Apis mellifera) against their viral pathogens. Here we set out to fill this knowledge gap by investigating how the gut microbiota modulates the virulence of a major honey bee viral pathogen, deformed wing virus (DWV). We found that, upon oral virus exposure, honey bee survival was significantly increased in bees with an experimentally established normal gut microbiota compared to control bees with a perturbed (dysbiotic) gut microbiota. Interestingly, viral titers were similar in bees with normal gut microbiota and dysbiotic bees, pointing to higher viral tolerance in bees with normal gut microbiota. Taken together, our results provide evidence for a positive role of the gut microbiota for honey bee fitness upon viral infection. We hypothesize that environmental stressors altering honey bee gut microbiota composition, e.g., antibiotics in beekeeping or pesticides in modern agriculture, could interact synergistically with pathogens, leading to negative effects on honey bee health and the epidemiology and impact of their viruses.Adult honey bees host a remarkably consistent gut microbial community that is thought to benefit host health and provide protection against parasites and pathogens. Currently, however, we lack experimental evidence for the causal role of the gut microbiota in protecting the Western honey bees ( Apis mellifera), the gut microbiota is dominated by up to nine bacterial phylotypes [Gut-associated microbial communities are ubiquitous in animals, and their presence can affect important host traits ,2. Sociaylotypes ,5, whichylotypes ,7. Severylotypes ,9,10) haVarroa destructor and the viruses it transmits [V. destructor has been introduced [A. mellifera when transmitted by V. destructor or experimentally by injection [Honey bees are important pollinators  that havransmits ,14,15,16troduced ,18,19. Tnjection , though njection .Apis cerana reported a lower abundance of two representatives of the associated microbiota in sacbrood virus-infected colonies [To date, only a single study surveying the presence of gut microbiota in larvae of the Asian honey bee colonies , suggestTo obtain adult bees, brood frames from two colonies  were bron = 16 cages, 288 bees) were given access to a gut homogenate for 24 h (group: microbiota+) to establish the characteristic bee gut microbiota (see n = 16 cages) retained the sterile sucrose-solution as their food source (group: microbiota-), which limits the establishment of the normal gut microbiota [On day 1, half of the cages . As a reference to experimental microbiota+ and microbiota− bees, eight hive bees taken from brood frames from each of the two source colonies were collected and similarly stored for later quantification of bacterial abundance in a subset of these hive bees (n = 4 for colony G1 and n = 2-3 for colony 5.1). Bacterial abundance was determined of either specific members of the bee gut microbiota  or universally all bacteria (16S) via quantitative polymerase chain reaction (qPCR). The remaining experimental bees in the cages at day 6 were starved for 3–4h before individually feeding all bees in half of the microbiota+ and the microbiota- cages (n = 8 cages each) with 5 µL of a DWV-B inoculum  . Thereafter, bee survival was checked daily for a total of 31 experimental days, with dead bees being removed daily from the cages. During this time, sterile 1:1 sucrose-water solution was the only food source given to the bees.On day 11 of the experiment, a time point after successful establishment of DWV-B infection but likely before virus-induced mortality ,25, we a® and were then, two weeks after treatment with Bayvarol® and three weeks before the start of the experiments, screened for the presence of six common bee viral targets: deformed wing virus A and B (DWV-A and DWV-B), black queen cell virus (BQCV), chronic bee paralysis virus (CBPV), sacbrood virus (SBV), and slow bee paralysis virus (SBPV) using the methodology described below (Honey bees originated from two colonies (5.1 and G1) in the General Zoology apiary at Martin Luther University Halle-Wittenberg, Germany. The colonies were treated with Bayvaroled below . None ofThe gut homogenate used to inoculate experimental bees with the characteristic gut microbiota via feeding was freshly prepared from hive workers on the day of inoculation (day 1 of the experiment). To prepare the gut homogenate, ten bees were collected from brood frames of each of the two source colonies, brought into the laboratory, cold anesthetized on ice, and then sacrificed by dissecting their gastrointestinal tracts  under sterile conditions near a flame. The dissected gastrointestinal tracts were then pooled per source colony, homogenized in 3 mL sterile 1:1 sucrose-water with a sterile pestle, and finally diluted 3:8 with sterile 1:1 sucrose-water solution to obtain the gut homogenate. This mixture was then given to experimental bees in the cages via bulk feeding, i.e., providing them with a feeding tube containing the mixture for 24 h.Gilliamella apicola, Frischella perrara, Snodgrasella alvi, Bartonella apis, Bifidobacterium asteroids, Lactobacillus Firm-4, Lactobacillus Firm-5) or universally all bacteria (16S).For bacterial abundance estimation in experimental bees collected on day six of the experiment and in-hive bees removed directly from brood frames of the source colonies, we followed the methods outlined in  for diss20 to 1 L), 250–350 µL 0.1 mm silica zirconia beads (BioSpec), and 20 µL Proteinase K (Sigma). Samples were then homogenized with a Tissue Lyser LT (Qiagen) at full speed for 2 min, placed on ice for 1 min, and bead-beaten again for 2 min before incubating the samples overnight at 56 °C. Thereafter, 750 µL phenol-chloroform-isoamyl alcohol (25:24:1) was added, tubes were mixed by inverting and placed on ice for at least 2 min before centrifugation at 7000 rpm for 15 min at 4 °C. Then, the DNA in the aqueous phase was alcohol precipitated (twice with 200 µL 2-propanol), washed (200 µL ice-cold 70% Ethanol), and air-dried prior to resuspension in 50 µL nuclease-free water. The concentration of extracted DNA was then determined with an Epoch™Microplate Spectrophotometer (BioTek), and the DNA was stored at −80 °C.For dissection, individual bees  stored in 95% ethanol at −20 °C were first dried on a clean laboratory tissue for 4–8 min, and then the gut region, including the midgut/ventriculus, the ileum, and the rectum was dissected out of each bee under sterile conditions near a flame. For DNA extraction using a cetyltrimethylammonium bromide (CTAB) bead-beating method, dissected guts were individually placed in 2 mL tubes together with 730 µL 2% CTAB-buffer  for the specific gut microbiota members in 10 µL reactions with 5 µL SYBRgreen Sensimix , 3.6 µL ddH2O, 0.2 µL of each primer (10 µM) and 1 µL 1:10 diluted template DNA with the following program: 10 min at 95 °C, followed by 40 cycles of 15 s at 95 °C, 30 s at 60 °C and 30 s at 72 °C. The qPCRs targeting universally all bacteria were run in a QuantStudio 3 Real-Time PCR System  in 20 µL reactions with 10 µL Fast SYBR-Green Master Mix , 5 µL ddH2O, 1.25 µL of each primer (10 µM) and 2.5 µL template DNA (65 ng/µL) with the following program: 95 °C for 20 s followed by 40 cycles at 95 °C for 3 s and 60 °C for 30 s.9-103 16S rRNA gene copies), which was used to generate calibration curves for the quantification of the bacterial target. External standards for specific members of the bee gut microbiota, except for Snodgrasella alvi, consisted of purified qPCR fragments that were generated in qPCRs with primers listed in Gilliamella apicola: DSM 104097; Frischella perrara: DSM 104328; Bartonella apis: DSM 29779; Bifidobacterium asteroids: DSM 20089; Lactobacillus Firm-4: DSM 26255 Lactobacillus Firm-5: DSM 26256). To create external DNA standards for Snodgrasella alvi and universally all bacteria, we cultured Snodgrasella alvi  and Escherichia coli , extracted their DNA as described in Snodgrasella alvi)/56 °C (Escherichia coli) for 45 s and 72 °C for 30 s with a final 72 °C for 5 min. To calculate the starting concentration of the external standard (copy number/µL), the equation in [All qPCRs included a duplicate dilution series of an external DNA standard . In addition, two duplicated no template controls (negative control) were included on 96-well plates detecting universally all bacteria or Snodgrasella alvi and universally all bacteria  and Escherichia coli  were grown in liquid culture for 24 h at 30 °C in 5 mL Caso medium (Roth) and LB-medium , respectively. The culture of E. coli was performed under a normal atmosphere while the culture of Snodgrasella alvi was performed under an 8–10% CO2 atmosphere, placing the liquid culture in an airtight 2 L plastic container (Emsa clip and close) and adding an Anearocoult® C sachet (Merck) according to the manufacturer’s instructions.To create external DNA standards for bacterial abundance estimation of bacteria , Snodgra5 DWV-B virus particles in 1 µL and incubated them for three days in an acrylic box at 35 °C and 50% relative humidity. After three days, three pupae were pooled at a time, crushed in 900 µL of 0.5 M potassium phosphate buffer (pH 8.0) using a sterile plastic pestle, mixed thoroughly, and centrifuged for 2 min at 15,000× g. The supernatant was kept as the new inoculum and stored at −80 °C while precipitated honey bee pupal debris was discarded. This newly created inoculum was then checked for the presence of six common bee viral targets: deformed wing virus A and B (DWV-A and DWV-B), black queen cell virus (BQCV), chronic bee paralysis virus (CBPV), sacbrood virus (SBV), and slow bee paralysis virus (SBPV) and the concentration of DWV-B quantified using the methodology described below  was administered to bees in the experimental group microbiota+|virus+ and microbiota−|virus+ group using a pipette [To ensure full uptake of the virus inoculum, all bees were fed individually on day six. For this, bees were removed singly from each cage using forceps, their wings were grasped between the thumb and index finger to expose the mouthparts, and then 5 µL of the virus inoculum  with 7.5 mL of diethylpyrocarbonate (DEPC)-treated water, and recovered 100 µL of the homogenate from beyond the BioReba mesh for RNA extraction. To screen the experimental DWV-B virus inoculum for the presence of other honey bee viruses and for quantification of DWV-B titers in the inoculum, we used 100 µL of the inoculum for RNA isolation. For RNA extraction of bees arising from the experiment, whole bees stored at −80 °C were crushed in 500 µL RLT-Buffer using a plastic pestle, and 100 µL of the homogenate was used for RNA extraction.18 primers  and reverse transcriptase  following the manufacturer’s instructions. For cDNA synthesis, 800 ng of RNA was used, and the resultant cDNA was diluted 1:10 prior to use in qPCRs.RNA was extracted using an RNeasy mini kit  following the manufacturer’s instructions in a QIAcube robot (Qiagen). cDNA was synthesized from RNA extracts using oligo(dT)For viral detection in the two honey bee source colonies  and in t10–103 viral particles), which was used to generate calibration curves for the quantification of the virus target. The external DNA standard consisted of purified PCR fragments which were generated using a 20 µL PCR reaction with 8 µL 5X Buffer (Promega), 9.2 µL ddH2O, 0.6 µL dNTP, 0.5 µL of each primer (10 µM), 0.2 µL Taq  and 1 µL template 1:10 diluted cDNA of the DWV-B inoculum with the following program: 95 °C for 2 min, 40 cycles of at 95 °C for 30 s, 57 °C for 45 s and 72 °C for 30 s, with a final 72 °C for 5 min. To calculate the starting concentration of the external standard (copy number/µL), the equation in [For absolute viral quantification of DWV-B in the experimental DWV-B virus inoculum  and the ation in  was usedA. mellifera β-actin was also amplified for all of the samples as a honey bee internal reference marker using primers in The following quality control checks were run for each qPCR 96-well reaction plate. To check that the correct template had been amplified, qPCR products were denatured for one minute at 95 °C, cooled to 55 °C for one minute, and then a melting profile was generated from 55 to 95 °C (0.5 °C per second increment). To check for RNA degradation, error in RNA extraction, or failure in cDNA synthesis, 2 = 15.126, df = 1, p < 0.001; random effect colony: LR-test, χ2 = 4.013, df = 1, p < 0.045). Bacterial abundance  of specific members of the bee gut microbiota and universally all bacteria were analyzed in separate linear mixed-effects models . Bacter “lme4”, ) with so “lme4”, ).Model assumptions of LMMs were checked with diagnostic tests and plots implemented in the package “DHARMa” . No modeGilliamella apicola  microbiota+ bees led to the establishment of normal gut microbiota. Experimental microbiota+ bees did not differ in total abundance of gut bacteria and specific honey bee gut microbiota members in comparison to hive bees from their source colonies, except for the microbiota member  apicola . Experim apicola . This in2 = 31.672, df = 3, p < 0.001). Bees that were not exposed to the virus survived best, with microbiota+|virus− bees being only half as likely to die than microbiota−|virus− bees . Bees exposed to the virus survived significantly worse, with microbiota+|virus+ bees, again being only half as likely to die as microbiota−|virus+ bees . This indicates an overall negative effect of viral exposure on honey bee survival but a beneficial effect of the honey bee gut microbiota in reducing the viral impact on host honey bees.Bee survival was significantly affected by the presence of the normal gut microbiota and oral exposure to DWV-B at 6 days of age . Experimental bees that were not fed the virus showed only a low background infection, especially bees originating from source colony G1. Viral titer did not differ statistically in microbiota+|virus− and microbiota−|virus− bees .Irrespective of whether or not the normal gut microbiota was established in bees, feeding of DWV-B virus to bees resulted in similar, high viral titers in microbiota+|virus+ and microbiota−|virus+ bees at day 11 of the experiment  al6 cells for universally all gut bacteria, and for some of the specific honey bee gut microbiota members, a threshold often used to designate honey bees as microbiota-depleted [The results of our study potentially even underestimate the beneficial effect of the honey bee gut microbiota upon virus exposure. Our microbiota− bees showed bacterial abundances in excess of 10depleted ,22,23,24depleted ,24, we mWe found that viral titers reached similarly high levels in virus-exposed bees irrespective of whether bees carried the characteristic gut microbiota or not. Higher fitness  of bees with an established characteristic gut microbiota without control of parasite loads potentially suggests that the honey bee gut microbiota confers viral tolerance. Viral tolerance has been inferred in previous studies investigating varroa mite-resistant honey bees ,39 (see Many direct links between gut microbiota, disease, and dietary resources have been uncovered in animals in general and in the honey bee specifically ( and refe


Ilarvirus. BlastN analysis revealed 68.1–71.9% nt identity of PrVI with strawberry necrotic shock virus (SNSV). In subsequent phylogenetic analysis, PrVI was grouped together with SNSV and blackberry chlorotic ringspot virus (BCRV), both members of subgroup 1 of ilarviruses. In addition, mini-scale surveys in stone fruit orchards revealed the presence of PrVI in a limited number of sweet cherries and in one peach tree. Overall, our data suggest that PrVI is a novel species of the genus Ilarvirus and it consists the fifth member of the genus that is currently known to infect Prunus spp.In the present study, we utilized high throughput and Sanger sequencing to determine the complete nucleotide sequence of a putative new ilarvirus species infecting sweet cherry, tentatively named prunus virus I (PrVI). The genome of PrVI is comprised of three RNA segments of 3474 nt (RNA1), 2911 nt (RNA2), and 2231 nt (RNA3) and features conserved motifs representative of the genus  Prunus spp. are infected by a significant number of plant viruses, including at least four members of the genus Ilarvirus (family Bromoviridae): apple mosaic virus (ApMV), American plum line pattern virus (APLPV), prune dwarf virus (PDV), and prunus necrotic ringspot virus (PNRSV). Among these viruses, PDV and PNRSV are the most prevalent and have been associated with various stone fruit diseases, such as “ringspot disease” or “peach stunt disease” [Prunus hosts [disease” . Neverthus hosts , thus thus hosts ,3.Prunus avium) orchards in Imathia region in Northern Greece for the presence of Betaflexiviridae viruses [Ilarvirus. Preliminary surveys in Imathia region were also conducted, in order to investigate the incidence of PrVI in Prunus orchards.In a four-year (2009–2013) survey, conducted on sweet cherry  [Ilarvirus . Iterative mapping of the reads to the assembled contigs , 2911 nt (RNA2) and 2231 nt (RNA3) A and theThe three genomic RNAs of PrVI start with ‘GTATT’, whereas the terminal nucleotide sequences of all three segments show high sequence similarity B. UTRs sNucleotide and amino acid comparisons of the new ilarvirus’ ORFs with their cognates of other ilarviruses are illustrated in A total of 138 samples  were also tested for the presence of PrVI by RT-PCR and using specific primers PrVI-CP-F/PrVI-CP-R, designed in this study. RT-PCR revealed the presence of PrVI in four sweet cherry samples collected in 2009, 2013, 2014, and 2019, and in one peach sample collected in 2019 . The preIlarvirus (family Bromoviridae) is composed of 22 permanent virus species, according to the ICTV taxonomy, whilst five tentative ilarviruses await official ICTV designations [The genus gnations . From a gnations . Neverthgnations . FinallyPrunus spp.In this study, we characterized the complete nucleotide sequence of a novel ilarvirus from a sweet cherry tree, collected from Imathia region. Collective data from in silico analysis revealed that PrVI shares a similar genome organization with ilarviruses and harbors several motifs that are typical of the majority of members in the genus or even in the Bromoviridae family. Phylogenetically, PrVI is closely related to SNSV, BCRV, TSV, PMoV, privet ringspot virus, and ageratum latent virus, all members of the subgroup 1 of ilarviruses . TherefoFurthermore, PrVI UTRs showed high nucleotide similarities with those of their cognate ilarviruses from subgroup I. A series of studies have shown that alfalfa mosaic virus (AMV) and ilarviruses require the interaction of their own CP with the 3′UTRs of their viral RNAs to initiate replication and establish infection ,8 and thA small-scale survey was conducted in Imathia region, which consists a major area of stone fruit tree cultivation in Greece. The purpose of this survey was to investigate the presence of PrVI in sweet cherry and other stone fruit trees. In this context, in 2019–2020, we collected samples from sweet cherry, peach and plum orchards as so to identify potentially hosts for PrVI and we used plant material from 2009, 2013–2014 from the collection of the Plant Pathology Lab (AUTH). PrVI was identified in a low incidence of 3.6% (4/138) in sweet cherries. Notably, PrVI was also detected in one peach sample. Nonetheless, further experimental data are needed to address whether peach consists another host for PrVI and, possibly, plum, as we only tested a small number of plum samples. Moreover, the virus was identified in samples collected during 2009, 2014 and 2019 thus indicating that PrVI is infecting trees in the area for over a decade.Prunus samples that were found positive to PrVI, did not exhibit any obvious symptoms of viral infection. As fulfilling Koch’s postulates faces several limitations [It is worth mentioning that the itations ,13, espeitations , could phttps://plants.ensembl.org/Prunus_avium/Info/Index, accessed on 3 September 2020) were removed using the ‘Bowtie2′ mapper incorporated in Geneious Prime® 2019.1.1. . Then, reads were assembled into contigs using the de novo assembler ‘Trinity’ (v.2.2.0) [® 2019.1.1.Total RNA was extracted from leaves of the sweet cherry sample c18 using the TRIzol reagent  and it was subjected to HTS analysis on an Illumina Hi-seq 4000 platform . Paired-end reads were trimmed using PrinSeq and quality was checked with FastQC . Prior to de novo assembly, the host genome sequences (v.2.2.0)  with def® 2019.1.1.In order to validate the correctness of the de novo assembly, Sanger sequencing of overlapping amplicons with virus-specific primers  and RACEFull-length viral genome sequences were submitted to ORF finder  to deterPrunus spp., such as sweet cherry, peach and plum. Moreover, plant material was also used from the collection of the Laboratory of Plant Pathology  from previous years, including Imathia and Arta counties  1.5 U GRS HotStart Taq DNA polymerase (GRiSP Research Solutions) and DEPC-treated water to a final volume of 25 μL. The cycling conditions were 45 °C for 30 min; 94 °C for 5 min, 40 cycles of 94 °C for 30 s, 57 °C for 30 s, and 72 °C for 20 s; and a final extension at 72 °C for 2 min. Amplicons derived from the RT-PCR assays were directly submitted for Sanger sequencing at Genewiz .A small-scale survey was conducted in 2019-2020 in Imathia region, with a view to investigate the presence of PrVI in counties . A total


SD = 0.308, 95% CI = 0.177, 1.254), inpatient/outpatient and drugs costs , direct non-medical costs , and total economic burden ; besides, time interval between 4 and 6 months was significantly related to large indirect costs  in the 12-month period after diagnosis. Similarly, time interval between 1 and 3 months was significantly associated with high direct non-medical costs  in the 12-month period after diagnosis. However, time interval from diagnosis to treatment was not correlated to economic costs in the recent 12 months. In the long term, shortening the time interval from diagnosis to treatment would reduce the economic burden on families, especially in the 12-month period after diagnosis.The study aimed to investigate the economic costs in families of children with autism spectrum disorder (ASD) and explored how the time interval from diagnosis to treatment time interval from the date children first diagnosed with ASD to the date of first speech/behavior treatment influenced the economic costs. It was a cross-sectional study that recruited families with autistic children in Changsha, Hunan Province of China during March to November 2018. A self-designed questionnaire was applied to collect ASD-related economic costs in the two vital periods including the 12-month period after diagnosis and the most recent 12 months during the course of ASD. In total, 136 families with autistic children completed the interview. The results showed that 46.3% of children started intervention within 1 month. The median of total economic costs of these families in the 12-month period after diagnosis and the most recent 12 months was 26,502.26 RMB and 29,411.91 RMB, respectively. Compared with the time interval shorter than 1 month, time interval over 6 months was significantly associated with high direct economic costs (β Autism spectrum disorder (ASD) is a highly heterogeneous group of neurodevelopmental disorders characterized by different levels of impairment in social communication and interaction, repetitive behaviors, and restricted language ability . An incrThere is a lack of unified and effective approaches for the prevention and treatment of ASD in clinical practice. The long-term prognosis of most individuals with ASD is poor, namely, they lack the ability to study and work independently in adulthood . TherefoThe direct and indirect economic costs are two aspects of the total economic costs of ASD. The direct costs are related to diagnosis, medical check, rehabilitation, and behavioral therapy. Referring to Rogger et al., the direct economic costs is direct economic costs are defined as the total sum of ASD-related medical or healthcare costs and therapeutic costs . Montes Indirect costs, such as the informal care burden and lost parental productivity, are also important components of the economic costs . PreviouSeveral surveys have explored the factors related to the economic costs in families of children with ASD. For instance, Parish et al. found that per-capita Medicaid expenditures were likely to reduce the financial burden in families of children with autism . Horlin In summary, there was more significant burden associated with ASD (on a population level) as compared to other diagnoses (such as ADHD or ODD) and children with normal development. It is very important to note that the earlier the treatment for children with ASD, the better the children's prognosis for developing language and social skills, which, to some extent, also means less ASD-related economic burden for the family. It was suggested that the time interval from the date children first diagnosed with ASD to the date of first speech/behavior treatment was strongly associated with the economic burden in families with autistic children. However, there was limited evidence to support this conclusion. Therefore, this study aimed to investigate the economic costs in families with autistic children and explore its potential association with the time interval from diagnosis to treatment. We hypothesized that the family economic costs were positively associated with the time interval from diagnosis to treatment.n = 150) of children with ASD from those centers. Autistic children were strictly defined as having an autistic disorder based on DSM-IV, while children with a pervasive developmental disorder not otherwise specified (PDD-NOS) or with Asperger syndrome were excluded from the study.This was a cross-sectional study conducted in Changsha, Hunan Province, from March to November 2018. There are a total of 10 autism rehabilitation centers in the five main districts of Changsha. We selected four autism rehabilitation centers using the clustering random sampling method and recruited all the families . The ABC was a screening tool used to evaluate the symptoms of autistic children with satisfactory reliability and validity, and it could be completed by the parents or caregivers of children . The ABCWe collected the ASD-related economic costs in two vital periods during the course of the disease including the 12-month period after the date of the child was first diagnosed with ASD and the most recent 12 months before the date of interview. Most of the parents would seek medical consultations around everywhere during the first period, which resulted in large costs for medical-related expenditure, while in the second period, the expenditure of ASD-related interventions and therapies in most families was relatively stable and reflects the economic burden. The parent-reported ASD-related economic costs were divided into three categories: direct, indirect, and total economic costs.(i) Direct economic cost was calculated by the following formula:1 = X1 + X2 + X3Y1: inpatient, outpatient, and drug expenses .X2: therapeutic costs .X3: direct non-medical costs ;X(ii) Indirect economic cost was defined as production loss for parents, which was calculated by the human capital approach as follows :2 = 5Y4: labor force time lost by parentsX5: labor-time value per unitXhttps://tjj.hunan.gov.cn/). For example, the per-capita net income of resident labor in Hunan Province in 2018 was 25,241 RMB, so if there were 180 total days of labor time lost for an adult, the indirect economic costs would be 12,447 Yuan .Specifically, the labor-time value per unit was divided into farmer and resident labor value. In our study, the participants were composed of residents in the urban areas and a small number of farmers. The per-capita net of farmer and resident labor value in Hunan Province was collected by the Hunan Provincial Bureau of Statistics ((iii) The total economic cost of children with ASD was calculated by the following formula:1 + Y2Y = Y25 and P75) were reported in the study. The categorical data were described as n (%). Multivariate linear regression models were carried out to explore the probable association between the family economic costs and the time interval from diagnosis to treatment after adjusted for the general characteristic of families and children. The Z-score transformation was used to transform the raw data pertaining to the economic costs in the 12-month period after diagnosis and the most recent 12 months to a linear, additive scale as a dependent variable in the linear models. A p-value of <0.05 was considered statistically significant in our study.Statistical analysis was performed using SPSS version 23.0. The continuous data following the law of normal distribution were described as the mean ± SD. Otherwise, the median and quantiles (PThere were 37 girls and 99 boys between 2 and 11 years old who were diagnosed with ASD by a neurologist based on the DSM-IV were recruited into the survey. More boys (72.8%) were enrolled than girls (27.2%). Among these children, 95 (69.9%) lived in urban areas. The mean age of the children was 4.44 years (SD = 1.88). Most of the children (89.7%) were of Han ethnicity.The time interval from diagnosis to treatment and other disorder characteristics of children are presented in The expenditures on autistic children in the 12-month period after diagnosis are shown in The expenditures on autistic children in the recent 12-month period are shown in SD = 0.308, 95% CI = 0.177, 1.254), inpatient/outpatient and drugs costs , direct non-medical costs , and total economic burden ; besides, time interval between 4 and 6 months was significantly related to large indirect costs  in the 12-month period after diagnosis. Similarly, the time interval between 1 and 3 months was significantly associated with high direct non-medical costs  in the 12-month period after diagnosis. However, the association between economic costs in the recent 12-month period and time interval from diagnosis to treatment was not observed in this paper   but lowe%  but loWang et al. analyzed annual family expenditures on ASD-related health services in 178 urban families with autistic children from Heilongjiang Province, and the mean costs were 17,497.28 RMB . SimilarIn addition, adjustment in job time also has important impact on economic costs. For example, in the current study, the median indirect economic cost in the recent 12 months was 379.01 RMB, which was slightly lower than that found from a survey conducted in Malaysia  . SpecifiThe present study also demonstrated that longer time interval from diagnosis to treatment was associated with heavy ASD-related economic costs of children in the 12 months after diagnosis. The course of doctor consultation and seeking appropriate institutions was an important period before long-term intervention in a rehabilitation institution. The expenditure of this course was catastrophic because it usually exceeded an acceptable percentage of consumption or household income. For parents, the course meant less work time and higher expenditure. A previous study suggested that the early diagnosis of ASD was important for improving the effectiveness of interventions in children with ASD . ResearcOur findings indicated that the shorter the time interval from diagnosis to treatment, the lower the economic costs. Meanwhile, previous studies reported that early diagnosis and therapy were the keys to reduce the complications. Therefore, to alleviate their economic burden as well as improve the prognosis of their children, parents should improve the recognition of the disease in order to strive for early diagnosis and therapy. Hence, improving social services is also important to shorten the time interval between diagnosis and intervention.Estimate of ASD-related medical and intervention costs are very crucial to evaluate future care needs and resources allocation. We reported ASD-related costs in two vital periods during the course of disease, which objectively reflected the economic burden in those families and received more attention. Nonetheless, there are several limitations in this study as it is designed as a cross-sectional study with a small sample size. Namely, only one geographic area of China was examined, which might impact the generalizability of this study. Further investigations with a larger number of families with autistic children  will be necessary to completely rule out such limitation.The present study investigated the economic costs in families of children with ASD, and the results revealed that ASD-related costs were a heavy economic burden for those families. Shortening the time interval from diagnosis to treatment was beneficial for reducing the total economic burden to some extent. Further investigations with a larger number of subjects will be necessary in the near future to verify the present conclusion.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.Ethical approval was provided by the Ethics Committee of Hunan Provincial Maternal and Child Health Care Hospital (EC20180318). The patients/participants provided their written informed consent to participate in this study.WZ, XX, and HX designed the study. WZ, KW, SC, DL, and XX collected the data. WZ, XX, and HX analyzed the results. WZ wrote the main manuscript text. XX and HX reviewed the manuscript.This study was financially supported by the National Natural Science Foundation of China (81701356), Major Scientific and Technological Projects for the Collaborative Prevention and Control of Birth Defects in Hunan Province (2019SK1015), the Science and Technology Programs of Changsha city (kq1801084), and Technology Projects of Administration of Traditional Chinese Medicine (201918).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Varroa destructor, feeds directly on honey bees and serves as a vector for transmitting viruses among them. The Varroa mite causes relatively little damage to its natural host, the Eastern honey bee (Apis cerana) but it is the most devastating pest for the Western honey bee (Apis mellifera). Using Illumina HiSeq sequencing technology, we conducted a metatranscriptome analysis of the microbial community associated with Varroa mites. This study led to the identification of a new Chinese strain of Varroa destructor virus-2 (VDV-2), which is a member of the Iflaviridae family and was previously reported to be specific to Varroa mites. A subsequent epidemiological investigation of Chinese strain of VDV-2 (VDV-2-China) showed that the virus was highly prevalent among Varroa populations and was not identified in any of the adult workers from both A. mellifera and A.cerana colonies distributed in six provinces in China, clearly indicating that VDV-2-China is predominantly a Varroa-adapted virus. While A. mellifera worker pupae exposed to less than two Varroa mites tested negative for VDV-2-China, VDV-2-China was detected in 12.5% of the A. mellifera worker pupae that were parasitized by more than 10 Varroa mites, bringing into play the possibility of a new scenario where VDV-2 could be transmitted to the honey bees during heavy Varroa infestations. Bioassay for the VDV-2-China infectivity showed that A. cerana was not a permissive host for VDV-2-China, yet A. mellifera could be a biological host that supports VDV-2-China’s replication. The different replication dynamics of the virus between the two host species reflect their variation in terms of susceptibility to the virus infection, posing a potential threat to the health of the Western honey bee. The information gained from this study contributes to the knowledge concerning genetic variabilities and evolutionary dynamics of Varroa-borne viruses, thereby enhancing our understanding of underlying molecular mechanisms governing honey bee Varroosis.The ectoparasitic mite,  Varroa destructor (hereafter referred to as the Varroa mite) [Apis mellifera, which is the primary managed pollinator in agricultural systems and natural ecosystems. Since its host expansion from the Eastern honey bee Apis cerana to A. mellifera in the mid-1900s, the Varroa mite has now spread to every region where honey bees are kept with the exception of Australia, and has been catastrophic for the beekeeping industry worldwide [Varroa mites cause limited damage to its original host A. cerana, they inflict profound damage on the A. mellifera hosts through the intake of their fat body tissue and hemolymph from immature brood and adult honey bees [A. mellifera host’s vigor, immunity, weight, and lifespan, and leads to the eventual collapse of entire colonies [Varroa mite infestations in A. mellifera colonies have been cited as strong predictive markers for honey bee colony mortality during winter [Varroa mite infestation causes a devastating honey bee disease called Varroosis and has destroyed millions of A. mellifera colonies since its establishment in various parts of the world [The ectoparasitic mite, oa mite) , is the orldwide ,3,4. Whiney bees ,6. The rcolonies ,11,12,13g winter ,16,17,18Varroa mite to carry and spread multiple debilitating viruses has added another layer to the complicated and dire situation of honey bee health [Varroa mites [V. destructor. Several bee viruses, including Acute bee paralysis virus (ABPV), Black queen cell virus (BQCV), Chronic bee paralysis virus (CBPV), Deformed wing virus (DWV), Kashmir bee virus (KBV), Sacbrood virus (SBV) and Israeli acute paralysis virus (IAPV), have been documented to be aggravated and transmitted by Varroa mites in field settings [Varroa mite infestations and virus infections in honey bees led to important laboratory experiments, which resulted in the conclusion that Varroa mite is a highly efficient mechanical and/or biological vector of honey bee viruses, and it drives the spread of viruses in honey bee colonies [Varroa mite activates bee viruses by suppressing the honey bees’ immune responses and triggering the replications of viruses in immunosuppressed hosts [The ability of the e health ,20,21. Boa mites . Viral isettings ,27,28,29colonies ,31,32,33ed hosts ,37,38,39Varroa mites, DWV is the most common and widespread honeybee viruses and infects a wide range of host species [Varroa mites is particularly worrisome [Varroa mite magnifies the negative effects of DWV infections and drives the selection of highly virulent DWV strains which has altered the viral landscape and resulted in the destruction of millions of bee colonies worldwide [Varroa vectoring has resulted in the emergence of at least three master variants in honeybees: DWV-A, DWV-B , and DWV-C [Varroa invasion, DWV-A was a predominant master variant and bees infected with DWV-A exhibited low viral titers and were non-symptomatic [Varroa vectoring caused genetic mutations among DWV populations, leading to a new master variant, Varroa destructor virus 1  which shares 84.4% nucleotide sequence identify with DWV-A and is closely linked to overwinter honeybee worker loss [Varroa mite infestation was not at economic injury levels [Of all honey bee viruses vectored by  species ,41. The orrisome . The Varorldwide . It has nd DWV-C ,43,44. Pptomatic . Howeverker loss ,47,48. Rker loss  and, in y levels ,50. Althy levels .So far, more than 20 viruses that cause honey bee infections ranging from asymptomatic to severe, debilitating illness and contribute to elevated colony losses worldwide have been identified ,20,52. TV. destructor [Varroa mites [Varroa mite infested honeybee colonies [Varroa mites collected in the U.S.A. and Europe led to the identification of RNA viruses including Varroa destructor virus 2 (VDV-2) and VDV-3, which were found to be able to replicate in the mite but not in the honey bee, suggesting that they are specific to Varroa mites [Additionally, recent studies have identified novel RNA viruses that are exclusively associated with structor ,57,58. Vstructor  and was oa mites . VDV-1 acolonies ,59,60. Toa mites ,58.A. mellifera and A. cerana are often kept in close proximity for honey production and crop pollination, which has created unique opportunities for the spread of Varroa mites and the transmission dynamics of Varroa-borne viruses between two host species. In the present study, we employed a high-throughput next-generation sequencing technology to detect the viruses associated with Varroa mites. Our study led to the identification of a new Chinese strain of VDV-2 (VDV-2-China). We conducted the subsequent studies to investigate the incidence and prevalence of VDV-2-China in the Varroa mites and honey bees, including A. mellifera and A. cerana, in different geographic regions of China. Furthermore, we investigated and compared the VDV-2-China replications in the two honey bee species under the laboratory conditions. The information gained from this study contributes to the existing body of literature concerning genetic variabilities and evolutionary dynamics of Varroa-borne viruses, thereby enhancing our understanding of underlying molecular mechanisms governing honey bee Varroosis and improving the management of Varroa mite infestation in honey bees.In China, both Apis mellifera ligustica) and the Eastern honey bees (Apis cerana cerana) used in the study are neither endangered nor protected species. No specific permits were required. The Italian honey bee  analysis, honey bee combs were taken out from the Varroa samples were collected from A. mellifera colonies and A. cerana colonies in an apiary located in Zhejiang province. For A. mellifera colonies, the brood cells in the frames were opened and pupae were removed individually with a pair of tweezers to check for the presence of Varroa mites. Individual worker pupae with one Varroa mite parasitizing on them when the brood cell was opened were designated as ng low count of mites, while worker pupae with more than 10 Varroa mites, including the foundresses and the offspring, were defined as having high count of mites For A. cerana colonies, our sampling only focused on the adult workers as Varroa mites express strong avoidance to the A. cerana worker brood in the field and no Varroa-infested A. cerana worker brood was identified [For the epidemiological study, entified ,62.V. destructor and Varroa. underwoodi were found in A. cerana colonies [V. underwoodi occurs at a much lower abundance, compared to V. destructor [Varroa mites collected from both A. mellifera and A. cerana colonies are confirmed to be V. destructor by morphological identification and molecular identification [According to our field survey over the past few years, only colonies ,63. The A. mellifera colonies and 180 A. cerana colonies distributed in six provinces  of China. These samples were placed individually in a microcentrifuge tube, snapped frozen in liquid nitrogen, and transferred to Zhejiang University for subsequent molecular analysis.In addition, 30 adult workers were collected by brushing off bees from a brood frame from each of 180 Varroa mites from three A. mellifera colonies were used for RNA-Seq analysis. For each colony, total RNA was extracted from the pool of five V. destructor mites according to the manufacturer’s instructions . The concentration of RNA samples was measured by using a Nanodrop2000 and the integrity of the RNA was confirmed using the Agilent 2100 BioAnalyzer. The Ribo-ZeroTM kit  was used to remove ribosomal RNA. cDNA was synthesized from the RNA using random hexamer primers and the QIAGEN Reverse Transcription Kit following the manufacturer’s instructions and submitted to a commercial company  for transcriptome sequencing analysis. The Illumina Hiseq sequencing platform was used for transcriptome sequencing. An Illumina PE library was constructed for 2 × 150 bp sequencing, and the obtained sequencing data were subjected to quality control. The Illumina reads were processed to remove low-quality sequences and adaptor by Trimmomatic v0.4 (PMID: 24695404).V. destructor and A. mellifera were eliminated. Then, the remaining reads were assembled by Trinity software with default parameters [−15 [The reads of RNA sequencing data were compared with sequences in the database through Bowtie2 with default parameters , and rearameters . The assrameters  and BLASers [−15 . ContigsV. destructor’s transcriptome, which showed a sequencing depth > 150× in all of the three sequenced samples. The genomic organization and location of the conserved motifs for the structural and non-structural proteins were determined by a multiple sequence alignment of iflaviruses. The protein domains were defined by pairwise amino acid sequence alignment between VDV-2-China and VDV-2-UK (QFS19921) whose functional regions have been identified and annotated and further confirmed by Pfam matches. The viral genome sequence identified in this study was submitted to Genbank with an accession number (MW590582). A full viral genome sequence with high homology to VDV-2 was identified in the Iflaviridae-Deformed wing virus (DWV) (AY292384), DWV-C (SAMEA3249778), Ectropis obliqua virus (AY365064), Infectious flacherie virus (AB000906), Perina nuda virus (AF323747), Sacbrood virus (AF092924), Varroa destructor virus 1 (AY251269), Varroa destructor virus 2 (QFS19921), Brevicoryne brassicae picorna-like virus (EF517277), Slow bee paralysis virus (EU035616), and Slow bee paralysis virus (Harpenden) (GU938761); Dicistroviridae-Acute bee paralysis virus (AF150629), Cricket paralysis virus (AF218039), Drosophila C virus (AF014388), Kashmir bee virus (AY27571O), Rhopalosiphum padi virus (AF022937), Solenopsis invicta virus 1 (AY634314), Taura syndrome virus (AF277675), and Israeli acute paralysis virus (EF219380); Secoviridae-Parsnip yellow fleck virus (D14066), Cowpea severe mosaic virus (M83830), Maize chlorotic dwarf virus (NP619716), Bean pod mottle virus , and Cowpea mosaic virus (NP613283); Picornaviridae-Poliovirus (VOl149), Encephalomyocarditis virus (M81861), Aimelvirus 1 strain (ASH99046), and Rabbit kobuvirus (YP009118268). A phylogenetic tree based on the amino acid sequence of RNA-dependent RNA polymerase (RdRp) was also generated to show the relationship between the VDV-2-China and other members of the family Iflaviridae.To classify the newly discovered virus, the phylogenetic analysis was conducted in MEGA 7  using thSequences were aligned individually using Multiple Sequence Comparison by Log-Expectation (MUSCLE) 3.8  that wasV. destructor RNA and 800 ng honey bee RNA. Samples were individually crushed into fine powder in liquid nitrogen and homogenized in TRIzol Reagent for RNA extraction. A cDNA synthesis was performed using PrimeScript RT Master Mix  with 200 ng of Polymerase chain reaction (PCR) amplifications were conducted using KOD FX  with 1 μLof cDNA. The VDV-2-China specific primers were Forward: 5′-AACACCAGACGAACAAGGCT-3′; Reverse: 5′-TTGGCTATGGTGAAGGCTCG-3′. A fragment length of 285 bp of VDV-2-China specific product was expected using these primers. The thermal cycling conditions of PCR amplification were as follows: 94 °C for 2 min, 35 cycles of 94 °C for 30 s, 58 °C for 30 s and 72 °C for 30 s, and 72 °C for 5 min. The PCR products were analyzed by electrophoresis in a 2% agarose gel. Purified PCR products were subjected to two directional Sanger sequencing and BLAST search to confirm the specificity of the primers. Varroa mite, (2) A. mellifera and A. cerana adult workers, (3) A. mellifera worker pupae with low Varroa parasitism, and (4) A. mellifera worker pupae with high Varroa parasitism. For the worker pupae samples, to avoid false positive results caused by possible contamination of Varroa offspring, additional PCR amplifications were performed with primers targeting Varroa tublin gene . None of the honeybee worker pupae samples were found to be contaminated by Varroa mites. The infection rate of VDV-2-China was determined by the proportion of the positive PCR results among all the tested individuals in each of the four groups: (1) Due to the ubiquitous presence of the Varroa mites in honey bee colonies, it is very possible that hive materials including food could also be contaminated by the virus and honey bees can acquire the virus via indirect food-borne horizontal transmission. Therefore, we assessed the possibility and likelihood of the VDV-2-China replication in honey bees via virus feeding.A. mellifera and A. cerana, a laboratory inoculation experiment was conducted. Approximately about 1000 adult Varroa mites were collected from the A. mellifera colonies maintained at an apiary of the College of Animal Sciences, Zhejiang University, Hangzhou, China. Collected mites were then ground into fine powder in liquid nitrogen and homogenized with 5 mL of phosphate-buffered saline (1 × PBS) in a tissue grinder. The homogenized mixture was centrifuged at 10,000 rpm at 4 °C for 40 min and the supernatant was passed through a 0.20 μm cell filter and stored at 4oC for the subsequent inoculation. To determine if honey bees could serve as a biological host to support the VDV-2-China replication and the infectivity of VDV-2-China in the host of the 4 genome copies/μL.The concentration of VDV-2-China in the purified solution described above was determined by absolute quantification using the standard curve method . The purA. mellifera (N = 75) and A. cerana (N = 75) adult workers were fed individually with 3 μL of virus solutions and transferred into rearing cages. Each cage consisted of 25 viral inoculated bees, resulting in three cages for A. mellifera, and three cages for A. cerana. Another group of newly emerged A. mellifera (N = 75) and A. cerana (N = 75) workers were fed with 3μL of PBS and used as a negative control. All the rearing cages were kept in an incubator  at a temperature of 30 ± 0.5 °C and a relative humidity of 70 ± 5%. A freshly made 50% (w/v) sucrose solution was provided for the honey bees every day. From each rearing cage, three bees were collected 12 h, two days, four days, six days, and eight days post treatment and subjected to the subsequent RNA extraction and strand-specific quantitative PCR (RT-qPCR).A group of newly emerged A. mellifera and A. cerana, RNA samples from the VDV-2-China inoculated bees and negative control were analyzed for the presence and abundance of negative-stranded RNA of VDV-2 China, a replicative intermediate, using the strand-specific reverse transcription coupled with RT-qPCR. For each sample, the first strand cDNA was synthesized from total RNA with Tag- VDV-2-China forward primer (5′agcctgcgcaccgtggGCCCCATCGACTTCACGATA-3′) where the lowercase letters corresponding to Tag sequences [® Premix Ex TaqTM  [−ΔΔCt) method [A. mellifera and A. cerana. One-way analysis of variance (ANOVA) was used to determine whether there is a statistical significance in the fold change of VDV-2-China replication among different time points post inoculation and Tukey’s honestly significant difference (HSD) test was used for all pairwise comparisons among different time points. A p-value ≤ 0.05 was considered statistically significant.In order to determine the likelihood and ability of VDV-2-China to replicate in equences . The syn, China) . To norm) method  was usedIflaviridae. The C-terminal portion of the polyprotein possesses consensus sequences in the order of helicase, protease and RNA-dependent RNA polymerase, similar to those of iflaviruses. Two conserved functional motifs, rhinovirus-like (rhv) motifs belonging to the picornavirus capsid protein domain-like were identified in the N-terminal portion of the polyprotein (Varroa destructor virus 2-UK (MK795517) with an 82.96% nucleotide sequence identity (95% query coverage) and an 88.95% amino acid sequence identity (100% query coverage). The BLAST search returned a second-best match to Varroa destructor virus 2–Israeli (NC-04061) with a 78.58% nucleotide sequence identity (90% query coverage) and an 85.75% amino acid sequence identity (85% query coverage). Due to the revealed high level of sequence similarity with the VDV-2, we named the virus as Varroa destructor virus 2–China (VDV-2-China). The transcriptome assembly on the RNA reads led to a contiguous full-length viral genome. The single-stranded positive-sense RNA genome is 9544 nt long and contains a single open reading frame (ORF). The ORF encoding a polyprotein of 2995 amino acid residues is flanked by approximately 413 nt of 5′-UTR and 147 nt of 3′-UTR, which is typical for the genome organization of yprotein . The BLAThe phylogenetic tree constructed with the amino acid sequences of structural capsids of VDV-2-China  showed that VDV-2-China was distantly related to other members of the Dicistrovidae, Secoviridae, and Picornaviridae families and clustered together with other members of Iflaviridae. Of all the members of Iflaviridae, VDV-2-China is the most closely related to VDV-2-UK . The seqiflaviruses revealed that VDV-2-UK and VDV-2-Israel were clustered together into the same clade. While VDV-1, DWV, and VDV-2 are closely associated with honey bee colonies, they are not the closest relatives in the phylogenetic tree. The clade of VDV-2 strains is nested within a clade of Graminella nigrifrons virus 1, a virus isolated from black-faced leafhopper, Graminella nigrifrons, and SBPV infecting honey bees. Compared to DWV and VDV-1, VDV-2 strains were found to be located more closely to the root of the tree, implying that DWV and VDV-1 may be more advanced than VDV-2 in their evolution  and A. cerana colonies (N = 28). Of all the adult workers collected from both A. mellifera (N = 180) and A. cerana colonies (N = 180) from six provinces, none of the samples was found to be positive for VDV-2-China. Of all the worker pupae with high levels of Varroa parasitism collected from A. mellifera colonies (N = 24), 12.5% of the A. mellifera worker pupae were found to be infected with VDV-2-China, while none of the A. mellifera worker pupae with low levels of Varroa parasitism (N = 24) tested positive for the virus  an infectious agent in its natural reservoir, (2) the acquisition of the disease agent by susceptible hosts via transmission, and (3) the efficient replication of a virus in the infected host. Infectivity and pathogenesis of a pathogen can be described as the ability of the pathogen to evade a host’s immune responses and to use the host’s resources to replicate and establish a persistent infection. Like any other positive-stranded RNA virus, the replication of VDV-2-China takes place through the production of negative-stranded intermediate; therefore, the presence of a negative-stranded RNA is proof of active viral replication . Our resvolution . While tVarroa mites. We also provide evidence that A. mellifera is more susceptible to the VDV-2-China infection than A. cerana. However, certain questions still remain: is VDV-2-China harmful to its parasite host? While VDV-2-China could replicate in A. mellifera, what is the infective dose of VDV-2-China that will cause disease in honey bees? Future investigations to define the virus–host interactions that regulate the replication and pathogenesis of VDV-2-China in the host would yield critical insights into the evolutionary change of the virus’ prevalence, distribution, and virulence, thereby contributing to an effective disease management program for honey bees. In sum, our present study reports the discovery of a new strain of VDV-2 and supports previous findings that VDV-2 predominantly infects


Begomovirus (93%) followed by Potyvirus (46%), cucumber green mottle mosaic virus (CGMMV-39%), Polerovirus (9%), cucumber mosaic virus (CMV-2%) and Orthotospovirus (2%). Nearly 65% of samples were co-infected with more than one virus. Additionally, host range expansion of CMV, CGMMV and polerovirus was also observed on cucurbit crops. A new potyvirus species, zucchini tigre mosaic virus, earlier not documented from India has also been identified on five crops during the study. Risk map generated using ArcGIS for virus disease incidence predicted the virus severity in unexplored areas. The distribution pattern of different cucurbit viruses throughout Uttar Pradesh will help identify the hot spots for viruses and will facilitate to devise efficient and eco-friendly integrated management strategies for the mitigation of viruses infecting cucurbit crops. Molecular diversity and evolutionary relationship of the virus isolates infecting cucurbits in Uttar Pradesh with previously reported strains were understood from the phylogenetic analysis. Diverse virus infections observed in the Eastern Plain zone, Central zone and North-Eastern Plain zone indicate an alarming situation for the cultivation of cucurbits in the foreseeable future.During 2018 an intensive study was conducted to determine the viruses associated with cucurbitaceous crops in nine agroclimatic zones of the state of Uttar Pradesh, India. Total of 563 samples collected and analysed across 14 different cucurbitaceous crops. The results showed the dominance of  An area of nearly, 0.6 million hectares was dedicated to cucurbits cultivation with an annual production of 10.86 million tonnes in Uttar Pradesh during 2017–182. Diseases caused by viruses are among the limiting factors to cucurbits cultivation worldwide. More than 70 different viruses were reported to cause a wide range of diseases in cucurbits3. To date, viruses in the genera Begomovirus, Potyvirus, Cucumovirus, Tobamovirus, Tymovirus, Nepovirus, and Polerovirus have been described as potential threats in cucurbits cultivation across the world11. Viruses belonging to these genera are mainly transmitted by insect-vectors, although seed transmission has been reported in some species belonging to the genera Potyvirus, Cucumovirus, and Tobamovirus14. Recently, six viruses associated with cucurbit crops have been documented from Southern India. They are Papaya ring spot virus (PRSV), Cucumber green mottle mosaic virus (CGMMV), Zucchini yellow mosaic virus (ZYMV), Cucumber mosaic virus (CMV) and Begomovirus (tomato leaf curl New Delhi virus and squash leaf curl China virus)15.Cucurbits are economically important vegetables grown extensively in tropical and subtropical regions for human consumption. The family Cucurbitaceae comprises 825 species in 118 generaStudies on the occurrence and distribution of viruses associated with cucurbit crops have been done only in southern India. So far, little effort has been made to determine the viruses infecting cucurbitaceous crops in Northern India. Therefore, the objective of the present study was to perform a comprehensive analysis of the occurrence, distribution and genetic diversity of viruses infecting cucurbit crops across Uttar Pradesh, India. Furthermore, an attempt was also made to map the epidemiological distribution and incidence proportion of the afore-mentioned viruses associated with cucurbit crops.A total of 563 samples from 14 different types of cucurbit crops were collected from nine agro-climatic zones of Uttar Pradesh , Tobamovirus (CGMMV), Orthotospovirus (PBNV and WBNV), Potexvirus, Crinivirus and poleroviruses. Out of 563 collected cucurbits samples, 95.4% (537/563) were found to be infected with viruses (either single or mixed infection). Despite showing virus like symptoms, the remaining 4.6% of samples tested negative for viruses. Universal and virus-specific primer pairs were used to test samples for eight virus genera, out of which samples were found to be positive for six genera . None of the samples were found to be positive for Potexvirus and Crinivirus. The relative frequency of viruses infecting cucurbit samples in our study showed dominance of Begomovirus (93%) followed by Potyvirus (46%), CGMMV (39%), poleroviruses (9%), CMV (2%) and Orthotospovirus (2%).All samples collected during the study were subjected to PCR for Begomoviruses and RT-PCR for RNA viruses such as potyviruses (PRSV and ZYMV), Begomovirus was higher in all the zones irrespective of the cucurbit crops. Diverse virus infection was observed only in samples tested from the Eastern Plain zone, Central zone and North-Eastern Plain zone while samples collected from the rest of the zones were positive for only potyviruses and CGMMV. Surprisingly, Polerovirus was primarily restricted to the Eastern plain zone, Central zone and North-Eastern Plain zone whereas Orthotospovirus and CMV were detected only among a few samples collected from the Eastern Plain zone and the North-Eastern Plain zone, respectively  on squash; melon aphid borne yellow virus (MABYV) on ivy gourd; Luffa aphid borne yellow mosaic (LABYV) on sponge gourd, bitter gourd and pumpkin has been recorded for the first time from India. In addition, CMV on sponge gourd, ivy gourd and ridge gourd and CGMMV on long melon were also documented. Besides, Zucchini tigre mosaic virus (ZTMV) was observed newly in India on pumpkin, bottle gourd, bitter gourd, squash and cucumber.Begomovirus (90%) followed by Orthotospovirus (6%), Potyvirus (2%) and CGMMV (2%)  were infected with a combination of four viruses (Begomovirus + Polerovirus + CGMMV + Potyvirus)  Fig. B. Of the2%) Fig. C. Moreovus) Fig. D. Among Polerovirus primer pair showed that three Polerovirus species  were associated with different cucurbits of Uttar Pradesh. Similarly, sequence analysis using the BLASTn programme of the Nib region showed association of three potyvirus species . In the coat protein region, PRSV showed more than 85% identity with isolates reported from India (EU475877) and China (KY933061); ZYMV showed > 98% identity with a Cucurbita pepo isolate (JN183062) reported from Iran; and ZTMV sequences showed > 85% identity with the sequences reported from France . Watermelon bud necrosis virus (WBNV) was the only Orthotospovirus found associated with both round melon and watermelon having identity of > 95% with Indian isolates . The coat protein gene of the CGMMV isolate infecting cucurbits  was observed with more than 98% nucleotide identity with the CGMMV isolates recorded on various cucurbit crops characterised earlier from India. BLASTn analysis of nucleotide sequences amplified using a universal e JN18306 reportedPhylogenetic analysis based on the nucleotide sequence of the 2a fragment showed that a CMV isolate infecting cucurbits shared ancestry with the CMV reported on tomato, snake gourd, bottle gourd, pepper and banana from India Fig. a. Based Polerovirus (50–89%)  Fig. B whereas9%) Fig. C, Begomorus Fig. D and Potrus Fig. E were obBegomovirus, Potyvirus, Cucumovirus, Tobamovirus, Orthotospovirus and Polerovirus were detected. Among the 563 samples tested, 26 samples did not test positive for any tested viruses. These samples may have been infected by viruses other than those tested in this study. In cucurbits, Begomovirus infection was the most identified, infecting 523 samples collected from thirteen different cucurbit crops across the UP state. Our result is consistent with previous finding of Nagendran et al.15 that Begomoviruses are the most dominant virus (98.6%) in cucurbit samples collected from southern India. High adaptability of Begomovirus, polyphagous nature of its vectors and the continuous availability of other host plants plays a major role in the Begomovirus infection.In this study, we explored cucurbit fields in different regions of Uttar Pradesh state (UP) (nine agro-climatic zones). Results showed disease incidences in different zones varied significantly. Association of one or more virus species belonging to the genera Begomovirus, Potyvirus was detected among 254 samples collected from 10 cucurbit crops . Due to the diverse nature of potyviruses prevailing in the cucurbits ecosystem, a single universal primer pair (PNIbF1/PCPR1) could not amplify the majority of samples. Therefore, different sets of primer pairs were used for potyvirus detection  were identified and characterized in pumpkin, bitter gourd, sponge gourd, squash and ivy gourd. A previous study from southern India has documented the infection of bitter gourd and teasel gourd by CABYV30. Findings from the present study further confirm the existence of CABYV on cucurbits cultivated in northern India with an expanded host range, and the existence of other species (MABYV and LABYV) may be indicative of its emergence in India.Besides, CMV was the least distributed virus detected only among 12 samples of bitter gourd, sponge gourd and ridge gourd. Though CMV has wide host range, the reason for its limited distribution among cucurbits remains unclear. Similarly, limited occurrence of CMV in cucurbits from commercial growers among the several viruses tested has been documented earlierBegomovirus coupled with Potyvirus/ Tobamovirus/ Polerovirus (44%) was by far the most common in tested samples. Infection of cucurbits by triple viruses (Begomovirus + Potyvirus + Tobamovirus) was recorded in 16% of the total tested samples. Similar results have been observed in India and Oklahoma with preponderance of double infection over triple infection27. Additionally, Kone et al.31 observed average multiple virus infections among 15% of cucurbits samples in Cote d’Ivoire. Interestingly, mixed infection of cucurbits by four viruses (Begomovirus + Potyvirus + Tobamovirus + Polerovirus) was observed in very few samples as previously reported on squash, melon and cucumber in Iran32.Further our study shows the predominance of mixed infection (64%) over single infection (32%) in infected samples. Although up to 32% single infection due to Begomoviruses, causing mosaic and mottling symptoms was observed in cucurbit samples, double infection by 34. It provides map showing probability of the occurrence of disease in the unexplored area based on the data collected from few pockets of the state. This gives clarity about the hot spot and cold spot for each virus separately as well as for the overall virus diseases infecting cucurbits. To our knowledge, this is the first of its kind in generating the risk map for virus diseases infecting cucurbits.The main aim of risk mapping of ArcGIS is to find the hazard level of the virus which is causing threat to crop cultivationPolerovirus on squash, pumpkin, ivy gourd and sponge gourd; and ZTMV on pumpkin, bottle gourd, bitter gourd, squash and cucumber. Further studies are needed to explore and characterize new and unidentified viruses which have been reported from different parts of world.Overall, the present work outlined the current status of cucurbits viruses in UP state and provided conclusive evidence of viral diversity and the potential presence of new viruses currently emerging in this area. The distribution pattern of different cucurbit viruses in this region will help to identify the hot spots for viruses and will facilitate to devise efficient and eco-friendly integrated management strategies for management. Additionally, we identified many new viruses such as CMV on sponge gourd, bitter gourd and ridge gourd; CGMMV on long melon; An intensive study was conducted on cucurbitaceous crops during the cropping seasons in 2018 from all nine agro-climatic zones of Uttar Pradesh state, India  of both symptomatic and non-symptomatic plants using the cetyl trimethyl ammonium bromide (CTAB) method as described by Doyle and Doyle22 Table .Total RNA was extracted from 100 mg of each symptomatic and apparently healthy leaf samples using TriReagent . Total RNA was subjected to reverse-transcription polymerase chain reaction (RT-PCR) for the preparation of cDNA using the RevertAid First Strand cDNA synthesis kit  according to the manufacturer's instructions. Prepared cDNA was used for virus detection through PCR amplification using specific primers Table .36. Plasmid DNA preparations were obtained using Wizard Plus Minipreps DNA Purification (Promega Corp). Two clones were selected from each sample for sequencing and sequencing was performed at the Delhi University-South campus, New Delhi (India). Sequences were analyzed using the Basic Local Alignment Search Tool (BLAST) for the identification of virus at species level37. The top three to five hits against each database were included in the analysis for each sequence. The molecular evolutionary genetics analysis software  was employed to determine the phylogenetic relationship of the study isolates with the earlier reported viruses using the neighbour joining method38.Amplified PCR products of representative samples were purified using the QIAquick Gel Extraction Kit (Qiagen) and cloned in the pGEM-T Easy Vector System (Promega Corp.)Polerovirus, CGMMV, Potyvirus, Begomovirus and overall disease incidence in nine agro-climatic zones were prepared using Geostatistical Analyst extension in ArcGIS 9.1 software. Inverse distance weighted (IDW) method was used for interpolation. The IDW is a simple interpolation technique which is based on the assumption that the variable values at unmeasured locations are influenced most by nearby observation points and less by distant points. This technique assumes that each measured location has a local effect, which reduces with distance by means of the utilization of a power parameter39. The formula of IDW40 is given as follows:0) is the predicted value at location S0, n is the number of measured sample points surrounding the prediction location, λi is the weight assigned to each measured point, Z(Si) is the observed value at the location Si.The GPS  data and disease incidence data of the explored areas were collected to be used for mapping the epidemiological distribution and incidence proportion of viruses infecting cucurbit crops. The spatial variability maps of i0 is the distance between the prediction location (S0) and each of the measured locations (Si).The formula to calculate the weights is given as follows:41. A variable search radius with maximum of 15 sample points and minimum of 10 sample points was used.The optimal power value of IDW was estimated using root mean square error of cross-validation (RMSECV). Power value with the lowest RMSECV was selected for IDW interpolationSupplementary Table 1.Supplementary Figures.


Alzheimer’s disease (AD) substantially increases health-related costs. This study investigates direct medical costs and characterizes the caregiver burden across AD stages.N = 1998) visiting a memory clinic at Lyon University Hospital in France between 2014 and 2019 were included. Real healthcare costs  were collected for patients 1 year prior to the date of the first memory visit and 2 years following the first visit (reference year: 2019). Patients were grouped based on a clinical diagnosis of cognitively normal with a subjective cognitive complaint (SCC), all-cause mild cognitive impairment (MCI), or AD dementia. The severity of AD dementia was defined by the Mini-Mental State Examination score. Caregiver burden was measured using the mini Zarit Burden Interview. A generalized linear model was used for statistical analyses. Other patient nonmedical and indirect costs and caregiver costs were not included.This study analyzed data from the French Primary Health Insurance Fund claims database and reflected this public payer perspective. Outpatients (n = 640), MCI (n = 630), mild (n = 212), moderate (n = 256), or moderately severe/severe AD dementia (n = 260). One year after the first consultation, mean total costs were higher with progressive cognitive deficit, with little difference between dementia groups . Public hospital stays comprised the majority of direct medical costs during the first semester following the visit , regardless of the severity of cognitive deficit. Caregiver burden increased with the severity of cognitive deficit (P < .0001).The study sample included patients with SCC (Direct medical costs and caregiver burden rose from SCC to AD dementia; in patients with AD dementia, the direct medical costs increased over the 2 years after the first consultation. These results, in conjunction with data from other care components, will be critical to elucidate the potential economic value of a therapeutic intervention that slows AD progression.The online version contains supplementary material available at 10.1186/s13195-022-00969-x. Alzheimer’s disease (AD) substantially increases health-related costs in developed countries . In 2015Here, we investigated medical and nonmedical direct costs, obtained from the local branch of the French Primary Health Insurance Fund (PHIF) in patients with a clinical diagnosis of cognitively normal with a subjective cognitive complaint (SCC), all-cause mild cognitive impairment (MCI), or mild, moderate, or moderately severe/severe AD dementia. We also investigate the caregiver burden associated with AD progression.This is an ancillary study from the MEMORA cohort, which aimed to investigate the determinants associated with functional change in individuals receiving routine care . In the ClinicalTrials.gov code: NCT02302482).Patients met the following inclusion criteria: living at home or in community-based housing, having coverage by the PHIF, having ≥ 1 year of follow-up, and having a clinical diagnosis at the first visit by SCC and a Mini-Mental State Examination (MMSE) score > 26, all-cause MCI and an MMSE score < 26, or AD dementia at mild, moderate, or moderately severe/severe stages defined by an MMSE score of 20 to 26, 15 to 19, or < 14, respectively. Exclusion criteria included patients under legal protection. Information regarding the collection of individual data, with the aim of performing research on routine care, was provided to the patients. This ancillary research of the MEMORA study was considered noninterventional by the local ethics committee CPP Lyon Sud-Est IV (Comité de Protection des Personnes [Committee for the Protection of People]). No signed consent was required for participation, but patients may refuse the use of their data for research purposes. Authorization for handling personal data was granted by the representative of the French Data Protection Authority, the Commission Nationale de l’Informatique et Libertés. All procedures are in compliance with the Declaration of Helsinki. The MEMORA cohort also obtained agreements from the regional ethics committee, Comité de Protection des Personnes Sud Est III and the French Data Protection Authority  ambulatory medicine  and other ambulatory care ; (2) paramedical care from nurses, physiotherapists, and others, such as speech therapists or orthoptists; (3) pharmaceutical treatment from retail pharmacies for AD medication, psychotics/hypnotics, and other pharmaceutical treatment using the Anatomical Therapeutic Chemical classification of the World Health Organization; (4) costs related to hospital stays in geriatric wards, psychiatric wards, internal medicine wards, and surgery wards and all other costs related to hospital stays; and (5) private hospital stays. Medical transportation is the only nonmedical direct cost covered by the PHIF that was considered in this study.https://www.insee.fr/fr/information/2417794). Costs per patient were expressed as the sum of the costs per semester and per year , both overall and according to the item of interest, within the time frame of 1 year prior to the date of the first memory visit and 2 years following the first visit. Total costs for patients who died were considered in the corresponding semester. Costs related to a nursing home were not included for all groups. Notably, the PHIF applies a specific reimbursement level, which is similar nationally, for each care, act, and treatment. However, reimbursement rates may vary according to several criteria; details are publicly available at https://www.service-public.fr/particuliers/vosdroits/N418. The prices and rates taken in charge by the PHIF are listed in Supplementary Table Third, valorization of costs was presented as constant costs adjusted for the value of the euro in 2019 according to Institut Nationale de la Statistique et des Etudes Economiques  during a face-to-face interview between the caregiver and nurses during the memory consultation . A highethe Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition [Baseline characteristics were collected at the initial visit. Clinical data were collected at the memory consultation by trained nurses and administrative staff and recorded in an electronic case report form. Cognitive performance was assessed using the MMSE. The total score ranges from 0 to 30, and a lower score indicates increased cognitive impairment . Functio Edition –20. In a Edition , 22.The dates of nursing home admission and death and the treatments for comorbidities  were collected from the PHIF database. During the study, a patient was considered to have a comorbidity if they received reimbursement of treatment for one.Patient demographics were presented as mean ± standard deviation (SD) or frequency (percentage). Between-group comparisons were performed using analysis of variance or Pearson chi-squared test. Paired-wise comparisons were made using post hoc Bonferroni and Sheffé tests. The occurrence of nursing home admission and death was described according to the semester and during the study period (2014–2019).Costs per patient were described in euros per semester and per year and according to the diagnosis. Total costs were classified as medical or nonmedical and categorized according to the different origins of the costs, using means  and medians (IQR). Total costs were also described by age (≥ 80 years vs. < 80 years), gender, educational level (≥ 12 years vs. < 12 years), and treatment for comorbidities.Total costs were compared between groups by semester using generalized linear models (GLM) with gamma distribution and log link . As the t-test or the Pearson chi-squared test was used to assess patient characteristics with 3 SDs above or below average total costs. The association between diagnosis and total costs was tested when excluding outliers using GLM with log link and gamma distribution.Due to large differences between mean and median costs, patients with costs ≥ 3 SDs from the mean were identified as outliers. Outlier patient characteristics and resource utilization, as well as the implications of removing outliers from analyses, were assessed. A Student N = 1998) included in the study, 640 were cognitively normal with SCC; 630 patients had MCI of unspecified etiology; and 212, 256, and 260 patients had mild, moderate, or moderately severe/severe AD dementia, respectively (Table P < .001). The mean MMSE decreased significantly with the severity of cognitive deficit (P < .001). Similarly, the IADL score decreased with cognitive deficit severity (P < .001). However, no significant difference in IADL scores occurred between the mild AD dementia (mean IADL = 4 ± 2) and moderate AD dementia groups (mean IADL = 3.6 ± 2); a post hoc test result was 0.16. Further, the proportion of patients treated for depression (P < .001) was significantly higher in the AD dementia group compared with other groups.In patients N = 998 incluP < .001)   with the rest of the population (n = 1947) in the first semester, outliers were more frequently treated for anxiety  and diabetes mellitus  (Supplementary Table P < .0001).When comparing the patient characteristics of outliers  costs and caregiver burden significantly increased with greater progression of cognitive deficit in the SCC, MCI, and AD dementia groups. Costs increased with disease severity when assessed both before and after the initial visit. These results build on previous findings suggesting that greater cognitive impairment results in higher direct medical costs and higher caregiver impact in various settings , 24–33.Although there was a trend of increased cost with greater cognitive decline, medical costs were similar the first year after diagnosis among the different cognitive stages in AD dementia. This finding is consistent with those of previous studies that did not highlight significant differences among the severity stages in AD dementia , 34, 35 Another possible explanation is that the costs may shift from the medical sector covered by the PHIF to other social care sectors. While this study presented the direct medical costs covered by the local PHIF, previous studies have shown increased patient social care and caregiver informal care costs with the cognitive severity groups in AD dementia, while the patient healthcare costs were similar or decreased between the groups , 6, 34. Higher healthcare costs were observed in this study compared with those in the French GERAS cohort, which analyzed data from patients at memory clinics with mild, moderate, or moderately severe/severe AD dementia. These higher costs in the MEMORA cohort were observed even after accounting for differences in the years that the costs were reported . In the In our study, the majority of direct medical costs were incurred during public hospital stays, which is consistent across studies in Europe and the US , 21.Regardless of the disease stage, costs increased the year after the first consultation. Two years after the first consultation, the evolution of costs varied according to the patient group: The average total cost decreased in patients with SCC and MCI and increased in the AD dementia groups. An explanation for this result may be that another medical condition caused the patient to enter into the healthcare system initially; thus, the bulk of the costs in the first year could be associated with another medical condition unrelated to cognitive impairment. Alternatively, cognitive decline may have been the rationale to seek a memory clinic consultation, which may have led to increased care services to confirm a diagnosis and to create an individualized care or management plan .Total costs were higher for older patients and patients treated for comorbidities , which is consistent with previous studies . AdditioAs typical in costs analyses, there were some patients who accumulated particularly high costs, resulting in discrepancies between means and medians. Skewed data was accounted for using gamma function in the models, and a sensitivity analysis was performed with statistically significant, high-costs outliers removed from the sample. Results of the sensitivity analysis showed that patients with extremely high costs were generally in poorer health and had a higher incidence of anxiety, which is consistent with previous studies , 42. As In this study, direct medical and nondirect transportation costs were assessed using information from the PHIF claims database. To our knowledge, this is the first study to describe direct medical costs and medical transportation costs according to the severity of cognitive impairment in France from the perspective of the public payer and to report the costs before and after an initial memory clinic visit. Approximately 90% of the French population is covered by the PHIF; therefore, using this database permitted a reliable representation of the health spending from the public payer .Besides transportation, other nonmedical direct costs, such as home support and indirect costs, were not included in cost analyses because these costs are not covered by the PHIF. As such, nonmedical costs, like informal care time, which may represent 50% to 80% of the overall costs associated with AD depending on the study , 37, shoThe neurocognitive diagnosis was determined at the first visit; thus, it is important to consider that the evolution of costs over time may have been accompanied by the decline of patients’ health statuses, particularly cognitive and functional impairment in the AD dementia groups. It is less certain for patients in the SCC and the MCI groups, whose disease may not progress to a more advanced stage. Although the data did not allow us to show patients’ health status decline, the increase in nursing home admissions and deaths over time supports this hypothesis (Supplementary Table AD was diagnosed based on clinical and neuropsychological evaluations and was not confirmed by biomarkers. Future studies should include biomarker assessment during diagnosis. The present study is limited to findings from an older French population at 1 memory clinic; however, the patients’ characteristics were comparable to those of the multicentric GERAS cohort in France . NeverthThe economic toll of AD is debilitating and continues to grow. These results show that direct medical costs and caregiver burden rise with the severity of cognitive impairment from SCC to AD dementia; they were similar in the AD dementia groups that were determined by the MMSE. In AD dementia, the direct medical costs increased 2 years after the first consultation in a memory clinic. These results, in conjunction with data from other care components, will be critical in revealing the potential economic value of a therapeutic intervention that halts or slows the progression of AD.Additional file 1: Table S1.Additional file 2: Figure S1. Flowchart.Additional file 3: Table S2. Cost by Semester.Additional file 4: Table S3. Cost by Domain 1.Additional file 5: Table S4. Cost by Domain 2.Additional file 6: Table S5. Cost by Characteristics.Additional file 7: Table S6. Sensitivity.Additional file 8: Table S7. Characteristics of patients.Additional file 9: Table S8. Other Studies.Additional file 10: Table S9. Events.


Oz virus is a novel thogotovirus isolated from ticks that causes lethal infection in mice. We conducted serosurveillance of Oz virus infection among humans and wild mammals in Japan using virus-neutralization tests and ELISAs. Results showed that Oz virus may be naturally infecting humans and other mammalian hosts. Thogotovirus, family Orthomyxoviridae, comprises viruses that are most frequently transmitted by a variety of hard and soft tick species  captured in Yamaguchi prefecture, Japan, during 2013–2019. Because Yamaguchi prefecture is close to Ehime prefecture and the environment in Yamaguchi is very similar to that in Ehime, we used stocked samples in Yamaguchi prefecture for the first surveillance of Oz virus infection. To test for the presence of Oz virus antibodies in the serum samples, we performed a PRNT80  using Oz virus  as the secondary antibody and KPL ABTS peroxidase substrate  as the detection reagent. We measured absorbance using a spectrophotometer  with a 405 nm filter and subtracted the value of the corresponding control mock-infected cells from all values.We applied ELISA protocol used for serosurveillance of many infectious diseases  curve analysis as described elsewhere .Next, we surveyed Oz virus infection among macaques, wild boars, and sika deer in many prefectures in Japan using the established ELISA . Among 180 to detect Oz virus antibodies in humans and wild animals in Yamaguchi prefecture. The results showed that 60.5% of wild boars, a major host of A. testudinarium, and 73.7% of sika deer in Yamaguchi prefecture during 2013 and 2015 had Oz virus VN antibodies, indicating that the virus was infecting wild animals in the western part of Japan. Next, we examined wild macaques for Oz virus infection; 48% were infected, and the antibody titers were high. In addition, 2 persons who hunted wild boars and sika deer in Yamaguchi prefecture had Oz virus antibodies. These results indicate that humans and macaques are also exposed to Oz virus. First, we applied PRNTWe compared results from an ELISA, established for this study, using an Oz virus–infected cell extract for the surveillance of Oz virus infection among many mammalians, with those from the VN test to determine correlation between the 2 tests. The correlation coefficient was 0.9163 for macaques, 0.8807 for wild boars, and 0.7569 for sika deer, suggesting that the ELISA is effective for serosurveillance of Oz virus infection in samples from many animal species. However, because its sensitivity and specificity differed among animal species and values were lower for sika deer, in particular, cutoff values should be determined for each animal species. In addition, VN testing should be performed to confirm the presence of Oz virus antibodies.A. testudinarium is the major tick species that infests humans in the southern and western parts of Japan (Our nationwide surveillance of Oz virus infection in Japan indicated that many wild animals were positive for Oz virus antibodies. However, wild boars in Toyama and Tochigi prefectures did not have Oz virus antibodies, suggesting that the virus might not be distributed in the northern and eastern parts of Japan.