In 2007, a novel bunyavirus was found in Henan Province, China and named fever, thrombocytopenia and leukocytopenia syndrome virus (FTLSV); since then, FTLSV has been found in ticks and animals in many Chinese provinces. Human-to-human transmission has been documented, indicating that FTLSV should be considered a potential public health threat. Determining the historical spread of FTLSV could help curtail its spread and prevent future movement of this virus.To examine the pattern of FTLSV evolution and the origin of outbreak strains, as well to examine the rate of evolution, the genome of 12 FTLSV strains were sequenced and a phylogenetic and Bayesian phylogeographic analysis of all available FTLSV sequences in China were performed. Analysis based on the FTLSV L segment suggests that the virus likely originated somewhere in Huaiyangshan circa 1790  and began spreading around 1806 . Analysis also indicates that when FTLSV arrived in Jiangsu province from Huaiyangshan, Jiangsu Province became another source for the spread of the disease. Bayesian factor test analysis identified three major transmission routes: Huaiyangshan to Jiangsu, Jiangsu to Liaoning, and Jiangsu to Shandong. The speed of FTLSV movement has increased in recent decades, likely facilitated by modern human activity and ecosystem changes. In addition, evidence of RNA segment reassortment was found in FTLSV; purifying selection appears to have been the dominant force in the evolution of this virus.Results presented in the manuscript suggest that the Huaiyangshan area is likely be the origin of FTLSV in China and identified probable viral migration routes. These results provide new insights into the origin and spread of FTLSV in China, and provide a foundation for future virological surveillance and control. FTLSV is novel bunyavirus belonging to genus Phlebovirus and was first found in Huaiyangshan area. The epidemiology and pathogenesis of FTLSV remain poorly understood. This lack of information underscores the importance of analyzing the movement and genetic history of FTLSV in China. Recent advances in Bayesian coalescent phylogenetic analyses have resulted in more sophisticated methods being available for determining the relative age of emerging pathogens. In this study, a phylogenetic and Bayesian phylogeographic analysis was performed for FTLSV whole genomic sequences isolated from China. Results identified the Huaiyangshan area as the most probable origin of FTLSV and suggested migrating routes of the virus. These results offer the first description of the movement and history of FTLSV in China. RNA segment reassortment was found in FTLSV; purifying selection appears to have been the dominant force driving the evolution of this virus. The results of this study could be used to facilitate the development of new strategies for controlling FTLSV. Bunyaviridae family, genus Phlebovirus in FTLS cases; the virus has been named several times including severe fever with thrombocytopenia syndrome virus (SFSTV), Henan fever virus (HFV), fever, thrombocytopenia and leukopenia syndrome virus (FTLSV), and Huaiyangshan virus (HYSV) In 2007, the fever, thrombocytopenia and leukopenia syndrome  was first reported in Henan province, China Bunyaviridae; it is composed of three segments, designated L, M and S. The L segment contains 6391 nucleotides encoding an RNA-dependent RNA polymerase; the M segment contains 3366 nucleotides encoding glycoproteins Gn and Gc; and the S segment contains 1760 nucleotides of antisense RNA encoding a nonstructural protein (NS) and a nucleocapsid protein (N) in opposite orientations. Partial sequencing of L and S segments from human cases and ticks confirmed that FTLSV is a novel Phlebovirus and is most closely related to the non-pathogenic Uukuniemi virus  The genome of FTLSV is similar to that of other Haemaphysalis longicornis and Rhipicephalus microplus ticks collected from a number of domestic animals, including cattle, buffalo, goats, cats and dogs Only a few members of the Phlebovirus genus use ticks as a vector; FTLSV is likely to be transmitted to human populations from an animal reservoir via feeding of infected ticks In the present study, a powerful Bayesian phylogeographic approach to reconstruct the transmission of FTLSV through space and time was used to infer the geographic locations of ancestral viral lineages. In addition estimates of viral evolution rate and the divergence date of FTLSV were calculated.Serum samples from FTLSV-infected patients (n = 12) were obtained by disease control and prevention workers in the Xinyang and Nanyang counties of Henan Province, China, during 2011–2012, and viral isolates were cultured from the sera 2, 10 mM DTT, 100 ng of random hexamer primers, 200 units of Superscript II (Invitrogen), 25 units of RNasin (Promega) and 0.5 mM dNTPs. Overlapping PCR was performed, and products were subjected to Sanger sequencing For sequencing, total RNA was extracted from 140 µl aliquots of cell culture supernatant obtained from each sample using a QIAamp viral RNA Mini Kit (Qiagen) according to the manufacturer's instructions. cDNA was reverse transcribed from 6 µl of RNA at 45°C for 50 min in a 20 µl solution containing 50 mM Tris–HCl (pH 8.3), 75 mM KCl, 3 mM MgClSequences of FTLSV isolates available in the GenBank were downloaded and used in phylogenetic analyses. Only full-length S, M and L segment sequences with available collection dates and locations were included. The viral sequences that were newly determined in this study have been deposited in GenBank under accession numbers KF356517 to KF356552. Sequences were aligned by Clustal W using BioEdit software Phylogenetic trees for the three viral RNA segments were constructed using the maximum likelihood (ML) method, a feature of the software MEGA 5 Evolution rates and estimates of time since the most recent common ancestor (MRCA) were generated via Bayesian coalescent phylogenetic analysis using the BEAST software package version 2.0.2 http://earth.google.com). Following our discrete phylogeographic visualizations, we used SPREAD 1.04 To investigate the phylogeographic diffusion process along the posterior sets of the trees, relationships between locations were identified using the Bayesian stochastic variable search selection (BSSVS) applications in BEAST version 2.0.2 For phylogeographic analysis, each FTLSV sequence (or isolate/strain) was first assigned a character state reflecting its location of origin. Because the FTLS cases reported in Henan and Hubei province were located near the border of Tongboshan, belonging to the Huaiyangshan Mountain region, Henan and Hubei Provinces were combined into the Huaiyangshan (HYS) region in the analysis. Based on the geographic locations from which the studied isolates were obtained, migration was considered among four provinces  and one area (Huaiyangshan). For each taxon in the dataset, character states were assigned to the respective locations , the association index (AI) and parsimony score (PS) statistics of clustering strength was computed using the BaTS (Bayesian tip-association significance testing) method Selection analyses were performed on the full dataset using the Datamonkey server implementation of HyPhy In this study, whole genome sequencing was performed on 12 FLTSV strains isolated in Henan Province, China. And the sequences were submitted into the Genebank (KF356517 to KF356552). Little variation was observed in the overall nucleotide lengths of the S, M, and L segments from viruses circulating in Henan from 2011 to 2012, and pairwise differences in the percent nucleotide identities were low, ranging from 0.1%–4.2%, 0.2%–4.7% and 0.1%–5.8% for the L, M, and S segments, respectively.For the three viral RNA segments, Bayesian analysis yielded highly supported tree topologies that were consistent with the ML results , 2 and 3Tree topologies obtained from the L segment analysis were similar to those generated using the M and S segments, but a more detailed analysis revealed some inconsistencies that seemed to indicate reassortment events. Two typical reassortment events appear to have occurred: 1) in the AHL/2011 strains, the L and M segments belonged to the D genotype, while the S segment fell into the B linage , 2 and 3Analysis with the SLAC algorithm showed that the global ratio of nonsynonymous to synonymous nucleotide substitutions (dN/dS) in the L segment was 0.0480, suggesting the presence of predominantly purifying selection. The SLAC algorithm further identified 72 sites in the L segment that appeared to be under negative selection, while the FEL, IFEL and REL analyses detected one site (positions D691E/G) that appeared to be under positive selection in this segment. For the M segment, the SLAC algorithm analysis showed that the dN/dS was 0.0909 and detected 76 sites under negative selection. With respect to sites that appeared to be under positive selection, the FEL, IFEL and REL algorithms agreed on two sites (positions D37G/A and T501A/S); FEL and REL indicated one site (V323I); the REL algorithm alone detected one site (position I11T/V); and the IFEL method alone identified one site (T960I/S). For N and NS (encoded by the S segment), the dN/dS ratios were 0.0367 and 0.0991, respectively, and the SLAC, FEL, IFEL and REL methods failed to identify any sites that appeared to be under positive selection.−4 (1.58×10−5–6.46×10−4), M = 3.08×10−4 (5.56×10−5–6.67×10−4) and L = 1.95×10−4 (5.01×10−5–3.37×10−4) nucleotide substitutions/site/year. The MRCA of the current viruses identified today as FTLSV is estimated to have existed 117 (95%HPD = 36–241) years before present based the M segment analysis, 159 (95% HPD = 54–321) years before present based on the L segment analysis, and 195 (95% HPD = 28–455) years before present based on the S segment analysis.The mean molecular evolutionary rate estimates and 95% highest posterior density (HPD) intervals based on the Bayesian coalescent analyses were S = 3.17t10To determine the geographic origins and movements of FLTSV in China, the results of the Bayesian phylogeographic analyses were summarized by annotating the MCC tree nodes with their most probable location states via color labeling . The colin situ evolution rather than extensive migration. However, the number of sequences from Anhui, Liaoning and Shandong was small, which may bias the result.Both the AI and PS statistics indicated that there was very strong geographic clustering of FTLSV strains by province or area of origin (P<0.05) . When thFTLS represents a threat to public health, and understanding the how the causative virus sustains and spreads in the environment is important to implementing effective prevention and control measures. Currently, however, the mechanisms underlying the emergence and spread of FTLSV are unknown. The virus was first reported in 2007 Haemaphysalis longicornis and Rhipicephalus microplus) and domestic animals such as sheep, goat and cattle The phylogenetic relationships between strains circulating in China and Japan were reconfirmed as a part of this study, as were identification of the five genotypes already identified as circulating in China, consistent with the results reported by Zhang and Lam et al Evolution of FTLSV has impacted the sequence of all three viral RNA segments, creating unique viral genotypes and S, M and L RNA segment phylogenetic topologies indicate that FTLSV reassortment (particularly in the S segment) is not uncommon. Genetic reassortment can profoundly affect the pathogenicity and diversity of RNA viruses Purifying selection also appears to be another potential force in the evolution of FTLSV, although some sites were also found to be under positive selection. These results indicated that nucleotide fixation events are due primarily to genetic drift and stochastic processes, which may be important in the evolution of FTLSV.Strong purifying selection can maintain evidence of sequence homology long after saturation has occurred at synonymous sites th century. Bayesian analysis indicated that the most recent common ancestor of the FTLSV strains existed an estimated 117 to 195 year prior to 2012. Similar estimates were obtained for the L, M and S segments, indicating that these segments have co-evolved. Lam et al. Bunyaviridae, RVFV is mosquito-borne while FTLSV is tick-borne, and mosquito-borne RNA viruses are believed to evolve more rapidly than tick-borne viruses within the same family Although the emergence of FTLSV and its association with FTLS was first confirmed during the summer of 2009 Haemaphysalis longicornis and Rhipicephalus microplus, which are widely distributed across China and globally, conditions exist for FTLSV to have been transmitted from Huaiyangshan to neighboring provinces in China in situ evolution has played an important role in the maintenance of FTLSV in China. Additionally, the results of the BaTS analysis that considered the extent of population subdivision between individual provinces or areas and all others as a group indicate that for two of the five provinces or areas sampled , the observed FTLSV genetic diversity was shaped primarily by in situ evolution as opposed to extensive migration.Bayesian phylogeographic analysis indicated that the Huaiyangshan area might be the origin of FTLSV. Huaiyangshan Mountain borders \ Henan and Hubei Provinces in China; these provinces are the source of the Huaihe River, which forms the dividing line between southern and northern China. This biologically diverse region has been and remains a home to cultural and economic exchanges between the two halves of China. As FTLSV has been detected in the circulating tick vectors This paper offers the first description of the movement of FTLSV in China. Our results indicate that this movement was slow during the early years of the spread, but has increasingly become more rapid in recent decades. Bayesian phylogeographic analysis showed that FTLSV arose in Huaiyangshan between 1756 and 1817, and then moved into the Jiangsu and Anhui Provinces between 1773 and 1834. Over the next hundred years, FTLSV continued to circulate through Jiangsu, Anhui and the Huaiyangshan region. Once FTLSV reached Jiangsu Province, this province became a secondary source of FTLSV spread, as the virus moved from Jiangsu Province into Liaoning Province between 1905 and 1943. In the past 50 or 60 years FTLSV has moved more rapidly, as the MCC tree shows that many strains isolated from Shandong, Liaoning and Anhui were recently introduced from Huaiyangshan and Jiangsu. Finally, the Bayesian test provided statistical support for three transmission routes: from Huaiyangshan to Jiangsu, from Jiangsu to Shandong and from Jiangsu to Liaoning.Collectively, these findings indicate that Huaiyangshan and Jiangsu may be the two major origins of FTLSV in China. Movement over large distances was observed, such as that between Liaoning and Jiangsu Province and Huaiyangshan (∼1500 km). It is likely that an animal infected with FTLSV or carrying virus-infected ticks introduce FTLSV into Liaoning Province. The recent dramatic increases in unregulated wildlife trade, livestock import/export, and global human movement are likely to have created additional opportunities for spread of this severe disease. In addition, expanding urban populations have triggered ecosystem changes that may have promoted the emergence of FTLSV by increasing human exposure to the natural reservoir or vector.In conclusion, our results provide new insights into the origin and spread of FTLSV in China. Further studies are needed to obtain complete FTLSV genomes from other countries in which the virus is endemic, and to elucidate the dynamics of the worldwide dispersion of FTLSV.


Bio aerosols were captured using an SKC Biosampler. In low viscosity artificial vomitus, there were notable differences between recovered aerosolized MS2 as a function of pressure , although this was not always statistically significant. This relationship disappeared when using high viscosity simulated vomitus. The amount of MS2 aerosolized as a percent of total virus “vomited” ranged from 7.2 x 10-5 to 2.67 x 10-2 . To our knowledge, this is the first study to document and measure aerosolization of a NoV surrogate in a similitude-based physical model. This has implications for better understanding the transmission dynamics of human NoV and for risk modeling purposes, both of which can help in designing effective infection control measures.Human noroviruses (NoV) are the leading cause of acute gastroenteritis worldwide. Epidemiological studies of outbreaks have suggested that vomiting facilitates transmission of human NoV, but there have been no laboratory-based studies characterizing the degree of NoV release during a vomiting event. The purpose of this work was to demonstrate that virus aerosolization occurs in a simulated vomiting event, and to estimate the amount of virus that is released in those aerosols. A simulated vomiting device was constructed at one-quarter scale of the human body following similitude principles. Simulated vomitus matrices at low (6.24 mPa*s) and high (177.5 mPa*s) viscosities were inoculated with low (10 There are 21 million cases of human norovirus (NoV) infection in the U.S. each year, and this virus genus is now recognized as the leading cause of outbreaks of acute gastroenteritis. According to CDC National Outbreak Reporting Systems (NORS) data for 2009–2010, NoV are responsible for 68% of reported enteric disease outbreaks and 78% of illnesses. They have also been associated with 46% of hospitalizations and 86% of deaths associated with these enteric disease outbreaks. The majority of these outbreaks occur in healthcare facilities (64%), but about 15% occur in association with food service establishments  [Human NoV can be transmitted by a variety of means. The most widely recognized is the fecal-oral route, which is particularly relevant to contamination of food. However, the virus is also released during projectile vomiting, the hallmark symptom of NoV illness. It is estimated that as many as 30 million virus particles are released in a single episode of vomiting . When coEpidemiological evidence from outbreaks suggests that projectile vomiting produces aerosols that contain human NoV ,13. AeroAside from epidemiological studies, the relative importance of aerosol formation in the transmission of human NoV through vomiting is largely unknown. However, there have been studies on aerosolization of influenza virus, usually in association with the physical act of coughing or sneezing. The aerosolization of pathogens by sneezing, coughing, talking, or exhaling depends on many factors such as the flow rate of air suspending the pathogens, evaporation, and the velocity of coughing or sneezing ,15. The in vitro, nor is there an animal model for their propagation. Consequently, surrogate viruses that are morphologically similar, but cultivable, are often used in studies to mimic human NoV behavior. The male-specific bacteriophage MS2 is one such surrogate that resembles human NoV in that it has a positive sense single stranded RNA genome, icosahedral capsid symmetry, and is within the same size range [11 plaque forming units (PFU)/mL). As a bacteriophage, it is also non-pathogenic to humans or animals and is commonly used in aerosolization studies as a surrogate for pathogenic viruses [There are many challenges that hinder work with human NoV, not the least of which is that they cannot be cultivated ze range ,18. Bact viruses .The purpose of this study was to demonstrate that virus aerosolization occurs in a simulated vomiting event, and to estimate the amount of virus that is released in those aerosols. The work was performed in two parts: (i) creation of a laboratory physical model to simulate human vomiting; and (ii) using that model to characterize the degree of virus aerosolization under various conditions of volume and pressure. The human NoV surrogate MS2 was used in the simulated vomiting experiments.To better understand the physiology of vomiting and potential effects on aerosolization, and in the absence of data in the literature, an expert in gastroenterology (author KLK) provided advice to aid in estimating values for key design features. There were a number of parameters in which this advice was useful. The first was volume of vomitus, which varies depending on a person’s height, weight, and diet consumed prior to a vomiting episode. Considering these variations, 800 mL of vomitus in a single vomiting episode was estimated to be a maximum volume. It was assumed to be unlikely that a person would expel less than 50 mL, as this volume might be considered a “dry heave.” The 800 mL estimated vomitus volume was used exclusively in this study to allow the use of a manageable scaled down volume see .The second variable for expert consideration was vomitus viscosity, which depends upon the mix of solid, semi-solid, and liquefied (triturated) foods present in the stomach prior to the vomiting episode. Vomitus with high solids contents would be thick with suspended food particles; pre-gelatinized starch was chosen as a model for high solids content vomitus. Vomitus with low solids contents would be very thin and watery; artificial saliva was used as a model for low solids content vomitus.It was pointed out that air is present in the gastric fundus, the portion of the stomach immediately distal to the lower esophageal sphincter (LES). The fundic air volume likely contributes to the aerosolization of vomitus and was estimated to be in the range of 50–200 mL. Further, the LES is normally contracted to prevent reflux of gastric content into the esophagus. The normal sphincter pressure ranges from 13 mmHg to 43 mmHg. Increases in intragastric pressure and reverse peristalsis in the gastric antrum and corpus result in abrupt relaxation of the lower esophageal sphincter pressure during vomiting [Finally, during vomiting the neck is flexed with the mouth pointed toward the ground, a posture that limits the potential for aspiration of vomitus. It was assumed that reproduction of the exact size and shape of the stomach was not necessary in model design as long as scaled lengths and diameters of the esophagus and mouth were used, as well as physiologically relevant pressures of the stomach and esophagus.The simulated vomiting device was constructed based on the concept of similitude, which allows a scaled prototype to behave similarly to the full-scale phenomenon being simulated. In this case, the device was designed to function similarly to the full-scale human upper gastrointestinal tract but created at one-quarter scale. Achieving similitude in an engineered model is based on three types of similarity to the full-scale application: geometric, kinematic, and dynamic . Having The vomitus containment chamber  was a PlEscherichia coli C3000 host (ATCC B-15597) were purchased from the American Type Culture Collection . To prepare MS2 stock solutions, the protocol described in NSF Standard 55 was used  [x g for 10 min followed by filter sterilization using a 0.22 μm filter . Aliquots of this were considered high titer MS2 stock (1010 PFU/mL). The low titer stock (108 PFU/mL) was prepared by dilution. Stocks were aliquoted and stored at -80°C until use.Bacteriophage MS2 (ATCC 15597-B1) and its d below) . After 1E. coli C3000 host was incubated for 4–6 h with gentle shaking . Simultaneously, 8 mL tubes of 0.6% tryptic soy agar (TSA) (Fisher Scientific) were melted and tempered in a 42°C water bath. Previously prepared petri dishes (Fisher Scientific) containing 1.2% TSA were allowed to warm to room temperature. Then, 10-fold serial dilutions of MS2  were prepared. A volume of 0.7 mL of each dilution was added to the tempered 8 mL TSA tube after which 0.3 mL of E. coli solution was added, the suspension quickly vortexed and poured on top of the 1.2% TSA plates. Duplicates were done for each dilution. Upon solidification, the plates were inverted, incubated overnight at 37°C and then plaques were counted. Counts were expressed as plaque forming units per milliliter (PFU/mL).Enumeration of MS2 was also performed using the double agar layer method in accordance with the method of Su and D’Souza (2011) with minor modifications . Briefly10 PFU/mL) and low (108 PFU/mL) titer were adjusted to high or low viscosity. To prepare the MS2 low viscosity solution (0.1% carboxymethylcellulose (CMC)), 15 mL of MS2 stock was mixed with 0.15 g of high viscosity CMC powder . This was used to simulate artificial saliva with a viscosity of 6.24 mPa*s [Vomitus solutions consisted of MS2 bacteriophage at high  of each solution was pipetted into the stomach chamber of the device, which contained 3.27 mL of air . Using the pump, the stomach was pressurized to 1,283 mmHg , 290 mmHg , and 115.1 mmHg (minimum pressure for the device) . PressurThe components of the vomiting device and chamber were sterilized using 10% bleach for a 5 min exposure followed by rinsing with tap water and wiping with 70% ethanol. The biosampler was autoclaved after each experiment. A negative control with no MS2 was included in all experiments to demonstrate the absence of cross contamination. Immediately before experiments, the entire device was exposed to 254 nm of ultraviolet light for 1 h. Samples collected (by pipet) and analyzed (enumerated for MS2) included: (i) MS2 stock aliquot; (ii) MS2 with thickener ; (iii) PBS from the biosampler (captured aerosolized virus); (iv) PBS rinse of the biosampler ; and (v) liquid splatter on the bottom of the chamber. Volumes of samples collected and amount of surrogate vomitus remaining in the stomach chamber were also recorded. Previous experiments, in which the chamber was swabbed after a simulated vomiting event, and those swabs enumerated for MS2, confirmed that virus deposition on dry surfaces of the chamber was minimal  (data not shown).p<0.05,α = 0.05. For comparing the percent recoveries, the data were not normally distributed; therefore non-parametric Kruskall-Wallis ANOVA by ranks was performed.Experiments were performed in triplicate. To calculate the amount of MS2 aerosolized, the concentration of MS2 captured by the biosampler was normalized for both volume and for biosampler capture efficiency (8.5%). The Holm-Sidak multiple comparisons test  was used for all pairwise comparisons between treatments and pressures. Statistical significance was established at This research meets all applicable standards for the ethics of experimentation and research integrity.http://youtu.be/jGvqb87DXSI). After each vomiting episode, virtually all of the vomitus solution was deposited at the bottom of the chamber. However, there was evidence of aerosolized MS2 after every simulated vomiting episode (8 PFU/mL) suspended in 0.1% CMC (low viscosity), there were statistically significant differences between log10 concentration of MS2 recovered from aerosolized vomitus as a function of pressure . The same occurred for high titer (1010 PFU/mL), low viscosity experiments, although these differences were not statistically significant. There appeared to be little relationship between pressure and aerosolization for the high titer, high viscosity experiments. The high viscosity, high titer MS2 inoculum was not expelled out of the simulator at the low pressure of 115.1 mmHg, presumably because of the low expulsion force. There was also no statistically significant difference in the concentration of MS2 aerosolized for high viscosity, high titer MS2 solution when compared to low viscosity, high titer MS2 simulated vomitus solution. Although not statistically significant, there appeared to be a slight difference of increased MS2 aerosolization when simulated coughing (at 290 mmHg) was added, regardless of virus titer or simulated vomitus viscosity.A snapshot of a simulated projectile vomiting event is shown in  episode . At low −5 ± 0.00006 to a high of 2.67 x 10−2 ± 0.03 (p<0.01). When the data were log-transformed and reanalyzed, there were no statistically significant differences when comparing MS2 percent aerosolization at 1,283 mmHg to 290 mmHg with coughing, regardless of virus titer or solution viscosity. There were statistically significant differences when comparing percent aerosolization at pressures of 1,283 mmHg and 115 mmHg (p<0.05). The general trend was greater percent aerosolization for high titer MS2 at 1,283 mmHg and 290 mmHg with coughing, than 290 mmHg and 115 mmHg without coughing.The amount of MS2 aerosolized as a percent of total virus “vomited” ranged from a low of 7.2 x 102 ± 0.03 . These d1–2.4 x 103 genome copies per m3 of air. We, on the other hand, provide evidence that virus aerosols can be produced during the act of vomiting. Together, our work and that of Bonifait et al. (2015) add to the growing evidence that NoV aerosolization occurs by vomiting.By simulating vomiting using a device scaled to human physiological parameters according to similitude principles, this study demonstrated that virus (MS2) aerosolization did indeed occur. These results complement the recent work of Bonifait et al. (2015), who provided the first definitive evidence of NoV bioaerosolization . Specifi6 particles/mL ), this would mean 5 x 107 particles would be vomited. Even with the lowest percent of aerosolized virus (7.2 x 10−5% for 115 mmHg at low titer), approximately 36 virus particles would become aerosolized. In contrast, the highest percent aerosolized  would result in aerosolization of >13,000 particles. Interestingly, these numbers are consistent with those estimated for bioaerosols in outbreak settings (1.4 x 101–2.4 x 103 genome copies per m3 of air) by Bonifait et al. (2015)[In all cases, <0.03% of the initial concentration of MS2 in the artificial vomitus was aerosolized, though the numbers were quite variable. While a small percentage of the virus released during simulated vomiting was aerosolized, what was released could be enough to cause a significant disease risk. For instance, if an individual vomits at least 50 mL with at least 10l. (2015). Given tSpatial associations and attack rate patterns occurring as a consequence of vomiting incidents support human NoV aerosolization. Marks et al. (2000) demonstrated that attack rates were related to how far individuals sat from the initial vomiting incident in a hotel restaurant: 91% for those sitting at the same table, 56–71% for those at adjacent tables, and 25% for those seated at the table furthest from the incident . SimilarPressure was a major parameter investigated in this study. Booth (2014) recently reported on a simulated vomiting system that was used to characterize the extent of splatter occurring in vomiting event . AlthougAlthough the amount of virus aerosolized was generally positively correlated with the pressure with which the vomitus was released, this relationship was not always statistically significant. This was partially due to the large standard deviations in the measurements, suggesting high variability in degree of virus aerosolization during vomiting. This implies that even a relatively minor vomiting event may have public health significance. We did not observe a major role for viscosity in the degree of virus aerosolization, despite the fact that others have found that suspension media can play an important role in resistance of virus to aerosolization .3 [−8 m/s. This is very slow, and if left uninterrupted, the virus could remain in the air for months. Of course, it is highly unlikely that virus travel would remain uninterrupted, or that single viruses would be aerosolized without some attachment to the suspending matrix.Human NoV particles have a diameter of 32 nm and a buoyant density of 1.41 g/cm3 . Particl3 settling in air at 20° C, is predicted to travel 0.46 m/s, meaning that for a distance of 1 meter it will only take the droplet a few seconds to reach the ground [Hence, droplets formed as a consequence of a vomiting incident are very important in transmission. Droplet transmission occurs when aerosolized particles are large enough (100–500 μm in diameter) to settle to the ground quickly. For example, a 100 μm droplet, with density of 1.41 g/cme ground . These dConsistent with the work of others –37, we uAlthough due diligence was taken in model and experimental design, there are a few limitations to this study. For instance, even though the equipment was appropriately scaled, the structural features of the simulated vomiting device were not the same as human anatomy. While the pressures used for simulated vomiting were scaled, the force with which the vomiting occurred using the device sometimes appeared greater than one might expect in real life. Vomitus in nature would undoubtedly contain solids, and the use of solids-free simulated fluids could have impacted the likelihood or degree of virus aerosolization. Based on the model’s design, a solids-containing suspension could not be used. The SKC Biosampler has been shown to be more effective at collecting larger airborne particles, but is unable to distinguish particle size. There may potentially be greater aerosolization that could not be detected using the SKC Biosampler, as the efficiency of recovery decreased as size of the particle decreased. Lastly, although MS2 is a logical surrogate virus for human NoV because of its ease of enumeration and safety, it is still necessary to extrapolate the behavior of the surrogate to that of human NoV. Not only has MS2 been a popular surrogate for many pathogenic viruses, it is often used in aerosol studies to examine air samplers and aerosol generation techniques ,38. MS2 To our knowledge, this is the first study to document and measure aerosolization of a NoV surrogate in a similitude-based physical model. Relative to the MS2 titers “vomited,” the degree of aerosolization was rather minimal (<0.01%). However, based on human NoV infectious dose and estimated virus concentrations in vomitus, even these small percentages of aerosolization would likely result in significant disease risk, as was suggested in the recent findings of Bonifait et al. (2015) . Future S1 File(PDF)Click here for additional data file.


Influenza viruses transcribe and replicate their genomes in the nuclei of infected host cells. The viral ribonucleoprotein (vRNP) complex of influenza virus is the essential genetic unit of the virus. The viral proteins play important roles in multiple processes, including virus structural maintenance, mediating nucleocytoplasmic shuttling of the vRNP complex, virus particle assembly, and budding. Nucleocytoplasmic shuttling of viral proteins occurs throughout the entire virus life cycle. This review mainly focuses on matrix protein (M1), nucleoprotein (NP), nonstructural protein (NS1), and nuclear export protein (NEP), summarizing the mechanisms of their nucleocytoplasmic shuttling and the regulation of virus replication through their phosphorylation to further understand the regulation of nucleocytoplasmic shuttling in host adaptation of the viruses. Influenza A virus (IAV), which contains an eight-segment, single-stranded, negative-sense RNA genome, is a member of the Orthomyxovirus family. Further subtyping is based on the antigenicity of the hemagglutinin (HA) and neuramindase (NA) surface glycoproteins. Wild waterfowl are the natural reservoir of IAV, which can infect many kinds of mammals, including humans . CurrentInfluenza virions are roughly spherical, made up of a viral envelope, a matrix layer, and a central core. The envelope consists of HA and NA, usually in a 4:1 ratio , and thevice versa) is an active, energy-dependent, signal-mediated process. Taking into account that virus RNAs transport as RNPs rather than naked RNAs, RNA-binding proteins play a key role in RNA transport. Most of these proteins both bind RNA and contain sequences that allow them to be exported/imported between the cytoplasm and nucleus. In this review, we discuss key findings that have advanced our understanding of the nucleocytoplasmic shuttling of influenza virus proteins  and their influence on virus replication.Unlike most RNA viruses, IAV replicates in the host nucleus . In the 126PKKKRKV132, the basic amino acids are shown in bold). The second category is represented by the NLS of nucleoplasmin, which is characterized by continuous basic amino acid sequences at both ends separated by >10 random amino acid residues  [In eukaryotic cells, the transport of proteins and RNAs into and out of the nucleus through nuclear pore complexes (NPCs)-large macromolecular structures embedded in the double membrane of the nuclear envelope, requires the help of transporter molecules and is an active process. There are two types of transporter molecules, named importin and exportin based on their functions. The importins, α and β, both belong to the importin β super-family. The former is able to recognize and bind the nuclear location signals (NLSs) in the target protein, and the complex is recognized and bound by importin β, which subsequently interacts with the NPC to accomplish the translocation of target proteins. Like the importins, exportins are responsible for ferrying cargo out of the nucleus via the same working principle. Chromosome region maintenance protein 1 (CRM1) is an exportin that recognizes and binds to target proteins carrying a nuclear export signal (NES) and mediates their export from the nucleus . The clain bold) ,15,16. Tin bold) .After the first NLS of SV40 LT was identified in 1984, functional NLSs and NESs were subsequently found in influenza virus proteins, including PB1, PB2, PA, NP, M1, NS1, and NEP . The proM1 is the most abundant protein in the virion and forms the matrix layer inside the virus envelope. The exterior matrix layer combines with HA, NA, and M2 located on the envelope, and the interior matrix layer combines with vRNP. Both layers form the virion structure. Initially, it was thought that M1 interacted with HA and NA inside the cytoplasm. Subsequently, the M1 protein was found to enter the nucleus and be indispensable for vRNP nuclear export . Aside fin vitro experiments and a reverse genetics approach reveal that NLS1 plays a pivotal role in mediating vRNP nuclear import [There are at least two NLSs in NP, including the unconventional NLS1 (3–13), which interacts with importin α , and NLSr import ,49.Three NESs have been identified in NP that have the familiar sequence characteristics of common export signals. Two of them do not rely on CRM1 for export, though the third does. Further, all three must be simultaneously mutated to inhibit NP nuclear export, proving their functional independence . The thrNS1 is mainly located inside the nucleus and transports to the cytoplasm in the late stage of infection. Two NLSs and one NES have been identified in NS1 . S221 inNEP is known as a nuclear export protein. It may not need a NLS as it is only 14 kDa in size, and at present, no NLS has been found in NEP. Through the use of an inhibitor of NLS-dependent active nuclear transport and an energy depletion assay, it was demonstrated that NEP enters the nucleus by passive diffusion .NEP is involved in the nuclear export of vRNPs . NEP is The vRNP is the basic unit for the replication and transcription of IAV. The interaction between members of the vRNP complex is of great significance for the structural stability and function of the complex. Several functional domains of related proteins involved in the interaction with the members of the polymerase complex ,56. For In the process of infection, IAV enters the host cytoplasm, and at the same time, the M2 ion channel opens, internally acidifying the virus. Subsequently, the matrix layer depolymerizes, and as a result, M1 and vRNP dissociate from each other . This coFor vRNP nuclear export, a “CRM1-NEP-M1-vRNP” complex forms, where CRM1 recognizes and binds to the NES on NEP, accompanied by GTP hydrolysis . Thus, tThe phosphorylation of IAV proteins is an important regulatory mechanism that influences viral replication by affecting the nucleocytoplasmic shuttling of both the individual viral proteins themselves and the vRNP complex. Nuclear transport of M1 depends on phosphorylation mediated by protein kinase C (PKC), as PKC inhibition effectively decreases virus replication . MutatioNP is rich in serine residues, which is crucial for its phosphorylation, especially on the N-terminus of NLS1 . InhibitThe phosphorylation of T215 in NS1 is mediated by the CDK/ERK pathway, and the T215A mutation attenuates virus replication . The funTo adapt to new host species, influenza viruses must overcome significant barriers to cross-species transmission and replication. The changes in the receptor-binding properties of the viral HA to adapt to new host species are well characterized, but the nuclear import machinery to determine the host tropism requires a better understanding. Previous studies show that the preference of PB2 for different importin-α isoforms  differs between hosts. For efficient virus replication in different hosts, all viruses depend on importin-α1. Meanwhile, the polymerase subunit PB2 of avian viruses requires importin-α3, PB2 of mammalian virus shows importin-α7 specificity, and H1N1v replication depends on both, suggesting ongoing adaptation of this virus . PB2 spePhosphorylation is one of the most common and efficient post-translational modification methods in organisms, playing an important role in regulating many metabolic pathways. Nucleocytoplasmic shuttling of proteins and phosphorylation are closely related. Phosphorylation and dephosphorylation can strengthen or weaken the nucleocytoplasmic shuttling of a protein through a variety of mechanisms. For instance, phosphorylation of key NLS or NES residues on viral proteins can strengthen the affinity between the proteins and their nuclear transport receptors . Alterna


A direct way to study cell tropism and virus spread in vivo is with an influenza virus expressing a reporter gene. However, reporter gene-expressing influenza viruses are often attenuated in vivo and may be genetically unstable. Here, we describe the generation of an influenza A virus expressing GFP from a tri-cistronic NS segment. To reduce the size of this engineered gene segment, we used a truncated NS1 protein of 73 amino acids combined with a heterologous dimerization domain to increase protein stability. GFP and nuclear export protein coding information were fused in frame with the truncated NS1 open reading frame and separated from each other by 2A self-processing sites. The resulting PR8-NS1(1–73)GFP virus was successfully rescued and replicated as efficiently as the parental PR8 virus in vitro and was slightly attenuated in vivo. Flow cytometry-based monitoring of cells isolated from PR8-NS1(1–73)GFP virus infected BALB/c mice revealed that GFP expression peaked on day two in all cell types tested. In particular respiratory epithelial cells and myeloid cells known to be involved in antigen presentation, including dendritic cells (CD11c+) and inflammatory monocytes (CD11b+ GR1+), became GFP positive following infection. Prophylactic treatment with anti-M2e monoclonal antibody or oseltamivir reduced GFP expression in all cell types studied, demonstrating the usefulness of this reporter virus to analyze the efficacy of antiviral treatments in vivo. Finally, deep sequencing analysis, serial in vitro passages and ex vivo analysis of PR8-NS1(1–73)GFP virus, indicate that this virus is genetically and phenotypically stable.The severity of influenza-related illness is mediated by many factors, including  In mice, for instance, highly pathogenic A/Puerto Rico/8/34 (PR8) and low pathogenic A/Texas/36/91 virus achieve similar infectious particle loads, but PR8 virus spreads better in lung tissue 18] or NA viruses . In addi [et al. . For mosay three . This raversus a small compound that blocks viral NA activity). Moreover, they were administered differently: anti-M2e monoclonal antibody was administered only once intranasally 24 h before challenge, whereas oseltamivir was administered daily by oral gavage. Pre-existing anti-M2e IgG, in concert with Fcγ Receptor-bearing lung residing alveolar macrophages, could eliminate the first wave of infected respiratory epithelial cells. Therefore, the resulting effect on virus replication and spread might be quite comparable to that of daily administered oseltamivir, which also would mainly hinder newly produced viruses from spreading further in the lungs. Taken together, our results show that this PR8-NS1(1–73)GFP virus can be used to assess the efficacy of anti-influenza treatments or vaccination. This system could be adapted in the future to harbor other reporter proteins, e.g. red fluorescent protein. It could also be used with other genetic backgrounds of influenza virus, including different subtypes and influenza B viruses.Treatment of mice with anti-M2e IgG monoclonal antibody and with oseltamivir resulted in a strong decrease of the percentage of GFP-expressing cells for all cell types analyzed. It is surprising that there was no obvious difference between the two treatments, although they are entirely different molecules GFP virus.Identification of the different cell populations was based on forward scatter (FSC), side scatter (SSC), autofluorescence, and the expression level of the surface markers CD45, CD3e, B220, DX5, CD11b, CD11c and GR1. The graphs are derived from the analysis performed two days after infection in one mouse treated with 5 μg anti-NBe antibody and infected with 1 x 10(TIF)Click here for additional data file.S2 File3 PFU of WT PR8 virus. The mice in the other groups were infected with 1 x 104 PFU of PR8-NS1(1–73)GFP virus and treated with 5 μg of anti-NBe, 5 μg of anti-M2e or 25 mg/kg oseltamivir. cDCs: conventional dendritic cells.Determination of the amount of GFP expressing cells (%) in the different cell populations, for each treatment, on day two after infection (one mouse per group is shown). WT: one mouse that was left untreated and infected with 1 x 10(TIF)Click here for additional data file.S3 FileThe sequences obtained by Illumina Miseq analysis were mapped to the reference genome, which was based on the eight plasmids that were used to generate the virus. Mutations were considered significant when they occurred at a frequency > 0.5% (cut-off for background errors caused by the RT-PCR reaction), had a Phred score > 20, had a forward/reverse balance > 0.25 and appeared > 10x independently. SNV: single nucleotide variant.(XLSX)Click here for additional data file.


The study objective is to measure, analyse costs of scaling up HIV prevention for high-risk groups in India, in order to assist the design of future HIV prevention programmes in South Asia and beyond.Prospective costing study.This study is one of the most comprehensive studies of the costs of HIV prevention for high-risk groups to date in both its scope and size. HIV prevention included outreach, sexually transmitted infections (STI) services, condom provision, expertise enhancement, community mobilisation and enabling environment activities. Economic costs were collected from 138 non-government organisations (NGOs) in 64 districts, four state level lead implementing partners (SLPs), and the national programme level (Bill and Melinda Gates Foundation (BMGF)) office over four years using a top down costing approach, presented in US$ 2011.Mean total unit costs (2004–08) per person reached at least once a year and per monthly contact were US$ 235(56–1864) and US$ 82(12–969) respectively. 35% of the cost was incurred by NGOs, 30% at the state level SLP and 35% at the national programme level. The proportion of total costs by activity were 34% for expertise enhancement, 37% for programme management (including support and supervision), 22% for core HIV prevention activities (outreach and STI services) and 7% for community mobilisation and enabling environment activities. Total unit cost per person reached fell sharply as the programme expanded due to declining unit costs above the service level (from US$ 477 per person reached in 2004 to US$ 145 per person reached in 2008). At the service level also unit costs decreased slightly over time from US$ 68 to US$ 64 per person reached.Scaling up HIV prevention for high risk groups requires significant investment in expertise enhancement and programme administration. However, unit costs decreased with programme expansion in spite of an increase in the scope of activities. UNAIDS estimates that annually US$ 22 billion is required to achieve universal access to HIV prevention, treatment, care and support services globally by year 2015 Avahan, the India AIDS Initiative of the Bill & Melinda Gates Foundation, provides HIV prevention services to high-risk groups (HRGs) including female sex workers (FSWs) and high-risk men who have sex with men (HR-MSM) and transgender (TG) in six states in India. The goal of Avahan is to reduce HIV prevalence among HRGs and stabilize HIV infection rates among the general population Avahan programme aimed to scale up HIV prevention (2003–2008) and Phase II (2008–2013) to transition services to the National AIDS Control Organization (NACO), India. The scale of Avahan provides a unique opportunity to examine costs over a range of settings, over time and at different programmatic scales.Previous studies of HIV prevention provide some indication of the costs of HIV prevention for high risk groups Avahan scale up. This update includes additional data on the costs of HIV prevention for high risk groups at the national programmatic level. In addition, although all the Avahan interventions delivered a minimum package of interventions, as the programme evolved new elements were included such as the development of community mobilisation, building an enabling environment and vulnerability reduction. In summary, we present here a descriptive analysis of the costs of entire Phase I of the Avahan programme (2004–2008). In terms of both time frame and sample size this is the largest and the most comprehensive cost analysis of an HIV prevention programme globally to date.The study presented here is an update of previously published analysis of the costs of the first two years of Avahan . The two north-east states of Manipur and Nagaland are not included their epidemic is primarily driven by Injecting drug users. Details of HIV prevalence, incidence and the size of the key populations in each state are provided in We collected data from four of the six states served by Ethics approval was provided by the centre hospitalier affilie universitaire de Quebec, Canada; Health monitoring and screening committee (HMSC), India and Institutional ethical review board of St. John's Medical college and Hospital, St. John's Research Institute, Bangalore. Written informed consent was given by participants who participated in the study.15. Community mobilization, advocacy and enabling environment activities varied across the sites and included the formation of self-help groups, various drop-in center events, skills training, legal literacy workshops, police and stakeholder sensitization, crisis response teams and access to social entitlements The package of HIV prevention services costed includes outreach through peers, behavior change communication, condom distribution, clinical services for sexually transmitted infections (STIs), community mobilization, advocacy and enabling environment activities, and is outlined in detail in HIV prevention across all four states was guided by a common minimum programme Avahan was implemented in 64 of the total 120 districts in the four southern states by 138 NGOs, supported by six state level lead Partners (SLPs) contracted by the Bill and Melinda Gates foundation, which also had a national level office at Delhi. In Karnataka and Tamil Nadu there was one SLP each, while NGOs in the states of Maharashtra and Andhra Pradesh were supported by two SLPs each. In 2003–4 SLPs identified NGOs for sub-granting, worked with these NGOS to conducted state wide mapping of high risk populations and co-ordinated closely with state AIDS control societies (SACS) to avoid the duplication of activities. This mapping was conducted by Avahan NGO partners or through contracted technical assistance agencies. All partners used variations of a non-mathematical method that involved a combination of geographic and social mapping combined with the iterative intensive use of Delphi techniques with different key informants. Most of the partners repeated the indirect non-mathematical size estimation exercise on an annual basis In the four study states, Thereafter SLPs provided technical assistance to develop key programme strategies, developed communication materials, enhanced the expertise of NGO staff, provided supportive supervision and consolidated the programme outputs through computerised management information system (CMIS), and supported the purchase and distribution of commodities. In their grant management role SLPs reviewed programme implementation and financial reporting of the NGOs.Avahan foundation office developed over-arching programme strategies and organised annual partners meetings to share lessons learned and co-ordinate with the Indian authorities. They also co-ordinated with the agency sub-contracted for setting up and maintaining the centralised management information system, provided financial oversight and monitored programme evaluation. International NGOs and academic institutions were contracted in by the national office to provide pan-Avahan technical support. Technical assistance was primarily focused on enhancing the expertise to deliver STI services, provide advocacy, inter-personal communication and community mobilisation.At the national level, Avahan in sectors like education and poverty alleviation. A few NGOs had previous experience in HIV prevention. In some districts, Avahan funded NGOs were the sole provider of HIV prevention services in the district while in other districts provision was shared with NGOs funded by the National AIDS control organisation (NACO) with distinct catchment areas.All NGOs were registered and operating prior to Avahan districts, condom social marketing, a separate male STI service delivery program, and client intervention and a trucker focused intervention. These costs were excluded as they are not a part of core activities of NGO's interventions for the targeted high risk groups.We collected cost data for each year of Phase 1 (2004–8) prospectively from a provider perspective. Further details can be found in our initial two year study, but are outlined in summary here The costing approach used was primarily top-down – allocating out expenditures and economic costs to districts then NGOs and then to activities Costs were also disaggregated and categorized by activities and input type. A full list of the inputs included are presented in Avahan programme management costs  were allocated among all grantees according to size of the expenditures for grant in year of analysis; and then from SLP's to districts and NGOs based on estimated population size. This allocation criteria was selected following extensive discussion with programme managers; who reported that estimated population size was the criteria they used to apportion their efforts. A more sophisticated method was used for allocating SLP level expenses to each NGO, first allocating out specific expenditures that could be clearly tracked to particular NGOs, then, for remaining expenditures, allocating to activities on the basis of SLP staff interviews, and thereafter allocating costs either equally or by persons reached to each NGO, depending on the activity. This procedure was determined following extensive interviews and discussions with SLP staff on how they spent their time and resource for different programme activities.We report economic costs. Financial costs represent expenditure on goods and services purchased. Economic costs include items for which there were no financial transactions, for example volunteer time and/or donated goods. These goods were valued using market prices. Where peer educators were volunteers, we used the NACO peer honorarium as the market price. Economic capital costs were annualised using a discount rate of 3%.Unit costs were estimated using output indicators obtained from the Computerised Management Information system (CMIS) Avahan partners meetings and SLP meetings to brief participants about the study methods, and receive feedback on preliminary results. Other key participants included NGO staff and SLP local partners. Extensive work was carried out to ensure the full involvement of participants in this study: and this was particularly helpful in terms of validating our results. Data were entered and analysed using Microsoft Excel. All costs are presented in using US dollars 2011 (www.data.worldbank.org/indicator). The dataset on costs presented here is available from the corresponding author on request.We followed a participatory approach during data collection. We utilised the common platforms during Ethics approval was provided by the centre hospitalier affilie universitaire de Quebec, Canada, Health monitoring and screening committee (HMSC), India and St. John's Research Institute, Bangalore. Written informed consent was given by all participants who participated in the study.Avahan was US$ 102,057,077 of which US$ 35,890,683 was spent at the service level (NGO level)(35%) and US$ 66,166,394 (65%) at above service level , support and supervision (18%) and expertise enhancement (19%) were the activities that incurred costs by SLPs Table 2.At the service level Table 2,Figure S1 shows the distribution of costs for all 64 districts across the period. There are substantial differences between districts on the proportion spent for each activity, particularly for STI services. Additional analysis of start-up costs (not shown) found that the mean start-up time for the 23 detailed costing districts was 4.8 months (ranging from 1 to 8 months). Start -up costs ranged from 2 to 8% of the total costs across all NGOs.Figure S2 shows the variation in cost profiles of NGOs and SLPS by district. The items that show the highest degree of proportional variation are commodities and supplies, buildings and indirect expenses, and travel costs.. By year 4 the Avahan programme in the four districts was reaching over 300,000 target population members at least once a year, and the number of monthly contacts was over 2 million. The mean total unit costs (2004-08) per person reached at least once a year and per monthly contact were US$ US$ 235(56-1864) and US$ 82(12-969) respectively. NGO level unit costs per person reached fell slightly over the period at the service level (US$ 68 to US$ 64), but total unit cost per person reached fell more substantially as the programme expanded due to sharply decreasing unit costs at the above service level (from US$ 477 in 2004 to US$ 145 in 2008). While the variation of unit cost per person reached at the service level narrowed over time, this narrowing was more distinct at the above service level. Median unit costs were considerably lower than the mean costs with a smaller inter quartile range values as a few very high values skew the distribution of unit costs.Programme outputs and unit costs are presented in Avahan programme presents the most comprehensive study to data on the changing cost structure of HIV prevention to high risk group during scale-up, updating our previous two year costing study This descriptive cost analysis of the Avahan is broader than that in the intervention package costed in many of these other studies21. In addition, cost differences may be due to the different estimation methods used. We primarily use a top down method, which may be less precise in terms of disaggregating costs at the activity level, but may better capture total cost. Previous studies only focus on small sample of NGOs who agreed to participate, and thus may suffer from selection bias. Finally, some of the previous studies did not include STI services costs which were referred to government hospitals or private providers.Our mean service level unit cost estimates (US$64) are higher than those from other studies US$ 32(22-57) rd and 4th year. However, although total above service level costs did not escalate during scale-up, the variation between expenditures by different SLPs suggests that there may be room for efficiency gain – and further qualitative and quantitative work is required to better understand the causes of this variation and how different patterns of above service level costs may relate to NGO performance. At the very least, our findings highlight that other countries expanding HIV prevention to high risk groups need to critically examine and plan their above service support activities with the same level of scrutiny as they monitor costs of those directly providing services.One of the new and central findings of this update is that the greatest proportion of costs is incurred above the service level. Assessing the appropriate level of above service costs is complex. Aside from programme management, much of the above service cost was used to enhance the expertise of service providers. India has a robust NGO sector: and, in this sense, the degree of support required to provide quality services quickly may be less than elsewhere. The scale-up of services was also rapid, reaching full coverage of FSWs in most sites by the second year of the programme: and slower scale up may require less support. The programme then continued to expand to include coverage of HR-MSM/TG during 3Our updated results add further support to our previous evidence on the economies of scale of HIV prevention to key populations Avahan evolved and the capacity of NGOs grew to deliver core activities, NGOs extended their services from prioritising the female sex worker programme to targeting high risk men also. Moreover, some activities such as STI service provision and community mobilisation were added to the core package of peer education. For example, community mobilisation started with relatively modest activities such as the provision of drop-in centres, but as more members of key populations were involved activities widened and intensified We also find slight decline in unit costs at the service level as the programme scales up in spite of increase in the scope of services and difficulty of reaching more dispersed groups We did not find a decrease in the variation of unit costs at the service level as scale-up progressed. This finding is somewhat surprising as learning effects are important to consider when examining the efficiency in the rapid scaling-up of HIV prevention activities When interpreting our results, care should be taken to consider the quality of our data. This study is the largest study to date of HIV prevention costs, it is also is the only study that collects data over time. However, conducting a study at this scale, using primarily top down methods, means that the quality of any disaggregated findings by activity may be less robust than studies that employ more site intensive methods, such as comprehensive time in motion studies. Moreover, although every effort was made to include donated goods, it is likely some sites' data was under-reported ). Another challenge also is the allocation of above service level costs and indirect costs generally. While our approached is based on interviews and detailed analysis of expenditure reports, due to the scale of the study we were not able to provide timesheets to all above service level staff. The most important limitation of the data however is on the output side and the use of routine data to measure the level of service utilisation. Programme indicators in the initial years lacked consistency across the states and different NGOs may have started reporting at different times. This may have impacted the estimation of unit costs in the first year of the programme, resulting in an over-estimation of unit costs in the first year. Moreover, routine data may be subject to various biases, including an incentive to demonstrate strong performance by NGO level managers.Finally, during our study we learned several important practical and methodological lessons. Firstly, we were able to conduct our study within a reasonable cost, due to our reliance on the top down method; and our complete access to all expenditure data, CMIS data, programme staff and key resource data. While this approach is not always feasible or desirable, the extensive time taken and effort made at the beginning and throughout the study by local staff to involve participants was pivotal to the ability of the costing team the data required. Both the comprehensiveness and longitudinal nature of the dataset provide the potential for econometric analysis of cost determinants, and provide an evidence base for those interested in resource allocation across interventions at varying scales. Such extensive estimates also help validate previous estimates made in small scale pilot settings. However, pragmatically, such large scale costing studies may be considered expensive; and thus may be most appropriate to questions focused on technical efficiency; and early pragmatic trials of the initial roll-out of new technologies and interventions. Even on these occasions it may be possible to take a more limited sampling approach and frequency of data collection. As part of our further econometric analysis of these results, we will explore whether collecting less cost data would substantially alter our policy recommendations; in order to inform and guide investment in HIV prevention costing methods going forward.Avahan experience and are able to achieve value for money.This descriptive analysis of the costs of HIV prevention confirms that total costs, cost profiles and unit costs all evolve over time during the process of scale-up. In particular, policy makers and planners should note that above service costs can be considerable, that unit costs per person reached fall with scale, and that cost profiles by activity can change substantially over time. Further work exploring the optimal service package, how to reduce cost variation over time, and the efficiency of different models of above service support are recommended to ensure that other programmes learn fully from the Figure S1NGO economic cost by district and by activity 2004 to 2008 (US$ 2011).(TIF)Click here for additional data file.Figure S2SLP and NGO economic cost by district by input 2004 to 2008 (US$ 2011).(TIF)Click here for additional data file.Table S1Description of the activity considered at different organisational levels.(DOCX)Click here for additional data file.Table S2Costs considered for input categories.(DOCX)Click here for additional data file.


Considerable interest exists in health care costs for the growing Micronesian population in the United States (US) due to their significant health care needs, poor average socioeconomic status, and unique immigration status, which impacts their access to public health care coverage. Using Hawai‘i statewide impatient data from 2010 to 2012 for Micronesians, whites, Japanese, and Native Hawaiians , we compared inpatient hospital costs across racial/ethnic groups using multivariable models including age, gender, payer, residence location, and severity of illness (SOI). We also examined total inpatient hospital costs of Micronesians generally and for Medicaid specifically. Costs were estimated using standard cost-to-charge metrics overall and within nine major disease categories determined by All Patient Refined Diagnosis Related Groups. Micronesians had higher unadjusted hospitalization costs overall and specifically within several disease categories (including infectious and heart diseases). Higher SOI in Micronesians explained some, but not all, of these higher costs. The total cost of the 3486 Micronesian hospitalizations in the three-year study period was $58.1 million and 75% was covered by Medicaid; 23% of Native Hawaiian, 3% of Japanese, and 15% of white hospitalizations costs were covered by Medicaid. These findings may be of particular interests to hospitals, Medicaid programs, and policy makers. The health care costs of Micronesians in the United States (US) is a topic of increasing importance to health care administrators, health disparities researchers, and health policy makers, as Micronesians are a growing population in the US  who ofteMicronesia is made up of thousands of islands and atolls in the middle of the Pacific Ocean. The political relationship between Micronesian nations and the US began during World War II. After the war, the US military conducted major nuclear testing in the region, with significant health consequences ,7. In thSoon after the Compacts were enacted, the number of citizens of COFA nations migrating to the US increased . In the Initially, COFA migrants were eligible for Medicaid under federal guidelines. However, under the federal Personal Responsibility and Work Opportunity Reconciliation Act of 1996 (PRWORA), COFA migrants were deemed ineligible for federal Medicaid coverage. In contrast to immigrants who can become eligible for Medicaid after five years of residence, under PRWORA, COFA migrants can never qualify for Medicaid under federal guidelines regardless of how many years they live in the US.After PRWORA passed, some states continued to allow Medicaid participation for COFA migrants who were not otherwise insured. The cost of this coverage was subsidized by the states. Hawai‘i, which has the largest proportion of the COFA migrants in the US, originally provided coverage to COFA migrants through its state Medicaid program. In 2009, the Hawai‘i state government, citing economic reasons, started to disqualify COFA migrants from its Medicaid rolls. After a long legal battle, with appeals up to the US Supreme Court, in late 2014, it was deemed legal for the State of Hawai‘i to discontinue Medicaid coverage for COFA migrants. Soon after, the state announced that non-pregnant, non-aged, blind, or disabled (non-ABD) COFA migrant adults were no longer eligible for state-funded Medicaid. Instead, these individuals were expected to enroll in private insurance plans through the state insurance exchange, with premiums for many currently subsidized by the state . AlthougDespite considerable policy action with important consequences in health care equity, access, quality, and outcomes for the Micronesians population, little quantitative evidence exists regarding the cost of health care for this population. In fact, limited data exists on the health care utilization of this population generally. Only very general estimates of health care and other social costs exist. For instance, the state of Hawai‘i estimated that in 2007 it spent $101 million in social and health costs for COFA migrants including $37 million by the Department of Human Services . This daThe current study seeks to address a critical evidence gap regarding health care costs for this population focusing on inpatient hospital costs, a notably expensive part of the US health care system. We examined total inpatient hospital costs for Micronesians generally and for those covered by Medicaid specifically in the state of Hawai‘i. We also compared Micronesian inpatient hospital costs to those of three other major racial/ethnic groups . Whites were included because most often national, race-based health comparison research uses them as the reference group. Japanese were included as they are one of the healthiest groups in Hawai‘i ,17. NatiDischarge data from all 24 acute care, non-military hospitals operating in Hawai‘i from 2010 to 2012 were obtained from the Hawaii Health Information Corporation (HHIC) inpatient data [pregnancy, childbirth, and puerperium). Discharges missing data on patient’s payer type (n = 1) or location of residence (n = 248) were excluded for a final study sample of 162,152.Adult (18 years and older) non-pregnancy-related hospital admissions in Hawai‘i from 2010 to 2012 for Micronesians Native Hawaiians, Japanese, and whites were considered . Pregnancy-related hospitalizations were identified and excluded using Medical Diagnostic Category (MCD) 14  * (APRDRG Adjustment Factor (APRDRG-AF)) = Estimated cost. All costs were adjusted to constant 2012 dollars using the Medical component of the Consumer Price Index [Costs were estimated using established cost/charge ratio (CCR) guidelines available from the Agency of Healthcare Research and Quality . This alce Index .Costs were compared in general and specifically within disease categories, which were determined using the All Patient Refined Diagnosis Related Groups (APR-DRGs) from 3M grouper version 29 . APR-DRGMultiple hospitalizations of the same individual within each disease category were identified using their unique ID number assigned in the database. Only the first entry for each individual was used for racial/ethnic comparisons of costs in unadjusted and adjusted models. This was to prevent individuals who were hospitalized multiple times from skewing racial/ethnic group comparisons. This left a study population of 69,449 unique individuals for the racial/ethnic cost comparisons within APR-DRGs and a study population of 109,258 unique individuals for the “overall” analyses. For the cumulative cost estimates for Micronesians overall and by disease categories, all admissions by individuals were included to identify the full cost burden.Race/ethnicity was the main independent variable. The HHIC race/ethnicity variable was collected consistently (with a minor exception noted below) across all included hospitals in Hawai‘i during the study period and is self-reported by patients at intake as one primary race/ethnicity. Mixed race patients are thus included as their primary self-reported racial/ethnic identity. We focused on Micronesians and three comparison populations: Native Hawaiians, Japanese, and whites. The Micronesian category included individuals reporting Marshallese or Other Micronesian (excluding Guamanian and Chamorro) as their primary racial/ethnic identity. The Micronesian category likely includes COFA migrants, immigrants from other Micronesian nations, and Micronesians born in the US or in the US-affiliated Pacific.Data from two small, rural hospitals did not conform to the race/ethnicity specifications needed to identify all Micronesian groups during the year of 2010. The impact on study results was likely minimal as the combined number of Micronesian hospitalization from these two hospitals during 2010 was 18 total and 23 total Micronesian hospitalizations per year for 2011 and 2012, respectively.vs. other payment type due to the policy relevance of Medicaid costs for the Micronesian population specifically.Insurance status was categorized as Department of Defense (insurance available to active military and their families), Medicare, Medicaid, Private, or Self Pay. For the total cost analyses, we focus on the Medicaid Severity of illness was determined using 3M classification methods within the APR-DRG . The 3M For most hospitalizations, coverage type is highly associated with costs. Therefore, in our multivariable model we controlled for type of insurance as well as age, gender, insurance status, and location of residence. Age was measured continuously 0–90 years (top-coded). All persons 90 years and above were reported as 90 in the data set to maintain confidentially. Gender was female or male. Location of residence was categorized as Hawai‘i not Oahu, Oahu, and Outside Hawai‘i. Location of patient’s residence was included to capture possible differences caused by limited availability of healthcare on Hawai‘i’s neighbor islands, including primary, mental health, and specialized care .vs. not Medicaid.STATA 12.0  was usedCosts by hospitalization were compared by racial/ethnic group using Kruskal-Wallis tests due to the highly skewed distribution of cost data. Costs by race/ethnicity adjusting for other factors were then predicted in a multivariable model using the gamma regression with log link . Gamma rThe first set of multivariable models included age, gender, insurance status, and location of residence. The second set of multivariable models included age, gender, insurance status, location of residence, and severity of illness (SOI) to specifically investigate the role of severity of illness in explaining differences in costs by race/ethnicity. These variables were chosen a priori based on previous research and theory as likely to be significant in predicting costs . Thus, ap-value of less than 0.05 was regarded as statistically significant.Multivariable models were used to calculate cost ratio estimates (RE) and 95% confidence intervals (CI) for each racial/ethnic group compared with Micronesians  after adjustment for other factors. A two-tailed p < 0.001). Micronesians were significantly more likely than other studied groups to have Medicaid (p < 0.001) and self-pay health insurance (p < 0.001). Specifically, 75.2% of Micronesians had Medicaid, compared to 24.7% of Native Hawaiians, 15.6% of whites, and 3.3% of Japanese.Micronesian non-pregnancy-related hospitalizations accounted for 2.15% of the total sample (n = 3486) while white hospitalizations accounted for 44.3% , Japanese hospitalizations accounted for 30.3% , and Native Hawaiian hospitalizations accounted for 23.3% . Briefly summarized, for all ethnicities about half of the samples were female and the majority were from Oahu. Specifically, 47.5% of Micronesians were female and 76.7% lived on Oahu. Eighty-two percent of the Micronesian sample was under 65, a significantly higher percentage than seen in other racial/ethnic groups; 65.7% of Native Hawaiians, 55.8% of whites and 27.1% of Japanese were under 65 (p < 0.001). Micronesians had the highest median costs ($9993 per person) compared to $9752 for Japanese, $9594 for whites, and $9348 for Native Hawaiians.p < 0.05) were seen by race/ethnicity for all these categories. Micronesians also had the highest costs for dental hospitalizations, but the racial/ethnic comparison was not statistically significant for this disease category type. Costs for mental health-related hospitalizations also varied significantly by race/ethnicity (p < 0.001) and Micronesians had the second highest median costs for these hospitalizations (after Japanese).In unadjusted analyses, Micronesians had the highest median hospitalization costs overall and for cardiac, infectious disease, and substance abuse-related hospitalizations. The substance abuse category includes all drug and alcohol abuse and dependence-related hospitalizations, including but not limited to opioids and cocaine. Significant differences (p < 0.001). Micronesians also had the lowest median costs for endocrine and skin-related hospitalizations, but the racial/ethnic comparison was not significant for these disease category types. Median costs for cancer also did not differ significantly by race/ethnicity.Micronesians had the lowest median costs for the pulmonary disease category type, which differed significantly by race/ethnicity , p < 0.001, with the greatest differences seen within the extreme SOI level. Whites had the highest median costs for both minor and major SOI levels, Japanese had the highest median cost for the moderate SOI level, and Micronesians had the highest median cost in the extreme SOI level.Within each SOI level, racial/ethnic comparisons were significant at Micronesians had higher unadjusted hospitalization costs overall and specifically for several disease types compared to other racial/ethnic groups. In unadjusted analyses, Micronesians had the highest median hospitalization costs overall and for cardiac, infectious disease, and substance abuse-related hospitalizations. Importantly, infectious and heart disease were the two most expensive hospitalization types in term of total costs. In models adjusted for payer, age, gender, and location of residence, Micronesians still had significantly higher costs overall and for infectious and heart disease hospitalizations compared to all three other studied racial/ethnic groups.Hospitalized Micronesians have higher SOI in many disease categories compared to Native Hawaiians, Japanese, and whites in Hawai‘i . Thus, iThese findings may be of particular interests to state Medicaid programs. The Hawai‘i state Medicaid program was a major payer for Micronesian hospitalizations during this time period, particularly in some disease categories, including heart disease, where Medicaid was responsible for 80% of costs for Micronesian hospitalizations. As federal policies created the unique immigration status for this population while allowing them to be excluded from Medicaid participation under federal guidelines, a strong argument can be made that federal solutions are needed.Our estimates suggests that one year of hospitals costs in Hawai‘i, if the size of the Micronesian population does not change and the case-mix does not change from the 2010–2012 years, is around $19 million total for public and private payers. For Medicaid alone, this estimate is $14.5 million. This figure accords with the cost cited in testimony by the Director of Human Services . InpatieThis analysis sheds light on one important consequence of current policies to bar COFA migrants from Hawai‘i’s state Medicaid program: changes in the payer mix that will cover this population. Medicaid was covering 75% of overall costs for Micronesians, with higher percentages in some important disease categories—including cardiology . While hospitals lose the reimbursements that they had received previously from Medicaid, coverage for COFA migrants aged 20 to 64 years previously on Medicaid has shifted to the two major Hawai‘i insurers participating in the Affordable Care Act (ACA) exchange: Kaiser and HMSA. As private insurance reimbursements are higher than those from Medicaid, hospitals may actually gain financially from this change.Coverage plans available through the ACA are not designed for COFA migrants who may face significant linguistic, health literacy, and computer access challenges in enrollment. These plans may also not be appropriate for this population as the cost sharing under the private plans is substantially higher than under Medicaid. While the state is currently paying enrollment premiums for the COFA population moved from Medicaid, under the HMSA plan individuals are responsible for co-pays. (Kaiser is currently covering co-pays for this population.) Therefore Hawai‘i’s decision to move all non-ABD, non-pregnant, adult COFA migrants onto ACA insurance plans, even though they may fall below 133% of the federal poverty line, may decrease health care access for COFA migrants because they cannot afford the co-pays and any future premiums. Several surveys have found that co-pays and deductibles can deter people from seeking care in order to save money . As noteThe lack of attendance for primary and preventative care may result in patient’s presenting to emergency departments and being hospitalized with more severe and more costly conditions. This is especially relevant as a recent study found that Micronesians were already hospitalized younger and often sicker in a number of disease categories compared to Japanese, whites, and Native Hawaiians in Hawai‘i . Thus, uThese findings should be of interest not just to hospitals and insurance companies, but to many stakeholders, including advocates for health equity. While this research focused on the state of Hawai‘i, it has relevance for the other states with significant and/or growing populations of Micronesians, including Washington, Oregon, and Arkansas . AdditioThere are several limitations to our study. Firstly the costs described here may not represent true costs as they are only an estimate. In addition, costs were determined from charges using a cost-to-charge ratio and do not represent necessarily the payments received for these services. Medicaid, for instance, often pays a significantly lower portion percentage of costs than Medicare or private payers. On the positive side, this means that our cost analysis is not confounded by the fact a wide variation was seen in the percent of hospitalizations by racial/ethnic group covered under Medicaid. In addition, the data included only non-pregnancy related hospitalizations of individuals over the age of 18 and therefore does not represent the total estimates of healthcare costs provided by the state to younger individuals, outpatient health care, and childbirth, which is the most common reason for hospitalization. We did not have data on individual hospitals so could not control for this in our models. Although we looked at overall costs, we did not analyze costs within all disease types. Instead we chose categories likely to be most relevant for Micronesians to help ensure we had samples large enough for reliable analyses. To be more comprehensive, we did our analyses by APR-DRG grouping rather than within each individual APR-DRG, despite the fact that the SOI measure is designed to be used only within individual APR-DRG categories. We did not include additional factors, such as length of stay or comorbidity in the multivariable models, which would have likely helped to explain cost differences by racial/ethnic groups. We also did not include a hospital variable in the multivariable models, which would have been useful. However, the cost adjustment factor is specific to each hospital. Although this analysis is not comprehensive, it does provide quantitative data to estimate the cost of inpatient health care for Micronesians overall and relative to other racial/ethnic groups. Finally, we compare costs, but it not clear whether higher cost signifies worse care or better care. The reasons for these differential costs by racial/ethnic group may be an important area for future research.Diabetes is a good example of an area where future work on these topics, ideally with larger sample sizes, would be particularly relevant. Although diabetes is known to be a large problem for the Micronesian community, we did not find endocrine-related hospitalizations to be the largest overall total cost for this group, nor did Micronesians have a significantly higher median cost for this diagnostic grouping when compared to the other racial/ethnic groups. We would have liked to have considered diabetes-focused hospitalization specifically but the APR-DRG for diabetes-specific hospitalizations (420) included small numbers generally and very small numbers of Micronesians specifically. Additionally, the focus of our study was comparisons through the lenses of APR-DRGs, which codes hospitalizations based on the primary reason for each hospitalization. As diabetes is often comorbid with other conditions rather than the primary reasons for hospitalization, our methods would hide the full role of diabetes-related conditions on costs or outcomes. Future work considering diabetes-specific hospitalizations as well as the role of comorbid diabetes in Micronesian hospitalization costs and outcomes would be very useful. This would be particularly useful as there is evidence that Micronesians are hospitalized with endocrine-related diseases at significantly younger ages than the other three comparison racial/ethnic populations and significantly sicker than the Japanese . These ySimilarly, another important issue to consider in future research is the link between infectious disease and heart disease, especially given that Pacific Islanders have a high prevalence of rheumatic heart disease . This waMicronesians have higher unadjusted hospitalization costs overall and specifically for several disease types. Higher SOI in Micronesians explains some, but not all of these higher costs. It is important to find the root causes of these apparent health inequities so that we may not only lower healthcare costs but decrease suffering. Based on our findings, we suggest health equity research should consider the root causes of the higher SOI in Micronesians to address these high healthcare cost burdens. Policy makers should include Micronesians as a covered group under federal Medicaid guidelines to provide an important infrastructure to sustain coverage of this population and improve their population health outcomes.