Transmission Of Infectious Diseases Research Articles

Research on Early Warning of Transmission of Tuberculosis Infectious Diseases from the Perspective of Social Factors

In this study, the infiltration model was established to study the early warning of pulmonary tuberculosis data in Xiamen public hospitals. Based on the gender characteristics of residents in Xiamen, a percolation model was established to analyze the transmission rates of diseases under different contact types. In addition, the calculation method of the percolation threshold is discussed, and the model is verified by a simulation experiment. The results show that the model can predict the spread of epidemic situations well. The early warning value and relevant preventive measures were obtained by simulating the spread of tuberculosis under different exposure numbers. Bond percolation analysis was used to predict the proportion of the eventually infected population, this threshold of percolation was the basic regeneration number of tuberculosis, and the tuberculosis infection situation was effectively predicted.

Status of zoonotic disease research in refugees, asylum seekers and internally displaced people, globally: A scoping review of forty clinically important zoonotic pathogens.

At the end of 2022, there were over 108 million forcibly displaced people globally, including refugees, asylum seekers (AS) and internally displaced people (IDPs). Forced migration increases the risk of infectious disease transmission, and zoonotic pathogens account for 61% of emerging and re-emerging infectious diseases. Zoonoses create a high burden of disease and have the potential to cause large-scale outbreaks. This scoping review aimed to assess the state of research on a range of clinically relevant zoonotic pathogens in displaced populations in order to identify the gaps in literature and guide future research. Literature was systematically searched to identify original research related to 40 selected zoonotic pathogens of interest in refugees, AS and IDPs. We included only peer-reviewed original research in English, with no publication date restrictions. Demographic data, migration pathways, health factors, associated outbreaks, predictive factors and preventative measures were extracted and synthesized. We identified 4,295 articles, of which 347 were included; dates of publications ranged from 1937 to 2022. Refugees were the most common population investigated (75%). Migration pathways of displaced populations increased over time towards a more complex web, involving migration in dual directions. The most frequent pathogen investigated was Schistosoma spp. (n = 99 articles). Disease outbreaks were reported in 46 publications (13.3%), with viruses being the most commonly reported pathogen type. Limited access to hygiene/sanitation, crowding and refugee status were the most commonly discussed predictors of infection. Vaccination/prophylaxis drug administration, surveillance/screening and improved hygiene/sanitation were the most commonly discussed preventative measures. The current research on zoonoses in displaced populations displays gaps in the spectrum of pathogens studied, as well as in the (sub)populations investigated. Future studies should be more inclusive of One Health approaches to adequately investigate the impact of zoonotic pathogens and identify transmission pathways as a basis for designing interventions for displaced populations.

A Stochastic Semi-Parametric SEIR Model with Infectivity in an Incubation Period

This paper introduces stochastic disturbances into a semi-parametric SEIR model with infectivity in an incubation period. The model combines the randomness of disease transmission and the nonlinearity of transmission rate, providing a flexible framework for more accurate description of the process of infectious disease transmission. On the basis of the discussion of the deterministic model, the stochastic semi-parametric SEIR model is studied. Firstly, we use Lyapunov analysis to prove the existence and uniqueness of global positive solutions for the model. Secondly, the conditions for disease extinction are established, and appropriate stochastic Lyapunov functions are constructed to discuss the asymptotic behavior of the model’s solution at the disease-free equilibrium point of the deterministic model. Finally, the specific transmission functions are enumerated, and the accuracy of the results are demonstrated through numerical simulations.

Capillary Condensation Mediated Fluidic Straining for Enhanced Bacterial Inactivation

AbstractBiomaterials capable of continuously inactivating pathogens are essential for suppressing transmission of infectious diseases, such as epidemic cerebrospinal meningitis and pulmonary tuberculosis. Here, capillary condensation of air moisture within nano‐confined spaces between superhydrophilic rigid nanorods is shown and target microbiology spontaneously stretch and inactivate aerosolized microorganisms. Specifically, the negative Gaussian curvature‐shaped water condensate causes fluidic straining, comprising surface tension and Laplace pressure, strong enough to deform and eliminate the selected bacteria. Plate counting quantifies the sharply reduced contact‐killing period for superhydrophilic and bare nanorods (6 vs 100 min for E. coli, 20 vs 120 min for S. aureus) under relative humidity of 70%. Theoretical calculations and experimental studies indicate increased mechanical straining and mechano‐bactericidal by improving air moisture content. To further illustrate utility, long‐term antibacterial medical masks are fabricated by integrating such nanorods onto commercial fabrics. Collectively, these findings highlight the immense potential of capillary condensation‐induced fluidic straining as an eco‐friendly, broad‐spectrum, and highly efficient antibacterial strategy.

HOW TO REDUCE TRANSMISSION OF RESPIRATORY INFECTIOUS DISEASE IN INTERIOR SPACES: AN EMPIRICAL STUDY WITH INTERIOR DESIGN PROFESSIONALS

ABSTRACT This study was motivated by the need for empirical evidence to inform design guidelines for interior workspaces during the COVID-19 pandemic. This research had two goals: to identify the features of interior spaces and behaviors in Korea where many confirmed cases of COVID-19 were found; and to examine design professionals’ opinions on workplace management and operation to reduce transmission of respiratory infectious disease. A content analysis of newspaper articles on confirmed cases was conducted and a survey was administered to design professionals. The analysis identified common features of the interior spaces with confirmed cases of COVID-19. Based on the analysis of the article contents, a questionnaire was constructed. The questionnaire asked design professionals to suggest interior design considerations that could prevent the spread of the virus in interior spaces. They emphasized the separation of individual spaces from shared spaces; installing partitions in rooms that could not be divided; ending two-way traffic in narrow hallways; reducing room density and avoiding crowding; adopting touchless technologies and no-touch access to interior spaces; automating interior equipment and facilities; and encouraging office users to work from home if possible. These findings should be factored into interior space planning and management to reduce the risk of exposing future users of these spaces to infectious respiratory diseases.

Social contacts patterns relevant to the transmission of infectious diseases in Suzhou, China following the COVID-19 epidemic

BackgroundThe COVID-19 pandemic has profoundly affected human social contact patterns, but there is limited understanding regarding the post-pandemic social contact patterns. Our objective is to quantitatively assess social contact patterns in Suzhou post-COVID-19.MethodsWe employed a diary design and conducted social contact surveys from June to October 2023, utilizing paper questionnaires. A generalized linear model was utilized to analyze the relationship between individual contacts and covariates. We examined the proportions of contact type, location, duration, and frequency. Additionally, age-related mixed matrices were established.ResultsThe participants reported an average of 11.51 (SD 5.96) contact numbers and a total of 19.78 (SD 20.94) contact numbers per day, respectively. The number of contacts was significantly associated with age, household size, and the type of week. Compared to the 0–9 age group, those in the 10–19 age group reported a higher number of contacts (IRR = 1.12, CI: 1.01–1.24), while participants aged 20 and older reported fewer (IRR range: 0.54–0.67). Larger households (5 or more) reported more contacts (IRR = 1.09, CI: 1.01–1.18) and fewer contacts were reported on weekends (IRR = 0.95, CI: 0.90–0.99). School had the highest proportion of contact durations exceeding 4 h (49.5%) and daily frequencies (90.4%), followed by home and workplace. The contact patterns exhibited clear age-assortative mixing, with Q indices of 0.27 and 0.28.ConclusionsWe assessed the characteristics of social contact patterns in Suzhou, which are essential for parameterizing models of infectious disease transmission. The high frequency and intensity of contacts among school-aged children should be given special attention, making school intervention policies a crucial component in controlling infectious disease transmission.

Temporal shifts in 24 notifiable infectious diseases in China before and during the COVID-19 pandemic

The coronavirus disease 2019 (COVID-19) pandemic, along with the implementation of public health and social measures (PHSMs), have markedly reshaped infectious disease transmission dynamics. We analysed the impact of PHSMs on 24 notifiable infectious diseases (NIDs) in the Chinese mainland, using time series models to forecast transmission trends without PHSMs or pandemic. Our findings revealed distinct seasonal patterns in NID incidence, with respiratory diseases showing the greatest response to PHSMs, while bloodborne and sexually transmitted diseases responded more moderately. 8 NIDs were identified as susceptible to PHSMs, including hand, foot, and mouth disease, dengue fever, rubella, scarlet fever, pertussis, mumps, malaria, and Japanese encephalitis. The termination of PHSMs did not cause NIDs resurgence immediately, except for pertussis, which experienced its highest peak in December 2023 since January 2008. Our findings highlight the varied impact of PHSMs on different NIDs and the importance of sustainable, long-term strategies, like vaccine development.

Development of a protocol for using geo-trackers to identify zoonotic enteric pathogen transmission pathways in a pilot study in Kenya

Abstract Humans and animals can be exposed to fecally-transmitted pathogens in both private and public domain environments. Animals may also acquire pathogen infections from these two environments and transmit them to humans through different pathways. Evidence on how often and where interactions occur between the two environments could improve the effectiveness of public health programs for preventing zoonotic disease transmission and response to disease outbreaks. This study aimed to develop a protocol for using geo-trackers to measure the spatial-temporal movement and interaction between animals and children in households and public areas in low- and middle-income categories of urban neighbourhoods in Kenya. It also aimed to identify opportunities and challenges for the scale-up of these methods’ for surveillance of other zoonotic diseases of public health significance. One commercial geo-tracker device with the best technological performance and usability that met pre-defined criteria for the study context was identified. Community engagement meetings were then conducted to gather input on a proposed study protocol. Afterwards, infants and animals were geo-tracked in 10 households in urban informal settlements of Kibera and Jericho, Nairobi over two consecutive weeks with iterative improvements to protocols. The effectiveness of the geo-tracking exercise was evaluated through in-depth interviews with Community Health Volunteers (CHVs) and infant caregivers. Animal and infant behaviour and battery reliability of the geo-trackers were also monitored; and observed opportunities and challenges in implementing the protocol during the exercise were documented. Community members were receptive and accepted the use of geo-trackers on animals and children. In pilot testing, there was no change of behaviour from 10 infants tracked. Discomfort was observed for up to 30 min after the placement for some of the seven animals tracked, but the animals quickly adjusted. The battery for all geo-tracker devices lasted for the 24-h geo-tracking period. Some caregivers and CHVs were concerned whether the geo-trackers could record personal information. It was shown that geo-tracker devices can be successfully deployed to study animal-child interactions and movement in different categories of urban neighbourhoods. Recommendations have been made on the lessons learnt from the study to help scientists who would use geo-trackers for future community-based human and animal research. One Health impact statement Assessing human and animal risks of acquiring enteric infections from environmental contamination, or contributing to pathogen contamination of the environment requires understanding spatial-temporal patterns of human and animal movement between private households and the community. Movement of domestic animals is relevant for understanding household-community spatial patterns of pathogen transmission because animal ownership and contact with humans is common, and free-roaming animals carrying enteric pathogens can spread diverse faecal pathogens between environments. The community-based participatory research approach of this study evaluated implementation feasibility from the lens of technical usability and reliability of geo-tracking devices, as well as social acceptability and ethics related to using such devices for the community-based study of human and animal subjects in urban settings. Evidence and recommendations from this study will be useful to anyone interested in understanding human-animal-environment interactions and their contributions to infectious disease transmission.

Epidemiological and health economic implications of symptom propagation in respiratory pathogens: A mathematical modelling investigation.

Respiratory pathogens inflict a substantial burden on public health and the economy. Although the severity of symptoms caused by these pathogens can vary from asymptomatic to fatal, the factors that determine symptom severity are not fully understood. Correlations in symptoms between infector-infectee pairs, for which evidence is accumulating, can generate large-scale clusters of severe infections that could be devastating to those most at risk, whilst also conceivably leading to chains of mild or asymptomatic infections that generate widespread immunity with minimal cost to public health. Although this effect could be harnessed to amplify the impact of interventions that reduce symptom severity, the mechanistic representation of symptom propagation within mathematical and health economic modelling of respiratory diseases is understudied. We propose a novel framework for incorporating different levels of symptom propagation into models of infectious disease transmission via a single parameter, α. Varying α tunes the model from having no symptom propagation (α = 0, as typically assumed) to one where symptoms always propagate (α = 1). For parameters corresponding to three respiratory pathogens-seasonal influenza, pandemic influenza and SARS-CoV-2-we explored how symptom propagation impacted the relative epidemiological and health-economic performance of three interventions, conceptualised as vaccines with different actions: symptom-attenuating (labelled SA), infection-blocking (IB) and infection-blocking admitting only mild breakthrough infections (IB_MB). In the absence of interventions, with fixed underlying epidemiological parameters, stronger symptom propagation increased the proportion of cases that were severe. For SA and IB_MB, interventions were more effective at reducing prevalence (all infections and severe cases) for higher strengths of symptom propagation. For IB, symptom propagation had no impact on effectiveness, and for seasonal influenza this intervention type was more effective than SA at reducing severe infections for all strengths of symptom propagation. For pandemic influenza and SARS-CoV-2, at low intervention uptake, SA was more effective than IB for all levels of symptom propagation; for high uptake, SA only became more effective under strong symptom propagation. Health economic assessments found that, for SA-type interventions, the amount one could spend on control whilst maintaining a cost-effective intervention (termed threshold unit intervention cost) was very sensitive to the strength of symptom propagation. Overall, the preferred intervention type depended on the combination of the strength of symptom propagation and uptake. Given the importance of determining robust public health responses, we highlight the need to gather further data on symptom propagation, with our modelling framework acting as a template for future analysis.

Autonomous and policy-induced behavior change during the COVID-19 pandemic: Towards understanding and modeling the interplay of behavioral adaptation.

Changes in human behaviors, such as reductions of physical contacts and the adoption of preventive measures, impact the transmission of infectious diseases considerably. Behavioral adaptations may be the result of individuals aiming to protect themselves or mere responses to public containment measures, or a combination of both. What drives autonomous and policy-induced adaptation, how they are related and change over time is insufficiently understood. Here, we develop a framework for more precise analysis of behavioral adaptation, focusing on confluence, interactions and time variance of autonomous and policy-induced adaptation. We carry out an empirical analysis of Germany during the fall of 2020 and beyond. Subsequently, we discuss how behavioral adaptation processes can be better represented in behavioral-epidemiological models. We find that our framework is useful to understand the interplay of autonomous and policy-induced adaptation as a "moving target". Our empirical analysis suggests that mobility patterns in Germany changed significantly due to both autonomous and policy-induced adaption, with potentially weaker effects over time due to decreasing risk signals, diminishing risk perceptions and an erosion of trust in the government. We find that while a number of simulation and prediction models have made great efforts to represent behavioral adaptation, the interplay of autonomous and policy-induced adaption needs to be better understood to construct convincing counterfactual scenarios for policy analysis. The insights presented here are of interest to modelers and policy makers aiming to understand and account for behaviors during a pandemic response more accurately.

Evaluating Seasonal Variations in Human Contact Patterns and Their Impact on the Transmission of Respiratory Infectious Diseases.

Human contact patterns are a key determinant driving the spread of respiratory infectious diseases. However, the relationship between contact patterns and seasonality as well as their possible association with the seasonality of respiratory diseases is yet to be clarified. We investigated the association between temperature and human contact patterns using data collected through a cross-sectional diary-based contact survey in Shanghai, China, between December 24, 2017, and May 30, 2018. We then developed a compartmental model of influenza transmission informed by the derived seasonal trends in the number of contacts and validated it against A(H1N1)pdm09 influenza data collected in Shanghai during the same period. We identified a significant inverse relationship between the number of contacts and the seasonal temperature trend defined as a spline interpolation of temperature data (p = 0.003). We estimated an average of 16.4 (95% PrI: 15.1-17.5) contacts per day in December 2017 that increased to an average of 17.6 contacts (95% PrI: 16.5-19.3) in January 2018 and then declined to an average of 10.3 (95% PrI: 9.4-10.8) in May 2018. Estimates of influenza incidence obtained by the compartmental model comply with the observed epidemiological data. The reproduction number was estimated to increase from 1.24 (95% CI: 1.21-1.27) in December to a peak of 1.34 (95% CI: 1.31-1.37) in January. The estimated median infection attack rate at the end of the season was 27.4% (95% CI: 23.7-30.5%). Our findings support a relationship between temperature and contact patterns, which can contribute to deepen the understanding of the relationship between social interactions and the epidemiology of respiratory infectious diseases.

Tuning the Topography of Non‐Wetting Surfaces to Reduce Short‐Term Microbial Contamination Within Hospitals

AbstractMicrobial contamination of hospital surfaces is a major contributor to infectious disease transmission. This work demonstrates that superhydrophobic (Cassie‐Baxter) micro post topographies can significantly reduce cell attachment compared to flat controls. For ordered micro post arrays (post diameters 0.3 to 150 µm), the attachment of four pathogens (Pseudomonas aeruginosa, Staphylococcus aureus, Escherichia coli, and Candida albicans) from discrete contaminant droplets upon short‐term contact (15 s to 30 min) are assessed. There is a 3‐4‐log decrease in microbial attachment when reducing the micro posts diameters from 150 to 0.3 µm for all strains, with large posts (>20 µm) exhibiting similar attachment rates to flat controls. The critical, maximum feature size to prevent attachment can be tuned depending on the ratio of the cell size to post diameter. Two potential mechanisms are discussed for this size effect. First, application of the random sequential adsorption model shows that this relative post/cell size effect may be due to a reduced probability of attachment, which is theorized to be the dominant mechanism. Alternatively, a physical model is suggested for bacterial cell “pull‐off” due to surface tension forces during droplet dewetting. This work may be important for the design of non‐wetting antimicrobial surfaces within healthcare environments.

Managing risk of infectious disease transmission at religious mass gatherings: Insights from survey, COVID-19 PCR, and antibody tests from Arbaeen walkers in 2020.

Arbaeen in Iraq has been one of the largest mass gatherings during the COVID-19 pandemic with 14.5 million attendees in 2020. We set out to assess the prevalence of current or past COVID-19 among 2020 Arbaeen participants, and establish associations between COVID-19 test results, symptoms, and known recent exposure. This was a cross-sectional study involving participants who joined Arbaeen walk in Iraq in October 2020. COVID-19 PCR and/or rapid antibody test were conducted among consented participants. A short questionnaire was administered. Rapid antibody testing was done onsite. Nasal and throat swab samples were transferred to the laboratory for PCR testing. A total of 835 (88.3% male; 11.7% female) participants were recruited. The most common symptom overall was cough (9.6%) followed by sore throat, fever, and loss of taste/smell (6.6%, 5.5%, and 5.0%, respectively). One in five (20.3%) participants reported close contact with a confirmed COVID-19 case in the past 14 days. Of the 237 participants with a PCR test, 18 (7.6%) were positive. Of the 765 participants with rapid antibody test, 19.3% tested positive for IgM, 39.3% for IgG, and 16.4% for both. Approximately 40% of the participants had evidence of current or past COVID-19 infection based on antibody and PCR. The almost 1 in 10 COVID-19 cases within such a multimillion person gathering, illustrates the difficulty in limiting the participation of infectious individuals in religious mass gatherings. There is a pressing need to explore measures to reduce the risk of transmission of infectious diseases at major mass gathering events.

UV-mediated photochemical synthesis and investigation of the antiviral properties of Silver nanoparticle-polyvinyl butyral nanocomposite coatings as a novel antiviral material with high stability and activity

Effectively developing new antimicrobial surfaces for viral diseases requires considerable research, money, and time. Moreover, new species of microorganisms and pathogens are constantly appearing or entering from other regions, which can cause epidemics or pandemics. The ongoing presence of SARS-CoV-2 underscores the need to develop new antimicrobial materials. In this context, a novel UV-irradiated photochemical in-situ synthesis method is introduced for producing durable, long-lasting antiviral silver-polymer (AgNP-PVB) nanocomposite coatings. These coatings are intended to mitigate infectious disease transmission across various frequently touched surfaces, such as door handles, keypads, bank encoders, telephone locks, lift buttons, etc. Additionally, the significance of the size and concentration of AgNP in influencing the physical and antiviral properties of these nanocomposite coatings is illustrated. Detailed studies of AgNP-PVB coatings were conducted using X-ray diffraction, Raman spectroscopy, atomic force microscopy (AFM), and ultraviolet-visible-near-infrared spectroscopy, and contact angle measurements. The antiviral properties of the coatings were evaluated by a one-step reverse transcription real-time polymerase chain reaction (one-step qRT‒PCR) using synthetic SARS-CoV-2 RNA. Raman spectra signatures confirm AgNPs in the PVB matrix by matching identified peaks in X-ray diffractograms. AFM analysis revealed a reduction in AgNP size in the nanocomposite with an increase in the irradiation duration from 5 to 30 min. Spectroscopic results corresponding to AFM measurements highlighted specific wavelengths related to different AgNP size ranges. Contact angle measurements suggest that antiviral activity can be predicted by calculating the surface free energy (SFE) of the sample. As the SFE value increases, antiviral activity decreases. Nanocomposite coatings (with concentrations of 150, 200, 500, and 1000 ppm AgNP) are effective in reducing the activity of SARS-CoV-2, indicating their potential as long-acting preventive agents against viral infections. A methodology incorporating a specialized algorithm was devised for the application of the investigated coatings, which also integrates 3D scanning and printing techniques for fabricating complex geometry flexible protective cover. Subsequently, this coating was applied to produce a protective cover for the widely utilized public object, the door handle, employing 3D printing technology. As a result of the work, a long-term, durable antiviral AgNP-PVB nanocomposite coating with varying AgNP sizes (ranging from 15 to 118 nm) and concentrations (150, 200, 500, and 1000 ppm) was successfully developed.

Bayesian workflow for time-varying transmission in stratified compartmental infectious disease transmission models.

Compartmental models that describe infectious disease transmission across subpopulations are central for assessing the impact of non-pharmaceutical interventions, behavioral changes and seasonal effects on the spread of respiratory infections. We present a Bayesian workflow for such models, including four features: (1) an adjustment for incomplete case ascertainment, (2) an adequate sampling distribution of laboratory-confirmed cases, (3) a flexible, time-varying transmission rate, and (4) a stratification by age group. Within the workflow, we benchmarked the performance of various implementations of two of these features (2 and 3). For the second feature, we used SARS-CoV-2 data from the canton of Geneva (Switzerland) and found that a quasi-Poisson distribution is the most suitable sampling distribution for describing the overdispersion in the observed laboratory-confirmed cases. For the third feature, we implemented three methods: Brownian motion, B-splines, and approximate Gaussian processes (aGP). We compared their performance in terms of the number of effective samples per second, and the error and sharpness in estimating the time-varying transmission rate over a selection of ordinary differential equation solvers and tuning parameters, using simulated seroprevalence and laboratory-confirmed case data. Even though all methods could recover the time-varying dynamics in the transmission rate accurately, we found that B-splines perform up to four and ten times faster than Brownian motion and aGPs, respectively. We validated the B-spline model with simulated age-stratified data. We applied this model to 2020 laboratory-confirmed SARS-CoV-2 cases and two seroprevalence studies from the canton of Geneva. This resulted in detailed estimates of the transmission rate over time and the case ascertainment. Our results illustrate the potential of the presented workflow including stratified transmission to estimate age-specific epidemiological parameters. The workflow is freely available in the R package HETTMO, and can be easily adapted and applied to other infectious diseases.

Ptičja influenca u divljih kanida

The risk of cross-species transmission of infectious diseases and zoonoses has increased due to the adaptive evolution of pathogens and anthropogenic landscape changes. A current example is the avian influenza (AI) virus, which can infect not only avian species but also mammals. In these species, infections are often associated with severe neurological symptoms. AI viruses are primarily not well adapted to mammalian hosts and are not efficiently transmitted among them. To accomplish this, AI viruses must acquire adaptations or mutations that contribute to replication efficiency and virulence in mammals. The exact combination and interaction of mutations that result in optimal adaptation to mammals is still unknown and may vary between host species and virus subtypes. The globally increasing number of infected birds with highly pathogenic AI (HPAI) increases the likelihood of contact between birds and mammals, especially wildlife. One reason for the adaptation of HPAI to mammals is theexposure of wild mammals to infected birds or their carcasses. According to the current data, wild canids, such as red foxes, are among the most infected mammals. However, infections caused by neurotropic viruses, as well as HPAI, have been scarcely studied or not at all in jackals. Since jackals are scavengers that have spread rapidly in Europe and Croatia in recent years, surveillance of AI virus infection in these canids is of the utmost importance. Furthermore, interactions between wild carnivores and domestic animals are of concern, as infections with HPAI pose a public health threat due to the increased risk of mammalian adaptation.

Long-Term Effects of Assisted Reproductive Technologies on the Health and Productivity of Animals in Ethiopia

Purpose: The aim of the study was to long-term effects of assisted reproductive technologies on the health and productivity of animals in Ethiopia. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The study found that the long-term effects of assisted reproductive technologies (ARTs) on the health and productivity of animals in Ethiopia present both opportunities and challenges. ARTs have the potential to improve livestock breeding programs, enhance genetic diversity, and increase productivity, their implementation requires careful consideration of various factors to ensure sustainable outcomes. While these technologies offer the possibility of overcoming reproductive challenges and genetic limitations, they may also pose risks such as increased rates of reproductive disorders, stress associated with handling and manipulation, and potential transmission of infectious diseases. Therefore, ongoing monitoring and evaluation of animal health and welfare are essential to mitigate any adverse effects and ensure the ethical use of ARTs in livestock production systems. Unique Contribution to Theory, Practice and Policy: Life course theory & epigenetic theory may be used to anchor future studies on long-term effects of assisted reproductive technologies on the health and productivity of animals in Ethiopia. Implement rigorous monitoring and evaluation programs to assess the long-term health, welfare, and productivity outcomes of animals produced through ART. Utilize comprehensive datasets to track indicators such as disease incidence, reproductive performance, growth rates, and longevity over multiple generations. Develop evidence-based guidelines and regulations governing the ethical and responsible use of ART in animal breeding programs. Establish standards for the welfare, monitoring, and management of animals produced through reproductive technologies to ensure compliance with ethical principles and animal welfare standards.

A Markov chain-based approach for assessing respiratory infection risk in a multi-zone office building

Most respiratory infectious disease transmission events occur in indoor environments, and examining the infection risk in different types of multi-zone buildings is critical to the safe reopening and use of public buildings. Appropriate space design influences occupant behavior and virus spread, thereby aiding in mitigating indoor infection risk. This study aims to quickly evaluate the multi-route infection risk in multi-zone buildings with relatively stable occupant populations, and to quantify the effectiveness of spatial interventions at different levels. A Markov chain-based approach was proposed to characterize occupants' time-activity trajectories with low time cost and relatively high accuracy. Four transmission routes are considered, especially for the fine-grained characterization of close contact. A real university office building was selected as a case study to quantitatively evaluate the effects of three non-pharmacological interventions including spatial layout, ventilation, and occupant behavioral control. Results showed that short-range airborne transmission dominated, and optimized combination spatial design interventions reduced the indoor infection risk by up to 10 %. Zone layout intervention was the most effective, with the division of the open-plan office area into three subzones, reducing the risk by 9.6 %, which was superior to the intervention of maintaining a one-meter interpersonal distance. Followed by the furniture layout, without changing the seating capacity and without desktop baffles, the L-shaped table layout worked better reducing the risk by 2.78 %. This study can help architects and managers better understand the risk of indoor transmission in multizone buildings from a spatial design perspective, to select appropriate interventions to reduce the risk.

The emergence and regression of political priority for refugee integration into the Jordanian health system: an analysis using the Kingdon’s multiple streams model

BackgroundThe prolonged presence of Syrian refugees in Jordan has highlighted the need for sustainable health service delivery models for refugees. In 2012, the Jordanian government adopted a policy that granted Syrian refugees access, free of charge, to the national health system. However since 2012, successive policy revisions have limited refugee access. This paper seeks to understand factors that initially put refugee integration into the health system on the policy agenda, as well as how these same factors later affected commitment to sustain the policy.MethodsThis paper draws on data from a document review of 197 peer-reviewed and grey literature publications, a media analysis of newspaper articles retrieved from four officially recognized newspapers in Jordan, and 33 semi-structured key informant interviews. We used Kingdon’s Multiple Streams Model – a well-established tool for analyzing policy adoption – to understand how political priority developed for integration of refugees into the health system.ResultsWe find that several factors helped bring attention to the issue, namely concerns over infectious disease transmission to host communities, high rates of chronic conditions among the refugee population and the increasingly urban and dispersed nature of refugees. At the outset of the conflict, the national mood was receptive to refugees. Politicians and government officials quickly recognized the crisis as an opportunity to secure material and technical support from the international humanitarian community. At the same time, global pressures for integrating refugees into national health systems helped move the integration agenda forward in Jordan and the region more broadly. Since 2012, there were several modifications to the policy that signal profound changes in national views around the continued presence of Syrian refugees in the country, as well as reduced external financial support which has undermined the sustainability of the policy.ConclusionThis case study underscores the dynamic nature of policymaking and the challenge of sustaining government commitment to the right to health among refugees. Our analysis has important implications for advocates seeking to advance and maintain momentum for the integration of refugees into national health systems.

Lineage frequency time series reveal elevated levels of genetic drift in SARS-CoV-2 transmission in England.

Genetic drift in infectious disease transmission results from randomness of transmission and host recovery or death. The strength of genetic drift for SARS-CoV-2 transmission is expected to be high due to high levels of superspreading, and this is expected to substantially impact disease epidemiology and evolution. However, we don't yet have an understanding of how genetic drift changes over time or across locations. Furthermore, noise that results from data collection can potentially confound estimates of genetic drift. To address this challenge, we develop and validate a method to jointly infer genetic drift and measurement noise from time-series lineage frequency data. Our method is highly scalable to increasingly large genomic datasets, which overcomes a limitation in commonly used phylogenetic methods. We apply this method to over 490,000 SARS-CoV-2 genomic sequences from England collected between March 2020 and December 2021 by the COVID-19 Genomics UK (COG-UK) consortium and separately infer the strength of genetic drift for pre-B.1.177, B.1.177, Alpha, and Delta. We find that even after correcting for measurement noise, the strength of genetic drift is consistently, throughout time, higher than that expected from the observed number of COVID-19 positive individuals in England by 1 to 3 orders of magnitude, which cannot be explained by literature values of superspreading. Our estimates of genetic drift suggest low and time-varying establishment probabilities for new mutations, inform the parametrization of SARS-CoV-2 evolutionary models, and motivate future studies of the potential mechanisms for increased stochasticity in this system.