Low Probability Of Infection Research Articles

Interleukin-6 on postoperative day three as an early predictor of infections following laparoscopic gastric cancer resection

BackgroundTo investigate the role of C-reactive protein (CRP), procalcitonin (PCT), and interleukin-6 (IL-6) as early predictors of infectious complications after laparoscopic gastric cancer surgery.MethodsPatients who underwent laparoscopic gastric cancer surgery between January 2020 and June 2022 were retrospectively enrolled. IL-6, PCT, and CRP levels were assessed before surgery and on postoperative days (PODs) 3 and 5. Differences in serum IL-6, PCT, and CRP levels between the infected and non-infected groups were compared. The diagnostic accuracy was determined using the area under the receiver operating characteristic curve (AUC).ResultsA total of 206 patients were enrolled, and 21 patients (10.19%) developed postoperative infections. Serum IL-6, PCT, and CRP levels in the infected group were significantly higher than those in the non-infected group on PODs 3 and 5. IL-6 with an optimal cutoff value of 84.00 pg/mL (AUC 0.84), PCT with an optimal cutoff value of 1.39 ng/mL (AUC 0.80), CRP with an optimal cutoff value of 150.00 mg/L (AUC 0.76) on POD 3 had superior diagnostic accuracy in predicting postoperative infections. Multivariate analysis identified PCT and IL-6 levels on POD 3 as independent risk factors, the AUC of the combination of IL-6 and PCT was 0.89. The Delong test showed no difference between the AUC of IL-6 alone and IL-6 combined with PCT prediction (P = 0.07, Z = 1.81).ConclusionsIL-6 level on POD 3 is an excellent predictor of infectious complications following laparoscopic gastric cancer surgery. Patients with IL-6 levels lower than 84.00 pg/mL on POD 3 can ensure safe early discharge with a low probability of infection.

Finding the Optimal Screening Test for Periprosthetic Joint Infection: A Prospective Study

BackgroundNo single test has demonstrated absolute accuracy in the diagnosis of periprosthetic joint infection (PJI). Serological markers are often used as screening tools to avoid unnecessary joint aspiration in cases with a low probability of infection. This study aimed to determine the utility of standard-of-care serological tests as a screening tool for PJI in patients undergoing revision arthroplasty. MethodsThis prospective study enrolled 502 patients undergoing revision hip or knee arthroplasty between May 2017 and August 2021. A PJI was defined using a modified definition of the 2018 International Consensus Meeting criteria. Plasma D-dimer, erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), and fibrinogen were measured preoperatively. There were 82 patients undergoing reimplantation who were excluded. Additionally, 8 patients who had an inconclusive International Consensus Meeting score were also excluded. Of the 412 included patients, 317 (76.9%) underwent revision for aseptic failure, and 95 (23.1%) had PJI. Receiver operating characteristic curves were used to assess the diagnostic utility of each serological test. A pairwise comparison with Bonferroni correction was performed to determine whether the differences in areas under the curve (AUCs) between the tests were significant. Additional analyses were performed to find the threshold for each test that offered 100% sensitivity, allowing it to be the optimal screening test. ResultsAll 4 serological markers, D-dimer (AUC 0.860, sensitivity 81.3%, specificity 81.7%), CRP (AUC 0.862, sensitivity 90.4%, specificity 70.0%), ESR (AUC 0.833, sensitivity 73.9%, specificity 85.2%), and fibrinogen (AUC 0.798, sensitivity 74.7%, specificity 75.4%), demonstrated comparable accuracy for the diagnosis of PJI (all P > .05). When maximizing sensitivity to 100%, D-dimer demonstrated the highest specificity (AUC 0.860, specificity 40.2%), outperforming ESR (AUC 0.833, specificity 3.3%), fibrinogen (AUC 0.798, specificity 2.3%), and CRP (AUC 0.862, specificity 0%). A plasma D-dimer level of ≥ 244 ng/mL was identified as the optimal cutoff for use as a screening test. ConclusionsAlthough plasma D-dimer demonstrated similar diagnostic accuracy as CRP, ESR, and fibrinogen, it outperformed all 3 aforementioned serological markers when used as a screening test for PJI. Level of EvidenceLevel II.

Successful pandemic management through computer science: a case study of a financial corporation with workers on premises.

In November 2019, an infectious agent that caused a severe acute respiratory illness was first detected in China. Its rapid spread resulted in a global lockdown with negative economic impacts. In this regard, we expose the solutions proposed by a multinational financial institution that maintained their workers on premises, so this methodology can be applied to possible future health crisis. To ensure a secure workplace for the personnel on premises employing biomedical prevention measures and computational tools. Professionals were subjected to recurrent COVID-19 diagnostic tests during the pandemic. The sanitary team implemented an individual following to all personnel and introduced the information in databases. The data collected were used for clustering algorithms, decision trees, and networking diagrams to predict outbreaks in the workplace. Individualized control panels assisted the decision-making process to increase, maintain, or relax restrictive measures. 55,789 diagnostic tests were performed. A positive correlation was observed between the cumulative incidence reported by Madrid's Ministry of Health and the headcount. No correlation was observed for occupational infections, representing 1.9% of the total positives. An overall 1.7% of the cases continued testing positive for COVID-19 after 14 days of quarantine. Based on a combined approach of medical and computational science tools, we propose a management model that can be extended to other industries that can be applied to possible future health crises. This work shows that this model resulted in a safe workplace with a low probability of infection among workers during the pandemic.

COVID-19 incidence in women of reproductive age: a population-based study in Reggio Emilia, northern Italy

BackgroundDespite being at higher risk of severe disease and pregnancy complications, evidence on susceptibility to SARS-CoV-2 infection in pregnancy is still limited. The aim of the study is to compare the likelihood of undergoing a SARS-CoV-2 test and testing positive for COVID-19 in pregnancy and puerperium with that of the general female population of reproductive age.MethodsThis is a retrospective population-based cohort study including 117,606 women of reproductive age (March 2020-September 2021) with 6608 (5.6%) women having ≥ 1 pregnancy.Women were linked to the pregnancy registry to be classified as “non-pregnant”, “pregnant”, and “puerperium”; then, according to the national case-based integrated COVID-19 surveillance system, all women undergoing a SARS-CoV-2 test during the study period were identified. The Incidence Rate Ratio was calculated to compare the likelihood of being tested for SARS-CoV-2 in pregnant, puerperium and non-pregnant women among all women included. The likelihood of having a COVID-19 diagnosis was calculated using two comparators (not-pregnant women and the person-time before/after pregnancy) by means of Cox proportional hazards models, adjusting for age and with the cluster option to control standard error calculation in repeated pregnancies. Only first infection and swabs before the first one positive were included.ResultsThe probability of being tested for SARS-CoV-2 was 4.9 (95% CI: 4.8–5.1) and 3.6 times higher (95%CI: 3.4–3.9) in pregnancy (including spontaneous miscarriages) and in the puerperium, respectively.The Hazard Ratio (HR) of covid-19 diagnosis during pregnancy vs. non-pregnancy was 1.17 (95% CI 1.03–1.33) with similar results when comparing the risk during pregnancy with that of the same women outside pregnancy (puerperium excluded), with an HR of 1.13 (95% CI 0.96–1.33); the excess decreased when excluding the test performed at admission for delivery (HR 1.08 (95%CI 0.90–1.30). In the puerperium, the HR was 0.62 (95% CI 0.41–0.92) comparing women with ≥ 1childbirth with all other women and excluding the first two weeks of puerperium.ConclusionsWomen during pregnancy showed a small increase in the risk of infection, compatible with a higher likelihood of being tested. A lower probability of infection during the puerperium was observed during the entire pandemic period, suggesting likely protective behaviors which were effective in reducing their probability of infection.

Strategic incentives when implementing Dorfman testing with assortative matching

The Dorfman pooled testing scheme is a process in which individual specimens (e.g., blood, urine, swabs, etc.) are pooled and tested together; if the merged sample tests positive for infection, each specimen from the pool is tested individually. Through this procedure, laboratories can reduce the expected number of tests required to screen a population. The literature has often advocated in favor of using ordered partitions to screen the population, i.e., of pooling subjects with similar probability of infection together, as doing so simultaneously minimizes the expected number of tests, the expected number of false negatives, and the expected number of false positive classifications, provided that certain technical conditions hold. One potential limitation of using ordered partitions, however, is that they may incentivize some subjects to misreport their types to the tester. Indeed, if subjects wish to avoid being detected as infected, ordered partitions would incentivize them to falsely claim that they have a low probability of infection (assuming that pooled testing is subject to dilution effects). These incentives would disappear if subjects were matched randomly, regardless of their probability of infection. In this article, we derive conditions under which ordered partitions outperform matching subjects randomly, despite these incentives.

Investigating the dynamics of a novel fractional-order monkeypox epidemic model with optimal control

In this paper, a novel fractional-order monkeypox epidemic model is introduced, wherefractional-order derivativesin the sense of Caputo are applied to achieve more realistic results for the proposednonlinear model. The newly developed model, which models the transmission and spread of monkeypox across the interacting populations of humans and rodents, is controlled by a 14-dimensional system of fractional-order differential equations. To comply with empirical and reported observations, the state variables of the proposed model are categorized into three main groups of state variables: the population who are at high risk of being infected, people with low infection probability, and finally, rodents who can carry and transmit the virus. The high-risk group represents individuals who might be more vulnerable to the virus due to their habits, workplace, or hygienic behaviors. The existence, uniqueness, non-negativity, and boundedness of the solution to the proposed model are proved. The next-generation matrix approach is used to determine the control monkeypox reproduction number, R0, and the equilibrium points for the proposed model are obtained. The effect of the main parameters in the model is thoroughly investigated to provide new insight into the new dynamics of the model. The region of stability of the disease-free points (DFE) is obtained in the space of parameters, and the effect of the parameters is examined. In addition, theoptimal control strategyis applied to the model to provide insight into some prevention control to stop the disease from spreading and to provide new control strategies during the monkeypox outbreak. Numerical simulations are performed to validate the theoretical results of the different optimal control strategies.

Synergistic effect of two formulations of hypochlorous acid in the treatment of 346 chronic ulcers.

Our objective was to assess the efficacy of two successive applications of hypochlorous acid, first as a liquid and then as a gel because liquid hypochlorous acid is effective but has little residual effect, while the gel form has more residual power, and compare it with that of other products. An experimental non-randomised study was carried out, treating 346 chronic ulcers in 220 patients. The antiseptic treatment has been divided into 'hypochlorous acid' (Clortech), 'hypochlorous acid liquid + gel' (Clortech + Microdacyn60R -hydrogel) and 'Others' (Prontosan or Chlorhexidine or Microdacyn60R -hydrogel). Bivariate and multivariate studies analysed the characteristics of the patients and their ulcers, including size, symptoms, signs, treatments received and their duration, and so on. The ulcers were complicated, of long evolution, and most had a vascular origin. On average, antiseptic treatment lasted 14 weeks. At the time of their discharge, or last treatment in the clinics, 59% of the ulcers had healed completely, 9.5% worsened, and 6.9% had become infected during this period. In the bivariate and multivariate studies, we took as reference the 'others' treatments that showed no significant differences in healing time or infection rates compared with liquid hypochlorous acid 100-500 mg/L alone. However, hypochlorous acid liquid + gel showed a synergistic effect, with a higher probability of achieving complete healing (four times) and a lower probability of infection (a fifth), compared to the 'other' antiseptics. In conclusion, a synergistic effect was found with the successive application of hypochlorous acid in liquid followed by gel, an effect that increased healing probability and decreased the risk of the ulcer becoming infected.

Effect of a Fourth Dose of mRNA Vaccine and of Immunosuppression in Preventing SARS-CoV-2 Breakthrough Infections in Heart Transplant Patients

Patients with heart transplantation (HT) have an increased risk of COVID-19 disease and the efficacy of vaccines on antibody induction is lower, even after three or four doses. The aim of our study was to assess the efficacy of four doses on infections and their interplay with immunosuppression. We included in this retrospective study all adult HT patients (12/21-11/22) without prior infection receiving a third or fourth dose of mRNA vaccine. The endpoints were infections and the combined incidence of ICU hospitalizations/death after the last dose (6-month survival rate). Among 268 patients, 62 had an infection, and 27.3% received four doses. Following multivariate analysis, three vs. four doses, mycophenolate (MMF) therapy, and HT < 5 years were associated with an increased risk of infection. MMF ≥ 2000 mg/day independently predicted infection, together with the other variables, and was associated with ICU hospitalization/death. Patients on MMF had lower levels of anti-RBD antibodies, and a positive antibody response after the third dose was associated with a lower probability of infection. In HT patients, a fourth dose of vaccine against SARS-CoV-2 reduces the risk of infection at six months. Mycophenolate, particularly at high doses, reduces the clinical effectiveness of the fourth dose and the antibody response to the vaccine.

The Impact of COVID-19 Pandemic on Nature-Based Tourism in National Parks. Case Studies for Poland

The study aims concern to nature-based tourism in national parks, to compare visitor behavior and visitors’ spatial and temporal distribution in national parks during the COVID-19 (2020) and pre- COVID-19 period (2017–2019). The research is based on a pyroelectric sensors data, entrance fees and questionnaire survey of visitors, in order to: (1) assess the spatial and temporal distribution and changes of visitors, (2) characterize changes in visitors’ behavior. The visitor number and spatial and temporal distribution changed during COVID-19 period. The visitor’s behavior identifies three visitor clusters depending on the strength of COVID-19 pandemic impact on stay on national parks: High fear visitors (HFV), Low fear visitors (LFV) and No fear visitors (NFV). Each cluster represents a different attitude toward the pandemic and its effects. The research was conducted in two national parks in Poland: Stołowe Mountains National Park and Karkonosze/Giant Mts. National Park. The resulting data were compared with data from previous years. A total of 935 respondents participated in the survey, which demonstrated a significant impact of the ongoing pandemic on many aspects of the behaviors. Most visitors argued that the pandemic had not changed their behavior because society began to perceive national parks as safe destination with a low probability of infection. &#x0D;

Computed Tomography Image: Guided Needle Biopsy in the Diagnosis of Lung Malignant Tumors under Artificial Intelligence Algorithm

The computed tomography (CT) image-guided needle biopsy was applied in the diagnosis of lung malignant tumors based on artificial intelligence (AI) algorithm under convolutional neural network (CNN) to explore the effect of artificial intelligence algorithms segmentation in needle biopsy surgery and to guide the diagnosis of lung malignant tumors. The subjects of the study were 100 patients with lung malignant tumors admitted to the hospital. The cases were diagnosed as lung cancers by CT, and they were divided into two groups with 50 people in each group. Among them, 50 people in the control group did not use algorithms for guidance and 50 people in the experimental group used algorithms for guidance. The 50 patients who received needle biopsy without guidance of any algorithm were included in the control group. The results showed that the average coincidence rate of automatic segmentation and manual segmentation by the artificial intelligence algorithm was 97.46%, and the average false positive rate (FPR) and false negative rate (FNR) were 0.07% and 0.08%, respectively. The segmentation time of the algorithm group was 12.5 s, which was significantly shorter than the 36.11 s of the control group, and the segmentation speed was significantly faster. The positive rate of pathology in the control group was 78%, and the pathological positive rate of the algorithm group was 80%. The difference in the pathological positive rate between the two groups was 2%, and the detection effect of the pathological positive rate in the algorithm group was close to that in the control group, which was of positive significance in pathological detection. The satisfaction rate of patients in the algorithm group with the detection effect was 88%, and that of the patients in the control group was 94%. The difference in the detection satisfaction rate between the two groups was 6%. The number of patients with pneumothorax in the algorithm group was 22, the number of patients with bleeding was 21, and the number of patients with infection was 2. The number of patients with pneumothorax in the control group was 17, the number of patients with bleeding was 19, and the number of patients with infection was 3. The patients had a higher probability of pneumothorax and bleeding and a lower probability of infection; there was no significant difference in the incidence of complications between the two groups of patients. In summary, the intelligent algorithm was effective and feasible in segmenting lesions, and the accuracy of segmentation could meet the clinical needs, which can be used as a reference for surgery. CT images based on artificial intelligence algorithms were a good way to guide the needle biopsy in the diagnosis of lung malignant tumors, improving the accuracy and sensitivity of the diagnosis of lung malignant tumors.

An improved numerical model for epidemic transmission and infection risks assessment in indoor environment

Social distance will remain the key measure to contain COVID-19 before the global widespread vaccination coverage expected in 2024. Containing the virus outbreak in the office is prioritised to relieve socio-economic burdens caused by COVID-19 and potential pandemics in the future. However, “what is the transmissible distance of SARS-CoV-2” and “what are the appropriate ventilation rates in the office” have been under debate. Without quantitative evaluation of the infection risk, some studies challenged the current social distance policies of 1–2 m adopted by most countries and suggested that longer social distance rule is required as the maximum transmission distance of cough ejected droplets could reach 3–10 m. With the emergence of virus variants such as the Delta variant, the applicability of previous social distance rules are also in doubt. To address the above problem, this study conducted transient Computational Fluid Dynamics (CFD) simulations to evaluate the infection risks under calm and wind scenarios. The calculated Social Distance Index (SDI) indicates that lower humidity leads to a higher infection risk due to weaker evaporation. The infection risk in office was found more sensitive to social distance than ventilation rate. In standard ventilation conditions, social distance of 1.7 m–1.8 m is sufficient distances to reach low probability of infection (PI) target in a calm scenario when coughing is the dominant transmission route. However in the wind scenario (0.25 m/s indoor wind), distance of 2.8 m is required to contain the wild virus type and 3 m is insufficient to contain the spread of the Delta variant. The numerical methods developed in this study provide a framework to evaluate the COVID-19 infection risk in indoor environment. The predicted PI will be beneficial for governments and regulators to make appropriate social-distance and ventilation rules in the office.

Droplet digital PCR as a tool for investigating dynamics of cryptic symbionts.

Interactions among symbiotic organisms and their hosts are major drivers of ecological and evolutionary processes. Monitoring the infection patterns among natural populations and identifying factors affecting these interactions are critical for understanding symbiont–host relationships. However, many of these interactions remain understudied since the knowledge about the symbiont species is lacking, which hinders the development of appropriate tools. In this study, we developed a digital droplet PCR (ddPCR) assay based on apicomplexan COX1 gene to detect an undescribed agamococcidian symbiont. We show that the method gives precise and reproducible results and enables detecting cryptic symbionts in low target concentration. We further exemplify the assay's use to survey seasonally sampled natural host (Pygospio elegans) populations for symbiont infection dynamics. We found that symbiont prevalence differs spatially but does not show seasonal changes. Infection load differed between populations and was low in spring and significantly increased towards fall in all populations. We also found that the symbiont prevalence is affected by host length and population density. Larger hosts were more likely to be infected, and high host densities were found to have a lower probability of infection. The observed variations could be due to characteristics of both symbiont and host biology, especially the seasonal variation in encounter rates. Our findings show that the developed ddPCR assay is a robust tool for detecting undescribed symbionts that are otherwise difficult to quantify, enabling further insight into the impact cryptic symbionts have on their hosts.

Benefit of COVID-19 vaccination accounting for potential risk compensation

People receiving COVID-19 vaccines may subsequently markedly increase their previously suppressed exposure risk. A simple model can evaluate the benefit of vaccination to the vaccinated (index) person and others exposed to that person; and calculate the amount of risk compensation required to eliminate all the benefits or to halve the benefit. As shown, 2.5-fold increase in exposure will eliminate the benefit of a vaccine of moderate efficacy (E = 0.6) unless the probability of infection in the population of interest is very high. With very high vaccine efficacy (E = 0.95), substantial benefit is maintained except in situations where there is a very low probability of infection in the population. If the vaccine efficacy decreases to 0.8, the benefit gets eroded easily with modest risk compensation. Risk compensation may markedly affect the benefit of COVID-19 vaccination, especially if vaccine efficacy in real-life or specific high-risk populations (e.g., nursing home residents) is not very high.

Impact of visitation and cohorting policies to shield residents from covid-19 spread in care homes: an agent-based model

BackgroundThis study examines the impact of visitation and cohorting policies as well as the care home population size upon the spread of COVID-19 and the risk of outbreak occurrence in this setting. MethodsAgent-based modelling ResultsThe likelihood of the presence of an outbreak in a care home is associated with the care home population size. Cohorting of residents and staff into smaller, self-contained units reduces the spread of COVID-19. Restricting the number of visitors to the care home to shield its residents does not significantly impact the cumulative number of infected residents and risk of outbreak occurrence in most scenarios. Only when the community prevalence where staff live is considerably lower than the prevalence where visitors live (the former prevalence is less than or equal to 30% of the latter), relaxing visitation increases predicted infections much more significantly than it does in other scenarios. Maintaining a low infection probability per resident-visitor contact helps reduce the effect of allowing more visitors into care homes. ConclusionsOur model predictions suggest that cohorting is effective in controlling the spread of COVID-19 in care homes. However, according to predictions shielding residents in care homes is not as effective as predicted in a number of studies that have modelled shielding of vulnerable population in the wider communities.

Benefit of COVID-19 Vaccination Accounting for Potential Risk Compensation

Newly developed vaccines have tremendous potential in the fight against the COVID-19 pandemic. Risk compensation is the phenomenon where people receiving vaccines or other preventive measures may subsequently increase their previously suppressed exposure risk. Here a parsimonious mathematical model is presented that aims to evaluate the benefit of vaccination to the vaccinated (index) person and others exposed to that person; and calculate the amount of risk compensation required to eliminate all the benefit or to halve the benefit. As shown, 2.5-fold increase in exposure may eliminate the benefit of a vaccine of moderate efficacy (E=0.6) unless the probability of infection in the population of interest is very high. With very high vaccine efficacy (E=0.95), substantial benefit is maintained except in situations where there is very low probability of infection in the population. If the vaccine efficacy decreases to 0.8, the benefit may get eroded easily with modest risk compensation. Risk compensation may markedly affect the benefit of COVID-19 vaccination, especially if vaccine efficacy in real-life or specific high-risk populations (e.g. nursing home residents) is not very high.

Artificial Neural Network based COVID-19 Suspected Area Identification

This paper deals with the symptoms based COVID-19 suspected area identification using an artificial neural network by which a country or region can be divided into red, yellow, and green zone representing the highly infected area, moderate infected area, and controlled or low infected area, respectively. At first, an online survey of twenty (20) patients was conducted based on the nine (09) major symptoms of COVID-19. Then, a model based on the fuzzy logic system was designed consisting of COVID-19 symptoms identification, fuzzification, rule evaluation, fuzzy inference mechanism, etc. for getting the data sets to be trained in neural networks. For different combinations of 09 symptoms, different rules were generated and evaluated for possible recommendations. Based on different rules, three possible outputs representing high infection probability, medium infection probability, and low infection probability were obtained using the Mamdani inference mechanism. These outputs were termed as red, yellow, and green zone separated by the crisp value of +1, 0, -1, respectively, and considered as target data to be trained in neural networks.

Adaptive targeted infectious disease testing

We show how to efficiently use costly testing resources in an epidemic, when testing outcomes can be used to make quarantine decisions. If the costs of false quarantine and false release exceed the cost of testing, the optimal myopic testing policy targets individuals with an intermediate likelihood of being infected. A high cost of false release means that testing is optimal for individuals with a low probability of infection, and a high cost of false quarantine means that testing is optimal for individuals with a high probability of infection. If individuals arrive over time, the policy-maker faces a dynamic trade-off: using tests for individuals for whom testing yields the maximum immediate benefit vs spreading out testing capacity across the population to learn prevalence rates thereby benefiting later individuals. We describe a simple policy that is nearly optimal from a dynamic perspective. We briefly discuss practical aspects of implementing our proposed policy, including imperfect testing technology, appropriate choice of prior, and non-stationarity of the prevalence rate.

Is It Possible to Use Entomopathogenic Nematodes inside Honey Bee, (Apis mellifera L.) Colonies?

Some hypotheses supported the concept that entomopathogenic nematodes are safe bio-agents, causing low infection probability to honey bee workers and brood under colonies conditions and have no effects on the colony strength and might be used as a bio-control agent against the greater wax moth Galleria mellonella.However, the obtained results showed that the mortality percentages in bee larvae after treatment with EPNs ranged from 49.2% to 77.6 % in the case ofSteinernema sp. isolates and from 39.8% to 55.2 % in Heterorhabditis sp. isolates under the colony conditions, the nematode infection inside the entire colony was restricted to the treated areas and didn’t widespread through the other frames. Direct treatments inside the laboratory also confirmed the susptibility of bee workers and larvae to nematode infection of all tested isolates with differences in successful recycling. The present work strongly supported that both Steinernematidae and Heterorhabditidae families are not recommended to be used in bee colonies as bio-control agents. Further research is needed to cover the possibilities of using them for infected wax combs during storage before reusing it in the bee colonies.

Heterozygosity and fitness in a threatened songbird: blood parasite infection is explained by single-locus but not genome-wide effects

In non-pedigreed populations, insights into effects of inbreeding can be obtained by correlations between individual heterozygosity and fitness-related traits (HFCs). Using an information-theoretic approach, we explored whether heterozygosity of microsatellite markers, measured as internal relatedness (IR), is associated with infection by blood parasites (Plasmodium, Trypanosoma, or Leucocytozoon) in the threatened Aquatic Warbler (Acrocephalus paludicola). We also explored whether any of the markers is more influential than others, or than IR, in explaining blood parasitism (single-locus effects). While we observed that IR was a relatively important predictor of Plasmodium parasitism, we did not find strong evidence for IR to correlate with infection by the identified blood parasites, accounting for sex and population effects. Therefore, our data did not support negative inbreeding effects on blood parasite infection in the Aquatic Warbler. However, we found single-locus effects, such that individuals heterozygous at AW-03 and Ase19 had lower probability of infection by blood parasites pooled together and by Plasmodium, respectively. This indicates that these two markers are in linkage disequilibrium with unknown fitness loci which are related to resisting or clearing blood parasites, and which confer a heterozygote advantage in the Aquatic Warbler. Our results add to the growing evidence that single-locus effects contribute more to HFCs than formerly recognized and have implications for Aquatic Warbler conservation.

When are infection risks of blood transfusion tolerable? Towards understanding the ethical views of stakeholders in the blood supply.

Background and objectivesThe perception of transfusion‐transmitted infections (TTIs) is sensitive to various concerns besides the probability and impact of infection, and some of these concerns may be ethically relevant. This paper aims to advance thinking about blood safety policies by exploring and explaining stakeholders’ reasons to consider TTI risks tolerable or intolerable.Materials and methodsInspired by critical empirical ethics and phenomenological hermeneutics, we held interviews and focus group discussions to explore the moral experience of policymakers, hematologists, blood donors and recipients. Respondents were invited to discuss general concerns about the blood supply, to address the tolerability of TTI risks compared with other hazards and to comment on the costs of blood safety. Arguments for tolerance or intolerance towards TTI risks were analysed qualitatively.ResultsStakeholders’ views could be clustered into seven categories: (1) clinical impact; (2) probability of infection; (3) avoidability of infection; (4) cost and health benefits; (5) other consequences of safety measures; (6) non‐consequentialist ethical arguments; and (7) stakeholders’ interests. Various arguments were offered that resonate with current ethical thinking about blood safety. Assuming that resources spent on inefficient blood safety measures could be applied more beneficially elsewhere, for example, responders typically expressed tolerance towards TTI risks. Some other arguments seem novel, for instance arguments for risk intolerance based on the low probability of infection and arguments for risk tolerance if patients have a poor prognosis.ConclusionUnderstanding the moral experience of stakeholders enriches ethical debate about blood safety and prepares developing more widely acceptable policies.