Global burden of Clostridium difficile infections::a systematic review and meta-analysis

Background: Clostridium difficile is a leading cause of morbidity and mortality in several countries. However, there are limited evidence characterizing its role as a global public health problem. We conducted a systematic review to provide a comprehensive overview of C. difficile infections (CDI) rates.Methods: Seven databases were searched (January 2016) to identify studies and surveillance reports published between 2005 and 2015 reporting CDI incidence rates. CDI incidence rates for health care facility-associated (HCF), hospital onset-health care facility-associated, medical or general intensive care unit (ICU), internal medicine (IM), long-term care facility (LTCF), and community-associated (CA) were extracted and standardized. Meta-analysis was conducted using a random effects model.Results: 229 publications, with data from 41 countries, were included. The overall rate of HCF-CDI was 2.24 (95% confidence interval CI = 1.66- 3.03) per 1000 admissions/y and 3.54 (95%CI = 3.19-3.92) per 10 000 patient- days/y. Estimated rates for CDI with onset in ICU or IM wards were 11.08 (95%CI = 7.19-17.08) and 10.80 (95%CI = 3.15-37.06) per 1000 admission/ y, respectively. Rates for CA-CDI were lower: 0.55 (95%CI = 0.13- 2.37) per 1000 admissions/y. CDI rates were generally higher in North America and among the elderly but similar rates were identified in other regions and age groups.Conclusions: Our review highlights the widespread burden of disease of C. difficile, evidence gaps, and the need for sustainable surveillance of CDI in the health care setting and the community.</p

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance.

Investment in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing in Africa over the past year has led to a major increase in the number of sequences that have been generated and used to track the pandemic on the continent, a number that now exceeds 100,000 genomes. Our results show an increase in the number of African countries that are able to sequence domestically and highlight that local sequencing enables faster turnaround times and more-regular routine surveillance. Despite limitations of low testing proportions, findings from this genomic surveillance study underscore the heterogeneous nature of the pandemic and illuminate the distinct dispersal dynamics of variants of concern-particularly Alpha, Beta, Delta, and Omicron-on the continent. Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve while the continent faces many emerging and reemerging infectious disease threats. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

A theoretical study of the performance improvement in GSM networks due to slow frequency hopping

This paper presents a theoretical method to study the performance improvement in GSM networks due to slow frequency hopping when a limited number of hopping channels are available. By comparing the performance improvement offered by frequency hopping with intra-timeslot handover, new design thresholds and capacity gain figures are derived for GSM networks. The analysis shows that to gain an advantage from frequency hopping it is necessary to deploy more than two hopping channels. Frequency hopping enables the network designer to reduce the C/I protection margin by about 5dB when the channel occupancy is low and by about 3dB when the channel occupancy is high. This reduction in protection margin results in the improvement in spectral efficiency of 82% when channel occupancy is low and 54% when channel occupancy is high. Frequency hopping can be used to improve the network quality where significant improvements can be achieved. The improvement in network quality depends on the channel occupancy

Analysis of traffic distribution in cellular networks

Accurate air interface traffic forecasting and dimensioning is of importance in any cellular network for achieving cost and quality requirements. A previous paper [l] analysed the appropriateness of the Erlang B model to estimate the mean call blocking experienced by cellular traffic using the traditional confidence interval method. This paper presents a modified confidence interval method to compare the mean blocking of the measured data and Erlang B results. In addition to a more complete study of the mean, the blocking distribution is also considered. The Erlang Loss Model (ELM) is studied to completely characterise the distribution of blocking using the ELM. Exact expressions for the busy time distribution are derived for this study. The results presented in this paper indicate that Erlang B formula is an appropriate model for calculating mean call blocking on the air interface. The ELM on the other hand appears to be rather a poor model for the overall blocking distribution. Further study is needed to establish the appropriateness of Erlang B formula as a general tool

Analysis of traffic distribution in cellular networks

Accurate air interface traffic forecasting and dimensioning is of importance in any cellular network for achieving cost and quality requirements. Previous studies of traffic modeling in cellular networks have tended to derive distributions to fit the measured data for the arrival rate and call holding processes or derive expressions for call blocking on the air interface for different handover and channel assignment procedures. In most cases it is assumed that the Erlang B model is not sufficiently accurate and some other call blocking model is required. However, there have not been a large number of studies published on how accurate or otherwise (and under what circumstances) the Erlang B model is in modeling air interface call blocking in practical cellular networks. In this paper call blocking measurements of the air interface of a “real” cellular network are presented. A statistical analysis is undertaken which shows that the measured data is correctly modeled by Erlang B at a level of significance of 0.05 when the number of channels are greater than 12 and the blocking experienced is greater than 1%. For available channels less than 12 and blocking less than 1% the Erlang B model overestimates the blocking