Evaluation of diagnostic test procedures for SARS-CoV-2 using latent class models.

Polymerase chain reaction (PCR) and antigen tests have been used extensively for screening during the severe acute respiratory syndrome coronavirus 2 pandemics. However, the real-world sensitivity and specificity of the two testing procedures in the field have not yet been estimated without assuming that the PCR constitutes a gold standard test. We use latent class models to estimate the in situ performance of both tests using data from the Danish national registries. We find that the specificity of both tests is very high (>99.7%), while the sensitivities are 95.7% (95% confidence interval [CI]: 92.8%-98.4%) and 53.8% (95% CI: 49.8%-57.9%) for the PCR and antigen tests, respectively. These findings have implications for the use of confirmatory PCR tests following a positive antigen test result: we estimate that serial testing is counterproductive at higher prevalence levels.

Introduction and transmission of SARS-CoV-2 lineage B.1.1.7, Alpha variant, in Denmark.

BACKGROUND: In early 2021, the SARS-CoV-2 lineage B.1.1.7 (Alpha variant) became dominant across large parts of the world. In Denmark, comprehensive and real-time test, contact-tracing, and sequencing efforts were applied to sustain epidemic control. Here, we use these data to investigate the transmissibility, introduction, and onward transmission of B.1.1.7 in Denmark. METHODS: We analyzed a comprehensive set of 60,178 SARS-CoV-2 genomes generated from high-throughput sequencing by the Danish COVID-19 Genome Consortium, representing 34% of all positive cases in the period 14 November 2020 to 7 February 2021. We calculated the transmissibility of B.1.1.7 relative to other lineages using Poisson regression. Including all 1976 high-quality B.1.1.7 genomes collected in the study period, we constructed a time-scaled phylogeny, which was coupled with detailed travel history and register data to outline the introduction and onward transmission of B.1.1.7 in Denmark. RESULTS: In a period with unchanged restrictions, we estimated an increased B.1.1.7 transmissibility of 58% (95% CI: [56%, 60%]) relative to other lineages. Epidemiological and phylogenetic analyses revealed that 37% of B.1.1.7 cases were related to the initial introduction in November 2020. The relative number of cases directly linked to introductions varied between 10 and 50% throughout the study period. CONCLUSIONS: Our findings corroborate early estimates of increased transmissibility of B.1.1.7. Both substantial early expansion when B.1.1.7 was still unmonitored and continuous foreign introductions contributed considerably to case numbers. Finally, our study highlights the benefit of balanced travel restrictions and self-isolation procedures coupled with comprehensive surveillance efforts, to sustain epidemic control in the face of emerging variants.

Simulating the Epidemiological and Economic Impact of Paratuberculosis Control Actions in Dairy Cattle.

We describe a new mechanistic bioeconomic model for simulating the spread of Mycobacterium avium subsp. paratuberculosis (MAP) within a dairy cattle herd. The model includes age-dependent susceptibility for infection; age-dependent sensitivity for detection; environmental MAP build up in five separate areas of the farm; in utero infection; infection via colostrum and waste milk, and it allows for realistic culling (i.e., due to other diseases) by including a ranking system. We calibrated the model using a unique dataset from Denmark, including 102 random farms with no control actions against spread of MAP. Likewise, four control actions recommended in the Danish MAP control program were implemented in the model based on reported management strategies in Danish dairy herds in a MAP control scheme. We tested the model parameterization in a sensitivity analysis. We show that a test-and-cull strategy is on average the most cost-effective solution to decrease the prevalence and increase the total net revenue on a farm with low hygiene, but not more profitable than no control strategy on a farm with average hygiene. Although it is possible to eradicate MAP from the farm by implementing all four control actions from the Danish MAP control program, it was not economically attractive since the expenses for the control actions outweigh the benefits. Furthermore, the three most popular control actions against the spread of MAP on the farm were found to be costly and inefficient in lowering the prevalence when used independently.

A comparison between two simulation models for spread of foot-and-mouth disease.

Two widely used simulation models of foot-and-mouth disease (FMD) were used in order to compare the models' predictions in term of disease spread, consequence, and the ranking of the applied control strategies, and to discuss the effect of the way disease spread is modeled on the predicted outcomes of each model. The DTU-DADS (version 0.100), and ISP (version 2.001.11) were used to simulate a hypothetical spread of FMD in Denmark. Actual herd type, movements, and location data in the period 1st October 2006 and 30th September 2007 was used. The models simulated the spread of FMD using 3 different control scenarios: 1) A basic scenario representing EU and Danish control strategies, 2) pre-emptive depopulation of susceptible herds within a 500 meters radius around the detected herds, and 3) suppressive vaccination of susceptible herds within a 1,000 meters radius around the detected herds. Depopulation and vaccination started 14 days following the detection of the first infected herd. Five thousand index herds were selected randomly, of which there were 1,000 cattle herds located in high density cattle areas and 1,000 in low density cattle areas, 1,000 swine herds located in high density swine areas and 1,000 in low density swine areas, and 1,000 sheep herds. Generally, DTU-DADS predicted larger, longer duration and costlier epidemics than ISP, except when epidemics started in cattle herds located in high density cattle areas. ISP supported suppressive vaccination rather than pre-emptive depopulation, while DTU-DADS was indifferent to the alternative control strategies. Nonetheless, the absolute differences between control strategies were small making the choice of control strategy during an outbreak to be most likely based on practical reasons.

The range of attraction for light traps catching Culicoides biting midges (Diptera: Ceratopogonidae).

BACKGROUND: Culicoides are vectors of e.g. bluetongue virus and Schmallenberg virus in northern Europe. Light trapping is an important tool for detecting the presence and quantifying the abundance of vectors in the field. Until now, few studies have investigated the range of attraction of light traps. METHODS: Here we test a previously described mathematical model (Model I) and two novel models for the attraction of vectors to light traps (Model II and III). In Model I, Culicoides fly to the nearest trap from within a fixed range of attraction. In Model II Culicoides fly towards areas with greater light intensity, and in Model III Culicoides evaluate light sources in the field of view and fly towards the strongest. Model II and III incorporated the directionally dependent light field created around light traps with fluorescent light tubes. All three models were fitted to light trap collections obtained from two novel experimental setups in the field where traps were placed in different configurations. RESULTS: Results showed that overlapping ranges of attraction of neighboring traps extended the shared range of attraction. Model I did not fit data from any of the experimental setups. Model II could only fit data from one of the setups, while Model III fitted data from both experimental setups. CONCLUSIONS: The model with the best fit, Model III, indicates that Culicoides continuously evaluate the light source direction and intensity. The maximum range of attraction of a single 4W CDC light trap was estimated to be approximately 15.25 meters. The attraction towards light traps is different from the attraction to host animals and thus light trap catches may not represent the vector species and numbers attracted to hosts.

Simulating spread of Bluetongue Virus by flying vectors between hosts on pasture.

Bluetongue is a disease of ruminants which reached Denmark in 2007. We present a process-based stochastic simulation model of vector-borne diseases, where host animals are not confined to a central geographic farm coordinate, but can be distributed onto pasture areas. Furthermore vectors fly freely and display search behavior to locate areas with hosts. We also include wind spread of vectors, host movements, and vector seasonality. Results show that temperature and seasonality of vectors determines the period in which an incursion of Bluetongue may lead to epidemic spread in Denmark. Within this period of risk the number of infected hosts is affected by temperature, vector abundance, vector behavior, vectors' ability to locate hosts, and use of pasture. These results indicate that restricted grazing during outbreaks can reduce the number of infected hosts and the size of the affected area. The model can be implemented on other vector-borne diseases of grazing animals.

Development of antibiotic resistance and up-regulation of the antimutator gene pfpI in mutator Pseudomonas aeruginosa due to inactivation of two DNA oxidative repair genes (mutY, mutM).

Prevention and correction of oxidative DNA lesions in Pseudomonas aeruginosa is ensured by the DNA oxidative repair system (GO). Single inactivation of mutT, mutY and mutM involved in GO led to elevated mutation rates (MRs) that correlated to increased development of resistance to antibiotics. In this study, we constructed a double mutant in mutY and mutM (PAOMY-Mgm) and characterized the phenotype and the gene expression profile using microarray and RT-PCR. PAOMY-Mgm presented 28-fold increases in MR compared with wild-type reference strain PAO1. In comparison, the PAOMYgm (mutY) single mutant showed only a fivefold increase, whereas the single mutant PAOMMgm (mutM) showed a nonsignificant increase in MR compared with PAO1 and the single mutants. Mutations in the regulator nfxB leading to hyperexpression of MexCD-OprJ efflux pump were found as the mechanism of resistance to ciprofloxacin in the double mutant. A better fitness of the mutator compared with PAO1 was found in growth competition experiments in the presence of ciprofloxacin at concentrations just below minimal inhibitory concentration. Up-regulation of the antimutator gene pfpI, that has been shown to provide protection to oxidative stress, was found in PAOMY-Mgm compared with PAO1. In conclusion, we showed that MutY and MutM are cooperating in the GO of P. aeruginosa, and that oxidative DNA lesions might represent an oxidative stress for the bacteria.

Geographic distribution of autism in California: a retrospective birth cohort analysis.

Prenatal environmental exposures are among the risk factors being explored for associations with autism. We applied a new procedure combining multiple scan cluster detection tests to identify geographically defined areas of increased autism incidence. This procedure can serve as a first hypothesis-generating step aimed at localized environmental exposures, but would not be useful for assessing widely distributed exposures, such as household products, nor for exposures from nonpoint sources, such as traffic. Geocoded mothers' residences on 2,453,717 California birth records, 1996-2000, were analyzed including 9,900 autism cases recorded in the California Department of Developmental Services (DDS) database through February 2006 which were matched to their corresponding birth records. We analyzed each of the 21 DDS Regional Center (RC) catchment areas separately because of the wide variation in diagnostic practices. Ten clusters of increased autism risk were identified in eight RC regions, and one Potential Cluster in each of two other RC regions.After determination of clusters, multiple mixed Poisson regression models were fit to assess differences in known demographic autism risk factors between the births within and outside areas of elevated autism incidence, independent of case status.Adjusted for other covariates, the majority of areas of autism clustering were characterized by high parental education, e.g. relative risks >4 for college-graduate vs. nonhigh-school graduate parents. This geographic association possibly occurs because RCs do not actively conduct case finding and parents with lower education are, for various reasons, less likely to successfully seek services.

The effect of pH and storage on copper speciation and bacterial growth in complex growth media.

In this paper we examine how the bacterial growth is influenced by the availability of copper ions in complex Mueller Hinton growth media. The data shows that the free copper concentration is seven to eight orders of magnitude lower the total copper concentration and that there seems to be a better correlation between the free copper concentration and bacterial growth, than for the total copper concentration and growth. Furthermore, it is shown that the initial pH influences the amount of free copper ions in the media and that this has a direct effect on the ability of bacterial cultures to grow. However, there still remains an effect of pH on bacterial growth which cannot be attributed to the influence of the Cu(2+) concentration alone. The study also shows that the sterilization treatment can have some effect on the availability of copper ions in the media over time. Freshly autoclaved and sterile filtered media contain the same level of free copper ions and perform equally well in the biological assay. However, storage in the refrigerator influences the free copper contents in media, which have been autoclaved, but not in media, which were sterile filtered. Therefore, the latter method is to be recommended, when working with bacterial copper testing.

A procedure to characterize geographic distributions of rare disorders in cohorts.

BACKGROUND: Individual point data can be analyzed against an entire cohort instead of only sampled controls to accurately picture the geographic distribution of populations at risk for low prevalence diseases. Analyzed as individual points, many smaller clusters with high relative risks (RR) and low empirical p values are indistinguishable from a random distribution. When points are aggregated into areal units, small clusters may result in a larger cluster with a low RR or be lost if divided into pieces included in units of larger populations that show no increased prevalence. Previous simulation studies showed lowered validity of spatial scan tests for true clusters with low RR. Using simulations, this study explored the effects of low cluster RR and areal unit size on local area clustering test (LACT) results, proposing a procedure to improve accuracy of cohort spatial analysis for rare events. RESULTS: Our simulations demonstrated the relationship of true RR to observed RR and p values with various, randomly located, cluster shapes, areal unit sizes and scanning window shapes in a diverse population distribution. Clusters with RR < 1.7 had elevated observed RRs and high p values. We propose a cluster identification procedure that applies parallel multiple LACTs, one on point data and three on two distinct sets of areal units created with varying population parameters that minimize the range of population sizes among units. By accepting only clusters identified by all LACTs, having a minimum population size, a minimum relative risk and a maximum p value, this procedure improves the specificity achieved by any one of these tests alone on a cohort study of low prevalence data while retaining sensitivity for small clusters. The procedure is demonstrated on two study regions, each with a five-year cohort of births and cases of a rare developmental disorder. CONCLUSION: For truly exploratory research on a rare disorder, false positive clusters can cause costly diverted research efforts. By limiting false positives, this procedure identifies 'crude' clusters that can then be analyzed for known demographic risk factors to focus exploration for geographically-based environmental exposure on areas of otherwise unexplained raised incidence.

Potential impact of an introduction of foot-and-mouth disease into the California State Fair.

OBJECTIVE: To estimate the potential spread of foot-and-mouth disease (FMD) if infected livestock had been exhibited at the 2005 California State Fair. DESIGN: Epidemic model. ANIMALS: Dairy cattle, dairy goats, and pygmy goats exhibited between August 24 and August 28 by 195 exhibitors. PROCEDURES: 2 stochastic models were used to simulate epidemics of FMD that might originate from 1, 3, 5, 7, or 10 index cases at the state fair. Data obtained from state fair exhibitors were used to determine the spatial distribution and types of herds to which livestock visiting the state fair returned. RESULTS: Mean estimated numbers of latently infected animals on day 5 were 12.3 and 75.9, respectively, when it was assumed that there were 1 and 10 index cases. Regardless of the number of index cases, mean estimated numbers of subclinically infected and clinically infected animals were low throughout the 5-day study period. Mean estimated duration of the resulting epidemic ranged from 111 to 155 days, mean number of infected premises ranged from 33 to 244, and mean probability that at least 1 animal that became infected with FMD would subsequently leave the state ranged from 28% to 96% as the number of index cases increased from 1 to 10, respectively. CONCLUSIONS AND CLINICAL RELEVANCE: Results suggested that following introduction of FMD at the California State Fair, infection would likely go undetected until after animals left the fair and that the subsequent outbreak would spread rapidly.