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Multiple sclerosis is associated with Epstein–Barr virus (EBV) infection, B-cell dysfunction, gut dysbiosis, and environmental and genetic risk factors, including female sex.
Human movement drives spatial transmission patterns of infectious diseases. Population-level mobility patterns are often quantified using aggregated data sets, such as census migration surveys or mobile phone data. These data are often unable to quantify individual-level travel patterns and lack the information needed to discern how mobility varies by demographic groups. Individual-level datasets can capture additional, more precise, aspects of mobility that may impact disease risk or transmission patterns and determine how mobility differs across cohorts; however, these data are rare, particularly in locations such as sub-Saharan Africa.
The intensity of transmission of Aedes-borne viruses is heterogeneous, and multiple factors can contribute to variation at small spatial scales. Illuminating drivers of heterogeneity in prevalence over time and space would provide information for public health authorities. The objective of this study is to detect the spatiotemporal clusters and determine the risk factors of three major Aedes-borne diseases, Chikungunya virus, Dengue virus, and Zika virus clusters in Mexico.
Despite substantial declines since 2000, lower respiratory infections (LRIs), diarrhoeal diseases, and malaria remain among the leading causes of nonfatal and fatal disease burden for children under 5 years of age (under 5), primarily in sub-Saharan Africa.
Pharyngitis, more commonly known as sore throat, is caused by viral and/or bacterial infections. Group A Streptococcus (Strep A) is the most common bacterial cause of pharyngitis. Strep A pharyngitis is an acute, self-limiting disease but if undertreated can lead to suppurative complications, nonsuppurative poststreptococcal immune-mediated diseases, and toxigenic presentations.
Acute poststreptococcal glomerulonephritis (APSGN) is an immune complex-induced glomerulonephritis that develops as a sequela of streptococcal infections. This article provides guidelines for the surveillance of APSGN due to group A Streptococcus (Strep A). The primary objectives of APSGN surveillance are to monitor trends in age- and sex-specific incidence, describe the demographic and clinical characteristics of patients with APSGN, document accompanying risk factors, then monitor trends in frequency of complications, illness duration, hospitalization rates, and mortality.
In malaria epidemiology, interpolation frameworks based on available observations are critical for policy decisions and interpreting disease burden. Updating our understanding of the empirical evidence across different populations, settings, and timeframes is crucial to improving inference for supporting public health.
Contact investigations with drug-susceptible tuberculosis (DS-TB) patients have demonstrated a high prevalence of tuberculosis infection (TBI). However, the prevalence of TBI among individuals in close contact with drug-resistant tuberculosis (DR-TB) patients is poorly understood. This systematic review and meta-analysis aimed to determine the prevalence of TBI among household and non-household contacts of DR-TB patients.
Difficulties in executive functioning (EF) can result in impulsivity, forgetfulness, and inattention. Children living in remote/regional communities are particularly at risk of impairment in these cognitive skills due to reduced educational engagement and poorer access to interventions. This vulnerability has been exacerbated by the COVID-19 pandemic and strategies are needed to mitigate long-term negative impacts on EF.
Individual-based models of infectious disease dynamics commonly use network structures to represent human interactions. Network structures can vary in complexity, from single-layered with homogeneous mixing to multi-layered with clustering and layer-specific contact weights. Here we assessed policy-relevant consequences of network choice by simulating different network structures within an established individual-based model of SARS-CoV-2 dynamics.