Power-law population heterogeneity governs epidemic waves

We generalize the Susceptible-Infected-Removed (SIR) model for epidemics to take into account generic effects of heterogeneity in the degree of susceptibility to infection in the population. We introduce a single new parameter corresponding to a power-law exponent of the susceptibility distribution at small susceptibilities. We find that for this class of distributions the gamma distribution is the attractor of the dynamics. This allows us to identify generic effects of population heterogeneity in a model as simple as the original SIR model which is contained as a limiting case. Because of this simplicity, numerical solutions can be generated easily and key properties of the epidemic wave can still be obtained exactly. In particular, we present exact expressions for the herd immunity level, the final size of the epidemic, as well as for the shape of the wave and for observables that can be quantified during an epidemic. In strongly heterogeneous populations, the herd immunity level can be much lower than in models with homogeneous populations as commonly used for example to discuss effects of mitigation. Using our model to analyze data for the SARS-CoV-2 epidemic in Germany shows that the reported time course is consistent with several scenarios characterized by different levels of immunity. These scenarios differ in population heterogeneity and in the time course of the infection rate, for example due to mitigation efforts or seasonality. Our analysis reveals that quantifying the effects of mitigation requires knowledge on the degree of heterogeneity in the population. Our work shows that key effects of population heterogeneity can be captured without increasing the complexity of the model. We show that information about population heterogeneity will be key to understand how far an epidemic has progressed and what can be expected for its future course

Why do men have worse COVID-19-related outcomes? A systematic review and meta-analysis with sex adjusted for age

We aimed to study the mechanism behind worse coronavirus disease-19 (COVID-19) outcomes in men and whether the differences between sexes regarding mortality as well as disease severity are influenced by sex hormones. To do so, we used age as a covariate in the meta-regression and subgroup analyses. This was a systematic search and meta-analysis of observational cohorts reporting COVID-19 outcomes. The PubMed (Medline) and Cochrane Library databases were searched. The primary outcome was COVID-19-associated mortality and the secondary outcome was COVID-19 severity. The study was registered at PROSPERO: 42020182924. For mortality, men had a relative risk of 1.36 (95%CI: 1.17 to 1.59; I² 63%, P for heterogeneity <0.01) compared to women. Age was not a significant covariate in meta-analysis heterogeneity (P=0.393) or subgroup analysis. For disease severity, being male was associated with a relative risk of 1.29 (95%CI: 1.19 to 1.40; I² 48%, P for heterogeneity <0.01) compared to the relative risk of women. Again, age did not influence the outcomes of the metaregression (P=0.914) or subgroup analysis. Men had a higher risk of COVID-19 mortality and severity regardless of age, decreasing the odds of hormonal influences in the described outcomes

Using noninvasive metagenomics to characterize viral communities from wildlife

Microbial communities play an important role in organismal and ecosystem health. While high‐throughput metabarcoding has revolutionized the study of bacterial communities, generating comparable viral communities has proven elusive, particularly in wildlife samples where the diversity of viruses and limited quantities of viral nucleic acid present distinctive challenges. Metagenomic sequencing is a promising solution for studying viral communities, but the lack of standardized methods currently precludes comparisons across host taxa or localities. Here, we developed an untargeted shotgun metagenomic sequencing protocol to generate comparable viral communities from noninvasively collected faecal and oropharyngeal swabs. Using samples from common vampire bats (Desmodus rotundus), a key species for virus transmission to humans and domestic animals, we tested how different storage media, nucleic acid extraction procedures and enrichment steps affect viral community detection. Based on finding viral contamination in foetal bovine serum, we recommend storing swabs in RNAlater or another nonbiological medium. We recommend extracting nucleic acid directly from swabs rather than from supernatant or pelleted material, which had undetectable levels of viral RNA. Results from a low‐input RNA library preparation protocol suggest that ribosomal RNA depletion and light DNase treatment reduce host and bacterial nucleic acid, and improve virus detection. Finally, applying our approach to twelve pooled samples from seven localities in Peru, we showed that detected viral communities saturated at the attained sequencing depth, allowing unbiased comparisons of viral community composition. Future studies using the methods outlined here will elucidate the determinants of viral communities across host species, environments and time

Portuguese-Brazilian Evidence-Based Guideline on the Management of Hyperglycemia in Type 2 Diabetes Mellitus

Background: In current management of type 2 diabetes (T2DM), cardiovascular and renal prevention have become important targets to be achieved. In this context, a joint panel of four endocrinology societies from Brazil and Portugal was established to develop an evidence-based guideline for treatment of hyperglycemia in T2DM. Methods: MEDLINE (via PubMed) was searched for randomized clinical trials, meta-analyses, and observational studies related to diabetes treatment. When there was insufficient high-quality evidence, expert opinion was sought. Updated positions on treatment of T2DM patients with heart failure (HF), atherosclerotic CV disease (ASCVD), chronic kidney disease (CKD), and patients with no vascular complications were developed. The degree of recommendation and the level of evidence were determined using predefined criteria. Results and conclusions: In non-pregnant adults, the recommended HbA1c target is below 7%. Higher levels are recommended in frail older adults and patients at higher risk of hypoglycemia. Lifestyle modification is recommended at all phases of treatment. Metformin is the first choice when HbA1c is 6.5-7.5%. When HbA1c is 7.5-9.0%, dual therapy with metformin plus an SGLT2i and/or GLP-1RA (first-line antidiabetic agents, AD1) is recommended due to cardiovascular and renal benefits. If an AD1 is unaffordable, other antidiabetic drugs (AD) may be used. Triple or quadruple therapy should be considered when HbA1c remains above target. In patients with clinical or subclinical atherosclerosis, the combination of one AD1 plus metformin is the recommended first-line therapy to reduce cardiovascular events and improve blood glucose control. In stable heart failure with low ejection fraction ( 30 mL/min/1.73 m2, metformin plus an SGLT-2i is recommended to reduce cardiovascular mortality and heart failure hospitalizations and improve blood glucose control. In patients with diabetes-associated chronic kidney disease (CKD) (eGFR 30-60 mL/min/1.73 m2 or eGFR 30-90 mL/min/1.73 m2 with albuminuria > 30 mg/g), the combination of metformin and an SGLT2i is recommended to attenuate loss of renal function, reduce albuminuria and improve blood glucose control. In patients with severe renal failure, insulin-based therapy is recommended to improve blood glucose control. Alternatively, GLP-1RA, DPP4i, gliclazide MR and pioglitazone may be considered to reduce albuminuria. In conclusion, the current evidence supports individualizing anti-hyperglycemic treatment for T2DM.info:eu-repo/semantics/publishedVersio