The Social Life of Pigs: Changes in Affiliative and Agonistic Behaviors following Mixing

This study investigated potentially affiliative behaviors in grow-finish pigs, how these behaviors changed over time and their relationship to agonistic behaviors. A total of 257 Yorkshire barrows were observed for agonistic (reciprocal fights, attacks) and affiliative (nosing, play, non-agonistic contact) behaviors after mixing (at 10 weeks of age), and weeks 3, 6, and 9 after mix. The least square means of affiliative behaviors were compared across time points. Relationships among affiliative and agonistic behaviors were assessed using generalized linear mixed models. Non-agonistic contact with conspecifics increased until week 6 then remained stable between weeks 6 and 9. Nosing was highest at mix, then decreased in the following weeks. Play was lowest at mix and highest at week 3. Affiliative behaviors were negatively related with aggression at mix (p < 0.001). Pigs who engaged in play and nosing behaviors were more likely to be involved in agonistic interactions in the weeks after mixing (p < 0.05), while pigs engaging in non-agonistic contact were less likely to be involved in agonistic interactions (p < 0.001). There appear to be relationships between affiliative and agonistic behaviors in pigs, with contact being the most predictive of less aggression. Future studies could focus on promoting positive non-agonistic contact in unfamiliar pigs as a way to mitigate aggressive interactions.

Patient-reported outcomes among people living with HIV on single- versus multi-tablet regimens: Data from a real-life setting

Background The use of single-tablet regimens (STRs) in HIV treatment is ubiquitous. However, reintroducing the (generic) components as multi-tablet regimens (MTRs) could be an interesting cost-reducing strategy. It is essential to involve patient-reported outcome measures (PROs) to examine the effects of such an approach. Hence, this study compared PROs of people living with HIV taking an STR versus a MTR in a real world setting. Materials and methods This longitudinal study included 188 people living with HIV. 132 remained on a MTR and 56 switched to an STR. At baseline, months 1-3-6-12-18 and 24, participants filled in questionnaires on health-related quality of life (HRQoL), depressive symptoms, HIV symptoms, neurocognitive complaints (NCC), treatment satisfaction and adherence. Generalized linear mixed models and generalized estimation equations mixed models were built. Results Clinical parameters and PROs of the two groups were comparable at baseline. Neurocognitive complaints and treatment satisfaction did differ over time among the groups. In the STR-group, the odds of having NCC increased monthly by 4,1% as compared to the MTR-group (p = 0.035). Moreover, people taking an STR were more satisfied with their treatment after 6 months: the median change score was high: 24 (IQR 7,5–29). Further, treatment satisfaction showed a contrary evolution in the groups: the estimated state score of the STR-group increased by 3,3 while it decreased by 0,2 in the MTR-group (p = 0.003). No differences over time between the groups were observed with regard to HRQoL, HIV symptoms, depressive symptoms and adherence. Conclusions Neurocognitive complaints were more frequently reported among people on an STR versus MTR. This finding contrasts with the higher treatment satisfaction in the STR-group over time. The long-term effects of both PROs should guide the decision-making on STRs vs. (generic) MTRs.

Household secondary attack rates of SARS-CoV-2 by variant and vaccination status: an updated systematic review and meta-analysis

We previously reported a household secondary attack rate (SAR) for SARS-CoV-2 of 18.9% through June 17, 2021. To examine how emerging variants and increased vaccination have affected transmission rates, we searched PubMed from June 18, 2021, through January 7, 2022. Meta-analyses used generalized linear mixed models to obtain SAR estimates and 95%CI, disaggregated by several covariates. SARs were used to estimate vaccine effectiveness based on the transmission probability for susceptibility (VE_S,p), infectiousness (VE_I,p), and total vaccine effectiveness (VE_T,p). Household SAR for 27 studies with midpoints in 2021 was 35.8% (95%CI, 30.6%-41.3%), compared to 15.7% (95%CI, 13.3%-18.4%) for 62 studies with midpoints through April 2020. Household SARs were 38.0% (95%CI, 36.0%-40.0%), 30.8% (95%CI, 23.5%-39.3%), and 22.5% (95%CI, 18.6%-26.8%) for Alpha, Delta, and Beta, respectively. VE_I,p, VE_S,p, and VE_T,p were 56.6% (95%CI, 28.7%-73.6%), 70.3% (95%CI, 59.3%-78.4%), and 86.8% (95%CI, 76.7%-92.5%) for full vaccination, and 27.5% (95%CI, -6.4%-50.7%), 43.9% (95%CI, 21.8%-59.7%), and 59.9% (95%CI, 34.4%-75.5%) for partial vaccination, respectively. Household contacts exposed to Alpha or Delta are at increased risk of infection compared to the original wild-type strain. Vaccination reduced susceptibility to infection and transmission to others.

Estimation of excess all-cause mortality due to COVID-19 in Thailand

Background: Thailand has recently experienced the most prominent COVID-19 outbreak, resulting in a new record for COVID-19 cases and deaths. To assess the influence of the COVID-19 outbreak on mortality, we aimed to estimate excess mortality in Thailand. Methods: We estimated the baseline number of deaths in the absence of COVID-19 using generalized linear mixed models (GLMMs). The models were adjusted for seasonality and demographics. We evaluated the excess mortality from April to October 2021 in Thailand. Results: We found that the estimated cumulative excess death from April to October 2021 was 14.3% (95% CI: 8.6%-18.8%) higher than the baseline. The results also showed that the excess deaths in males were higher than in females by approximately 26.3%. The excess deaths directly caused by the COVID-19 infections accounted for approximately 75.0% of the all-cause excess deaths. Furthermore, the cumulative COVID-19 cases were found to be correlated with the cumulative excess deaths with a correlation coefficient of 0.9912 (95% CI, 0.9392-0.9987). Conclusions: The recent COVID-19 outbreak in Thailand significantly impacts mortality and affects people for specific ages and sex. During the outbreak in 2021, there was a significant rise in excess fatalities, especially in the older age groups. The increase in mortality was higher in men than in women.

Shift of radiotherapy use during the first wave of the COVID-19 pandemic? An analysis of German inpatient data

Objective To assess the change in inpatient radiotherapy related to COVID-19 lockdown measures during the first wave of the pandemic in 2020. Methods We included cases hospitalized between January 1 and August 31, 2018–2020, with a primary ICD-10 diagnosis of C00–C13, C32 (head and neck cancer, HNC) and C53 (cervical cancer, CC). Data collection was conducted within the Medical Informatics Initiative. Outcomes were fractions and admissions. Controlling for decreasing hospital admissions during holidays, calendar weeks of 2018/2019 were aligned to Easter 2020. A lockdown period (LP; 16/03/2020–02/08/2020) and a return-to-normal period (RNP; 04/05/2020–02/08/2020) were defined. The study sample comprised a control (admission 2018/19) and study cohort (admission 2020). We computed weekly incidence and IR ratios from generalized linear mixed models. Results We included 9365 (CC: 2040, HNC: 7325) inpatient hospital admissions from 14 German university hospitals. For CC, fractions decreased by 19.97% in 2020 compared to 2018/19 in the LP. In the RNP the reduction was 28.57% (p < 0.001 for both periods). LP fractions for HNC increased by 10.38% (RNP: 9.27%; p < 0.001 for both periods). Admissions for CC decreased in both periods (LP: 10.2%, RNP: 22.14%), whereas for HNC, admissions increased (LP: 2.25%, RNP: 1.96%) in 2020. Within LP, for CC, radiotherapy admissions without brachytherapy were reduced by 23.92%, whereas surgery-related admissions increased by 20.48%. For HNC, admissions with radiotherapy increased by 13.84%, while surgery-related admissions decreased by 11.28% in the same period. Conclusion Related to the COVID-19 lockdown in an inpatient setting, radiotherapy for HNC treatment became a more frequently applied modality, while admissions of CC cases decreased.

A Flexible Mixed Model for Clustered Count Data

Clustered count data are commonly modeled using Poisson regression with random effects to account for the correlation induced by clustering. The Poisson mixed model allows for overdispersion via the nature of the within-cluster correlation, however, departures from equi-dispersion may also exist due to the underlying count process mechanism. We study the cross-sectional COM-Poisson regression model—a generalized regression model for count data in light of data dispersion—together with random effects for analysis of clustered count data. We demonstrate model flexibility of the COM-Poisson random intercept model, including choice of the random effect distribution, via simulated and real data examples. We find that COM-Poisson mixed models provide comparable model fit to well-known mixed models for associated special cases of clustered discrete data, and result in improved model fit for data with intermediate levels of over- or underdispersion in the count mechanism. Accordingly, the proposed models are useful for capturing dispersion not consistent with commonly used statistical models, and also serve as a practical diagnostic tool.

Characteristics of Trees Infested by the Invasive Primary Wood-Borer Aromia bungii (Coleoptera: Cerambycidae)

The expanding distribution and tree damage of the invasive, primary wood-borer Aromia bungii (Coleoptera: Cerambycidae), which kills trees of the Rosaceae family, is a problem in intruded areas. However, the tree characteristics associated with infestation by A. bungii, which are useful for early detection or prioritizing preventive measures, are not well examined. We investigated the presence or absence of tree damage (response variable) in pre- and post- surveys along with tree characteristics (four explanatory variables; bark roughness, size, species, and vigor) on monitoring trees in uninvaded sites (survey for the first trees to be damaged) and already invaded sites (survey for the next trees to be damaged). We evaluated the variables using generalized linear mixed models for each site (i.e., a first trees model and a next trees model). Three tree characteristics (bark roughness, size, and vigor) were included as explanatory variables in both best models, indicating that trees with rough surface bark, large in size, and weakened conditions were more susceptible to A. bungii infestation. The reasons for the difference between the two models (species was only chosen in the next trees model) will be considered in our future work.