A 2-month field cohort study of SARS-CoV-2 in saliva of BNT162b2 vaccinated nursing home workers

Tracing the origins of Plasmodium vivax resurgence after malaria elimination on Aneityum Island in Vanuatu

BACKGROUND

Five years after successful malaria elimination, Aneityum Island in Vanuatu experienced an outbreak of Plasmodium vivax of unknown origin in 2002. Epidemiological investigations revealed several potential sources of P. vivax. We aimed to identify the genetic origin of P. vivax responsible for the resurgence.

METHODS

Five P. vivax microsatellite markers were genotyped using DNA extracted from archived blood samples. A total of 69 samples from four P. vivax populations was included: 29 from the outbreak in 2002, seven from Aneityum in 1999 and 2000, 18 from visitors to Aneityum in 2000, and 15 from nearby Tanna Island in 2002. A neighbour-joining phylogenetic tree was constructed to elucidate the relationships among P. vivax isolates. STRUCTURE and principal component analysis were used to assess patterns of genetic structure.

RESULTS

Here we show distinct genetic origins of P. vivax during the outbreak on Aneityum. While the origin of most P. vivax lineages found during the outbreak remains unidentified, limited genetic diversity among these lineages is consistent with a rapid expansion from a recent common ancestor. Contemporaneous P. vivax from neighboring Tanna and potential relapse of P. vivax acquired from other islands in 1999 and 2000 are also identified as minor contributors to the outbreak.

CONCLUSIONS

Multiple reintroductions of P. vivax after elimination highlight the high receptivity and vulnerability to malaria resurgence in island settings of Vanuatu, despite robust surveillance and high community compliance to control measures.

Where do those data go? Reuse of screening results from clinical trials to estimate population prevalence of HBV infection in adults in Kilifi, Kenya

Chronic hepatitis B infection (CHB) is a significant problem worldwide with around 300 million people infected. Ambitious goals have been set towards its elimination as a public health threat by 2030. However, accurate seroprevalence estimates in many countries are lacking or fail to provide representative population estimates, particularly in the WHO African Region (AFRO). This means the full extent of HBV infection is not well described, leading to a lack of investment in diagnostics, treatment and disease prevention. Clinical trials in the WHO AFRO region have been increasing over time and many test for infectious diseases including hepatitis B virus (HBV) to determine baseline eligibility for participants, however these screening data are not reported. Here we review data from six clinical trials completed at the KEMRI-Wellcome Trust Research Programme between 2016 and 2023 that screened for HBV using hepatitis B surface antigen (HBsAg) as part of the trial exclusion criteria. 1727 people had HBsAg results available, of which 60 tested positive. We generated a crude period HBV prevalence estimate of 3.5% (95% CI 2.6-4.5%), and after standardisation for sex and age to account for the population structure of the Kilifi Health Demographics Surveillance System (KHDSS), the prevalence estimate increased to 5.0% (95% CI 3.4-6.6%). The underrepresentation of women in these trials was striking with 1263/1641 (77%) of participants being male. Alanine aminotransferase (ALT) was significantly higher in the HBsAg positive group but was not outside the normal range. We argue that routine collation and publishing of data from clinical trials could increase precision and geographical representation of global HBV prevalence estimates, enabling evidence-based provision of clinical care pathways and public health interventions to support progress towards global elimination targets. We do acknowledge when using clinical trials data for seroprevalence estimates, that local population structure data is necessary to allow standardisation of results, and the point of care tests used here are limited in sensitivity and specificity.

Accelerating pharmaceutical R&D with a user-friendly AI system for histopathology image analysis

A system for analysis of histopathology data within a pharmaceutical R&D environment has been developed with the intention of enabling interdisciplinary collaboration. State-of-the-art AI tools have been deployed as easy-to-use self-service modules within an open-source whole slide image viewing platform, so that non-data scientist users (e.g., clinicians) can utilize and evaluate pre-trained algorithms and retrieve quantitative results. The outputs of analysis are automatically cataloged in the database to track data provenance and can be viewed interactively on the slide as annotations or heatmaps. Commonly used models for analysis of whole slide images including segmentation, extraction of hand-engineered features for segmented regions, and slide-level classification using multi-instance learning are included and new models can be added as needed. The source code that supports running inference with these models internally is backed up by a robust CI/CD pipeline to ensure model versioning, robust testing, and seamless deployment of the latest models. Examples of the use of this system in a pharmaceutical development workflow include glomeruli segmentation, enumeration of podocyte count from WT-1 immuno-histochemistry, measurement of beta-1 integrin target engagement from immunofluorescence, digital glomerular phenotyping from periodic acid-Schiff histology, PD-L1 score prediction using multi-instance learning, and the deployment of the open-source Segment Anything model to speed up annotation.

Cholesterol Contributes to Risk, Severity, and Machine Learning-Driven Diagnosis of Lyme Disease

BACKGROUND

Lyme disease is the most prevalent vector-borne disease in the US, yet its host factors are poorly understood and diagnostic tests are limited. We evaluated patients in a large health system to uncover cholesterol's role in the susceptibility, severity, and machine learning-based diagnosis of Lyme disease.

METHODS

A longitudinal health system cohort comprised 1 019 175 individuals with electronic health record data and 50 329 with linked genetic data. Associations of blood cholesterol level, cholesterol genetic scores comprising common genetic variants, and burden of rare loss-of-function (LoF) variants in cholesterol metabolism genes with Lyme disease were investigated. A portable machine learning model was constructed and tested to predict Lyme disease using routine lipid and clinical measurements.

RESULTS

There were 3832 cases of Lyme disease. Increasing cholesterol was associated with greater risk of Lyme disease and hypercholesterolemia was more prevalent in Lyme disease cases than in controls. Cholesterol genetic scores and rare LoF variants in CD36 and LDLR were associated with Lyme disease risk. Serological profiling of cases revealed parallel trajectories of rising cholesterol and immunoglobulin levels over the disease course, including marked increases in individuals with LoF variants and high cholesterol genetic scores. The machine learning model predicted Lyme disease solely using routine lipid panel, blood count, and metabolic measurements.

CONCLUSIONS

These results demonstrate the value of large-scale genetic and clinical data to reveal host factors underlying infectious disease biology, risk, and prognosis and the potential for their clinical translation to machine learning diagnostics that do not need specialized assays.

The immunogenic radiation and new players in immunotherapy and targeted therapy for head and neck cancer

Although treatment modalities for head and neck cancer have evolved considerably over the past decades, survival rates have plateaued. The treatment options remained limited to definitive surgery, surgery followed by fractionated radiotherapy with optional chemotherapy, and a definitive combination of fractionated radiotherapy and chemotherapy. Lately, immunotherapy has been introduced as the fourth modality of treatment, mainly administered as a single checkpoint inhibitor for recurrent or metastatic disease. While other regimens and combinations of immunotherapy and targeted therapy are being tested in clinical trials, adapting the appropriate regimens to patients and predicting their outcomes have yet to reach the clinical setting. Radiotherapy is mainly regarded as a means to target cancer cells while minimizing the unwanted peripheral effect. Radiotherapy regimens and fractionation are designed to serve this purpose, while the systemic effect of radiation on the immune response is rarely considered a factor while designing treatment. To bridge this gap, this review will highlight the effect of radiotherapy on the tumor microenvironment locally, and the immune response systemically. We will review the methodology to identify potential targets for therapy in the tumor microenvironment and the scientific basis for combining targeted therapy and radiotherapy. We will describe a current experience in preclinical models to test these combinations and propose how challenges in this realm may be faced. We will review new players in targeted therapy and their utilization to drive immunogenic response against head and neck cancer. We will outline the factors contributing to head and neck cancer heterogeneity and their effect on the response to radiotherapy. We will review in-silico methods to decipher intertumoral and intratumoral heterogeneity and how these algorithms can predict treatment outcomes. We propose that (a) the sequence of surgery, radiotherapy, chemotherapy, and targeted therapy should be designed not only to annul cancer directly, but to prime the immune response. (b) Fractionation of radiotherapy and the extent of the irradiated field should facilitate systemic immunity to develop. (c) New players in targeted therapy should be evaluated in translational studies toward clinical trials. (d) Head and neck cancer treatment should be personalized according to patients and tumor-specific factors.

The synergistic effect of climatic factors on malaria transmission: a predictive approach for northeastern states of India

The northeast region of India is highlighted as the most vulnerable region for malaria. This study attempts to explore the epidemiological profile and quantify the climate-induced influence on malaria cases in the context of tropical states, taking Meghalaya and Tripura as study areas. Monthly malaria cases and meteorological data from 2011 to 2018 and 2013 to 2019 were collected from the states of Meghalaya and Tripura, respectively. The nonlinear associations between individual and synergistic effect of meteorological factors and malaria cases were assessed, and climate-based malaria prediction models were developed using the generalized additive model (GAM) with Gaussian distribution. During the study period, a total of 216,943 and 125,926 cases were recorded in Meghalaya and Tripura, respectively, and majority of the cases occurred due to the infection of Plasmodium falciparum in both the states. The temperature and relative humidity in Meghalaya and temperature, rainfall, relative humidity, and soil moisture in Tripura showed a significant nonlinear effect on malaria; moreover, the synergistic effects of temperature and relative humidity (SI=2.37, RERI=0.58, AP=0.29) and temperature and rainfall (SI=6.09, RERI=2.25, AP=0.61) were found to be the key determinants of malaria transmission in Meghalaya and Tripura, respectively. The developed climate-based malaria prediction models are able to predict the malaria cases accurately in both Meghalaya (RMSE: 0.0889; R²: 0.944) and Tripura (RMSE: 0.0451; R²: 0.884). The study found that not only the individual climatic factors can significantly increase the risk of malaria transmission but also the synergistic effects of climatic factors can drive the malaria transmission multifold. This reminds the policymakers to pay attention to the control of malaria in situations with high temperature and relative humidity and high temperature and rainfall in Meghalaya and Tripura, respectively.

Parosmia and altered taste in patients recovering from Covid 19

Parosmia is a well-documented consequence of smell loss associated with Covid 19. Those who experience this qualitative olfactory disorder during recovery find that the odour of common foods and household items is distorted, and the experience can range from merely altered to profoundly disgusting. This can lead to a greatly altered relationship with food, including the physical symptoms of loss of appetite, nausea, vomiting, as well as wider reaching issues such as withdrawal from social situations, emotional distancing from others in their close social circles, and anhedonia. There is at present no known cure or intervention to mitigate the condition. The AbScent Parosmia and Phantosmia support group on Facebook became an important resource for patients with this condition during the early part of the pandemic, and the crowd-sourcing of experiences, tips and peer-to-peer advice became a valuable source of information for the community as well as researchers trying to understand the condition. Using protocols described in earlier literature on the use of social media for qualitative research, this paper provides information on the management of parosmia based on the experiences of over 30k patients in the AbScent Parosmia and Phantosmia group on Facebook and 6k member of the AbScent Network.

Modelling the impact of timelines of testing and isolation on disease control

Testing and isolation remain a key component of public health responses to both persistent and emerging infectious diseases. Although the value of these measures have been demonstrated in combating recent outbreaks including the COVID-19 pandemic and monkeypox, their impact depends critically on the timelines of testing and start of isolation during the course of disease. To investigate this impact, we developed a delay differential model and incorporated age-since-symptom-onset as a parameter for delay in testing. We then used the model to compare the outcomes of reverse-transcription polymerase chain reaction (RT-PCR) and rapid antigen (RA) testing methods when isolation starts either at the time of testing or at the time of test result. Parameterizing the model with estimates of SARS-CoV-2 infection and diagnostic sensitivity of the tests, we found that the reduction of disease transmission using the RA test can be comparable to that achieved by applying the RT-PCR test. Given constraints and inevitable delays associated with sample collection and laboratory assays in RT-PCR testing post symptom onset, self-administered RA tests with short turnaround times present a viable alternative for timely isolation of infectious cases.

Adaptive behaviors and vaccination on curbing COVID-19 transmission: Modeling simulations in eight countries

Current persistent outbreak of COVID-19 is triggering a series of collective responses to avoid infection. To further clarify the impact mechanism of adaptive protection behavior and vaccination, we developed a new transmission model via a delay differential system, which parameterized the roles of adaptive behaviors and vaccination, and allowed to simulate the dynamic infection process among people. By validating the model with surveillance data during March 2020 and October 2021 in America, India, South Africa, Philippines, Brazil, UK, Spain and Germany, we quantified the protection effect of adaptive behaviors by different forms of activity function. The modeling results indicated that (1) the adaptive activity function can be used as a good indicator for fitting the intervention outcome, which exhibited short-term awareness in these countries, and it could reduce the total human infections by 3.68, 26.16, 15.23, 4.23, 7.26, 1.65, 5.51 and 7.07 times, compared with the reporting; (2) for complete prevention, the average proportions of people with immunity should be larger than 90%, 92%, 86%, 71%, 92%, 84%, 82% and 76% with adaptive protection behaviors, or 91%, 97%, 94%, 77%, 92%, 88%, 85% and 90% without protection behaviors; and (3) the required proportion of humans being vaccinated is a sub-linear decreasing function of vaccine efficiency, with small heterogeneity in different countries. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".

Real-time, smartphone-based processing of lateral flow assays for early failure detection and rapid testing workflows

Despite their simplicity, lateral flow immunoassays (LFIAs) remain a crucial weapon in the diagnostic arsenal, particularly at the point-of-need. However, methods for analysing LFIAs still rely heavily on sub-optimal human readout and rudimentary end-point analysis. This negatively impacts both testing accuracy and testing times, ultimately lowering diagnostic throughput. Herein, we present an automated computational imaging method for processing and analysing multiple LFIAs in real-time and in parallel. This method relies on the automated detection of signal intensity at the test line, control line, and background, and employs statistical comparison of these values to predictively categorise tests as "positive", "negative", or "failed". We show that such a computational methodology can be transferred to a smartphone and detail how real-time analysis of LFIAs can be leveraged to decrease the time-to-result and increase testing throughput. We compare our method to naked-eye readout and demonstrate a shorter time-to-result across a range of target antigen concentrations and fewer false negatives compared to human subjects at low antigen concentrations.

A quick test to objectify smell and taste dysfunction at home: a proof of concept for the validation of the chemosensory perception test

Recent studies have shown the efficacy of a home test for the self-evaluation of olfactory and gustatory functions in quarantined coronavirus disease-2019 (COVID-19) patients. However, testing was often limited to COVID-19 participants, and the accuracy of home test kits was rarely compared to standardized testing. This study aims at providing proof of concept for the validation of the new Chemosensory Perception Test (CPT) developed to remotely assess orthonasal olfactory, retronasal olfactory, and gustatory functions in various populations using common North American household items. In the 2 experiments, a total of 121 participants irrespective of having olfactory and/or gustatory complaints from various causes (COVID-19, sinunasal, post-viral, idiopathic) were tested first, with one or many of the following tests: (i) a brief chemosensory questionnaire, (ii) an olfactory test-Sniffin' Sticks Test (SST) or University of Pennsylvania Smell Identification Test (UPSIT), and/or (iii) a gustatory test-Brief Waterless Empirical Taste Test (B-WETT). We then applied the CPT which yielded 3 different subscores, namely orthonasal, retronasal, and gustatory CPT scores. The orthonasal CPT score was significantly correlated with SST (ρ = 0.837, P < 0.001) and UPSIT (ρ = 0.364, P < 0.001) scores, and exhibited an excellent accuracy to identify olfactory dysfunction (OD) as compared to SST (area under the curve [AUC]: 0.923 [95% confidence interval {CI}, 0.822-1.000], P < 0.001). The retronasal CPT score but not the gustatory CPT score allowed to distinguish between participants with or without subjective gustatory complaint (AUC: 0.818 [95% CI, 0.726-0.909], P < 0.001). The CPT has the ability to identify OD and to quantify subjective gustatory complaints.

COVID-19 detection using a model of photoplethysmography (PPG) signals

Objective:Coronavirus disease 2019 (COVID-19) targets several tissues of the human body; among these, a serious impact has been observed in the microvascular system. The aim of this study was to verify the presence of photoplethysmographic (PPG) signal modifications in patients affected by COVID-19 at different levels of severity.

Approach: The photoplethysmographic signal was evaluated in 93 patients with COVID-19 of different severity (46: grade 1; 47: grade 2) and in 50 healthy control subjects. A pre-processing step removes the long-term trend and segments of each pulsation in the input signal. Each pulse is approximated with a model generated from a multi-exponential curve, and a Least Squares fitting algorithm determines the optimal model parameters. Using the parameters of the mathematical model, three different classifiers (Bayesian, SVM and KNN) were trained and tested to discriminate among healthy controls and patients with COVID, stratified according to the severity of the disease. Results are validated with the leave-one-subject-out validation method.

Main results: Results indicate that the fitting procedure obtains a very high determination coefficient (above 99% in both controls and pathological subjects). The proposed Bayesian classifier obtains promising results, given the size of the dataset, and variable depending on the classification strategy. The optimal classification strategy corresponds to 79% of accuracy, with 90% of specificity and 67% of sensibility.

Significance:The proposed approach opens the possibility of introducing a low cost and non-invasive screening procedure for the fast detection of COVID-19 disease, as well as a promising monitoring tool for hospitalized patients, with the purpose of stratifying the severity of the disease.

Technical feasibility of using auditory phase-targeted stimulation after pediatric severe traumatic brain injury in an intensive care setting

Background

Supplementary treatment options after pediatric severe traumatic brain injury (TBI) are needed to improve neurodevelopmental outcome. Evidence suggests enhancement of brain delta waves via auditory phase-targeted stimulation might support neuronal reorganization, however, this method has never been applied in analgosedated patients on the pediatric intensive care unit (PICU). Therefore, we conducted a feasibility study to investigate this approach: In a first recording phase, we examined feasibility of recording over time and in a second stimulation phase, we applied stimulation to address tolerability and efficacy.

Methods

Pediatric patients (> 12 months of age) with severe TBI were included between May 2019 and August 2021. An electroencephalography (EEG) device capable of automatic delta wave detection and sound delivery through headphones was used to record brain activity and for stimulation (MHSL-SleepBand version 2). Stimulation tolerability was evaluated based on report of nurses, visual inspection of EEG data and clinical signals (heart rate, intracranial pressure), and whether escalation of therapy to reduce intracranial pressure was needed. Stimulation efficacy was investigated by comparing EEG power spectra of active stimulation versus muted stimulation (unpaired t-tests).

Results

In total, 4 out of 32 TBI patients admitted to the PICU (12.5%) between 4 and 15 years of age were enrolled in the study. All patients were enrolled in the recording phase and the last one also to the stimulation phase. Recordings started within 5 days after insult and lasted for 1–4 days. Overall, 23–88 h of EEG data per patient were collected. In patient 4, stimulation was enabled for 50 min: No signs of patient stress reactions were observed. Power spectrums between active and muted stimulation were not statistically different (all P > .05).

Conclusion

Results suggests good feasibility of continuously applying devices needed for auditory stimulation over multiple days in pediatric patients with TBI on PICU. Very preliminary evidence suggests good tolerability of auditory stimuli, but efficacy of auditory stimuli to enhance delta waves remains unclear and requires further investigation. However, only low numbers of severe TBI patients could be enrolled in the study and, thus, future studies should consider an international multicentre approach.

SARS-CoV-2 Transmission in Belgian French-Speaking Primary Schools: An Epidemiological Pilot Study

Schools have been a point of attention during the pandemic, and their closure one of the mitigating measures taken. A better understanding of the dynamics of the transmission of SARS-CoV-2 in elementary education is essential to advise decisionmakers. We conducted an uncontrolled non-interventional prospective study in Belgian French-speaking schools to describe the role of attending asymptomatic children and school staff in the spread of COVID-19 and to estimate the transmission to others. Each participant from selected schools was tested for SARS-CoV-2 using a polymerase chain reaction (PCR) analysis on saliva sample, on a weekly basis, during six consecutive visits. In accordance with recommendations in force at the time, symptomatic individuals were excluded from school, but per the study protocol, being that participants were blinded to PCR results, asymptomatic participants were maintained at school. Among 11 selected schools, 932 pupils and 242 school staff were included between January and May 2021. Overall, 6449 saliva samples were collected, of which 44 came back positive. Most positive samples came from isolated cases. We observed that asymptomatic positive children remaining at school did not lead to increasing numbers of cases or clusters. However, we conducted our study during a period of low prevalence in Belgium. It would be interesting to conduct the same analysis during a high prevalence period.

Awareness With Paralysis Among Critically Ill Emergency Department Patients: A Prospective Cohort Study

OBJECTIVES

In mechanically ventilated patients, awareness with paralysis (AWP) can have devastating consequences, including post-traumatic stress disorder (PTSD), depression, and thoughts of suicide. Single-center data from the emergency department (ED) demonstrate an event rate for AWP factors higher than that reported from the operating room. However, there remains a lack of data on AWP among critically ill, mechanically ventilated patients. The objective was to assess the proportion of ED patients experiencing AWP and investigate modifiable variables associated with its occurrence.

DESIGN

An a priori planned secondary analysis of a multicenter, prospective, before-and-after clinical trial.

SETTING

The ED of three academic medical centers.

PATIENTS

Mechanically ventilated adult patients that received neuromuscular blockers.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

All data related to sedation and analgesia were collected. AWP was the primary outcome, assessed with the modified Brice questionnaire, and was independently adjudicated by three expert reviewers. Perceived threat, in the causal pathway for PTSD, was the secondary outcome. A total of 388 patients were studied. The proportion of patients experiencing AWP was 3.4% ( n = 13), the majority of whom received rocuronium ( n = 12/13; 92.3%). Among patients who received rocuronium, 5.5% ( n = 12/230) experienced AWP, compared with 0.6% ( n = 1/158) among patients who did not receive rocuronium in the ED (odds ratio, 8.64; 95% CI, 1.11-67.15). Patients experiencing AWP had a higher mean ( sd ) threat perception scale score, compared with patients without AWP (15.6 [5.8] vs 7.7 [6.0]; p < 0.01).

CONCLUSIONS

AWP was present in a concerning proportion of mechanically ventilated ED patients, was associated with rocuronium exposure in the ED, and led to increased levels of perceived threat, placing patients at greater risk for PTSD. Studies that aim to further quantify AWP in this vulnerable population and eliminate its occurrence are urgently needed.

Epidemiological and Serological Analysis of a SARS-CoV-2 Outbreak in a Nursing Home: Impact of SARS-CoV-2 Vaccination and Enhanced Neutralizing Immunity Following Breakthrough Infection

Background: Despite a vaccination rate of 82.0% (n = 123/150), a SARS-CoV-2 (Alpha) outbreak with 64.7% (n = 97/150) confirmed infections occurred in a nursing home in Bavaria, Germany. Objective: the aim of this retrospective cohort study was to examine the effects of the Corminaty vaccine in a real-life outbreak situation and to obtain insights into the antibody response to both vaccination and breakthrough infection. Methods: the antibody status of 106 fully vaccinated individuals (54/106 breakthrough infections) and epidemiological data on all 150 residents and facility staff were evaluated. Results: SARS-CoV-2 infections (positive RT-qPCR) were detected in 56.9% (n = 70/123) of fully vaccinated, compared to 100% (n = 27/27) of incompletely or non-vaccinated individuals. The proportion of hospitalized and deceased was 4.1% (n = 5/123) among fully vaccinated and therewith lower compared to 18.5% (n = 5/27) hospitalized and 11.1% (n = 3/27) deceased among incompletely or non-vaccinated. Ct values were significantly lower in incompletely or non-vaccinated (p = 0.02). Neutralizing antibodies were detected in 99.1% (n = 105/106) of serum samples with significantly higher values (p < 0.001) being measured post-breakthrough infection. α-N-antibodies were detected in 37.7% of PCR positive but not in PCR negative individuals. Conclusion: Altogether, our data indicate that SARS-CoV-2 vaccination does provide protection against infection, severe disease progression and death with regards to the Alpha variant. Nonetheless, it also shows that infection and transmission are possible despite full vaccination. It further indicates that breakthrough infections can significantly enhance α-S- and neutralizing antibody responses, indicating a possible benefit from booster vaccinations.

Factors influencing the adoption and participation rate of nursing homes staff in a saliva testing screening programme for COVID-19

Testing strategies are crucial to prevent and control the spread of covid-19 but suffer from a lack of investment in understanding the human factors that influence their implementation. The aim of this study was to understand the factors that encourage participation and the level of engagement of nursing homes staff in a routine saliva testing programme for COVID-19 In December 2020, nursing homes (n = 571) in Wallonia (Belgium) were invited to participate in a saliva testing programme for their staff. The directors were questioned by telephone at the end of a 3-week pilot phase. 445 nursing homes took part in the evaluation questionnaire, of which 36(8%) answered that they chose not to participate in the testing programme. The average participation rate of nursing staff was 49(±25)%. Perception of the justification of the efforts required for testing and perception of practicability of the procedure were significantly associated with the adoption of the system by the nursing homes directors (OR(95%CI): 5.96(1.97–18.0), p = 0.0016); OR(95%CI): 5.64(1.94–16.4), p = 0.0015 respectively). Staff support, incentives and meetings increased the level of engagement in testing (p<0.05). While the adoption of the programme confirmed the acceptability of salivary testing as a means of screening, the participation rate confirmed the need for studies to understand the factors that encourage health care staff to take part. The results suggested rethinking strategies to consider staff engagement from a health promotion perspective.

Diagnosis of Coxiella burnetii Cattle Abortion: A One-Year Observational Study

Q fever is a zoonosis occurring worldwide in livestock. Often neglected in differential diagnoses, Q fever can persist in herds causing financial losses. In ruminants, well-known manifestations of Q fever are metritis, infertility, abortion, stillbirth and delivery of a weak or premature calf. In cattle, Q fever is frequently asymptomatic and/or under-reported. Few studies are available on the diagnosis of Coxiella burnetii as a cause of abortion in cattle using polymerase chain reaction (PCR) for pathogen detection while enzyme-linked immunosorbent assay (ELISA) is used to assess exposure. Moreover, existing studies include a relatively small number of abortions. The aim of this study is to assess, in the southern part of Belgium, during a year, the performance of diagnosis of C. burnetii as a cause of abortion and the putative benefit of enhanced serology using anamnesis (animal patient data, and present, past and environmental history). A one-year random selection of 1212 abortions was analysed both with the PCR method (tissues from fetuses) and two commercialised ELISAs (sera from the mothers). Relative sensitivity and specificity of the ELISA tests were assessed using PCR as the reference test. The prevalence of C. burnetii PCR positive was 8.5% (95% CI: 6.99–10.21). The diagnostic value of the ELISA tests was assessed using the area under the receiver operating characteristic curve (AUC-ROC). The sensitivity, specificity and AUC-ROC were similar for both ELISA tests. The diagnostic capacity of the ELISA was confirmed and slightly enhanced if anamnestic information was integrated with a unique scoring index system. A high negative predictive value was demonstrated and a significant reverse association between Ct values and a percentage of the ratio of the optical density between the sample and the positive control (ELISA A or ELISA B) enabling the use of ELISA as an exclusion diagnostic. This study is original by integrating the serological result and the anamnesis in a single index. It opens a new window in enhanced veterinary clinical decision-making.