Targeted mutagenesis in Anaplasma marginale to define virulence and vaccine development against bovine anaplasmosis.

Tick-borne Anaplasma species are obligate, intracellular, bacterial pathogens that cause important diseases globally in people, agricultural animals, and dogs. Targeted mutagenesis methods are yet to be developed to define genes essential for these pathogens. In addition, vaccines conferring protection against diseases caused by Anaplasma species are not available. Here, we describe a targeted mutagenesis method for deletion of the phage head-to-tail connector protein (phtcp) gene in Anaplasma marginale. The mutant did not cause disease and exhibited attenuated growth in its natural host (cattle). We then assessed its ability to confer protection against wild-type A. marginale infection challenge. Additionally, we compared vaccine protection with the mutant to that of whole cell A. marginale inactivated antigens as a vaccine (WCAV) candidate. Upon infection challenge, non-vaccinated control cattle developed severe disease, with an average 57% drop in packed cell volume (PCV) between days 26-31 post infection, an 11% peak in erythrocytic infection, and apparent anisocytosis. Conversely, following challenge, all animals receiving the live mutant did not develop clinical signs or anemia, or erythrocyte infection. In contrast, the WCAV vaccinees developed similar disease as the non-vaccinees following A. marginale infection, though the peak erythrocyte infection reduced to 6% and the PCV dropped 43%. This is the first study describing targeted mutagenesis and its application in determining in vivo virulence and vaccine development for an Anaplasma species pathogen. This study will pave the way for similar research in related Anaplasma pathogens impacting multiple hosts.

Ancestral Origin and Dissemination Dynamics of Reemerging Toxigenic Vibrio cholerae, Haiti.

The 2010 cholera epidemic in Haiti was thought to have ended in 2019, and the Prime Minister of Haiti declared the country cholera-free in February 2022. On September 25, 2022, cholera cases were again identified in Port-au-Prince. We compared genomic data from 42 clinical Vibrio cholerae strains from 2022 with data from 327 other strains from Haiti and 1,824 strains collected worldwide. The 2022 isolates were homogeneous and closely related to clinical and environmental strains circulating in Haiti during 2012-2019. Bayesian hypothesis testing indicated that the 2022 clinical isolates shared their most recent common ancestor with an environmental lineage circulating in Haiti in July 2018. Our findings strongly suggest that toxigenic V. cholerae O1 can persist for years in aquatic environmental reservoirs and ignite new outbreaks. These results highlight the urgent need for improved public health infrastructure and possible periodic vaccination campaigns to maintain population immunity against V. cholerae.

Using spatial video geonarratives to improve nursing care for people who use drugs and experience homelessness: A methodology for nurses.

BACKGROUND: People who are insecurely housed and use drugs are disproportionately affected by drug poisonings. Nurses are uniquely positioned to utilize harm reduction strategies to address the needs of the whole person. Needle debris encompasses drug paraphernalia discarded in public spaces. Studying needle debris provides a strategic opportunity to identify where drugs are being used and target public health strategies accordingly. AIM: Our aim in this article is to illustrate how spatial video geonarratives (SVG) combined GPS technology interviews, and videos of locations with needle debris, can elicit valuable data for nursing research. METHODS: Using SVG required knowledge of how to collect data wearing cameras and practice sessions were necessary. A Miufly camera worn at waist height on a belt provided the stability to walk while interviewing stakeholders. We wore the cameras and conducted go-along interviews with outreach workers, while filming the built environment. Upon completion of data collection, both the interview and GPS information were analysed using Wordmapper software. CONCLUSIONS: This methodology resulted in data presented uniquely in both a visual map and narrative. These data were richer than if a single modality had been used. These data highlighted specific contextual factors that were related to the location of needle debris, which created opportunities for nursing interventions to support people experiencing vulnerability.

Disparities in Pediatric Orthopedic Surgery Care During the COVID-19 Pandemic Pre-vaccine and Post-Vaccine Availability.

BACKGROUND: The COVID-19 pandemic has led to significant disruptions in medical care, resulting in an estimated 40% of US adults avoiding care. However, the return to baseline health care utilization following COVID-19 restrictions within the pediatric orthopedic population remains unexplored. We sought to analyze the visit volume and demographics of pediatric orthopedic patients at 3 timepoints: prepandemic (2019), pandemic (2020), and pandemic post-vaccine availability (2021), to determine the impact of COVID-19 restrictions on our single-center, multisite institution. METHODS: We performed a retrospective cohort study of 6318 patients seeking treatment at our institution from May through August in 2019, 2020, and 2021. Patient age, sex, address, encounter date, and ICD-10 codes were obtained. Diagnoses were classified into fractures and dislocations, non-fracture-related trauma, sports, elective, and other categories. Geospatial analysis comparing incidence and geospatial distribution of diagnoses across the time periods was performed and compared with the Centers for Disease Control (CDC) social vulnerability index (SVI). RESULTS: The total number of pediatric orthopedic visits decreased by 22.2% during the pandemic ( P <0.001) and remained 11.6% lower post-vaccine availability compared with prepandemic numbers ( P <0.001). There was no significant difference in age ( P =0.097) or sex ( P =0.248) of the patients across all 3 timepoints; however, patients seen during the pandemic were more often White race (67.7% vs. 59.3%, P <0.001). Post-vaccine availability, trauma visits increased by 18.2% ( P <0.001) and total fractures remained 13.4% lower than prepandemic volume ( P <0.001). Sports volume decreased during the pandemic but returned to prepandemic volume in the post-vaccine availability period ( P =0.298). Elective visits did not recover to prepandemic volume and remained 13.0% lower compared with baseline ( P <0.001). Geospatial analysis of patient distribution illustrated neighborhood trends in access to care during the COVID-19 pandemic, with fewer patients from high SVI and low socioeconomic status neighborhoods seeking fracture care during the pandemic than prepandemic. Post-vaccine availability, fracture population distribution resembled prepandemic levels, suggesting a return to baseline health care utilization. CONCLUSION: Pediatric orthopedic surgery visit volume broadly decreased during the COVID-19 pandemic and did not return to prepandemic levels. All categories increased in the post-vaccine availability time point except elective visits. Geospatial analysis revealed that neighborhoods with a high social vulnerability index (SVI) were associated with decreased fracture visits during the pandemic, whereas low SVI neighborhoods did not experience as much of a decline. Future research is needed to study these neighborhood trends and more completely characterize factors preventing equitable access to care in the pediatric orthopedic population. LEVEL OF EVIDENCE: Retrospective Study, Level III.

[Improving access to maternities: a key challenge in low-resource settings]. / Améliorer l'accès aux maternités : un enjeu clé lorsque les ressources manquent.

In low- and middle-income countries, pregnant women face considerable challenges in accessing emergency obstetric and neonatal care services. Several factors contribute to this, such as insufficient availability of services, their inadequate geographical distribution, and a lack of qualified staff and infrastructure. The United Nations Population Fund, in collaboration with the University of Geneva, has deployed an innovative approach in 14 countries to optimise service quality and geographical accessibility. This approach has formed the basis for a new global indicator contributing to the reduction of maternal mortality. Calculating this indicator requires various types of data, going beyond traditional indicators, but allowing for a more comprehensive consideration of the different facets of access to services.

Dans les pays à revenu faible ou intermédiaire, les femmes enceintes sont confrontées à des défis importants pour accéder aux services obstétricaux et néonatals d'urgence. Plusieurs facteurs y contribuent, tels qu'une disponibilité insuffisante des services, leur répartition géographique inadéquate et un manque de personnel qualifié ainsi que d'infrastructure. Le Fonds des Nations Unies pour la population, en collaboration avec l'Université de Genève, a déployé dans 14 pays une approche innovante optimisant la qualité des services et l'accessibilité géographique. Elle a été la base d'un nouvel indicateur global participant à la réduction de la mortalité maternelle. Le calcul de cet indicateur requiert des données allant au-delà des indicateurs classiques, permettant une meilleure considération des différentes facettes de l'accès aux services.

Effect of bupivacaine liposome suspension administered as a cornual nerve block on indicators of pain and distress during and after cautery dehorning in dairy calves.

Dehorning is performed on a high percentage of dairies worldwide. Concern about the negative effect of dehorning on animal welfare has contributed to the development of new guidelines that require the use of pain management at the time of disbudding in the United States. However, livestock producers are limited in how to address this requirement due to a lack of (1) approved analgesic drugs, (2) analgesic options that control pain for an extended duration, and (3) analgesic formulations that are practical for producers to administer. The objective of this study was to evaluate the effectiveness of bupivacaine liposome suspension, a novel, long-acting, local anesthetic formulation administered as a nerve block at dehorning, compared with current industry standard analgesic approaches using lidocaine nerve blocks alone or in combination with the nonsteroidal anti-inflammatory drug meloxicam. Fifty male Holstein calves, 10 to 14 wk of age, were enrolled and randomly assigned to 1 of 5 treatment groups before cautery dehorning as follows: (1) bupivacaine liposome suspension block, oral placebo (BUP); (2) lidocaine block, oral placebo (LID); (3) lidocaine block, oral meloxicam (1 mg/kg of body weight; LID + MEL); (4) saline block, oral placebo (CON); and (5) saline block, oral placebo, sham dehorn (SHAM). Biomarkers were collected from 0 to 120 h postdehorning and included infrared thermography, mechanical nociceptive threshold (MNT), pressure mat gait analysis, chute defense and behavior scoring, and blood sampling for serum cortisol and prostaglandin E2 metabolites. Responses were analyzed using repeated measures with calf nested in treatment designated as a random effect, and treatment, time, and their interaction designated as fixed effects. At 2 h postdehorning, the BUP group had a higher MNT compared with the CON group. Furthermore, at 24 h postdehorning, the BUP group had a higher MNT compared with the LID group. Gait distance differed significantly between treatment groups; the CON, LID, and LID + MEL groups had an increased gait distance relative to the SHAM group. The CON group exhibited a higher chute defense behavior score during the dehorning procedure compared with all other treatments. Furthermore, the CON group exhibited more ear flicks than the BUP and LID + MEL groups postdehorning. At 4 h and 24 h after dehorning, the LID + MEL group had a lower average prostaglandin E2 metabolites concentration compared with all other treatment groups. These data showed that administration of bupivacaine liposome suspension as a cornual nerve block at the time of dehorning was as effective at controlling pain as a multimodal approach of lidocaine and meloxicam.

Internal absorbing boundary conditions for closed-aperture wavefield decomposition in solid media with unknown interiors.

We present a method to create an internal numerical absorbing boundary within elastic solid media whose properties are largely unknown and use it to create the first wavefield separation method that retrieves all orders of outgoing elastic wavefield constituents for real data recorded on a closed free surface. The recorded data are injected into a numerical finite-difference (FD) simulation along a closed, transparent surface, and the new internal numerical absorbing boundary condition achieves high attenuation of the ingoing waves radiated from the injection surface. This internal wave absorption enables the data injection to radiate all outgoing waves for experimental domains that include arbitrary unknown scatterers in the interior. The injection-absorption-based separation scheme is validated using three-dimensional (3D) synthetic modeling and a real data experiment acquired using a 3D laser Doppler vibrometer on a granite rock. The wavefield separation method forms a key component of an elastic immersive wave experimentation laboratory, and the ability to numerically absorb ingoing scattered energy in an uncharacterized medium while still radiating the true outgoing energy is intriguing and may lead to other development and applications in the future.

Exploring convolutional neural networks and spatial video for on-the-ground mapping in informal settlements.

BACKGROUND: The health burden in developing world informal settlements often coincides with a lack of spatial data that could be used to guide intervention strategies. Spatial video (SV) has proven to be a useful tool to collect environmental and social data at a granular scale, though the effort required to turn these spatially encoded video frames into maps limits sustainability and scalability. In this paper we explore the use of convolution neural networks (CNN) to solve this problem by automatically identifying disease related environmental risks in a series of SV collected from Haiti. Our objective is to determine the potential of machine learning in health risk mapping for these environments by assessing the challenges faced in adequately training the required classification models. RESULTS: We show that SV can be a suitable source for automatically identifying and extracting health risk features using machine learning. While well-defined objects such as drains, buckets, tires and animals can be efficiently classified, more amorphous masses such as trash or standing water are difficult to classify. Our results further show that variations in the number of image frames selected, the image resolution, and combinations of these can be used to improve the overall model performance. CONCLUSION: Machine learning in combination with spatial video can be used to automatically identify environmental risks associated with common health problems in informal settlements, though there are likely to be variations in the type of data needed for training based on location. Success based on the risk type being identified are also likely to vary geographically. However, we are confident in identifying a series of best practices for data collection, model training and performance in these settings. We also discuss the next step of testing these findings in other environments, and how adding in the simultaneously collected geographic data could be used to create an automatic health risk mapping tool.

Identifying multiply scattered wavepaths in strongly scattering and dispersive media.

The ability to extract information from scattered waves is usually limited to singly scattered energy even if multiple scattering might occur in the medium. As a result, the information in arrival times of higher-order scattered events is underexplored. This information is extracted using fingerprinting theory. This theory has never previously been applied successfully to real measurements, particularly when the medium is dispersive. The theory is used to estimate the arrival times and scattering paths of multiply scattered waves in a thin sheet using an automated scheme in a dispersive medium by applying an additional dispersion compensation method. Estimated times and paths are compared with predictions based on a sequence of straight ray paths for each scattering event given the known scatterer locations. Additionally, numerical modelling is performed to verify the interpretations of the compensated data. Since the source also acts as a scatterer in these experiments, initially, the predictions and the numerical results did not conform to the experimental observations. By reformulating the theory and the processing scheme and adding a source scatterer in the modelling, it is shown that predictions of all observed scattering events are possible with both prediction methods, verifying that the methods are both effective and practically achievable.

Addressing the data guardian and geospatial scientist collaborator dilemma: how to share health records for spatial analysis while maintaining patient confidentiality.

BACKGROUND: The utility of being able to spatially analyze health care data in near-real time is a growing need. However, this potential is often limited by the level of in-house geospatial expertise. One solution is to form collaborative partnerships between the health and geoscience sectors. A challenge in achieving this is how to share data outside of a host institution's protection protocols without violating patient confidentiality, and while still maintaining locational geographic integrity. Geomasking techniques have been previously championed as a solution, though these still largely remain an unavailable option to institutions with limited geospatial expertise. This paper elaborates on the design, implementation, and testing of a new geomasking tool Privy, which is designed to be a simple yet efficient mechanism for health practitioners to share health data with geospatial scientists while maintaining an acceptable level of confidentiality. The basic premise of Privy is to move the important coordinates to a different geography, perform the analysis, and then return the resulting hotspot outputs to the original landscape. RESULTS: We show that by transporting coordinates through a combination of random translations and rotations, Privy is able to preserve location connectivity among spatial point data. Our experiments with typical analytical scenarios including spatial point pattern analysis and density analysis shows that, along with protecting spatial privacy, Privy maintains the spatial integrity of data which reduces information loss created due to data augmentation. CONCLUSION: The results from this study suggests that along with developing new mathematical techniques to augment geospatial health data for preserving confidentiality, simple yet efficient software solutions can be developed to enable collaborative research among custodians of medical and health data records and GIS experts. We have achieved this by developing Privy, a tool which is already being used in real-world situations to address the spatial confidentiality dilemma.

Compensating for source directivity in immersive wave experimentation.

A physical boundary mounted with active sources can cancel acoustic waves arriving at the boundary, and emit synthesized waves into the neighboring medium to fully control the acoustic wavefield in an experimental setup such as a water tank or air-filled cavity. Using the same principles, a physical experiment can be artificially immersed within an extended virtual (numerical) domain so that waves propagate seamlessly between the experimental setup and virtual domain. Such an immersive wave control experiment requires physical monopolar sources on the active boundary. However, real physical sources (e.g., piezoelectric transducers) project waves at middle-to-high sonic frequencies (e.g., 1-20 kHz) that do not fully conform to the theoretically required monopolar radiation pattern; if left uncorrected, this causes controlled wavefields to deviate from those desired in immersive experiments. A method is proposed to compensate for the non-monopole-like radiation patterns of the sources, and can be interpreted physically in terms of Huygens principle. The method is implemented as a pre-computation procedure that modifies the extrapolation Green's functions in the Kirchhoff-Helmholtz integral before the actual experiments take place. Two-dimensional finite-difference simulations show that the processing method can effectively suppress the undesired effect caused by non-monopolar active sources in immersive wave control experiments.

Breaking Out of Surveillance Silos: Integrative Geospatial Data Collection for Child Injury Risk and Active School Transport.

The preponderance of active school transport (AST) and child injury research has occurred independently, yet they are inherently related. This is particularly true in urban areas where the environmental context of AST may pose risks to safety. However, it can be difficult to make these connections due to the often segregated nature in which these veins of research operate. Spatial video presents a geospatial approach for simultaneous data collection related to both issues. This article reports on a multi-sector pilot project among researchers, a children's hospital, and a police department, using spatial video to map child AST behaviors; a geographic information system (GIS) is used to analyze these data in the environmental context of child pedestrian injury and community violence.

Uncertainty loops in travel-time tomography from nonlinear wave physics.

Estimating image uncertainty is fundamental to guiding the interpretation of geoscientific tomographic maps. We reveal novel uncertainty topologies (loops) which indicate that while the speeds of both low- and high-velocity anomalies may be well constrained, their locations tend to remain uncertain. The effect is widespread: loops dominate around a third of United Kingdom Love wave tomographic uncertainties, changing the nature of interpretation of the observed anomalies. Loops exist due to 2nd and higher order aspects of wave physics; hence, although such structures must exist in many tomographic studies in the physical sciences and medicine, they are unobservable using standard linearized methods. Higher order methods might fruitfully be adopted.

A space-time analysis of the WikiLeaks Afghan War Diary: a resource for analyzing the conflict-health nexus.

BACKGROUND: Although it is widely acknowledged that areas of conflict are associated with a high health burden, from a geospatial perspective it is difficult to establish these patterns at fine scales because of a lack of data. The release of the "WikiLeaks" Afghan War Diary (AWD) provides an interesting opportunity to advance analysis and theory into this interrelationship. METHODS: This paper will apply two different space time analyses to identify patterns of improvised explosive devices (IED) detonations for the period of 2004 to 2009 in Afghanistan. RESULTS: There is considerable spatial and temporal heterogeneity in IED explosions, with concentrations often following transportation links. The results are framed in terms of a resource for subsequent analyses to other existing health research in Afghanistan. To facilitate this, in our discussion we present a Google Earth file of overlapping rates that can be distributed to any researcher interested in combining his/her fine scale health data with a similarly granular layer of violence. CONCLUSION: The release of the AWD presents a previously unavailable opportunity to consider how spatially detailed data about violence can be incorporated into understanding, and predicting, health related spillover effects. The AWD can enrich previous research conducted on Afghanistan, and provide a justification for future "official" data sharing at appropriately fine scales.

Spatial video geonarratives and health: case studies in post-disaster recovery, crime, mosquito control and tuberculosis in the homeless.

BACKGROUND: A call has recently been made by the public health and medical communities to understand the neighborhood context of a patient's life in order to improve education and treatment. To do this, methods are required that can collect "contextual" characteristics while complementing the spatial analysis of more traditional data. This also needs to happen within a standardized, transferable, easy-to-implement framework. METHODS: The Spatial Video Geonarrative (SVG) is an environmentally-cued narrative where place is used to stimulate discussion about fine-scale geographic characteristics of an area and the context of their occurrence. It is a simple yet powerful approach to enable collection and spatial analysis of expert and resident health-related perceptions and experiences of places. Participants comment about where they live or work while guiding a driver through the area. Four GPS-enabled cameras are attached to the vehicle to capture the places that are observed and discussed by the participant. Audio recording of this narrative is linked to the video via time stamp. A program (G-Code) is then used to geotag each word as a point in a geographic information system (GIS). Querying and density analysis can then be performed on the narrative text to identify spatial patterns within one narrative or across multiple narratives. This approach is illustrated using case studies on post-disaster psychopathology, crime, mosquito control, and TB in homeless populations. RESULTS: SVG can be used to map individual, group, or contested group context for an environment. The method can also gather data for cohorts where traditional spatial data are absent. In addition, SVG provides a means to spatially capture, map and archive institutional knowledge. CONCLUSIONS: SVG GIS output can be used to advance theory by being used as input into qualitative and/or spatial analyses. SVG can also be used to gain near-real time insight therefore supporting applied interventions. Advances over existing geonarrative approaches include the simultaneous collection of video data to visually support any commentary, and the ease-of-application making it a transferable method across different environments and skillsets.

Automatic identification of multiply diffracted waves and their ordered scattering paths.

An automated algorithm uses recordings of acoustic energy across a spatially-distributed array to derive information about multiply scattered acoustic waves in heterogeneous media. The arrival time and scattering-order of each recorded diffracted acoustic wave, and the exact sequence of diffractors encountered by that wave, are estimated without requiring an explicit model of the medium through which the wave propagated. Individual diffractors are identified on the basis of their unique single-scattering relative travel-time curves (move-outs) across the array, and secondary (twice-scattered) waves are detected using semblance analysis along temporally offset primary move-outs. This information is sufficient to estimate travel times and scattering paths of all multiply diffracted waves of any order, and for these events to be identified in recorded data. The algorithm is applied to synthetic acoustic data sets from a variety of media, including different numbers of point-diffractors and a medium with strong heterogeneity and non-hyperbolic move-outs.

The post-disaster negative health legacy: pregnancy outcomes in Louisiana after Hurricane Andrew.

Disasters and displacement increasingly affect and challenge urban settings. How do pregnant women fare in the aftermath of a major disaster? This paper investigates the effect of pregnancies in disaster situations. The study tests a hypothesis that pregnant women residing in hurricane-prone areas suffer higher health risks. The setting is Louisiana in the Gulf Coast, United States, a state that continually experiences hurricane impacts. The time period for the analysis is three years following the landfall of Hurricane Andrew in 1992. We analysed low birth weight and preterm deliveries before and after landfall, as a whole and by race. Findings support an association between hazards and health of a community and indicate that pregnant women in the affected area, irrespective of race, are more likely to experience preterm deliveries compared to pre-event births. Results suggest there is a negative health legacy impact in Louisiana as a result of hurricane landfall.

Phase based venous suppression in resting-state BOLD GE-fMRI.

Resting-state functional MRI (RS-fMRI) is a widely used method for inferring connectivity between brain regions or nodes. As with task-based fMRI, the spatial specificity of the connectivity maps can be distorted by the strong biasing effect of the BOLD signal in macroscopic veins. In RS-fMRI this effect is exacerbated by the temporal coherences of physiological origin between large veins that are widely distributed in the brain. In gradient echo based EPI, used for the vast majority of RS-fMRI, macroscopic veins that carry BOLD-related changes exhibit a strong phase response. This allows for post-processing identification and removal of venous signals using a phase regressor technique. Here, we employ this approach to suppress macrovascular venous contributions in high-field whole-brain RS-fMRI data sets, resulting in significant changes to both the spatial localization of the networks and the correlations between the network nodes. These effects were observed at both the individual and group analysis level, suggesting that venous contamination is a confounding factor for RS-fMRI studies even at relatively low image resolutions. Suppression of the macrovascular signal using the phase regression approach may therefore help to better identify, delineate, and interpret the true structure of large-scale brain networks.

Household-level spatiotemporal patterns of incidence of cholera, Haiti, 2011.

A cholera outbreak began in Haiti during October, 2010. Spatiotemporal patterns of household-level cholera in Ouest Department showed that the initial clusters tended to follow major roadways; subsequent clusters occurred further inland. Our data highlight transmission pathway complexities and the need for case and household-level analysis to understand disease spread and optimize interventions.

Bayesian geochemical correlation and tomography.

To accurately reconstruct palaeoenvironmental change through time it is important to determine which rock samples were deposited contemporaneously at different sites or transects, as erroneous correlation may lead to incorrectly inferred processes and rates. To correlate samples, current practice interpolates geological age between datable units along each transect, then temporal signatures observed in geochemical logs are matched between transects. Unfortunately spatiotemporally variable and unknown rates of sedimentary deposition create highly nonlinear space-time transforms, significantly altering apparent geochemical signatures. The resulting correlational hypotheses are also untestable against independent transects, because correlations have no spatially-predictive power. Here we use geological process information stored within neural networks to correlate spatially offset logs nonlinearly and geologically. The same method creates tomographic images of geological age and geochemical signature across intervening rock volumes. Posterior tomographic images closely resemble the true depositional age throughout the inter-transect volume, even for scenarios with long hiatuses in preserved geochemical signals. Bayesian probability distributions describe data-consistent variations in the results, showing that centred summary statistics such as mean and variance do not adequately describe correlational uncertainties. Tomographic images demonstrate spatially predictive power away from geochemical transects, creating novel hypotheses attributable to each geochemical correlation which are testable against independent data.