post-acute infection. Results: Of 951 previously infected individuals who filled the survey 637(67%) were vaccinated. The most commonly reported symptoms were; fatigue (22%), headache (20%), weakness (13%), and persistent muscle pain (10%). After adjusting for follow-up time and baseline symptoms, fully vaccinated (2 or more doses) individuals were less likely than unvaccinated individuals to report any of these symptoms by 64%, 54%, 57%, and 68% respectively, (Risk ratios 0.36, 0.46, 0.43, 0.32, p<0.04 in the listed sequence). Conclusions: Vaccination with at least two doses of COVID-19 vaccine was associated with a substantial decrease in reporting the most common post-acute COVID19 symptoms. Our results suggest that, in addition to reducing the risk of acute illness, COVID-19 vaccination may have a protective effect against long COVID.

Marginal modeling in community randomized trials with rare events: Utilization of the negative binomial regression model

Background/aims This work is motivated by the HEALing Communities Study, which is a post-test only cluster randomized trial in which communities are randomized to two different trial arms. The primary interest is in reducing opioid overdose fatalities, which will be collected as a count outcome at the community level. Communities range in size from thousands to over one million residents, and fatalities are expected to be rare. Traditional marginal modeling approaches in the cluster randomized trial literature include the use of generalized estimating equations with an exchangeable correlation structure when utilizing subject-level data, or analogously quasi-likelihood based on an over-dispersed binomial variance when utilizing community-level data. These approaches account for and estimate the intra-cluster correlation coefficient, which should be provided in the results from a cluster randomized trial. Alternatively, the coefficient of variation or R coefficient could be reported. In this article, we show that negative binomial regression can also be utilized when communities are large and events are rare. The objectives of this article are (1) to show that the negative binomial regression approach targets the same marginal regression parameter(s) as an over-dispersed binomial model and to explain why the estimates may differ; (2) to derive formulas relating the negative binomial overdispersion parameter k with the intra-cluster correlation coefficient, coefficient of variation, and R coefficient; and (3) analyze pre-intervention data from the HEALing Communities Study to demonstrate and contrast models and to show how to report the intra-cluster correlation coefficient, coefficient of variation, and R coefficient when utilizing negative binomial regression. Methods Negative binomial and over-dispersed binomial regression modeling are contrasted in terms of model setup, regression parameter estimation, and formulation of the overdispersion parameter. Three specific models are used to illustrate concepts and address the third objective. Results The negative binomial regression approach targets the same marginal regression parameter(s) as an over-dispersed binomial model, although estimates may differ. Practical differences arise in regard to how overdispersion, and hence the intra-cluster correlation coefficient is modeled. The negative binomial overdispersion parameter is approximately equal to the ratio of the intra-cluster correlation coefficient and marginal probability, the square of the coefficient of variation, and the R coefficient minus 1. As a result, estimates corresponding to all four of these different types of overdispersion parameterizations can be reported when utilizing negative binomial regression. Conclusion Negative binomial regression provides a valid, practical, alternative approach to the analysis of count data, and corresponding reporting of overdispersion parameters, from community randomized trials in which communities are large and events are rare.

Déterminants de l’Usage du Transfert d’Argent Mobile par les Utilisateurs d’Internet Mobile au Mali

Le présent papier analyse les principaux déterminants de l’utilisation des services de transfert d’argent mobile par les internautes maliens en situation mobile. Les données collectées auprès de 1739 individus utilisateurs d’Internet mobile de l’étude du groupe de recherche en économie solidaire et industrielle (GRESI) ont été utilisées. Après avoir implémenté le modèle Logit qui est un modèle de régression binomiale, les résultats montrent qu’avoir un niveau d’instruction inférieur au niveau secondaire, avoir un âge compris entre 15-35 ans et la cherté du coût de connexion jouent négativement sur la probabilité d’utiliser le mobile money via Internet mobile au Mali. Tandis que le revenu, la zone de résidence urbaine, les compétences en informatiques et les professions : ouvrier, entrepreneur, commerçant et agriculteur influencent positivement l’utilisation des services de transfert d’argent mobile par le truchement d’Internet mobile. This paper analyses the main determinants of the use of mobile money transfer services by Malian Internet users in a mobile situation. Data collected from 1739 individual mobile Internet users of the study by the solidarity and industrial economy research group (GRESI) were used. After having implemented the Logit model which is a binomial regression model, our results show that having an education level below secondary level, having an age between 15-35 years old and the high cost of connection have a negative impact on the probability of using mobile money via mobile Internet in Mali. While income, urban area of residence, computer skills and occupations: worker, entrepreneur, trader and farmer positively influence the use of mobile money transfer services through the mobile internet.

GEOGRAPHICALLY WEIGHTED NEGATIVE BINOMIAL REGRESSION UNTUK MENANGANI OVERDISPERSI PADA JUMLAH PENDUDUK MISKIN

Poverty is a condition that is often associated with needs, difficulties an deficiencies in various life circumstances. The number of poor people in Indonesia increase in 2020. This research focus on modelling the number of poor people in Indonesia using Geographically Weighted Negative Binomial Regression (GWNBR) method. The number of poor people is count data, so analysis used to model the count data is poisson regression. If there is overdispersion, it can be overcome using negative binomial regression. Meanwhile to see the spatial effect, we can use the Geographically Weighted Negative Binomial Regression method. GWNBR uses a adaptive bisquare kernel for weighting function. GWNBR is better at modelling the number of poor people because it has the smallest AIC value than poisson regression and negative binomial regression. While the GWNBR method obtained 13 groups of province based on significant variables.