Successive waves of COVID-19 transmission have led to exponential increases in new infections globally. In this study, we have applied a decision-making tool to assess the risk of continuing transmission to inform decisions on tailored public health and social measures (PHSM) using data on cases and deaths reported by Member States to the WHO Regional Office for Africa as of 31 December 2020. Transmission classification and health system capacity were used to assess the risk level of each country to guide implementation and adjustments to PHSM. Two countries out of 46 assessed met the criteria for sporadic transmission, one for clusters of cases, and 43 (93.5%) for community transmission (CT) including three with uncontrolled disease incidence (Eswatini, Namibia and South Africa). Health system response's capacities were assessed as adequate in two countries (4.3%), moderate in 13 countries (28.3%) and limited in 31 countries (64.4%). The risk level, calculated as a combination of transmission classification and health system response's capacities, was assessed at level 0 in one country (2.1%), level 1 in two countries (4.3%), level 2 in 11 countries (23.9%) and level 3 in 32 (69.6%) countries. The scale of severity ranged from 0 to 4, with 0 the lowest. CT coupled with limited response capacity resulted in a level 3 risk assessment in most countries. Countries at level 3 should be considered as priority focus for additional assistance, in order to prevent the risk rising to level 4, which may necessitate enforcing hard and costly lockdown measures. The large number of countries at level 3 indicates the need for an effective risk management system to be used as a basis for adjusting PHSM at national and sub-national levels.

The role of the Eurasian badger (Meles meles) as a wildlife host has complicated the management of bovine tuberculosis (bTB) in cattle. Badger ranging behaviour has previously been found to be altered by culling of badgers and has been suggested to increase the transmission of bTB either among badgers or between badgers and cattle. In 2014, a five-year bTB intervention research project in a 100 km2 area in Northern Ireland was initiated involving selective removal of dual path platform (DPP) VetTB (immunoassay) test positive badgers and vaccination followed by release of DPP test negative badgers (‘Test and Vaccinate or Remove’). Home range sizes, based on position data obtained from global positioning system collared badgers, were compared between the first year of the project, where no DPP test positive badgers were removed, and follow-up years 2–4 when DPP test positive badgers were removed. A total of 105 individual badgers were followed over 21 200 collar tracking nights. Using multivariable analyses, neither annual nor monthly home ranges differed significantly in size between years, suggesting they were not significantly altered by the bTB intervention that was applied in the study area.

Varicella poses an occupational risk and a nosocomial risk for susceptible healthcare personnel and patients, respectively. Patients with varicella are thought to be infectious from 1 to 2 days before rash onset until all lesions are crusted, typically 4–7 days after onset of rash. We searched Medline, Embase, Cochrane Library and CINAHL databases to assess evidence of varicella-zoster virus (VZV) transmission before varicella rash onset. Few articles (7) contributed epidemiologic evidence; no formal studies were found. Published articles reported infectiousness at variable intervals before rash onset, between <1 day to 4 days prior to rash, with 1–2 patients for each interval. Laboratory assessment of transmission before rash was also limited (10 articles). No culture-positive results were reported. VZV DNA was identified by PCR before rash onset in only one study however, PCR does not indicate infectivity of the virus. Based on available medical literature, VZV transmission before rash onset seems unlikely, although the possibility of pre-rash, respiratory transmission cannot be entirely ruled out.

We explore the concept of parameter design applied to the production of glass beads in the manufacture of metal-encapsulated transistors. The main motivation is to complete the analysis hinted at in the original publication by Jim Morrison in 1957, which was an early example of discussing the idea of transmitted variation in engineering design, and an influential paper in the development of analytic parameter design as a data-centric engineering activity. Parameter design is a secondary design activity focused on selecting the nominals of the design variables to achieve the required target performance and to simultaneously reduce the variance around the target. Although the 1957 paper is not recent, its approach to engineering design is modern.

In August 2017, a cluster of four persons infected with genetically related strains of Shiga toxin-producing Escherichia coli (STEC) O157:H7 was identified. These strains possessed the Shiga toxin (stx) subtype stx2a, a toxin type known to be associated with severe clinical outcome. One person died after developing haemolytic uraemic syndrome. Interviews with cases revealed that three of the cases had been exposed to dogs fed on a raw meat-based diet (RMBD), specifically tripe. In two cases, the tripe had been purchased from the same supplier. Sampling and microbiological screening of raw pet food was undertaken and indicated the presence of STEC in the products. STEC was isolated from one sample of raw tripe but was different from the strain causing illness in humans. Nevertheless, the detection of STEC in the tripe provided evidence that raw pet food was a potential source of human STEC infection during this outbreak. This adds to the evidence of raw pet food as a risk factor for zoonotic transmission of gastrointestinal pathogens, which is widely accepted for Salmonella, Listeria and Campylobacter spp. Feeding RMBD to companion animals has recently increased in popularity due to the belief that they provide health benefits to animals. Although still rare, an increase in STEC cases reporting exposure to RMBDs was detected in 2017. There has also been an increased frequency of raw pet food incidents in 2017, suggesting an increasing trend in potential risk to humans from raw pet food. Recommendations to reduce the risk of infection included improved awareness of risk and promotion of good hygiene practices among the public when handling raw pet food.

Thematic analysis of personal networks involves identifying regularities in network structure and content, and grouping networks into types/clusters, to allow for a holistic understanding of social complexities. We propose an inductive approach to network thematic analysis, applying the learnings from qualitative coding, fused mixed-methods analysis, and typology development. It involves framing (changing focus by magnifying, aggregating, and graphical configuration), pattern detection (identification of underlying dimensions, sorting, and clustering), labeling, and triangulating (confirmation and fine-tuning using quantitative and qualitative approaches); applied repeatedly and emergently. We describe this approach utilized in two cases of studying support networks of caregivers.

During the coronavirus disease 2019 (COVID-19) pandemic, many countries opted for strict public health measures, including closing schools. After some time, they have started relaxing some of those restrictions. To avoid overwhelming health systems, predictions for the number of new COVID-19 cases need to be considered when choosing a school reopening strategy. Using a computer simulation based on a stochastic compartmental model that includes a heterogeneous and dynamic network, we analyse different strategies to reopen schools in the São Paulo Metropolitan Area, including one similar to the official reopening plan. Our model allows us to describe different types of relations between people, each type with a different infectiousness. Based on our simulations and model assumptions, our results indicate that reopening schools with all students at once has a big impact on the number of new COVID-19 cases, which could cause a collapse of the health system. On the other hand, our results also show that a controlled school reopening could possibly avoid the collapse of the health system, depending on how people follow sanitary measures. We estimate that postponing the schools' return date for after a vaccine becomes available may save tens of thousands of lives just in the São Paulo Metropolitan Area compared to a controlled reopening considering a worst-case scenario. We also discuss our model constraints and the uncertainty of its parameters.

The notion of the capacity of a polynomial was introduced by Gurvits around 2005, originally to give drastically simplified proofs of the van der Waerden lower bound for permanents of doubly stochastic matrices and Schrijver’s inequality for perfect matchings of regular bipartite graphs. Since this seminal work, the notion of capacity has been utilised to bound various combinatorial quantities and to give polynomial-time algorithms to approximate such quantities (e.g. the number of bases of a matroid). These types of results are often proven by giving bounds on how much a particular differential operator can change the capacity of a given polynomial. In this paper, we unify the theory surrounding such capacity-preserving operators by giving tight capacity preservation bounds for all nondegenerate real stability preservers. We then use this theory to give a new proof of a recent result of Csikvári, which settled Friedland’s lower matching conjecture.

In this paper, we consider multi-state coherent systems that can be regarded as a series/parallel/recurrent connection of multi-state modules with binary/multi-state components. The multi-state (survival) signatures of such systems are presented in terms of multi-state (survival) signatures of related modules based on the structures. For a recurrent structure, the multi-state survival signature of the structure is also needed. The results established here are finally illustrated with a number of examples.

Student's t test is valid for statistical inference under the normality assumption or asymptotically. By contrast, although the bootstrap t test was proposed in 1993, it is seldom adopted in medical research. We aim to demonstrate that the bootstrap t test outperforms Student's t test under normality in data. Using random data samples from normal distributions, we evaluated the testing performance, in terms of true-positive rate (TPR) and false-positive rate and diagnostic abilities, in terms of the area under the curve (AUC), of the bootstrap t test and Student's t test. We explore the AUC of both tests with varying sample size and coefficient of variation. We compare the testing outcomes using the COVID-19 serial interval (SI) data in Shenzhen and Hong Kong, China, for demonstration. With fixed TPR, the bootstrap t test maintained the equivalent accuracy in TPR, but significantly improved the true-negative rate from the Student's t test. With varying TPR, the diagnostic ability of bootstrap t test outperformed or equivalently performed as Student's t test in terms of the AUC. The equivalent performances are possible but rarely occur in practice. We find that the bootstrap t test outperforms by successfully detecting the difference in COVID-19 SI, which is defined as the time interval between consecutive transmission generations, due to sex and non-pharmaceutical interventions against the Student's t test. We demonstrated that the bootstrap t test outperforms Student's t test, and it is recommended to replace Student's t test in medical data analysis regardless of sample size.

The outbreak of pneumonia-like respiratory disorder at China and its rapid transmission world-wide resulted in public health emergency, which brought lineage B betacoronaviridae SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) into spotlight. The fairly high mutation rate, frequent recombination and interspecies transmission in betacoronaviridae are largely responsible for their temporal changes in infectivity and virulence. Investigation of global SARS-CoV-2 genotypes revealed considerable mutations in structural, non-structural, accessory proteins as well as untranslated regions. Among the various types of mutations, single-nucleotide substitutions are the predominant ones. In addition, insertion, deletion and frame-shift mutations are also reported, albeit at a lower frequency. Among the structural proteins, spike glycoprotein and nucleocapsid phosphoprotein accumulated a larger number of mutations whereas envelope and membrane proteins are mostly conserved. Spike protein and RNA-dependent RNA polymerase variants, D614G and P323L in combination became dominant world-wide. Divergent genetic variants created serious challenge towards the development of therapeutics and vaccines. This review will consolidate mutations in different SARS-CoV-2 proteins and their implications on viral fitness.

This paper derives the limit distribution of the rescaled sum of the absolute value of an integrated process with continuously distributed innovations raised to a negative power less than $-$1, and of the analogous statistic that is obtained using the same function of an integrated process but only considering positive values of the integrated process. We show that the limit behavior of this statistic is determined by the values of the integrated process that are closest to 0, and find the limit behavior of the values of the integrated process that are closest to 0.

Extending a result by Alon, Linial, and Meshulam to abelian groups, we prove that if G is a finite abelian group of exponent m and S is a sequence of elements of G such that any subsequence of S consisting of at least $$|S| - m\ln |G|$$ elements generates G, then S is an additive basis of G . We also prove that the additive span of any l generating sets of G contains a coset of a subgroup of size at least $$|G{|^{1 - c{ \in ^l}}}$$ for certain c=c(m) and $$ \in=\in (m) < 1$$; we use the probabilistic method to give sharper values of c(m) and $$ \in (m)$$ in the case when G is a vector space; and we give new proofs of related known results.

Susceptible S-Infected I-Recovered R-Death D (SIRD) compartmental models are often used for modelling of infectious diseases. On the basis of the analogy between SIRD and compartmental models in hydrology, this study makes mathematical formulations developed in hydrology available for modelling in epidemiology. We adapt the Hayami model solution of the diffusive wave equation generally used in hydrological modelling to compartmental I–R–D models in epidemiology by simulating the relationships between the number of infectious I(t), the number of recoveries R(t) and the number of deaths D(t). The Hayami model is easy-to-use, robust and parsimonious. We compare the empirical one-parameter exponential model usually used in SIRD models to the two-parameter Hayami model. Applications were implemented on the recent Covid-19 pandemic. The application on data from 24 countries shows that both models give comparable performances for modelling the I–D relationship. However, for modelling the I–R relationship and the active cases, the exponential model gives fair performances whereas the Hayami model substantially improves the model performances. The Hayami model also presents the advantage that its parameters can be easily estimated from the analysis of the data distributions of I(t), R(t) and D(t). The Hayami model is parsimonious with only two parameters which are useful to compare the temporal evolution of recoveries and deaths in different countries based on different contamination rates and recoveries strategies. This study highlights the interest of knowledge transfer between different scientific disciplines in order to model different processes.

Since 2015, the incidence of invasive meningococcal disease (IMD) caused by serogroup W (MenW) has increased in Sweden, due to the introduction of the 2013 strain belonging to clonal complex 11. The aim of this study was to describe the clinical presentation of MenW infections, in particular the 2013 strain, including genetic associations. Medical records of confirmed MenW IMD cases in Sweden during the years 1995–2019 (n = 113) were retrospectively reviewed and the clinical data analysed according to strain. Of all MenW patients, bacteraemia without the focus of infection was seen in 44%, bacteraemic pneumonia in 26%, meningitis in 13% and epiglottitis in 8%, gastrointestinal symptoms in 48% and 4% presented with petechiae. Phylogenetic analysis was used for possible links between genetic relationship and clinical picture. The 2013 strain infections, particularly in one cluster, were associated with more severe disease compared with other MenW infections. The patients with 2013 strain infections (n = 68) were older (52 years vs. 25 years for other strains), presented more often with diarrhoea as an atypical presentation (P = 0.045) and were more frequently admitted for intensive care (P = 0.032). There is a risk that the atypical clinical presentation of MenW infections, with predominantly gastrointestinal or respiratory symptoms rather than neck stiffness or petechiae, may lead to delay in life-saving treatment.

Systemic risk (SR) is considered as the risk of collapse of an entire system, which has played a significant role in explaining the recent financial turmoils from the insurance and financial industries. We consider the asymptotic behavior of the SR for portfolio losses in the model allowing for heavy-tailed primary losses, which are equipped with a wide type of dependence structure. This risk model provides an ideal framework for addressing both heavy-tailedness and dependence. As some extensions, several simulation experiments are conducted, where an insurance application of the asymptotic characterization to the determination and approximation of related SR capital has been proposed, based on the SR measure.