Coprostanol as a Population Biomarker for SARS-CoV-2 Wastewater Surveillance Studies

Wastewater surveillance is a cost-effective tool for monitoring SARS-CoV-2 transmission in a community. However, challenges remain with regard to interpretating such studies, not least in how to compare SARS-CoV-2 levels between different-sized wastewater treatment plants. Viral faecal indicators, including crAssphage and pepper mild mottle virus, have been proposed as population biomarkers to normalise SARS-CoV-2 levels in wastewater. However, as these indicators exhibit variability between individuals and may not be excreted by everyone, their utility as population biomarkers may be limited. Coprostanol, meanwhile, is a bacterial metabolite of cholesterol which is excreted by all individuals. In this study, composite influent samples were collected from a large- and medium-sized wastewater treatment plant in Dublin, Ireland and SARS-CoV-2 N1, crAssphage, pepper mild mottle virus, HF183 and coprostanol levels were determined. SARS-CoV-2 N1 RNA was detected and quantified in all samples from both treatment plants. Regardless of treatment plant size, coprostanol levels exhibited the lowest variation in composite influent samples, while crAssphage exhibited the greatest variation. Moreover, the strongest correlations were observed between SARS-CoV-2 levels and national and Dublin COVID-19 cases when levels were normalised to coprostanol. This work demonstrates the usefulness of coprostanol as a population biomarker for wastewater surveillance studies.

Lineage replacement and evolution captured by the United Kingdom Covid Infection Survey

The Office for National Statistics COVID-19 Infection Survey is a large household-based surveillance study based in the United Kingdom. Here, we report on the epidemiological and evolutionary dynamics of SARS-CoV-2 determined by analysing sequenced samples collected up until 13th November 2021. We observed four distinct sweeps or partial-sweeps, by lineages B.1.177, B.1.1.7/Alpha, B.1.617.2/Delta, and finally AY.4.2, a sublineage of B.1.617.2, with each sweeping lineage having a distinct growth advantage compared to their predecessors. Evolution was characterised by steady rates of evolution and increasing diversity within lineages, but with step increases in divergence associated with each sweeping major lineage, leading to a faster overall rate of evolution and fluctuating levels of diversity. These observations highlight the value of viral sequencing integrated into community surveillance studies to monitor the viral epidemiology and evolution of SARS-CoV-2, and potentially other pathogens, particularly as routine PCR testing is phased out or in settings where large-scale sequencing is not feasible.

Spatial distribution of anti-rabies post-exposure treatments associated with the decentralization process in Belo Horizonte, 2007 to 2011

Cases of canine attacks on people are reported because of the proximity of the dog to the households in several Brazilian cities. In the present study, we aim to evaluate post-exposure anti-rabies treatments with canine accidents between the years 2007 to 2011 in Belo Horizonte - MG. Duly notified data were obtained from the National System of Notifiable Diseases (SINAN). The spatial characteristics of the cases during the period of the study referred to the neighborhoods and the nine sanitary districts of the municipality of Belo Horizonte - MG. For georeferencing and spatial analysis, we used the software Maporama to identify the coordinates and the Geographic Information System ArcGIS for mapping. Considering the 6.153 prophylactic services that were georeferenced, the Norte, Venda Nova, Leste, and Centro Sul regions were highlighted due to the higher frequency of registered cases. It is suggested that an integrative action focused on canine population control, health education and epidemiological surveillance studies could contribute to the reduction of canine aggression cases.

Distinguishing gene flow between malaria parasite populations

Measuring gene flow between malaria parasite populations in different geographic locations can provide strategic information for malaria control interventions. Multiple important questions pertaining to the design of such studies remain unanswered, limiting efforts to operationalize genomic surveillance tools for routine public health use. This report examines the use of population-level summaries of genetic divergence (FST) and relatedness (identity-by-descent) to distinguish levels of gene flow between malaria populations, focused on field-relevant questions about data size, sampling, and interpretability of observations from genomic surveillance studies. To do this, we use P. falciparum whole genome sequence data and simulated sequence data approximating malaria populations evolving under different current and historical epidemiological conditions. We employ mobile-phone associated mobility data to estimate parasite migration rates over different spatial scales and use this to inform our analysis. This analysis underscores the complementary nature of divergence- and relatedness-based metrics for distinguishing gene flow over different temporal and spatial scales and characterizes the data requirements for using these metrics in different contexts. Our results have implications for the design and implementation of malaria genomic surveillance studies.

Success and Challenges Associated with Large Scale Collaborative Surveillance for Carbapenemase Genes in Gram Negative Bacteria

The emergence and spread of antimicrobial resistance, especially in Gram negative bacteria has led to significant morbidity and increased cost of healthcare. Large surveillance studies such as the one performed by the Antibiotic Resistance Laboratory Network are immensely valuable in understanding the scope of resistance mechanisms especially among carbapenemase producing Gram negative bacteria. However, the routine laboratory detection of carbapenemases in these bacteria remain challenging and require further optimization.

Investigating methods for using genetic data to estimate the association between host factors and being an infection source with application to probing the association between HIV infection and tuberculosis transmission

Identifying host factors that influence infectious disease transmission is an important step toward developing interventions to reduce disease incidence. Recent advances in methods for reconstructing infectious disease transmission events using pathogen genomic and epidemiological data open the door for investigation of host factors that affect onward transmission. While most transmission reconstruction methods are designed to work with densely sampled outbreaks, these methods are making their way into surveillance studies, where the fraction of sampled cases with sequenced pathogens could be relatively low. Surveillance studies that use transmission event reconstruction then use the reconstructed events as response variables (i.e., infection source status of each sampled case) and use host characteristics as predictors (e.g., presence of HIV infection) in regression models. We use simulations to study estimation of the effect of a host factor on probability of being an infection source via this multi-step inferential procedure. Using TransPhylo - a widely-used method for Bayesian estimation of infectious disease transmission events - and logistic regression, we find that low sensitivity of identifying infection sources leads to dilution of the signal, biasing logistic regression coefficients toward zero. We show that increasing the proportion of sampled cases improves sensitivity and estimation of logistic regression coefficients. Application of these approaches to real world data from a population-based TB study in Botswana fails to detect an association between HIV infection and probability of being a TB infection source. We conclude that application of a pipeline, where one first uses TransPhylo and sparsely sampled surveillance data to infer transmission events and then estimates effects of host characteristics on probabilities of these events, should be accompanied by a realistic simulation study to better understand biases stemming from imprecise transmission event inference.

Speculative Fiction, Sociology, and Surveillance Studies: Towards a Methodology of the Surveillance Imaginary

Utopian theorists often speak about the merits of reading utopian fiction in order to reimagine and rebuild a better world, but dystopian fiction is often overlooked. This is, in my view, misguided because dystopian fiction, like utopian fiction, diagnoses issues with the present, inspires activism and resistance, and, in the twenty-first century, often presents ideas of how to effect positive change through collective activism. As speculative literary genres concerned with world-building, utopian and dystopian fiction have inherent sociological concerns. These texts can therefore be utilised by sociologists and other researchers beyond the arts and humanities. Speculative fiction is important to the field of surveillance studies not only because surveillance is a major theme in these literary texts but also because their formal properties provide us with the language, imagery, and feelings associated with being under surveillance. Twenty-first-century utopian and dystopian fiction has not been thoroughly examined by surveillance scholars. Analysis of utopian and dystopian fiction in this field has also focused on texts set in, and written by authors from, the global north. Considering the plethora of dystopian novels in and beyond the global north published in recent years that discuss surveillance, the neglect of the study of these texts to date is an oversight.

Surveillance of avian influenza viruses from 2009 to 2013 in South Korea

Avian influenza viruses (AIVs) are carried by wild migratory waterfowl across migratory flyways. To determine the strains of circulating AIVs that may pose a risk to poultry and humans, regular surveillance studies must be performed. Here, we report the surveillance of circulating AIVs in South Korea during the winter seasons of 2009–2013. A total of 126 AIVs were isolated from 7942 fecal samples from wild migratory birds, with a total isolation rate of 1.59%. H1‒H7 and H9‒H11 hemagglutinin (HA) subtypes, and N1‒N3, N5, and N7‒N9 neuraminidase (NA) subtypes were successfully isolated, with H6 and N2 as the most predominant HA and NA subtypes, respectively. Sequence identity search showed that the HA and NA genes of the isolates were highly similar to those of low-pathogenicity influenza strains from the East Asian-Australasian flyway. No match was found for the HA genes of high-pathogenicity influenza strains. Thus, the AIV strains circulating in wild migratory birds from 2009 to 2013 in South Korea likely had low pathogenicity. Continuous surveillance studies such as this one must be performed to identify potential precursors of influenza viruses that may threaten animal and human health.

In Vitro Susceptibility of Gram-negative Pathogens to Cefiderocol in Five Consecutive Annual Multinational SIDERO-WT Surveillance Studies (2014-2019)

We report in vitro susceptibility data from five consecutive annual SIDERO-WT surveillance studies (2014-2019) for cefiderocol and comparators tested against Gram-negative clinical isolates from North America and Europe. CLSI broth microdilution was used to determine MICs for Enterobacterales ( n =31,896), Pseudomonas aeruginosa ( n =7,700), Acinetobacter baumannii complex ( n =5,225), Stenotrophomonas maltophilia ( n =2,030), and Burkholderia cepacia complex ( n =425). MICs were interpreted by CLSI-approved clinical breakpoints (February 2021). Cefiderocol inhibited 99.8%, 96.7%, 91.6%, and 97.7% of all Enterobacterales , meropenem-nonsusceptible, ceftazidime-avibactam-nonsusceptible, and ceftolozane-tazobactam-nonsusceptible isolates, respectively, at ≤4 μg/ml (susceptible breakpoint). Cefiderocol inhibited 99.9%, 99.8%, 100%, and 99.8% of all P. aeruginosa , meropenem-nonsusceptible, ceftazidime-avibactam-nonsusceptible, and ceftolozane-tazobactam-nonsusceptible isolates, respectively, at ≤4 μg/ml (susceptible breakpoint). Cefiderocol inhibited 96.0% of all A. baumannii complex isolates and 94.2% of meropenem-nonsusceptible isolates at ≤4 μg/ml (susceptible breakpoint), and 98.6% of S. maltophilia isolates at ≤1 μg/ml (susceptible breakpoint). B. cepacia complex isolates tested with a MIC 50 of ≤0.03 μg/ml and MIC 90 of 0.5 μg/ml. Annual cefiderocol percent susceptible rates for Enterobacterales (North America, range 99.6-100%/year; Europe, range 99.3-99.9%/year) and P. aeruginosa (99.8-100%; 99.9-100%) were unchanged from 2014 to 2019. Annual percent susceptible rates for A. baumannii complex demonstrated sporadic, non-directional differences (97.5-100%; 90.4-97.5%); the wider range for Europe (∼7%) was due to isolates from Russia. Annual percent susceptible rates for S. maltophilia showed minor, non-directional differences (96.4-100%; 95.6-100%). We conclude that clinical isolates of Enterobacterales (99.8% susceptible), P. aeruginosa (99.9%), A. baumannii (96.0%), and S. maltophilia (98.6%) collected in North America and Europe from 2014 to 2019 were highly susceptible to cefiderocol.