Standard epidemiological models rely on physical mobility and policy indicators, which fail when physical movement decouples from actual transmission risk. To address this, we establish a unified theoretical framework governed by risk-mediated transmission dynamics. Rather than treating societal responses as independent phenomenological proxies, we embed the underlying risk-avoidance tendency directly into the transmission mechanism. This is parsimoniously formulated via the Weber-Fechner law as a logarithmically scaled response to disease incidence, alongside behavioral fatigue. Analyzing multi-regional COVID-19 data, our risk-mediated model significantly outperforms traditional frameworks. While mobility metrics merely track movement volume, our approach directly captures unobserved qualitative contact changes, such as mask-wearing. By integrating this intrinsic behavioral principle, our framework provides a robust, mobility-independent baseline for predicting future epidemic trajectories.

OBJECTIVES:To compare secondary severe acute respiratory syndrome coronavirus 2 transmission detected through reverse transcription polymerase chain reaction (RT-PCR) screening in childcare and school-aged settings during the Omicron wave. METHODS:We analyzed Okinawa School PCR Project events from January 1 to March 11, 2022, in which secondary cases were ascertained through school-based RT-PCR screening conducted after the last exposure. Index cases were classified as child/student or teacher/staff. Secondary cases were defined as RT-PCR-confirmed infections detected through school-based screening. We estimated the proportion of events with ≥1 secondary case and the mean number of secondary cases per event (Revent). RESULTS:Among 897 events with known index case role, 73.1% detected no secondary cases. In nurseries/kindergartens, secondary cases were detected in 32.3% of teacher/staff-index events (Revent: 0.62; 95% confidence interval: 0.53-0.72), compared with 12.8% in elementary and secondary schools (Revent: 0.15; 95% confidence interval: 0.06-0.33). No secondary infections were detected after teacher/staff-index events in junior high (n = 11) or high schools (n = 6). CONCLUSIONS:Childcare worker-index events in nurseries and kindergartens generated secondary cases in ≈30% of events, whereas teacher/staff-index events in elementary and secondary schools infrequently generated secondary cases under mitigation measures. Prioritizing screening and prevention resources toward childcare workers may improve efficiency when diagnostic capacity is constrained.

The Asian lineage of H5 highly pathogenic avian influenza (HPAI) virus is causing a large number of outbreaks globally. This study was conducted to evaluate the current Japanese emergency surveillance policy of HPAI in poultry farms. Under the current regulation, five chickens, including three dead chickens if available, are sampled from neighbor non-notified poultry farms of an outbreak farm.A susceptible-exposed-infectious-death mathematical model describing HPAI transmission within a broiler farm was developed. Using the model, sample sizes of live and dead chickens, respectively, to detect an HPAI outbreak of the virus with high, moderate, and low transmission coefficients and progression rates from infectious to death, at 9, 14, and 24 days after starting the outbreak, with detection sensitivities from 50% to 99% were calculated using deterministic models.Sampling of five live chickens allowed outbreak detection with a detection sensitivity of 95% only 24 days post-infection for a virus with high transmission and a moderate or low progression rate from infectious to death. Cumulative mortality increased more than 10% at 9 days post-infection for a virus with a high transmission rate. However, sampling of three sick or dead chickens was successful in detecting an outbreak only on or after 14 days post-infection for such a virus.The results suggested that the current sampling framework for HPAI emergency surveillance does not provide a high detection sensitivity in most scenarios, especially in the early stage of an HPAI outbreak. It is important to maintain a high alert in detection and reporting from poultry farms, and the design of emergency surveillance requires careful discussions.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has continuously evolved since its emergence in the human population in 2019. As of 1st August 2025, more than 1,700 Omicron subvariants have been designated by the Pango nomenclature system. The Pango nomenclature system designates a new lineage based on genetic and epidemiological information of SARS-CoV-2 strains. However, there is a possibility that strains that have similar genetic backgrounds and the same phenotype are given different Pango lineage names. In this paper, we propose a new algorithm, called FindPart-w, which can identify groups of viral lineages that share the same relative effective reproduction numbers. We introduced a new lineage replacement model, called the constrained RelRe model, which constrains groups of lineages to have the same relative effective reproduction numbers. The FindPart-w algorithm searches the equality constraints that minimise the Akaike Information Criterion of constrained RelRe models. Using hypothetical observation count data created by simulation, we found that the FindPart-w algorithm can identify groups of lineages having the same relative effective reproduction number in a practical computational time. Applying FindPart-w to actual real-world data of time-stamped lineage counts from the United States, we found that the Pango lineage nomenclature system may have given different lineage names to SARS-CoV-2 strains even if they have the same relative effective reproduction number and similar genetic backgrounds. In conclusion, this study showed that viruses that had the same relative effective reproduction number were identifiable from temporal count data of viral sequences. These findings will contribute to the future development of lineage designation systems that consider both genetic backgrounds and transmissibilities of lineages. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement The development of the programs used in this work was supported by the Japan Agency for Medical Research and Development (grant numbers JP24fk0108685, JP24wm0125008). Kimihito I. received funding for JSPS KAKENHI (21H03490). R.M. was supported by the Ministry of Education, Culture, Sports, Science, and Technology (MEXT) scholarship, from the Government of Japan. The funders had no role of influence in the study design, data collection and analysis, decision to publish, or drafting and preparation of the manuscript. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The values used to build Figure 2, raw values used to get statistics in Table 1, Table 2, Table 3, and Table 4, the metadata of sequences downloaded from GISAID database can be found in the supplementary tables. The program code of the FindPart-w algorithm can be downloaded from our GitHub repository https:/github.com/musonda-richard/FindPart-w/. The dataset of the actual sequence counts from the United States, which were used to create Table 5, Table 6, and Table 7, are included in the same GitHub repository.

In April 2025, equine influenza re-emerged in Japan for the first time in 17 years, resulting in an outbreak at a horse racecourse for Ban'ei racing, a unique form of horse racing in which draft horses pull heavy sleds. This study aimed to describe the epidemiological characteristics of the outbreak and identify individual- and management-level factors associated with equine influenza cases in order to develop improved control programs. A retrospective analysis was conducted using clinical records reported to the racecourse authority between April 21 and June 18, 2025. Cases were defined based on one or more of the following clinical signs: fever, coughing, and nasal discharge. Generalized linear mixed models were used to assess associations between case status and age, sex, and trainer group. As individual-level spatial information was incomplete, multiple imputation was performed using trainer group-level spatial information to incorporate the effect of each horse's spatial location. A total of 438 out of 856 horses housed in the racecourse met the case definition (attack rate: 51.2%). Two-year-old horses showed significantly higher odds of being classified as a case than older horses, and females had higher odds than males. Evidence of clustering was observed at the trainer-group level (intraclass correlation coefficient = 0.136; 95% confidence interval: 0.044-0.152). Spatial effects were limited, although certain high-traffic areas suggested an elevated risk of being classified as a case. The outbreak demonstrated marked heterogeneity by age, sex, and management unit. The higher frequency of cases among two-year-old horses may reflect differences in vaccination history, although age-related susceptibility cannot be excluded. These findings highlight the importance of understanding age-related risk factors and optimizing vaccination strategies to mitigate future EI outbreaks in this high-density racing setting. Targeted biosecurity measures may also be important for more effective disease control.

Objectives:: COVID-19 outbreaks in residential facilities for the elderly can have severe consequences; however, effective preventive strategies remain under-evaluated. This study aimed to identify actionable, facility-level factors associated with outbreak size in such facilities in Okinawa, Japan. Methods:: We conducted a questionnaire-based cross-sectional study of 78 residential facilities for the elderly that experienced confirmed COVID-19 outbreaks between April and June 2022. Facility-level data on infection-control practices, outbreak characteristics, and staff testing approaches were analyzed using negative binomial regression models to quantify factors associated with outbreak size. Results:: Outbreaks detected via contact-based testing of staff were significantly smaller than those detected through routine staff reverse transcription polymerase chain reaction screening (adjusted relative risk [aRR]: 0.11; 95% confidence interval [CI]: 0.03-0.37). Resident mask-wearing was associated with smaller outbreak sizes (aRR: 0.40; 95% CI: 0.16-0.99). Routine screening identified only 16.7% of staff index cases despite being widely implemented, suggesting limitations in effectiveness. Conclusions:: Risk-based, exposure-driven testing appears markedly more effective than fixed-interval screening for limiting outbreak size in residential facilities for the elderly. Implementation should consider both operational feasibility and support systems for frontline staff.

Bait vaccination against classical swine fever virus (CSFV) among wild boar in Japan started in 2019 and has continued so far. While the proportion of immune individuals increased in the early phase of the CSFV epidemic, this proportion tended to decrease in some regions, even after the subsequent vaccination. Turnover of wild boar populations can reduce the proportion of immune individuals; however, the decrease was also observed among adult wild boar during the season when the influence of turnover was negligible. Waning immunity is hypothesized as an alternative mechanism. This study aimed to test the hypothesis of waning immunity and estimate the waning rate among wild boar. A mathematical model describing CSFV transmission dynamics, host population dynamics, effect of vaccination, and waning immunity was constructed. We also constructed a model without waning immunity. The two models were fitted to a time-series of the proportion of recovered/vaccinated animals (i.e., ELISA-positive and PCR-negative) among adult wild boar in Gifu, Japan, assuming that the influence of turnover was negligible from July to November. The hypothesis that immunity against CSFV can wane is accepted; the model with waning immunity showed a significantly better fit compared to another model. The time until ELISA test results became negative after recovery/vaccination was estimated to be 26.6 weeks. Our results imply that the acquired immunity against CSFV and bait vaccination wanes over time. The level of herd immunity after vaccination against CSFV should be evaluated taking the waning immunity into account.

We aimed to understand to what extent knowledge of the prevalence of one sexually transmitted infection (STI) can predict the prevalence of another STI, with application for men who have sex with men (MSM). An individual-based simulation model was used to study the concurrent transmission of HIV, HSV-2, chlamydia, gonorrhea, and syphilis in MSM sexual networks. Using the model outputs, 15 multiple linear regression models were conducted for each STI prevalence, treating the prevalence of each as the dependent variable and the prevalences of up to four other STIs as independent variables in various combinations. For HIV, HSV-2, chlamydia, gonorrhea, and syphilis, the proportion of variation in prevalence explained by the 15 models ranged from 34.2% to 88.3%, 19.5%-70.5%, 43.7%-82.9%, 48.7%-86.3%, and 19.5%-67.2%, respectively. Including multiple STI prevalences as independent variables enhanced the models' predictive power. Gonorrhea prevalence was a strong predictor of HIV prevalence, while HSV-2 and syphilis prevalences were weak predictors of each other. Propagation of STIs in sexual networks reveals intricate dynamics, displaying varied epidemiological profiles while also demonstrating how the shared mode of transmission creates ecological associations that facilitate predictive relationships between STI prevalences. (c) 2024 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/).

OBJECTIVES:Quantifying the durability of natural immunity is essential for understanding infectious disease dynamics and informing public health strategies. Existing methods typically require detailed longitudinal data rarely available in real-world settings. This study introduces a novel surveillance-based approach to estimate immune waning using routine testing data, providing a practical complement to data-intensive designs. STUDY DESIGN:Mathematical modeling. METHODS:The method estimates protection against reinfection as a function of time since prior infection and was applied to national SARS-CoV-2 testing data from Qatar to evaluate the durability of immunity following pre-omicron and omicron infections against homologous reinfection. Waning curves were fitted using Gompertz functions and validated against published estimates. RESULTS:Application of the method demonstrated distinct patterns in the durability of natural immunity. Pre-omicron infections were associated with strong and sustained protection against reinfection, with minimal evidence of waning over the follow-up period. In contrast, protection following omicron infection, while initially high, declined rapidly in the ensuing months and was largely diminished within approximately one year. The estimated waning immunity curves closely aligned with published estimates, supporting the validity of the introduced approach. CONCLUSIONS:This method offers a practical and adaptable approach for estimating waning immunity, suitable for use across different settings and infectious pathogens.

Lumpy skin disease (LSD) is a transboundary emerging disease of cattle and water buffaloes that threatens the livestock industry globally. Japan experienced its first outbreak in November 2024. This study aimed to describe the spatial and temporal characteristics of this outbreak and estimate the transmissibility using a mathematical model for within-farm transmission. The first and second cases were confirmed on dairy farms in Itoshima City, Fukuoka Prefecture, southern Japan, on November 6, 2024. Twenty-two farms were confirmed during this outbreak, with 17 cases in Itoshima City and the other two municipalities in Fukuoka Prefecture. The third case occurred in Kumamoto Prefecture on November 8, 2024, and was linked to the long-distance movement of potentially infected cattle via the livestock market from the first case on October 18, 2024. Two additional cases were detected near the third case. Control measures included isolation and voluntary culling of infected cattle; voluntary movement restrictions on infected, suspected, and apparently healthy cattle on the same premises; and voluntary suspension of the raw milk and semen shipments from infected and suspected animals. These measures were voluntary; however, no violations were reported. Vector control was achieved with insecticides and insect-proof netting. Voluntary vaccination was conducted within a 20 km radius of affected farms in Fukuoka Prefecture. Mathematical modeling of within-farm transmission dynamics revealed a transmission rate of 0.0031 (95% CI: 0.002-0.0044) per day. The basic reproduction number was 3.51 (95% CI: 2.26-4.98) based on a herd size of 49 and an infectious period of 23.1 days. Although the outbreak was geographically limited, this study highlights key epidemiological features of LSD, including its high transmission rate and long-distance transmission via cattle movement. Japan has a persisting LSD virus (LSDV)incursion risk due to recent outbreaks in Asia. Strengthening preparedness, including awareness among farmers and veterinarians, emergency vaccination plans, vector control, traceability, and quarantine protocols for cattle movement, is essential to mitigate future outbreaks.

Objectives:During the COVID-19 pandemic, airport-based measures, such as fever screening and polymerase chain reaction (PCR) testing were implemented in Japan. Okinawa Prefecture introduced a voluntary airport PCR testing program for domestic travelers at Naha Airport (OKA). Their indirect behavioral effects on travelers remain underexplored. This study aims to describe self-reported pre-travel health awareness among participants in this program. Methods:In February-March 2021, we conducted a cross-sectional questionnaire survey among Naha Airport PCR test Project (NAPP) participants (n = 4545; March subset n = 1859). The survey assessed demographics, travel purpose, awareness of airport screening (fever screening and PCR testing), pre-travel health awareness, COVID-19 history, and symptoms. Logistic regression evaluated factors associated with self-reported symptoms in the March subset. Results:Among respondents aware of fever screening and PCR testing, 94.1% and 96.4%, respectively, reported increased attention to their physical condition before travel. Overall, 3.9% reported symptoms, mainly mild respiratory complaints. The proportion symptomatic varied by reason for testing; workplace-mandated testers reported fewer symptoms than family-motivated testers (adjusted odds ratio 0.36, 95% confidence interval 0.15-0.78). Conclusions:Awareness of voluntary airport screening measures was associated with greater self-reported pre-travel health awareness among voluntary testers. These findings may inform context-specific behavioral strategies aimed at promoting health-conscious travel during infectious disease outbreaks.

Understanding the changes in human mobility in response to outbreaks is important for controlling emerging infectious disease outbreaks. This requires an understanding of the mechanism of human behavioural response as well as the timing of decisions for future mobility. However, most human mobility data only record the executed mobility that results from decision-making, and not the timing of decisions. In this study, we used accommodation reservation data to extract the decision-making process in response to the changing epidemic situation and compared it with data on executed mobility, ‘stay time’ in workplaces and stay time in places other than home or workplaces to clarify when people decide on their mobility. We confirmed that the decision-making process estimated from accommodation reservation data can accurately predict human mobility. The decision-making process estimated from accommodation reservation data was more strongly associated with stay time in places other than home or workplaces than stay time in workplaces. Furthermore, the comparison between the estimated decision-making process and mobility data quantitatively revealed that mobility was the result of integrating two types of decisions made in recent weeks (within two and five weeks for mobility to workplaces and places other than home or workplaces, respectively) and previous weeks.

ABSTRACT Historically, antibody reactivity to pathogens and vaccine antigens has been evaluated using serological measurements of antigen-specific antibodies. However, it is difficult to evaluate all antibodies that contribute to various functions in a single assay, such as the measurement of the neutralizing antibody titer. Bulk antibody repertoire analysis using next-generation sequencing is a comprehensive method for analyzing the overall antibody response; however, it is unreliable for estimating antigen-specific antibodies due to individual variation. To address this issue, we propose a method to subtract the background signal from the repertoire of data of interest. In this study, we analyzed changes in antibody diversity and inferred the heavy-chain complementarity-determining region 3 (CDRH3) sequences of antibody clones that were selected upon influenza virus infection in a mouse model using bulk repertoire analysis. A decrease in the diversity of the antibody repertoire was observed upon viral infection, along with an increase in neutralizing antibody titers. Using kernel density estimation of sequences in a high-dimensional sequence space with background signal subtraction, we identified several clusters of CDRH3 sequences induced upon influenza virus infection. Most of these repertoires were detected more frequently in infected mice than in uninfected control mice, suggesting that infection-specific antibody sequences can be extracted using this method. Such an accurate extraction of antigen- or infection-specific repertoire information will be a useful tool for vaccine evaluation in the future. IMPORTANCE As specific interactions between antigens and cell-surface antibodies trigger the proliferation of B-cell clones, the frequency of each antibody sequence in the samples reflects the size of each clonal population. Nevertheless, it is extremely difficult to extract antigen-specific antibody sequences from the comprehensive bulk antibody sequences obtained from blood samples due to repertoire bias influenced by exposure to dietary antigens and other infectious agents. This issue can be addressed by subtracting the background noise from the post-immunization or post-infection repertoire data. In the present study, we propose a method to quantify repertoire data from comprehensive repertoire data. This method allowed subtraction of the background repertoire, resulting in more accurate extraction of expanded antibody repertoires upon influenza virus infection. This accurate extraction of antigen- or infection-specific repertoire information is a useful tool for vaccine evaluation.

Revealing interactions between ticks and wild animals is vital for gaining insights into the dynamics of tick-borne pathogens in the natural environment. We aimed to elucidate the factors that determine tick infestation in wild animals by investigating ticks on invasive raccoons (Procyon lotor) in Hokkaido, Japan. We first examined the composition, intensity, and seasonal variation of ticks infesting raccoons in six study areas in Hokkaido from March 2022 to August 2023. In one study area, ticks infesting tanukis (raccoon dog, Nyctereutes procyonoides albus) were collected in May to July in both 2022 and 2023, and questing ticks were collected from the vegetation by flagging every other week in the same period. Next, we screened 17 environmental and host variables to determine factors that affect the number of ticks infesting raccoons using generalized linear (mixed) models. From 245 raccoons, we identified a total of 3,917 ticks belonging to eight species of two genera: the most prominent species were Ixodes ovatus (52.9 %), followed by Haemaphysalis megaspinosa (14.4 %), Ixodes tanuki (10.6 %), and Ixodes persulcatus (9.5 %). Ixodes ovatus was also predominant among questing ticks and ticks infesting tanukis. Although I. tanuki was frequently collected from raccoons and tanukis, it was rarely collected in the field. The variables that significantly affected the infestation on raccoons differed by genus, species and developmental stage of the tick. For instance, the infestation of adult I. ovatus was significantly affected by four variables: night-time temperature during nine days before capturing the raccoon, the size of forest area around the capture site, sex of the raccoon, and sampling season. The first two variables were also responsible for the infestation on raccoons of almost all species and stages of ticks. Our study revealed that the number and composition of ticks infesting raccoons can be affected not only by landscape of their habitats but also by weather conditions in several days before capturing.

The impact of infectious diseases on host populations is often not quantified because it is difficult to observe the host population and infectious disease dynamics. To address this problem, we developed a state-space model to simultaneously estimate host population and disease dynamics using wildlife rescue data. Using this model, we aimed to quantify the impact of sarcoptic mange on a Japanese raccoon dog population by estimating the change in their relative population size. We classified the status of rescued raccoon dogs into four categories: i) rescued due to infection with mange, ii) rescued due to traffic accidents without mange, iii) rescued due to traffic accidents with mange, and iv) rescued due to causes other than traffic accidents or mange. We modelled the observation process for each category and fitted the model to the reported number of raccoon dogs rescued between 1990 and 2010 at three wildlife rescue facilities in Kanagawa Prefecture, Japan. The mortality rate induced by mange was estimated to be 1.09 (95% credible interval (CI): 0.47-1.72) per year. The estimated prevalence of sarcoptic mange ranged between 4 and 80% in the study period. When a substantial prevalence of mange was observed (1995-2002), the host population size decreased by 91.2% (95% credible intervals: 86.3-94.7). We show that the impact of infectious disease outbreak on the wildlife population can be estimated from the time-series data of wildlife rescue events due to multiple causes. Our estimates suggest that sarcoptic mange triggered a substantial decrease in the Japanese wild raccoon dog populations.

During the COVID-19 pandemic, widespread school closures were implemented globally based on the assumption that transmission among children in the school environment is common. However, evidence regarding secondary infection rates by school type and level of contact is lacking. Our study estimated the frequency of SARS-CoV-2 infection in school settings by examining the positivity rate according to school type and level of contact by using data from a large-scale school-based PCR project conducted in Okinawa, Japan, during 2021-2022. Our results indicate that, despite detection of numerous positive cases, the average number of secondary infections remained relatively low at ≈0.5 cases across all types of schools. Considering the profound effects of prolonged closures on educational access, balancing public health benefits against potential long-term effects on children is crucial.

White spot syndrome virus (WSSV) triggers white spot disease and high mortality in farmed shrimp. To control the WSSV epidemic, understanding its dynamics through epidemiological analysis is essential. However, measuring the mortality by WSSV infection is difficult due to the rapid increase in mortality and the availability of epidemiological data on WSSV epidemics in aquaculture ponds is limited. In this study, we conducted an epidemiological analysis using field data collected during the early phase of the outbreak to estimate the complete picture of the outbreak. Thereafter, we constructed a mathematical model describing the WSSV epidemic in aquaculture ponds and fitted our model with data on WSSV outbreaks among kuruma shrimp (Penaeus japonicus) farmed in 40,000 m2 aquaculture ponds in Japan. We estimated the basic reproduction number (R0), which measures the average number of secondary infections by a single infected individual, i.e. the transmissibility of a pathogen. The estimated R0 per pond was large (3.21-4.56), suggesting that with no intervention WSSV outbreaks will likely result in large final epidemic size, with 98.0-99.7% of entire population infected by the virus. Once WSSV infection is detected in a pond, urgent intervention, such as enhanced removal of dead shrimp and harvesting all farmed shrimps immediately, is required.

This review article will present a comprehensive examination of the use of modeling, spatial analysis, and geographic information systems (GIS) in the surveillance of viruses in wastewater. With the advent of global health challenges like the COVID-19 pandemic, wastewater surveillance has emerged as a crucial tool for the early detection and management of viral outbreaks. This review will explore the application of various modeling techniques that enable the prediction and understanding of virus concentrations and spread patterns in wastewater systems. It highlights the role of spatial analysis in mapping the geographic distribution of viral loads, providing insights into the dynamics of virus transmission within communities. The integration of GIS in wastewater surveillance will be explored, emphasizing the utility of such systems in visualizing data, enhancing sampling site selection, and ensuring equitable monitoring across diverse populations. The review will also discuss the innovative combination of GIS with remote sensing data and predictive modeling, offering a multi-faceted approach to understand virus spread. Challenges such as data quality, privacy concerns, and the necessity for interdisciplinary collaboration will be addressed. This review concludes by underscoring the transformative potential of these analytical tools in public health, advocating for continued research and innovation to strengthen preparedness and response strategies for future viral threats. This article aims to provide a foundational understanding for researchers and public health officials, fostering advancements in the field of wastewater-based epidemiology.

The outbreak of infectious diseases in swine, such as classical swine fever (CSF), has become a significant concern in the pig-farming industry. In Japan, after the re-emergence of CSF in 2018, farms are now exposed to the risk of transmission from infected wild boar and CSF-contaminated farms. This study aimed to identify biosecurity measures that were effective for the prevention of CSF introduction into farms during the period from the beginning of the CSF epidemic to the implementation of a vaccination campaign for domestic pigs at risk. The probability of virus introduction was assumed to be increased by the elevated risk from CSF-infected wild boar and infected farms around the farm. The risk from infected wild boar was represented by the prevalence of CSF in wild boar or the occupancy of 1-km grid cells with infected wild boar within 10-km radii from a pig farm and the occurrence of CSF outbreaks on neighboring farms. Conversely, the probability of virus introduction was assumed to decrease in response to on-farm biosecurity measures being implemented on each farm. The implementation of biosecurity measures on the farms and farm attributes were obtained through a questionnaire survey. Analyses were performed on each farm under the weekly situations where infected wild boar were both absent and present in the vicinity using a binomial generalized linear model. On farms where infected wild boar were not present around farms, daily washing and disinfecting of work clothing in pig houses was identified as the main measure to reduce the risk of CSF introduction into farms. On farms with infected wild boar in the vicinity, the absence of public roads on the farm and preventing wildlife intrusion into the areas where pig carcasses were stored were demonstrated to be effective in preventing CSF introduction. Based on the assumption that strict and comprehensive biosecurity measures are required to prevent CSF introduction, the implementation of these potentially effective measures is worth being prioritized.

Yezo virus (YEZV) is an emerging tick-borne virus that causes acute febrile illness. It has been continuously reported in patients and ticks in Japan and China since its first identification in Hokkaido, Japan. While serological tests have demonstrated that YEZV infections are prevalent in wild animals, such as raccoons (Procyon lotor), the determinants of infection in wild animals remain largely unknown. We examined the prevalence of YEZV in invasive raccoons, native tanukis (raccoon dogs, Nyctereutes procyonoides albus), and ticks in six study areas in Hokkaido between 2018 and 2023 to identify ecological factors underlying YEZV infection in wild animals. YEZV RNA fragments were detected in 0.22% of the 1,857 questing ticks. Anti-YEZV antibodies were detected in 32 of the 514 (6.2%) raccoon serum samples and in 5 of the 40 (12.5%) tanuki serum samples. Notably, the seroprevalence in raccoons varied significantly in one of the study areas over the years, that is, 0.0%, 60.0%, and 28.6% in 2021, 2022, and 2023, respectively, implying the temporary emergence of YEZV microfoci. By analyzing the tick load and YEZV seropositivity in raccoons in a field-based setting, we found a positive correlation between adult Ixodes ovatus load and YEZV-antibody positivity, highlighting the importance of I. ovatus in YEZV infection in wild animals. We also explored the environmental and host factors influencing YEZV seropositivity in raccoons and tanukis and found that landscape factors, such as the size of forest area around the trap site, were crucial for YEZV seropositivity in these animals. The significant variables for YEZV seropositivity in raccoons were partially different from those affecting tick infestation intensity in raccoons. The present results extend our understanding of tick-borne virus circulation in the field, emphasizing the unique ecology of the emerging YEZV.