The COVID-19 pandemic has caused a multi-scale impact on the world population that started from a nano-scale respiratory virus and led to the shutdown of macro-scale economies. Direct transmission of SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) and its variants through aerosolized droplets is a major contributor towards increasing cases of this infection. To curb the spread, one of the best engineered solutions is the use of face masks to prevent the passage of infectious saliva micro-droplets from an infected person to a healthy person. The commercially available masks are single use, passive face-piece filters. These become difficult to breathe in during strenuous activities. Also, they need to be disposed regularly due to accumulation of unwanted particulate and pathogens over time. Frequent disposal of these masks is unsustainable for the environment. In this study, we have proposed a novel design for a filter for enhanced virus filtration, better breathability, and virus inactivation over time. The filter is called Hy–Cu named after its (Hy) drophobic properties and another significant layer comprises of copper (Cu). The breathability (pressure drop across filter) of Hy–Cu is tested and compared with widely used surgical masks and KN95 masks, both experimentally and numerically. The results show that the Hy–Cu filter offers at least 10% less air resistance as compared to commercially available masks. The experimental results on virus filtration and inactivation tests using MS2 bacteriophage (a similar protein structure as SARS-CoV-2) show that the novel filter has 90% filtering efficiency and 99% virus inactivation over a period of 2 h. This makes the Hy–Cu filter reusable and a judicious substitute to the single use masks. For example, in the 1918 Influenza epidemic, mandatory masking orders were passed around the globe2. In the 1980s and 1990s, with the outbreak of Avian influenza, wearing masks was taken as a preventive measure to curb the spread of respiratory infections. When the H1N1 flu hit Japan in 2009, wearing masks became a mandatory lifestyle choice and was adapted to normal living for a long time. In 2019, the first case of COVID infection was reported in China due to a respiratory virus called SARS-CoV-23. Research shows that the infection occurs due to airborne transmission, when an infected individual exhales the virus into air while talking, coughing, or sneezing. The viruses also get suspended on common inanimate surfaces. The discharged virus can enter into a healthy individual’s respiratory tract through inhalation of the infectious micro-droplets in air or through hand-to-nose transmission after touching the contaminated surface. Several evidence based studies were conducted to determine the effectiveness of mask mandates4, and positive results were obtained5,6 showing that mask use is one of the best potential solutions to curb the virus spread. The available mask options to general public are N95 and KN95 masks, surgical masks, and cloth masks7. Although a cloth mask prevents the spread of large saliva droplets in the air8, its efficiency in preventing virus is still questionable9. The surgical masks are loose fitting, disposable devices that consist of two sheets of non-woven layer with a meltblown polypropylene layer in the middle, that is responsible for most filtration7,10. The N95 and KN95 respirators are designed to achieve a very close facial fit and form a seal around the nose and mouth. The main filtration material on these masks is an electrostatic non-woven polypropylene fiber7. The filtration efficiency of the KN95 is reported to be close to the medical grade N95 mask, i.e., up to 95% for 0.3 µm particles and larger, with a mean efficiency of 98%. Previous studies11 have shown that N95 masks have a filter resistance (Rf) of 343 Pa for inhalation and 245 Pa for exhalation, respectively. Surgical masks are widely used due to their low air resistance because of their lower number of layers and thickness as compared to KN95. Their Rf and collecting efficiency have been characterized as 29 Pa and 32.9% respectively12.For centuries, respiratory viruses have been a common cause for initiating epidemics and pandemics worldwide14 that is also a potential source of micro-plastic pollution15. Another concern is the need for safe disposal of single use masks16 due to stable persistence of virus on these masks for days, that can cause unaccounted cases of virus infection if not handled and discarded properly. Studies have shown that when these pathogens are filtered and trapped in mask fibers, they can survive in between the layers for days which makes the masks hazardous for disposal with the non-hazardous waste4. The above limitations with commercially available and widely used engineered masks, form the motivational ground for our current study where the purpose is to design and test a novel sustainable filter that can achieve high breathability, longer life with re-usability, and better filtration efficiency.Both KN95 and surgical masks are efficient in virus filtration, however, they need to be disposed because of their short usable life. This causes generation of large amounts of PPE  waste17. The coating, due to its hydrophobic properties, rejects the aerosolized micro- droplets of saliva and mucous, a common carrier of the virus18. The lipophobic property of the coating helps in preventing the virus from hosting on the fibers of the external layer, since the outer envelope of the virus structure, like most respiratory viruses is lipidic in nature. This outer lipid envelope holds the RNA together19 and is also susceptible to mechanical and environmental stress. The rupture of this protective lipid layer exposes the vulnerable RNA of the virus20 and causes inactivation. Another significant layer is a DLC (Diamond-Like Carbon) coated copper mesh. Copper is well known for its anti-microbial/anti-viral properties and capability to attack and deactivate pathogens22. Borkow et al.23 shows that if respiratory protective face masks are impregnated with copper oxide, it imparts in them anti-influenza biocidal properties without altering their physical barrier properties. The deactivation mechanism works when the pathogen comes in contact with the copper surface. The metal surface releases ions that alter the morphological structure of the pathogen. Moreover, these ions can break through the membrane of the bacteria or virus leading to inactivation and decontamination over time24. Buchegger et al.25 found that the DLC coating doped with zinc oxide (ZnO) is a promising material that could be used for pathogen rejection and deactivation26. The properties of the DLC are its low surface roughness, very high resistance to wear and tear, pH sensitivity, hydrophobicity, and super-hydrophobicity in some cases27. In a particular case when the DLC is doped with ZnO particles, zinc ions are released causing important anti-microbial actions in infectious environments with a pH in the range between 7.4 and 5.4.The novel Hy–Cu filter proposed in this study composes of three unique layers that are tested in different configurations. The first unique layer is a spun-bond polypropylene material, coated with nano-engineered hydrophobic and lipophobic coating which is a water-based omni-phobic solutionRfilter and virus log reduction value (LRV) for the novel filter is discussed in the “In this study, performance of the proposed filter is analyzed in terms of a pressure resistance test, a virus filtration test and a virus inactivation, as well as a fluid resistance test, using well controlled experimental techniques. The experimental setup and methodology for finding http://nctmexico.com.mx/.) as described in the corresponding patent and data sheets17. Generally, siloxanes are well tolerated by the humans, and they are an integral part of innovative methods of health care and nursing. They are commonly considered as minimal to non-toxic to humans and environment28. Data is primarily found on the cyclic siloxanes D4 and D5 and the small linear HMDS (hexamethyldisilazane). Siloxanes have a relatively low order of acute toxicity by oral, dermal and inhalatory routes and do not require classification for this effect. They are not shown to be irritating to skin or eyes and are also not found sensitizing by skin contact. Data on respiratory sensitization have not been identified29. The middle layer, diamond-like carbon (DLC) coated copper mesh has a pore size of about 200 micrometers. The coating was prepared by Technometals in Dayton, OH. Hydrogenated carbon and diamond-like carbon can be obtained using multiple techniques like chemical vapor deposition (CVD) or physical vapor deposition (PVD)30. For this study, the PVD technique was used31. The DLC coating on the copper mesh has a thickness in the range of 1–5 µm. The DLC coating is well known as bio-compatible32 material used in implants33, biological applications34, dental drills35, heart valves36, and many other applications directly used in humans37. The innermost non-woven layer, close to mouth is made of light polypropylene fabric, and has good air permeability, is breathable, non-toxic, and non-irritating. This non-woven interfacing is characterized based on mass per unit area. These textiles have fibers that are held together by hydro-entanglement with random mechanical intertwining of the filaments. In a non-woven fiber, the particulate removal takes place according to different mechanisms depending on particle size, namely, straining or sieving, inertial impaction, interception, and Brownian diffusion4. Different grades of non-woven layers affect the filtering efficiency. With higher mass per unit area, better filtration is expected.In this study, the proposed novel filter has three unique layers and has been tested for efficiency in multiple configurations. Figure Two different configurations of the Hy–Cu filter were prepared to test for pressure resistance efficiency, as well as virus filtration efficiency. For former experiments, a 3 layer (Hy–Cu 3 layer) and 5 layer (Hy–Cu 5 layer) configuration was tested. In the 3 layer arrangement, there is an omniphobic layer , followed by a DLC coated copper layer (middle), and a non-woven layer . In the 5 layer configuration, there is an omniphobic layer (outermost), a non-woven layer, followed by a DLC coated copper layer (middle), and 2 non-woven layers, thereafter, closest to the mouth. In the 5 layer configuration, the purpose is to sandwich the middle DLC layer between two non-woven layers to expose viruses trapped in non-woven layers to the anti-microbial DLC layer for maximum inactivation of the viruses. For virus filtration test, we studied the 5 layer configuration of the Hy–Cu filter.Three standard tests are used to determine mask effectiveness to curb the spread of respiratory viruses. The standard tests that have been used to study the efficiency of the novel Hy–Cu filter include a pressure resistance test, a virus filtration test and a virus inactivation test. A qualitative test to understand the fluid resistance is also conducted and discussed in the Supplementary Note .5 m/s, 1.9 m/s, 3.5 m/s, 7.5 m/s, 9 m/s, 11 m/s, 12.5 m/s, 14.5 m/s. These velocity cases are decided based on human respiratory actions38 of breathing at about 1 m/s, talking at 5 m/s, coughing at 10 m/s and sneezing at 20 m/s. The filter/ mask samples that were tested for pressure resistance include a KN95 mask, a surgical mask, the Hy–Cu 3 layer filter and the Hy–Cu 5 layer filter. A 12V DC voltage blower with maximum flow rate of 178 m3/h was used to create air flow through the filter. Reducers were used to decrease the blower outlet diameter from 0.1 to 0.025 m. A ball valve was used to control the flow rate for various air speeds and two flanges were used to fix the filter/mask samples in place. A digital pressure transducer with a pressure range of 0–1000 Pa was used to measure differential pressure across the samples, and two pressure probes were inserted at a distance of 0.5 inch on upstream and downstream of the sample. A handheld vane anemometer was mounted at downstream of the flow to measure the average flow rate. National Instruments’ Data Acquisition (DAQ) system was used to record data from the pressure transducer to the computer. The length of the pipe was 2 m to achieve fully developed flow for given Reynolds number based on velocity cases, keeping in mind the experimental constraints. Pressure resistance versus velocity trends are analyzed from data collected, to determine the breathability of the filters and masks.Figure 40. MS2’s small size, and lack of outer lipid envelope makes it resistant to chemical and environmental resistances. It is used as a surrogate virus for human coronavirus in the current study. The filter/mask samples tested on the virus filtration test bed were a surgical mask and the Hy–Cu 5 layer filter. The idea was to test the novel filter against commercially and widely available surgical masks with comparable pressure drops as observed in pressure resistance test. Also, a single non-woven layer from each sample, namely a surgical mask and the Hy–Cu filter, was separately tested on this test bed with same experimental conditions to check the concentration of virus retained on the non-woven layer after the run.For virus filtration test, bacteriophage MS2 (ATCC 15597-B1) and Escherichia coli C-3000 (ATCC 15597) are used as the test virus and virus host bacteria, respectively. Morphologically, MS2 is a non-enveloped, icosahedral, positive-stranded RNA virus.05 to 20 µm at 40 psi pressure and 0.0456 ml/min flow rate. The nebulizer was running for 15 min for every test case for sample collection. Virus infused aerosol, from the nebulizer entered a 4-inch duct, 36-inches long, with diverging inlet to prevent back flow of the micro-droplets. The sample filter/mask was fitted at the center of the duct. At a 5-inch distance, upstream and downstream of the filter, two SKC fritted bio-samplers were placed for collection of virus sample. The bio-samplers contained 10 ml of phosphate buffer solution (PBS) for virus aerosol collection and the bio-sampler pumps were run at 0.8 L/min. The fritted samplers were run one at a time to prevent interference in sampling and to avoid non-uniform particle spread through duct cross-section, due to the wake region of the probe heads of the bio-samplers, inside the duct. This was obtained through ANSYS Fluent simulations shown in the Supplementary Fig. The test bed design given in Fig. For plaque assay analysis of the collected virus sample, soft tryptic soy agar (TSA) was mixed in DI water, and the solution was poured into Petri dishes and allowed to sit until solidified. The collected virus sample and host bacteria were mixed and poured into the Petri dish and incubated overnight at 36 °C. The number of plaques that appeared on the plate were counted and the viral log reduction for the two sample cases, was calculated using the equation,The virus filtration test bed as shown in Fig. −1, which is typical for most physical activities42. At higher flow velocities, both Hy–Cu filter configurations have shown comparable pressure resistance as the surgical mask. It can be noted that the KN95 mask has higher pressure drop compared to both surgical mask and Hy–Cu filters, at higher velocities. These results indicate that it is easier to breathe through the novel Hy–Cu filter as compared to the commercial medical masks. To support the experimental observations with numerical data, the Hy–Cu filter is modeled as porous media and numerical simulations are performed using ANSYS Fluent to extend the pressure drop over wide range of velocities. The detail of the numerical work is given in Supplementary Note The novel Hy–Cu filter has been tested for breathability, virus filtration and inactivation efficiencies. The plot in the Supplementary Fig. .3% virus concentration retention as compared to the non-woven in the disposable surgical mask that shows 1.6% of viral concentration after the 15 min of experiment run. This means that the non-woven layers in the Hy–Cu filter are efficiently holding up the virus particles from passing through the filter. The overall lower efficiency of the Hy–Cu filter can be attributed to few points as discussed here. The layers of the Hy–Cu filter are combined together for the experimental tests in laboratory conditions without proper infusion between the layers, whereas for the disposable masks available in market, commercial melt-blown processes are used for creating the mask system. The infusion between the layers of commercially produced masks is better as compared to the Hy–Cu filter system prepared in the laboratory. All three layers of the disposable surgical masks have polypropylene in combination with non-woven material making all the layers better in the hydrophobic property as compared to the novel filter. This can also be a reason for its lower overall efficiency against virus as compared to the medical mask. Also, there is no electrostatic charge applied to the Hy–Cu filter, which is present in disposable surgical masks, that helps in higher overall viral retention increasing the virus filtration capacity of the surgical masks.For the virus filtration test, the virus log reduction values for the Hy–Cu 5 layers and surgical mask are observed to be − 1.2 and − 1.9 respectively. This means that Hy–Cu 5 layers can filter 90% of MS2 bacteriophage virus in 15 min while the surgical mask can filter 95% of the nano-scale virus. To understand the difference in the filtration efficiencies, the non-woven layers from each sample are compared. The non-woven layer is a key factor in the straining, interception, inertial impaction, and diffusion processes that make the particles cling to the fibers. We obtain that the non-woven layer used in the Hy–Cu filter has 2For virus inactivation test, the Hy–Cu filter with DLC shows orders of magnitude difference in virus concentration reduction as compared to no DLC condition. The Hy–Cu filter with DLC is observed to have 99% viral inactivation efficiency as compared to no DLC case that shows << 90% of viral inactivation over a period of 2 h. This indicates that the DLC layer has a promising action against MS2 bacteriophage virus. Also, the higher virus retention capacity of non-woven layers present in the Hy–Cu filter is favorable since this subjects the viruses in close proximity to the DLC copper layer leading to eventual inactivation of the virus particles. The overall performance of novel Hy-Cu filter is summarized in Table 44. Hence the production and disposal of PPE waste materials and challenges associated with it can be controlled. Hewawaduge et al.45 shows that CuS (copper sulfide) incorporated three-layer mask has high inactivation efficacy against SARS-CoV-2 virus. Another study46 shows that copper coated KF94 masks show promise as antiviral protective face-piece for SARS-CoV-2 inactivation. Our study is the first to show the use of DLC coating on a fine copper mesh for virus inactivation and the use of DLC coating in a mask system. The property of inactivation of virus due to the DLC copper layer makes the Hy–Cu filter highly reusable and safe to use unlike the commercially available disposable masks. This reduces the needs for frequent mask disposal, and in turn bringing down the quantity of PPE, plastic and other related wastes that are being produced every day.The results indicate that the novel Hy–Cu filter is sustainable for use as compared to single-use disposable masks. The better pressure resistance efficiency for Hy–Cu filter as compared to other medical grade masks ensures that it can be used longer, since lower pressure drop across the filter media prevents the early formation of cake layer of dust and other unwanted particulate in air, that eventually clog any filter/maskOur study is the first to propose a novel filter design. Figure Supplementary Information.


The transmission of viruses between host populations is essential for viruses to persist on the landscape. Therefore, the identification of specific transmission links can provide insights into how a virus moves from source to recipient (sink) populations, allowing for the development of strategies to interrupt transmission routes and control viral disease. For the fish pathogen infectious hematopoietic necrosis virus (IHNV), this study identifies three transmission links associated with the emergence of IHNV in coastal Washington steelhead trout populations between 2007 and 2011. The links were identified by the genetic typing of virus isolates obtained from coastal fish and potential source fish from the Columbia River Basin. Three exact genotype matches were found, indicating at least three introductions of virus from Columbia fish to coastal fish during years of the emergence event. Likely sources were juvenile fish in the Columbia region experiencing disease, and the first detected recipient populations in all cases were adult fish returning to coastal hatcheries. Variation in timing and distance for these three transmission links will provide Pacific Northwest fish health managers with a better understanding of IHNV transmission routes from Columbia region fish to coastal steelhead trout.Oncorhynchus mykiss) experienced a high incidence of infection and disease outbreaks due to the rhabdovirus infectious hematopoietic necrosis virus (IHNV). Genetic typing showed that the introduced viruses were in the steelhead-specific MD subgroup of IHNV and indicated the most likely source was a virus from the nearby Columbia River Basin. In the current study, full-length viral glycoprotein (G) gene sequences were determined for 55 IHNV isolates from both coastal and Columbia fish populations to identify specific source populations and infer mechanisms of transmission to coastal steelhead. We identified three transmission links based on exact fullG genotype matches between Columbia and coastal fish. In all cases, the likely source population was infected juvenile fish, and sink populations were adult fish returning to coastal rivers to spawn. The time intervals between detection in source and sink populations varied from 6 months to nearly 4 years, suggesting different transmission pathways. Surprisingly, distances between source and sink populations varied between 140 and 1000 km. These results confirm repeated introductions of virus from Columbia River Basin fish as the cause of emergence of MD virus on the Washington coast from 2007 to 2011.In the coastal region of Washington State, a major pathogen emergence event occurred between 2007 and 2011 in which steelhead trout ( Oncorhynchus are hosts for the acute viral pathogen infectious hematopoietic necrosis virus (IHNV) [Oncorhynchus mykiss) populations in many coastal rivers of Washington State suffered an exceptional period of epidemic disease events and high infection prevalence due to IHNV [O. nerka) and does not cause overt disease in steelhead [O. mykiss) [In the Pacific Northwest, salmonid fishes of the genus s (IHNV) . Between to IHNV . Althoug to IHNV , the speteelhead ,5. Howevteelhead , which i mykiss) ,7,8,9. T mykiss) .Rhabdoviridae that was first recognized in the 1950s as the cause of a major disease, infectious hematopoietic necrosis (IHN), in sockeye salmon, steelhead/rainbow trout, and Chinook salmon (O. tshawytscha) [IHNV is a global pathogen in the family wytscha) . Within wytscha) . Adult fAt the genetic level, IHNV has diverged into several genogroups and subgroups that differ in host specificity and geographic range. In North America, IHNV occurs as three major genogroups, U, M, and L, that have specialized, with high virulence, in sockeye salmon, steelhead/rainbow trout, and Chinook salmon, respectively ,13,14. RA genetic typing system for IHNV field isolates was established in the 1990s based on the 303 nucleotide (nt) sequence of a variable portion of the viral glycoprotein (G) gene, called the ‘midG’ region ,16. ThisThe purpose of the current study is to provide finer resolution on possible transmission sources for the emergence events that resulted in widespread detection and several years of disease in coastal steelhead, specifically the second and third emergence events that together occurred between 2007 and 2011. To achieve finer epidemiological resolution, 55 virus isolates from the Columbia (putative source) and coast (sink) regions were analyzed here by sequencing the complete G gene, which is approximately 1500 nt in length. Since the midG region is 303 nt, this ‘fullG’ typing would provide substantially greater resolution for efforts to identify populations in the Columbia region that might have acted as sources for the coastal emergence events.This study revolves around events initially characterized by midG typing (genotypes written as mG###M) and refined here by fullG typing (genotypes written as fG###M). These terms are easy to conflate, so a clarifying structure will be used for ease of communication: the two emergence events investigated here will be described according to their temporal incidence. We will refer to the “second emergence” as that of IHNV with genotype mG110M during the period 2007–2011, and the “third emergence” as that of IHNV with genotype mG139M during the period 2009–2011. As an ancillary goal, we also present here fullG typing of two coastal virus isolates from the second emergence period that had a variant midG genotype, mG168M. Although these isolates are not directly related to transmission links between the Columbia and coast regions, they are of interest because they are hypothesized to represent a rare example indicating virus transmission from infected juvenile hatchery fish to free-ranging fish returning to a different hatchery farther upstream [Novirhabdovirus salmonid, in the genus Novirhabdovirus, in the family Rhabdoviridae [IHNV viruses are members of the species oviridae . A set oReverse transcription PCR (RT-PCR) and sequencing of overlapping cDNA fragments to determine the complete G gene nucleotide sequence was conducted as by Garver et al. . Brieflywww.genecodes.com (accessed on 1 September 2019)). Sequences were trimmed to the known G gene coding region of 1513 nucleotides (nt), including start methionine and stop codon and excluding the polyA tail, and exported via simple text. Every unique sequence within the dataset was given a universal sequence designator (USD), following a modification of the established midG genotyping USD nomenclature [www.megasoftware.net (accessed on 1 September 2019)).Electropherograms were inspected individually for quality, and then the three forward- and three reverse-primed sequence fragments were aligned in Sequencher v5.2.4  with stringent gap penalties. Phylogenetic analysis was conducted under the coalescent theory using Bayesian Markov-chain Monte-Carlo (MCMC) methods, using the BEAST software suite ) [Isolate sequences from this study were combined with other IHNV fullG sequences from North America and aligned using ClustalX (r 2019)) ,22,23. Dr 2019)) ,25,26. TTo identify possible transmission sources responsible for the second emergence of MD IHNV in Washington coastal steelhead, 11 isolates from the Washington coast region that were originally genotyped by midG sequencing as mG110M  were selO. kisutch). From the Columbia region, 24 isolates that were originally genotyped as mG110M [O. nerka)  .Among the 11 coastal isolates from the second emergence, four distinct fullG genotypes were found . The earWithin the 24 mG110M isolates selected from the Columbia region for analysis, there were 16 unique fullG genotypes . Of thesSince several closely related fullG genotypes were detected among the mG110M isolates analyzed from the coast and Columbia regions, similarity analysis was performed . FullG nPhylogenetic inference was performed to provide more statistically rigorous analysis of the evolutionary relatedness of the 19 fullG genotypes found among second emergence coastal isolates and potential source isolates from the Columbia region. In the phylogenetic tree shown in O. clarkii)  .Among the ten coastal isolates, four distinct fullG genotypes were found . The earWithin the eight Columbia isolates, six unique fullG types were found . These iA pairwise comparison of nucleotide and amino acid sequences of genotypes detected in the third emergence events indicated that the two types found in both regions, types fG139M and fG133M, differ by one nt, but they do not differ in amino acid sequences. Two of the other fullG genotypes found only in the Columbia region also encode the same amino acid sequence but differ from the dominant fG133M by 1–2 nt .Phylogenetic analysis of the eight fullG types found in the coastal third emergence isolates and candidate source isolates from the Columbia region indicated that they are distinct from all second emergence fullG genotypes, and they are all monophyletic within a clade defined by node C  could have occurred independently in both regions is theoretically possible, this is much less likely than the transmission of a pre-existing virus between fish populations, especially considering the long migrations inherent in Pacific salmonid life cycles. A caveat is that we did not sample all potential source fish populations in the Columbia region, so the same fullG genotypes identified here in transmission links may have existed in other Columbia fish populations from different locations or different years that were not tested for virus or were not selected for fullG sequencing. This could alter the temporal or spatial aspects of the transmission events described here. It is also possible that fullG genotypes in coastal fish that had no matching source could still have been introduced from Columbia fish populations that were not sampled or not sequenced. A likely example of this is coastal genotype fG029M, which was the very first MD virus detected in the second emergence in 2007, but no matching source was identified in the Columbia region. As the first detection of an MD virus in the coastal fish, it is virtually certain that this virus was introduced from outside the coast region, and phylogenetic analysis places it within the same clade as all other second-emergence Columbia and coastal isolates , node B.At the landscape scale, IHNV transmission is best characterized in freshwater because of the importance of IHN disease in fish farms and conservation hatcheries that rear fish in freshwater river systems ,28. HoweWhatever path of transmission followed by type fG127M, it is clear that the virus with this G gene sequence produced progeny and diversified in both source and sink regions. For coastal sink populations, this is evident as four descendant fullG types from coastal sources identified phylogenetically within the clade defined by node B . The preFullG sequence analysis of isolates related to the third emergence event revealed three unexpected features. First, there were two unique fullG types found shared between fish populations of the Columbia and coast regions, fG139M and fG133M, implying two discrete introduction events. Second, both source populations were found deep inland, more than 640 river kilometers farther from the sink population than for the translocation of type fG127M . Third, The temporal relationship between Columbia detection of type fG133M has an intermediate time interval with two years separating the incidence in source and sink populations . This trThe third coastal emergence event lasted from 2009 to 2011. The two emergent types fG133M and fG139M are most closely related to each other, and phylogenetic analysis revealed two fullG types that appear descendent from them in the coast region. Types fG138M and fG140M were detected in coastal fish in 2010 and 2011, and they were never detected in the Columbia region. Phylogenetic analysis did not identify fullG types that may have descended from types fG133M or fG139M after their detections in the Columbia region, however. As with the second emergence, this third emergence of MD group IHNV did not persist in the coastal region beyond 2011, despite ongoing virus surveillance.Thus, the three transmission links identified here differed in important ways that provided novel insights. The transmission of fG127M virus involved a relatively short migration distance and a long time interval of four years, suggesting mechanisms that most likely involve transmission between similar life stages and long-term persistence of virus in either Columbia or coastal fish. In contrast, the fG139 introduction was associated with a long migration distance and a very short time interval of 6 months, suggesting the possibility of infection of an intermediate host that was not sampled here, and transmission between juvenile and adult fish. The third event, fG133M, was also a long migration distance but with an intermediate time interval of 2 years, again suggesting a mechanism involving transmission between fish at different life stages.In addition to characterizing three transmission links associated with the second and third coastal emergence events, our ancillary goal of genotyping two coastal IHNV isolates with midG genotype mG168M identified a unique transmission link between coastal fish populations. The finding of an exact fullG genotype match greatly strengthens our previous inference that this is an example of transmission from infected juvenile hatchery fish to free-ranging adult fish . This isIt is not known why the repeated introductions and emergence events of subgroup MD IHNV in coastal steelhead populations did not result in MD virus becoming endemic in the coastal region as it has done in Columbia steelhead. The regions differ in several ways that might play a role. There are more sockeye salmon populations in the coast region than in the Columbia region. Within coastal sockeye salmon, the IHNV that is most prevalent is the subgroup UP ,30. AlthBased on fullG sequence analyses presented here, the emergence of MD IHNV in coastal steelhead from 2007 to 2011 involved at least three separate introductions of virus from Columbia region sources, rather than the two introductions hypothesized from midG typing. These were identified as exact matches of fullG sequences fG127M, fG139M, and fG133M in Columbia region source fish before they were detected in coastal steelhead. In addition to the finding of exact fullG type matches, phylogenetic analyses of coastal fullG sequences also suggest the possibility of two additional translocations of unsampled Columbia MD viruses that were detected on the coast as fG029M and fG141M. Thus, the actual number of transmission events from the Columbia to coast regions is at least three, and there were possibly five introductions between 2007 and 2011. In addition to identifying more transmission links and increasing confidence in previously identified links, fullG analysis also allowed us to rule out some candidate Columbia source populations when they were found to have genotypes that did not match those in coastal fish. This was most important in the fG139M and fG133M transmission links that involved very long-distance translocation of MD virus from Idaho fish populations. In this case, there were alternative candidate source populations in the lower Columbia region that would have involved a much shorter translocation distance, but these were ruled out by showing they did not have matching fullG virus types. This allowed us to conclude with confidence that at least two transmission events involved translocations of over 900 km. Although this seems unexpected, long migrations are part of the natural life cycle of Idaho salmonid populations, and we now conclude with confidence that they can participate in transmitting virus from the Snake River region to coastal fish populations.Overall, the higher resolution of full G sequencing provided stronger support for the general hypotheses derived from earlier midG typing, and it also provided novel data that advance our understanding of the mechanisms of emergence of MD IHNV in Washington coastal salmonids. We identify here at least three, and possibly five introductions of Columbia virus into coastal fish between 2007 and 2011. This suggests a continuing process of virus introduction from Columbia sources during the years of the coastal emergence, rather than one introduction that subsequently spread among coastal fish populations. The three specific transmission links identified by matching fullG genotypes varied in both timing and distance between Columbia source and coast sink populations, suggesting different transmission mechanisms. However, a common pattern in these specific transmission links is that the source populations were likely juvenile fish experiencing epidemic disease in the Columbia region, and the sink populations were returning coastal adult steelhead that carried the virus into coastal hatcheries. These repeated events occurred during a period of high MD epidemic activity in the Columbia region, and the disappearance of MD virus from the coast region after 2011 coincided with a general decline in MD IHNV detections and disease events in the Columbia region . This su


In SP, the results of the ANOVAs test indicate that age had a significant effect on ADF  = 0.015) but not on APF . Moreover, considering only the SP, a weak inverse correlation between ADF and HGS group ADF was found . Factors such as the non-linear trend of growth in young SP could hinder the definition of the relationship between ankle ROM, age, and muscle strength. However, the appropriate consideration of age and muscle strength could facilitate the management of ankle ROM in PF of different ages.Soccer  practice can induce a limitation of ankle range of motion (ROM) that is a possible risk factor for injury and other negative consequences over time. The main objective of this research was to investigate the effects of soccer practice on ankle ROM throughout the entire period of a sports career of soccer players (SP). Furthermore, the relationship between ankle ROM and muscle strength in SP of different ages was studied. A total of 204 SP (range 6.7–45.1 years) and 87 controls (range: 7.5–45.2 years) matched for age, body mass index (BMI), and gender, were assessed. Ankle ROM in both plantar flexion (APF) and dorsiflexion (ADF) in addition to handgrip strength (HGS) were evaluated using an inclinometer and the Jamar hydraulic hand dynamometer, respectively. The comparison between SP and control groups showed a significant reduction in ankle ROM of both APF (26.3 ± 7.2° vs. 32.6 ± 7.4°; d = −0.90;  Soccer  is one of the most practiced team sports in many countries worldwide. In particular, the majority of young people as well as a large number of adults who participate in amateur leagues choose to play soccer ,2.The very widespread practice of soccer entails the necessity of studying its effects on soccer players. Playing soccer is important because it is a significant source of physical activity and can have many positive health effects on both young people and adults ,4. HowevAmong them, several studies published over the last 50 years suggest that soccer players (SP) may show an alteration of ankle range of motion (ROM) ,10,11,12The causes of reduced ankle ROM in SP are still partially unknown. However, an important role has been attributed to repeated injuries of the joint ,15,20. AAnalysis of the causal factors and consequences of limited ankle ROM in SP indicate how complex vicious cycles might develop in these players. Vicious cycles can also be supported by alterations in muscle activity that SP can often have. As such, since early studies regarding the relationship between soccer practice and ankle ROM, it has been hypothesized that muscle activity may also play a role in limiting ankle joint ROM. In particular, some authors have hypothesized that SP can instinctively seek greater ankle joint stability in order to protect the ankle from continuous micro-traumatic or traumatic events ,32,36. TThis is very interesting considering that limited ankle ROM, in addition to being very evident in adults, can also be present in young SP with a short history of sports practice ,12,32,43The stiffness of the ankle joint in SP would paradoxically be at the same time, first a preventive factor for ankle injuries and then a risk factor for the same injuries. All this indicates that analyzing the effects of practicing soccer on ankle ROM and its relationship with muscle strength could provide useful information on actions aimed at the prevention of ankle ROM alterations and its possible immediate or long-term negative consequences. The main objective of this research was to investigate the effects of soccer practice on ankle ROM throughout the entire period of a sports career of SP. Furthermore, the relationship between ankle ROM and muscle strength in SP of different ages was studied.A total of 291 subjects, 204 soccer players (SP) [range: 6.7–45.1 years] and 87 controls [range: 7.5–45.2 years] matched for age, gender, and BMI were evaluated in this study . Ankle .In order to better study the effect of growth on ankle ROM, the group of SP adults was also divided into adults A SP (under 17 teams) and adults B SP  and by Ethics Committee of University of Urbino Carlo Bo (cod. CESU20221118VER37 November 2020). The study was carried out according to the principles expressed in the Declaration of Helsinki.Ankle  joint ROM was assessed as described in previous studies ,50,52. BPlayers were instructed to lie supine on a fixed treatment table with their feet crossed and ankles resting in line with the edge. The ipsilateral knee was placed on a rigid support that was 5 cm high. After marking the fifth metatarsal bone with a dermographic pen, the inclinometer  was placed along the diaphysis of the bone, with one extremity on the distal condyle. The ankle joint was in its natural resting position on the sagittal plane, with the subtalar joint in a neutral position. The maximal active APF and ADF angles were measured and reported as the means of three consecutive readings. The total ankle ROM (ATOT) was the sum of APF and ADF. This method yields a limited mean standard deviation (SD) of three consecutive readings of the ankle ROM (1.1 ± 0.9 degrees of plantar flexion and 1.4 ± 1.1 degrees of dorsiflexion) . The samAnkle joint active range of motion was measured as the changes in the ankle angle from the starting resting position (set at 0° in the inclinometer) to the maximal active plantar flexion and dorsiflexion positions . The ankle joint position on the sagittal plane was measured as the angle with the vertex at the center of the lateral malleolus (O) and straight lines passing through the head of the fifth metatarsal bone (A) and the second through the center of the head of the fibula (B).Hand grip strength was assessed using a Jamar hydraulic hand dynamometer (model 5030J1). The dominant upper limb was determined by asking the players which hand they used to write with . The exad was also computed and considered small (d = 0.2), medium (d = 0.5), and large (d = 0.8) effect sizes based on the benchmarks suggested by Cohen (1988) [t-test or the nonparametric test: (*) Mann–Whitney. The association between the ankle ROM and AGE, BMI, and hand strength was also evaluated in controls and separately in young and adult SP as well as considering all subjects assessed using Pearson or Spearman’s correlation coefficients. Since age, body mass index, and muscle strength had a role in the reduction of ankle ROM, multiple linear regression analysis was carried out considering ADF, APF, and ATOT (expressed in degrees) as dependent variables and age, BMI, and hand strength as independent variables in adult SP or in young SP. Additional models were also evaluated using a backward elimination procedure in order to maximize the prediction ability of the models. The analyses were performed using Stata  and SPSS Statistics  software. The α level of statistical significance was set at 0.05.Data were reported as mean ± SD. Range of motion values was expressed in degrees (°). Three separate two-way ANOVAs were performed to assess the effects of age and group on ADF, APF, and ATOT. Cohen’s n (1988) . A statip = 0.038, partial eta-squared (ηp2) = 0.015) but not in APF  and ATOT . The comparison between the groups showed a significant reduction in ankle range of motion of both APF and ADF in soccer players compared to controls . The groups of volleyball and basketball players have instead shown an ankle ROM in line with what has been reported in large-size samples studies that show how ankle ROM in plantar and dorsiflexion is about 70° ,60,61,62p < 0.001; p < 0.006; From the comparison between the adult and young groups, ankle ROM was significantly higher in young SP compared to the adult SP  and HGS  and adults (over 16 years) separately. In particular, the comparisons between adult and young groups highlighted how the ankle ROM was significantly higher in young SP compared to the adult SP. Similar values of ankle ROM were instead found considering young and adult control groups . FurtherThe analysis of the relationship between ankle ROM (dorsiflexion and plantarflexion) and the age or muscle strength of the PF showed only weak correlations. This result could be, at least in part, due to the non-linear trend of the ankle ROM reduction in SP. Among the causes of this non-linear trend, the changes related to the development of young SP and in particular the somatic and physiological ones could play an important role. In this sense, it is known that the growth of young SP and in particular puberty, may result in evident effects on the musculotendinous structures. In addition, it may be important to consider how the trend of development of muscle strength is not fully superimposable to that of bone tissue and height ,64,65. WOverall, the results of this study suggest the usefulness of considering both the age and the muscle strength trend in monitoring the ankle ROM of SP. However, these results are only partially in agreement with those reported in some previous studies. As for senior male SP, almost forty years ago, Hattori and Ohta (1987) measured the range of motion of the ankle joint in 68 male soccer players (18–22 years) and in 66 non-athletic male student controls. The results of the study showed a significant difference in ankle ROM between the two groups. This difference was about 20 degrees considering plantar and dorsiflexion together . This diThis study has limitations to consider. The study was carried out considering a sample of male subjects only without considering professional soccer players and the players positions. Furthermore, increasing the number of subjects investigated both for adult SP and for young SP could favor the description of the relationship between ankle ROM and soccer practice in footballers of different ages. Even if the BMI was assessed, the study did not consider the level of development of the subjects investigated. The use of an upper extremity test such as the HGS test can be considered a limit with respect to the study of the relationship between ankle ROM and muscle strength in SP. However, it is important to consider that HGS test is indicative of generalized muscle strength and it can be performed easily and quickly even in a sports environment ,47,48,49The results of this study relating to the significant reduction of ankle ROM, the ankle ROM values in SP of different ages, and the relationship between ankle ROM and muscle strength, suggest the need to organize activities aimed at the appropriate management of the ankle ROM in SP. This could have a positive effect on the prevention of injuries and other acute and chronic consequences associated with the presence of reduced ankle ROM. At the same time, further studies aimed at better describing the relationship between ankle ROM and age or muscle strength in SP and involving a larger number of subjects appear necessary.With this study, data relating to ankle ROM were obtained for the entire period of a soccer career. In particular, the results achieved highlighted how male soccer players (SP) may show a significant reduction in ankle joint range of motion. This alteration may also be present in children from the first years of sport activity. Although the reduction in ankle ROM is already significant in young SP, ankle stiffness worsens significantly in adult SP. In apparent contrast to that statement, the ankle joint range of motion values measured in the SP of the under 17 teams were similar or lower than those of the SP of amateur leagues. Factors such as the non-linear trend of somatic growth could explain some of this apparent discrepancy. In particular, during puberty ankle ROM could be less affected by the practice of soccer as a consequence of the effects of the same puberty on the somatic growth. At the end of this period, ankle ROM could rapidly deteriorate as a result of the maturation of the musculotendinous and joint structures. This condition could also explain the weak correlation found between ankle ROM and age of muscle strength of SP. Furthermore, this relationship could also be affected by the marked early effect of soccer on the ankle plantar flexion. This condition could anticipate and hide the effect of age on the ankle plantar flexion itself. The need to prevent injuries and maximize the positive health effects of sports practice raises the importance of studying the relationship between ankle ROM and muscle strength in SP of different ages. In this sense, further studies involving a greater number of subjects appear necessary to better describe this relationship.


Host-virus associations have co-evolved under ecological and evolutionary selection pressures that shape cross-species transmission and spillover to humans. Observed virus-host associations provide relevant context for newly discovered wildlife viruses to assess knowledge gaps in host-range and estimate pathways for potential human infection. Using models to predict virus-host networks, we predicted the likelihood of humans as hosts for 513 newly discovered viruses detected by large-scale wildlife surveillance at high-risk animal-human interfaces in Africa, Asia, and Latin America. Predictions indicated that novel coronaviruses are likely to infect a greater number of host species than viruses from other families. Our models further characterize novel viruses through prioritization scores and directly inform surveillance targets to identify host ranges for newly discovered viruses. Potential host range and spillover risk for novel viruses can be predicted using a network informed by known virus-host associations. Surveillance efforts resulted in 944 novel monophyletic clusters of virus sequences in wildlife (referred to as novel viruses henceforth) from 18 virus families sampled at high-risk animal-human disease transmission interfaces in 34 countries. As none of these viruses have yet been identified in humans, other indices were previously established to assess potential risk, such as virus host range or plasticity, and expert opinion based on integration of ecological and molecular characteristics of viruses5. We were able to quantify the risk of zoonotic transmission for 531 out of 944 novel animal viruses using data driven models to predict host-virus networks.Identifying zoonotic virus emergence events at the earliest possible stage is key to mitigating outbreaks and preventing future epidemic and pandemic threats. By the time novel viruses are recognized in humans, often as a cluster of unusual cases, public health interventions to prevent or contain an epidemic face major challenges. However, determining the potential zoonotic transmission for newly discovered animal viruses, in the absence of documented human infection, is currently a major scientific challenge. New approaches are needed to evaluate and characterize the risk of zoonotic transmission of newly discovered animal viruses in the face of very limited data. Here we analyze human, domesticated animal, and wildlife surveillance and viral discovery data collected from 2009 to 2019, as part of a consortium-led One Health project aimed at strengthening pandemic threat detection capabilities in Africa, Asia, and Latin America7, and predict cryptic links between mammalian, and avian hosts and their viruses10. Host-virus network linkages can be informed by virus traits, virus biogeography, host ecological niches, and propensity for host sharing among viruses11. Precedence in viral sharing among species and ecological opportunities for spillover, as characterized by network topology, can inform propensities for newly discovered viruses that lack data5. Further exploration of these networks can aid in estimating the host plasticity of viruses, an important characteristic associated with zoonotic potential5. Unfortunately, systematically collected surveillance data to parameterize and validate these models have been missing3. Here, we apply a network approach to gain ecological insights from viruses that have been shared among species in nature and inform potential virus-host associations and zoonotic risk of novel viruses recently discovered from wildlife.Patterns observed across host-virus networks have been used to understand virus sharing among vertebrate species12. Trained models were used to predict possible host links for 531 novel viruses due to commonalities in host sharing with known viruses and generated a predicted host-virus network . Furthermore, after accounting for sampling bias for individual viruses using PubMed hits (number of search results associated with virus using a specific search term), we ran a linear regression model with node-level permutations . Viruses in families Hantaviridae, Filoviridae, Flaviviridae, and Orthomyxoviridae had a significantly higher degree (p < 0.05) and eigenvector centrality (p < 0.05), indicating more connections in the host-virus network than other represented virus families. Viruses from the Flaviviridae family also had higher betweenness centrality (p = 0.01) indicating more connections based on shared host species 1. To predict associations (linkages) between novel viruses with other viruses formed due to common host species, gradient boosting models were trained using network topological characteristics and families of viruses in the virus pairs to estimate: (1) whether virus pairs have a species host in common; and (2) the taxonomical order of shared hosts . The degree  than the observed network ree Fig.  and betwree Fig.  distribuias Fig. .p = 0.39, Fig. p = 0.22, Fig. p < 0.05, Fig. p < 0.05, Fig. n = 944). Long tails of centrality distributions generated for the predicted network , our adjustment for search effort (PubMed hits) was found to have no effect on the degree  unique host species (maximum of 15 species) compared to 1.22  for other novel viruses detected in this study. This finding raises concern about the ability of novel coronaviruses to infect a greater number of species than viruses from other families. The recently emerged SARS-CoV-2 and the previously emerged SARS-CoV-1, have shown a wide host breadth16. These predictions for novel coronaviruses highlight their key ecological properties that can influence spillover into humans. Following coronaviruses, novel flaviviruses showed significantly higher betweenness centrality (p < 0.001). Host taxonomic order for novel viruses had no significant association with the degree centrality of the virus in the predicted network. Predicted network characteristics not only differentiate virus families based on network characteristics but also predict network characteristics that are key in understanding the ecology of a novel virus and its behavior within the network community of hosts, including the expected breadth of host species most likely to be infected by that novel virus.Importantly, a comparison between virus families of novel viruses showed that novel coronaviruses had a higher degree . Based on generalized linear mixed models, search effort (PubMed hits) was not associated with the predicted number of human links  compared to known non-zoonotic viruses. Prioritization scores were derived essentially from the prediction of new/yet unobserved network links generated by the virus with another virus formed due to sharing of hosts. However, models were unable to predict new links for well-recognized viruses that have numerous hosts, such as Rabies virus and West Nile virus, and consequently resulted in a prioritization score of zero. Figure Phyllostomidae bats from South America  scored the highest prioritization score in all novel viruses. Other top ten novel coronaviruses based on the prioritization score included viruses detected in Phyllostomidae bats . Out of these, PREDICT_CoV-11 was also detected in Mormoopidae species (Pteronotus personatus) and PREDICT_CoV-5 was found in Vespertilionidae species (Bauerus dubiaquercus) during the surveillance. These also included coronaviruses detected in Southeast Asian Pteropodidae bat species such as PREDICT_CoV-16 and PREDICT_CoV-22. PREDICT_CoV-22 was also detected in Hipposideridae bat species (Hipposideros lekaguli). PREDICT_CoV-78 detected in multiple bat and rodent species of Southeast Asia also showed a high prioritization score. These model outcomes, especially the prioritization score, provide a data-driven tool to quantify zoonotic risk for novel viruses. Even though the model is trained on numerous data points for known zoonotic and non-zoonotic viruses, individual predictions for newly discovered viruses would only require data on hosts and virus family if used within our modeling framework.For a relative comparison of zoonotic risk for novel viruses, a prioritization score was developed based on the predicted probability of links being human and the number of shared human links in the predicted network for a given virus. To understand the performance of the prioritization score, we compared scores for known zoonotic and non-zoonotic viruses generated by the ensemble of both binary and multi-class models. Results indicated significantly higher prioritization scores for known zoonotic viruses  for further surveillance of newly discovered viruses (Supplementary Data Miniopteridae family (Bent-winged bats) but none from Natalidae . Another prominent cluster prioritized all 11 chiropteran families, while the third cluster of coronaviruses showed relatively fewer host recommendations from Miniopteridae bats. Representation of these surveillance targets through these clusters highlights host predilection of novel coronaviruses and indicates their preferential sharing of hosts. These clusters also support earlier results related to the scale-free nature of the predicted network , particularly given previous host-centric work has produced mixed results when using trait-agnostic network modelling approaches17. Our network approach presents some limitations specifically for viruses that have been detected in species with limited surveillance efforts to date and are thus not part of the training data. For this reason, we were able to generate predictions for only 531 novel viruses out of 944. The remaining 413 novel viruses without predictions were detected in species that were never found positive for any virus, starkly indicating the lack of surveillance in wildlife. Further, model findings should be interpreted as associations between hosts and viruses based on the detection of viruses in samples collected from host species. These associations require further understanding around the role of hosts in the transmission ecology of viruses, especially to elaborate if hosts can serve as reservoir, amplifying, or dead-end hosts. Detection of a virus in a host species is not always correlated with that host’s ability to produce viremia for further transmission. Similarly, some of the novel viruses from Picobirnaviridae and Rhabdoviridae have been speculated to be hyperparasites and the interpretation of these detections and predicted host-associations need further investigations.Grange et al. developed a tool that ranks viruses for an animal to human spillover using a risk-based approach validated by inputs from various experts from the field of virology, epidemiology, and ecology11. These tools will improve with further surveillance and discovery of new viruses and their hosts19, ultimately informing our understanding of the mechanisms of zoonotic emergence for viruses from wildlife.Novel viruses with high scores on the prioritization metrics present a strong eco-evolutionary case for further genetic and in-vivo characterization to understand the risk of spillover. The scoring will help streamline in-depth in-vivo characterization and develop additional hypotheses related to genetic and ecological mechanisms for cross-species transmission and zoonotic spillover. Nucleotide data associated with novel viruses presented here are short, hence the current model framework of using only host associations provides a key advantage. However, network models have shown to improve prediction capacities when nucleotide data are included as features for prediction4., Pandit et al.3, and Johnson et al.13. In data provided by Olival et al (assessed September 2019), host-virus associations have been assigned a score, based on detection methods and tests that are specific and more reliable. We used associations that have been identified as the most reliable (stringent data) from Olival et al4. In addition, a query in GenBank was run to parse out hosts reported for each GenBank submission for viruses presented in each of these three databases. Initially, for each virus name, taxonomic ID was identified using entrez.esearch function in biopython package. The taxonomic ID helped linked to the GenBank databases, identify the ICTV lineage and associated data in PubMed21. NCBI TaxID closely follows the ICTV database, but some recent changes in ICTV might not always be reflected in NCBI, so we manually checked names to ensure matching. This included virus genus and family information along with a standard virus name. Host data were aggregated based on the taxonomic ID and associated standard name. Finally, for each virus, a search was completed in PubMed to compile the number of hits related to the virus and their vertebrate hosts using the search terms below. The number of PubMed hits (PMH1) were used as a proxy for sampling bias13. The virus-host association data source is presented in supplementary code and data files (https://zenodo.org/record/5899054).Virus-host data was collated from various sources. Major sources for the association databases included data shared by Olival et alnucleotide database on PubMed using the taxonomic ID to find the number of GenBank entries for these viruses (PMH2). A correlation analysis between the PMH1 and PMH2 of well-recognized known viruses showed a high correlation with each other for us to safely use GenBank hits for novel viruses during the prediction stage of the model  and clustering coefficient within the observed network  for viral nodes in the observed network : Is the sum of inverse logarithmic degree centrality of the neighbors shared by two nodes in the network25, the information flowing through neighborhoods formed by two nodes might not always be enough to have similar predictive power in an unipartite network. This warrants use of other topology features along with neighborhood-based features.Both Jaccard and Adamic Adar coefficients have been routinely used for generalized network prediction and have shown high accuracy in predicting missing links in networks, specifically bipartite networks3. Resource allocation: Similarity score of two nodes defined by the weights of common neighbors of two nodes. Resource allocation is another measure to quantify the closeness of two nodes in the network and hence to understand the similarity of hosts they infect.x is proportional to k26.4. Preferential attachment coefficients: The mechanism of preferential attachment can be used to generate evolving scale-free networks, where the probability that a new link is connected to node 5. Betweenness centrality: For a node in the network betweenness centrality is the sum of the fraction of all-pairs shortest paths that pass through it. The feature that we used for training the supervised learning model was the absolute difference between of betweenness centralities of two nodes. The difference between the betweenness centrality represents the difference in the sharing observed by two viruses in the pair.v is the fraction of nodes it is connected to. The feature that we used for training the supervised learning model was the absolute difference between degree centralities of two nodes. Unlike the difference in the betweenness centrality, the difference in degree centrality only looks at the difference in the number of observed host sharing.6. Degree centrality: The degree centrality for a node 27. A binary feature variable was generated to describe if both the nodes in the pair were part of the same cluster or not. If both viruses are from the same cluster, it represents a similar host predilection than when both viruses are not from the same cluster hence accounting for the evolutionary predilection of viruses (or virus families) to infect a certain type of host.7. Network clustering: All nodes were classified into community clusters using Louvain methodsThese topological network characteristics come with certain limitations when it comes to the unipartite network of viruses with links formed due to shared hosts and might not truly represent the flow of information between nodes as compared to a bipartite network. Therefore, to account for these limitations, we use multiple network features as weak learners in our model building characteristics summarizing the network through the use of several quantitative metrics. In addition to this, we estimated the feature importance of these metrics in predicting missing links between viruses to quantify the information pasting through these links.V1, PubMedV2) and the absolute difference between PubMedV1 and PubMedV2 to account for differences in sampling bias between the two viruses.Pearson’s correlation coefficients were calculated to identify highly correlated features and for choosing features for model training Fig. . VirologA nested-cross-validation was implemented for the binary model while simple cross-validation was implemented for the multiclass model (multiple output categories). The parameters of the binary model were first hyper-tuned using a cross-validated grid-search method. Values were tested using a grid search to find the best-performing model parameters that showed the highest sensitivity . The parameters tested for hypertuning and their performance are provided in the supplementary material , the percentage of times the feature appears in the XGboost tree model (weight), and the relative number of observations related to the specific feature (cover). Results for feature importance are shown in supplementary results Fig. .1. Specimens were tested using conventional Rt-PCR, Quantitative PCR, Sanger sequencing, and Next Generation Sequencing protocols to detect viruses from 28 virus families or taxonomic groups  conducted in 34 countries around the world between 2009–2019 Table 1. Specimps Table . Testing1. A new node representing the novel virus was inserted in the observed network , the difference in betweenness centrality of the novel virus and known virus, if the novel virus and known virus were in the same cluster, the difference in degree centrality, if the novel virus and known virus were from same virus family, the difference in PubMed hits, PubMed hits for the novel virus, PubMed hits for the known virus). Studies and nucleotide sequences for novel viruses are expected to be published and shared on PubMed’s Nucleotide database and in various peer-reviewed publications. Data associated with GenBank accession numbers and nucleotide sequences for novel viruses are presented in Supplementary Data 2. Using β = 0.72, p < 0.005) even after accounting for various virus families. Multiple virus families showed statistically different estimates than the reference virus family (Adenoviridae) indicating a significantly different association than other virus families. Results of the generalized linear regression model are presented in Table The results indicated that Genbank hits had statistically significant predictive value in predicting PubMed hits  influenced node (virus) level network centrality measures in the predicted network  was randomly assigned to covariate values and the model was re-fitted. A glmmTMB and glm packages in R. For relative comparison of zoonotic risk and for prioritizing novel viruses for further characterization, a prioritization metric was developed based on the predicted probability of sharing the humans as hosts with known viruses (Generalized Linear Mixed Models were used to understand the association effects of virus family, taxonomic order of the host and PubMed hits on the number of predicted human links and mean probability of the predicted links. The models were fit using Further information on research design is available in the Supplementary MaterialsDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Reporting Summary


Seventy-two percent of patients were treated in pediatrics. Twenty-five patients underwent liver transplantation, and 14 died after GSD diagnosis. In South Korea, more patients than expected had GSD diagnosis and were managed accordingly. GSD causes many complications and hospitalizations, resulting in high medical expenses. Serious complications can result in liver transplantation and, eventually, death in some cases. Although the patients' condition was identified only by the disease code, this is the first study to present the current situation of GSD patients in South Korea. Because GSD patients can have dangerous medical conditions, they should be managed consistently while minimizing various complications that may occur with optimal metabolic control.Glycogen storage disease (GSD) is a rare disease that can cause life-threatening problems owing to metabolic errors in storing or using glycogen. The disease course of GSD remains unknown, despite medical technology advances. We determined the prevalence and complications of GSD using data from the National Health Insurance Service database. Data were collected and analyzed for the entire South Korean population with GSD during 2007–2018. GSD was defined as a combination of disease code E74.0 and rare incurable disease insurance code V117, a unique disease code combination for GSD in South Korea. Overall, 23,055 patients had the E74 disease code; 404 had an additional V117 insurance code. Most GSD patients were aged <10 years. Many complications were identified, the most common being hepatomegaly, hyperuricemia, and elevated liver enzyme levels. The most prescribed drug was  Glycogen storage disease (GSD) is a rare disease that can cause life-threatening problems owing to metabolic errors in storing or using glycogen in the liver or muscle . FurtherTherefore, in this study, we investigated the prevalence of GSD in South Korea and possible complications and problems in GSD for more efficient treatment.The National Health Insurance system provides all medical information of the population in South Korea. Furthermore, the Health Insurance and Review Assessment Service (HIRA) has every medical database available for researchers. This retrospective, population-based cohort study was conducted using HIRA research data.South Korea defines GSD as a rare disease and provides financial support by registering the rare incurable disease insurance code V117, a unique disease code for patients with GSD in South Korea. When registering V117, laboratory tests, genetic tests, and doctor's judgment are required. We tried to define patients with GSD as having a combination of both disease codes E74.0 and V117.We obtained medical records of patients with GSD during 2007–2018. Among patients with GSD, we defined patients as having complications according to the International Classification of Diseases (ICD) codes other than E74.0.The Institutional Review Board of Wonju Severance Christian Hospital approved this study (IRB No. CR319323).t-test or Mann-Whitney U test.Data were expressed according to variable characteristics. Categorical data are reported as numbers with percentages and were compared using Pearson's chi-square test or Fisher's exact test. Continuous data are reported as means ± standard deviations and were compared using independent p value of < 0.05 was considered to indicate statistical significance for all analyses.Chi-square tests were used to detect any differences in the distribution of numbers and costs according to age, sex, and disease codes. The annual number of each procedure and its crude incidence, that is, the GSD patients/year-specific population, was calculated. Annual population data of South Koreans were obtained from the Korean Statistical Information Service. Data analysis was performed using SAS software (version 9.4). A Overall, 23,055 patients had the ICD code E74 during 2007–2018. Among them, 741 (3.21%) had only the ICD code E74.0, and 404 (1.7%) had both E74.0 and V117 codes .From 2007 to 2018, 404 patients with GSD were classified by age . The meaA graph of the age-adjusted rate of newly diagnosed GSD cases since 2007 is shown in After diagnosis, 71% of the patients were managed by a pediatrician in 2018 . PatientIn 2018, 363 patients with GSD visited hospital in Korea. A total of 261 admissions and 2,266 outpatient clinic visits were conducted. In 2018, the average medical cost per patient was 30,601,989 won. There was a difference, from a minimum of 16,890 won to a maximum of 752,667,350 won. From 2007 to 2018, the average total hospital cost of 404 patients with GSD was 169,730,862 won, which varied from a minimum of 256,740 won to a maximum of 3,525,930,160 won.Among the complications, the hepatomegaly code was the most frequently included code in the data. Furthermore, hyperuricemia and elevation of liver enzymes, followed by growth failure, hypoglycemia, cardiac hypertrophy, hypertriglyceridemia, and hematuria, were the most common complications of GSD .Various medications were prescribed to patients with GSD in 2018. The most prescribed medication for GSD was alpha-glucosidase, which is used for GSD II. Filgrastim was the next most prescribed treatment, and it was is thought to be for patients with GSD Ib. Allopurinol was widely administered to patients with GSD.Twenty-five patients  received liver transplantation after the diagnosis of GSD despite receiving various treatments. The average age at liver transplantation was 19.24 years . Since 2007, 14 patients have died of GSD complications. The average age was 25.43 years . Among the 14 patients, patients died at approximately 1,048 days after being diagnosed with GSD .This study described the current status of patients with GSD disease codes in South Korea, including age at diagnosis, number of hospitalizations and outpatient visits, medical expenses, complications, and mortality.Although it was not possible to distinguish the exact type of GSD patients, a total of 404 people were diagnosed with GSD in South Korea from 2007 to 2018, of whom 224 (56%) were diagnosed before the age of 9 years with the development of diagnostic technology and efforts of medical staff. However, most patients with GSD receive outpatient and inpatient treatment and spent an average of 30 million won a year, which increases medical expenses and leads to many complications.Rake et al. described the complications of 231 GSD Ia and 57 GSD Ib patients at 16 centers in 12 European countries in 1996 . AccordiHowever, recently, treatment using raw corn starch and maintenance of optimal metabolic control can reduce complications . ComplicTherefore, in cases of clinical suspicion, it is necessary to actively conduct related tests; the role of the pediatrician is very important, considering that GSD is diagnosed in individuals belonging to a relatively young age group. Reducing overall complications, medical costs, and mortality through early diagnosis and treatment will be of great help from a social and economic perspective.Although GSD is a chronic disease that requires lifelong management, not many large-scale analyses have been conducted, and relatively little attention has been paid to it.As already mentioned in studies conducted in other countries, complications such as hepatomegaly, hyperuricemia, elevated liver enzyme levels, growth failure, hypoglycemia, cardiac hypertrophy, and hyperlipidemia are highly prevalent in South Korean patients with GSD. In addition, it has been confirmed that if proper treatment is not received in time, then hepatic adenomas appear around the age of 10-30 years that become malignant tumors; this may increase the requirement for liver transplantation and may even lead to death.As described above, GSD is a disease that causes complications accompanied by various metabolic abnormalities, increases the frequency of hospitalization, increases medical expenses, and reduces the quality of life of patients and their families, eventually leading to death.A limitation of the study is that it confirmed only the disease code without seeing the patient directly. Additionally, there is a high possibility that the frequency of complications may not be accurate because there are many cases in which not all diagnosis names are included when prescribing inpatients and outpatient treatment. The author tried to classify the GSD type but failed in this study. Many attempts were made to classify the GSD type by complication diagnosis code that can be included by each type or a special drug used for each type, but the GSD type could not be distinguished because the diagnosis code was not written properly when treating GSD, and there were cases where proper treatment was not received. This is considered a major limitation in this study. Doctors' efforts should be made to fill in a specific type of patients with glycogen storage disease, complication code rather than just fill in with glycogen storage disease.In addition, since the registration of rare diseases started in 2007, several patients with GSD were registered between 2007 and 2009, and it may have biased the results. Because the number of previously diagnosed patients has been sufficiently registered, the prevalence rate is expected to be accurate from approximately 2010 onward. Despite these limitations, this is the first study to use big data to confirm the current status of patients with GSD in South Korea.In South Korea, more patients than expected are diagnosed with GSD and managed. GSD is associated with many complications and causes frequent hospitalizations, resulting in high medical expenses. Serious complications can result in liver transplantation and even death in some cases. Although there is a limitation that the patient's condition was identified only by the disease code included in the treatment, this is the first study to present the current situation of patients with GSD in South Korea. Because patients with GSD can have dangerous medical conditions, patients with GSD should be managed consistently while minimizing various complications that may occur with optimal metabolic control.


Fragility fractures are one of the leading causes of disability in older adults. Yet, evidence for effectiveness and cost-effectiveness of preventive approaches combining bone health and fall prevention is rare.To conduct a health-economic evaluation of the German osteoporotic fracture prevention program in rural areas (OFRA).Secondary cluster–randomized intervention study based on routine data.All districts in five federal states in Germany were cluster-randomized as intervention or control districts. OFRA was offered to community-living (a) women aged 75–79 years or (b) women and men aged 70–84 years with a prior fragility fracture in the intervention districts. Individuals who meet these criteria in the control districts were assigned to the control group.OFRA comprised mobility and falls prevention classes, examination of bone health by bone density measurement, and consultation on safety in the home living environment.We measured health-care costs and effectiveness in terms of time to fragility fracture or death within 1 year after initial contact, based on health insurance claims data. Implementation costs were recorded by the intervention performers. We calculated an incremental cost-effectiveness ratio (ICER) and employed the net-benefit approach to construct a cost-effectiveness acceptability curve (CEAC).p < .01) were reduced, but mean intervention costs (difference: 260.10€) increased total costs  in the intervention group. The ICER per fracture-free year of survival was 66,094.63€. The CEAC showed no acceptable probability of cost-effectiveness at a reasonable willingness to pay.There were 9408 individuals in the intervention group and 27,318 in the control group. Mean time to fragility fracture or death (difference: 0.82 days) and health-care costs (difference: 111.73€, OFRA showed reduced rates of fragility fractures, but had high implementation costs, resulting in an unfavorable ICER. The cost-effectiveness of OFRA may improve with a longer follow-up. Moreover, to the best of our knowledge, there are no studies evaluating a program combining bone health and fall prevention for community-dwelling older adults from a health-economic perspective.However, coordinated preventive approaches for community-living older adults that include both fall prevention measures and osteoporosis examination and treatment are limited,12 and the primary analysis.13The objective of this study was to conduct a health-economic evaluation of a large fragility fracture prevention program in Germany. The program was carried out in rural areas in Germany from October 2015 through to September 2017, and aimed at improving physical function and reducing the risk of falls and fractures in older adults. The components of the program were exercise classes, examination of bone health by a dual-energy X-ray absorptiometry (DXA) scan, and a consultation on safety adjustments in the living environment. The program was described in detail in the study protocolThe osteoporotic fracture prevention program in rural areas (OFRA) was a large health-insurance-driven program to improve safe mobility and reduce the risk of falls and fragility fractures in older adults living in rural areas. The participating health insurance company “Sozialversicherung für Landwirtschaft, Forsten und Gartenbau” (SVLFG) provides health insurance that is compulsory for people working in agriculture, gardening, and forestry, and insures approx. 670,000 persons. The health insurance company cooperated with the German Association of Rural Women (DLV), the German Gymnastics Association (DTB), and the Robert Bosch Institute for Medical Research (RBMF) as part of OFRA.OFRA consisted of mobility and fall prevention classes, examination of bone health by a DXA bone density measurement, osteoporotic treatment where indicated, and consultation on safety in the living environment.15 and on a fall prevention program by the DTB.16 Six sessions of 90 min were delivered within 6 weeks. Individuals were encouraged to perform exercises at home further on, for which they received an instruction booklet and a training log. In order to increase the spatial proximity for the individuals, classes took place at local facilities nearby the individuals’ home. The trainers were physiotherapists or exercise instructors from local sports clubs provided by the DTB with additional education regarding OFRA. Exercise devices such as weight cuffs were provided by the SVLFG. Participation was open to all individuals, including those not insured at the SVLFG, and free of charge.The mobility and fall prevention classes were based on the Otago exercise program17 The individuals were asked to talk to their general practitioners. The general practitioners were reimbursed for counseling and treatment, if necessary.A DXA scan for a bone density measurement was recommended to all individuals at no charge based on the German osteoporosis guideline.Nearly all individuals were visited by a prevention manager of the SVLFG who encouraged them to attend the classes or to make use of a DXA scan. If required, the prevention manager gave advice on how to improve safety of the living environment.Furthermore, the SVLFG established telecenters which initially contacted and informed selected individuals in the intervention districts about OFRA. Where an individual was interested in participating, the telecenters referred them to one of the classes nearby. The telecenters also coordinated the prevention classes, and sent training materials to the trainers. Further information was made available on a homepage.The study was registered at the German Clinical Trials Register (DRKS-ID: DRKS00009000) and approved by the ethics committee of Ulm University . Individuals gave informed consent for their data to be shared, for example, to the organizer of an exercise class.The implementation of OFRA took place in 47 administrative districts in five federal states , corresponding to around half of the area of Germany. All administrative districts were randomly assigned to either intervention or control districts using a 1:3 cluster randomization. The control districts received no intervention.The program was offered to (i) women and men aged 70 to < 85 years with a fragility fracture in the previous 5 years, and (ii) all women aged 75 to < 80 years, who were insured by the SVLFG and community-living in the intervention districts. Individuals were excluded if they were living in a nursing home or if their care need for the basic activities of daily living was 120 min or more according to the categorization of the German long-term-care insurance . All individuals in the control districts with identical selection criteria were categorized as control group (CG).OFRA started on October 1, 2015 and was offered for 2 years. The time period between the information letter and the start of an exercise class was usually at least 2 months. Therefore, follow-up began 2 months after the first contact of the intervention group (IG) individuals by the SVLFG. All individuals were followed for 1 year, or until fracture or death. For the analysis, each individual from the IG was randomly matched to three individuals from the CG. This matching was stratified by federal state and selection group. For each individual from the CG, a starting date was assigned according to the matched individual from the IG. After the matching, an equal distribution of pre-intervention characteristics was ensured.Health insurance claims data were provided by the SVLFG. Information on expenditures for OFRA was recorded by RBMF and SVLFG. The mobility and fall prevention classes were continued following the conclusion of OFRA in September 2017. When calculating costs, we assumed the last classes were in December 2017, allowing sufficient time for the IG to participate after initial contact. Costs were also incurred for the telecenter until December 2017.All costs occurring before the start of OFRA in October 2015 were assumed as preparation costs, and all costs during OFRA (October 2015–September 2017) as operation costs. Both RBMF and SVLFG had expenditures for OFRA, categorized as staff and other costs.18Staff costs were calculated as follows: personnel working time for the coordination of OFRA, cost of the staff in the telecenters, and cost of prevention managers . Additional payments by the employer such as social security contributions were added, if applicable. For the coordination of OFRA by the RBMF, we assumed all employees’ salary scales as E13 . For the coordination of OFRA by the SVLFG, we assumed an 80% share of A10 and 20% share of A13  according to the specifications of the SVLFG. For personnel costs for the telecenters as well as for the prevention managers, the civil servant salary scale A9 was assumed. All salary scales were calculated according the Federal Ministry of Finance.Other costs occurring before the start of OFRA were considered as preparation costs. Material costs for the mobility and fall prevention classes  were recorded by the SVLFG. Costs for the education of trainers were fixed at 350€ plus usual expenses for traveling. The number of trainers who completed the education was recorded by the SVLFG. Costs for information technology comprised the establishment and maintenance of the homepage and system adjustments for the monitoring of OFRA and were recorded by RBMF and SVLFG. Travel costs for the coordination of OFRA were recorded by the RBMF.Other costs occurring during OFRA were considered operational costs. Delivery of a mobility and fall prevention class of six sessions was reimbursed with a fixed 700€. The number of classes was recorded by the SVLFG. Costs for the design, print, and distribution of information material such as letters, reports, instruction booklets, and training logs were recorded by the RBMF and the SVLFG. Travel costs during OFRA were recorded by the RBMF.n = 2866) attended a class.19 As recorded by the SVLFG, there were 1733 classes during the period from October 2015 to December 2017 with an average participation rate of 11.2,20 which equals n = 19,410 class participants. Of those, 2866 belonged to the IG, which is a share of 14.8%. This share was applied to the material, training, and staff costs of the exercise classes. Furthermore, it was applied to the share of personnel working time of the telecenters which was used for tasks related to the classes, e.g., organization or distribution of training materials, which yielded a share of 59.5% for telecenter costs. Costs for the DXA scan were recorded in the claims data (see next section).The mobility and fall prevention classes were open to participation not only for the IG but for all individuals living nearby. Therefore, the share of individuals from the IG actually was lower than 100% and it would be inappropriate to fully take the costs for those classes into account. Therefore, we calculated a share of costs for the IG as follows: Of 9681 IG individuals, 29.6% , DXA scans , medication for osteoporosis with bisphosphonates and denosumab , and both inpatient and outpatient long-term care. We could not observe if long-term care was due to a fracture. However, we assume that the distribution of fracture-related and -unrelated long-term care is equal for IG and CG.22 and reported in 2017 Euro.All costs were adjusted for inflation using the gross domestic product price indexEffectiveness was measured as time to hospital admission due to fragility fractures  or death. For both health-care costs and time to fracture or death, individuals were followed up to 1 year from the date of first contact.The difference of fragility fractures between groups was tested with logit models. The difference of costs was tested with two-part models with logit models, to test if there were any costs per individual, and subsequent generalized linear models with gamma distribution to estimate the amount of costs. The difference of the time to fracture or death was tested with Cox proportional hazards models.The incremental cost-effectiveness ratio (ICER) was calculated:The ICER refers to the additional costs generated by OFRA to achieve an additional fracture-free year of survival, compared to usual care. Where OFRA is less costly and more effective, it is cost-effective. However, if OFRA is costlier and more effective, the cost-effectiveness depends on the maximum willingness to pay (WTP).Cost-effectiveness acceptability curves were constructed to handle the uncertainty of the ICER. This approach reformulates the ICER into a net-monetary benefit (NMB) and considers different maximum WTP. For each WTP, OFRA is cost-effective if the point estimate of the NMB is positive:Since the WTP was unknown, it was iterated from 0€ to 2,500,000€ in steps of 10,000. The iterated NMB was used as dependent variable in a regression model with OFRA as binary independent variable.The resulting cost-effectiveness acceptability curve (CEAC) describes OFRA’s probability of being cost-effective at different WTPs. OFRA may be considered cost-effective if the probability of being cost-effective is above 95%.There were 47 IG districts with 9408 individuals and 139 CG districts with 27,318 individuals . Fracture-free time of survival was slightly longer in the IG (0.82 days). Mean fracture-related health-care costs were significantly lower in the IG , driven by hospital and inpatient long-term care costs. Mean costs for DXA scans  and medication  significantly increased in IG, as intended by OFRA. When additionally considering intervention costs, mean total costs were significantly higher in the IG . The ICER per fracture-free year of survival was 66,094.63€.The proportion of fragility fractures was slightly lower in the IG than in the CG (difference: 0.3%) (Table The CEAC is displayed in Figure OFRA was shown to prevent fragility fractures. Health-care costs decreased, except for DXA bone density measurement and osteoporotic medication. Total costs including implementation costs increased. Cost-effectiveness could not be shown within 1-year follow-up.A differentiation between costs of preparation and operation is reasonable, as only the latter will occur to maintain the program. An additional analysis with only operational costs did not change the results considerably. Driving cost categories are staff costs for coordination, telecenters and prevention managers, all main elements of OFRA.13 Fractures other than femoral, mortality, and nursing home admission did not significantly differ between groups. Both exercises24 and treatment of osteoporosis may have beneficial effects on fractures according to literature.8 However, approaches combining both measures are rare25 and cost-effectiveness has not yet been evaluated.The health outcomes were investigated in detail in another publication.OFRA was based on a case-finding approach; thus, a large share of initially addressed individuals did not participate in one of the components of OFRA. This intention-to-treat approach induced a dilution effect which decreases the overall efficacy. By addressing particularly vulnerable risk groups, the uptake rate of OFRA components could be improved. This may increase efficacy.The 1-year follow-up period may be too short to investigate long-term effects. Probably, a longer follow-up would increase the effectiveness. Yet, a decrease of femoral fractures was observed. When focusing only on these fractures, the probability of cost-effectiveness may increase.OFRA may not only aim at reducing fragility fractures but additionally motivate regular exercise, a healthy lifestyle, and a general education on prevention to maintain physical abilities. OFRA may have increased the number of social interactions and decreased the number of falls not resulting in fractures. However, these factors were not considered in our analysis.This study has some limitations. The choice of intervention districts may not be representative of the whole of Germany, as they were limited to rural districts. An implementation of OFRA in the eastern part of Germany was not possible due to a different infrastructure. The individuals were insurants of the SVLFG, who are people working in agriculture, gardening, and forestry. Therefore, the representativeness of the study may be limited to a rural population working in agriculture, gardening, and forestry. Furthermore, the payer perspective on costs does not cover all costs actually occurring. Particularly, costs of informal care and productivity losses due to sick leave were not covered. However, we assume a large proportion of persons being retired due to older age.To name some strengths, our study was based on a large dataset of health insurance claims data. The intervention targeted a large German population and was implemented close to real-world conditions, as opposed to highly selected randomized controlled trials comprising a small population observed in non-daily conditions. The evaluation, therefore, has high external validity, and OFRA could be readily continued and further implemented.OFRA aimed at preventing fragility fractures in older adults living in rural areas in Germany by offering exercise classes, examination of bone health, and consultation on safety adjustments in the living environment. OFRA increased the fracture-free time of survival and improved examination and treatment of bone health. However, the costs for OFRA exceeded savings due to reduced health-care utilization. We found an unfavorable ratio of incremental costs and effectiveness. However, OFRA likely had further, unobserved effects on a physical and psychosocial level.