Lecanemab Unveiled:Exploring Alzheimer’s Treatment Advancements,Assessing Strengths,Limitations,and Its Therapeutic Landscape Position

In the ever-evolving landscape of Alzheimer’s treatment,lecanemab(Leqembi)has emerged as a promising drug.Unlike conventional therapies that merely alleviate symptoms,lecanemab is a humanized monoclonal antibody with a distinct focus.It targets protofibrils,insoluble fibrils,amyloid oligomers,and soluble amyloid-beta protofibrils,which are known to be especially damaging to neurons,with high accuracy.

Using data from‘visible’populations to estimate the size and importance of‘hidden’populations in an epidemic:A modelling technique

We used reported behavioural data from cisgender men who have sex with men and transgender women(MSM/TGW)in Bangalore,mainly collected from‘hot-spot’locations that attract MSM/TGW,to illustrate a technique to deal with potential issues with the representativeness of this sample.A deterministic dynamic model of HIV transmission was developed,incorporating three subgroups of MSM/TGW,grouped according to their reported predominant sexual role(insertive,receptive or versatile).Using mathematical modelling and data triangulation for‘balancing’numbers of partners and role preferences,we compared three different approaches to determine if our technique could be useful for inferring characteristics of a more‘hidden’insertive MSM subpopulation,and explored their potential importance for the HIV epidemic.Projections for 2009 across all three approaches suggest that HIV prevalence among insertive MSM was likely to be less than half that recorded in the surveys(4.5e6.5%versus 13.1%),but that the relative size of this subgroup was over four times larger(61e69%of all MSM/TGW versus 15%).We infer that the insertive MSM accounted for 10e20%of all prevalent HIV infections among urban males aged 15e49.Mathematical modelling can be used with data on‘visible’MSM/TGW to provide insights into the characteristics of‘hidden’MSM.A greater understanding of the sexual behaviour of all MSM/TGW is important for effective HIV programming.More broadly,a hidden subgroup with a lower infectious disease prevalence than more visible subgroups,has the potential to contain more infections,if the hidden subgroup is considerably larger in size.

Tuberculosis infection prevention and control:why we need a whole systems approach

Infection prevention and control(IPC)measures to reduce transmission of drug-resistant and drug-sensitive tuberculosis(TB)in health facilities are well described but poorly implemented.The implementation of TB IPC has been assessed primarily through quantitative and structured approaches that treat administrative,environmental,and personal protective measures as discrete entities.We present an on-going project entitled Umoya omuhle(“good air”),conducted in two provinces of South Africa,that adopts an interdisciplinary,‘whole systems’approach to problem analysis and intervention development for reducing nosocomial transmission of Mycobacterium tuberculosis(Mtb)through improved IPC.We suggest that TB IPC represents a complex intervention that is delivered within a dynamic context shaped by policy guidelines,health facility space,infrastructure,organisation of care,and management culture.Methods drawn from epidemiology,anthropology,and health policy and systems research enable rich contextual analysis of how nosocomial Mtb transmission occurs,as well as opportunities to address the problem holistically.A‘whole systems’approach can identify leverage points within the health facility infrastructure and organisation of care that can inform the design of interventions to reduce the risk of nosocomial Mtb transmission.

Using statistics and mathematical modelling to understand infectious disease outbreaks:COVID-19 as an example

During an infectious disease outbreak,biases in the data and complexities of the underlying dynamics pose significant challenges in mathematically modelling the outbreak and designing policy.Motivated by the ongoing response to COVID-19,we provide a toolkit of statistical and mathematical models beyond the simple SIR-type differential equation models for analysing the early stages of an outbreak and assessing interventions.In particular,we focus on parameter estimation in the presence of known biases in the data,and the effect of non-pharmaceutical interventions in enclosed subpopulations,such as households and care homes.We illustrate these methods by applying them to the COVID-19 pandemic.

One size does not fit all:adapt and localise for effective,proportionate and equitable responses to COVID-19 in Africa

INTRODUCTION The heterogeneous epidemiological picture for COVID-19 in Africa continues to generate debate.Modelling projections raise spec-ulation about the phases and trends of SARS-CoV-2 outbreaks across the continent and how these differ from outbreaks else-where.1-4 Continental efforts drew praise in the first wave of COVID-19,and success has been linked to African experience of epidemics and to decisive leadership.

卫生系统知证政策指导：指导制定的基本原理和挑战

本文是《PLoS Medicine》关于卫生系统知证政策指导三篇系列文章的第一篇,阐述了应如何将证据转化为指导,以形成卫生系统政策,并促进临床和公共卫生干预的实施。其要点如下:①薄弱的卫生系统阻碍了有效干预的实施,加强此系统的政策需要基于当前可得的最佳证据;②卫生系统证据最好以政策制定过程参考的指导的形式呈现,但目前卫生系统指导制定质量较差;③将问题、干预及实施相关的研究转化为影响卫生系统组织方式的决策和政策是卫生系统指导制定面临的一个挑战;④制定及时且适用于广大卫生系统利益相关者的指导,并确定评价卫生系统指导质量的方法是另一个挑战;⑤改编现有方法(如用于临床指南的那些方法)制定有意义的建议来应对卫生系统、政策系统及背景的复杂性,尚需进一步研究。