Optimizing the detection of emerging infections using mobility-based spatial sampling.

Timely and precise detection of emerging infections is imperative for effective outbreak management and disease control. Human mobility significantly influences the spatial transmission dynamics of infectious diseases. Spatial sampling, integrating the spatial structure of the target, holds promise as an approach for testing allocation in detecting infections, and leveraging information on individuals' movement and contact behavior can enhance targeting precision. This study introduces a spatial sampling framework informed by spatiotemporal analysis of human mobility data, aiming to optimize the allocation of testing resources for detecting emerging infections. Mobility patterns, derived from clustering point-of-interest and travel data, are integrated into four spatial sampling approaches at the community level. We evaluate the proposed mobility-based spatial sampling by analyzing both actual and simulated outbreaks, considering scenarios of transmissibility, intervention timing, and population density in cities. Results indicate that leveraging inter-community movement data and initial case locations, the proposed Case Flow Intensity (CFI) and Case Transmission Intensity (CTI)-informed spatial sampling enhances community-level testing efficiency by reducing the number of individuals screened while maintaining a high accuracy rate in infection identification. Furthermore, the prompt application of CFI and CTI within cities is crucial for effective detection, especially in highly contagious infections within densely populated areas. With the widespread use of human mobility data for infectious disease responses, the proposed theoretical framework extends spatiotemporal data analysis of mobility patterns into spatial sampling, providing a cost-effective solution to optimize testing resource deployment for containing emerging infectious diseases.

A descriptive epidemiology in syphilis in Tokyo, 2019-2022.

The number of syphilis cases in Tokyo has been found to increase in recent years. We conducted a descriptive epidemiology to elucidate the actual status of syphilis. Data on age, sex, disease stage, and presumed sexual partner of syphilis cases reported in Tokyo were tabulated and analyzed. A total of 9,419 syphilis cases have been reported between 2019 and 2022. There was a particularly sharp rise in the number of reported cases from 2021 to 2022. Comparing 2020 to 2022, the number of syphilis cases among women in their 20s, rapidly increased, more than triple. Furthermore, the number of pregnant women among syphilis cases increased in 2022. Despite the rapid increase in the number of young women with syphilis, there has been no increase in cases of congenital syphilis. One of the reasons may be that syphilis was detected early in pregnancy due to the high antenatal checkup rate in Tokyo. However, the continued incidence of syphilis among young women may increase congenital syphilis in the future. Public health strategy should include educational activities targeting high-risk populations or adolescents, early and appropriate testing, and treatment for preventing progression of syphilis.

Expert consensus on One Health for establishing an enhanced and integrated surveillance system for key infectious diseases.

China has been continuously improving its monitoring methods and strategies to address key infectious diseases (KIDs). After the severe acute respiratory syndrome epidemic in 2003, China established a comprehensive reporting system for infectious diseases (IDs) and public health emergencies. The relatively lagging warning thresholds, limited warning information, and outdated warning technology are insufficient to meet the needs of comprehensive monitoring for modern KIDs. Strengthening early monitoring and warning capabilities to enhance the public health system has become a top priority, with increasing demand for early warning thresholds, information, and techniques, thanks to constant innovation and development in molecular biology, bioinformatics, artificial intelligence, and other identification and analysis technologies. A panel of 31 experts has recommended a fourth-generation comprehensive surveillance system targeting KIDs (41 notifiable diseases and emerging IDs). The aim of this surveillance system is to systematically monitor the epidemiology and causal pathogens of KIDs in hosts such as humans, animals, and vectors, along with associated environmental pathogens. By integrating factors influencing epidemic spread and risk assessment, the surveillance system can serve to detect, predict, and provide early warnings for the occurrence, development, variation, and spread of known or novel KIDs. Moreover, we recommend comprehensive ID monitoring based on the fourth-generation surveillance system, along with a data-integrated monitoring and early warning platform and a consortium pathogen detection technology system. This series of considerations is based on systematic and comprehensive monitoring across multiple sectors, dimensions, factors, and pathogens that is supported by data integration and connectivity. This expert consensus will provides an opportunity for collaboration in various fields and relies on interdisciplinary application to enhance comprehensive monitoring, prediction, and early warning capabilities for the next generation of ID surveillance. This expert consensus will serve as a reference for ID prevention and control as well as other related activities.

Exploring the care experiences among clinical staffing during emerging infectious disease: from the COVID-19 pandemic approach.

PURPOSE: The coronavirus disease 2019 (COVID-19), one of the most significant recent emerging infectious diseases, has evolved into a global pandemic, resulting in an unprecedented public health crisis with substantial morbidity. The aim of this study was to investigate the care experiences of nursing staff during the COVID-19 pandemic. METHODS: A qualitative, exploratory interview study. This study was conducted from August 2022 to January 2023. Participants were recruited from a medical center in northern Taiwan. A purposive sampling approach was employed to select the participants, and in-depth interviews were conducted with a total of 30 individuals. The collected data were analyzed using content analysis. RESULTS: The findings of this study revealed five themes that summarized the care experiences of participants during the COVID-19 pandemic, enhanced nursing competence in pandemic mitigation, adherence to clear safety measures, effective adaptation to the stress of the "unknown," and recognition of the meaning of the pandemic mitigation experience. CONCLUSION: This study informs pandemic readiness for nurses and policy enhancement. Medical institutions and governments must prioritize policies ensuring staffing, PPE access, and mental health support. Educators and administrators should elevate on-the-job crisis management training. Future planning should cater to Taiwanese nurses' needs during unforeseen crises such as COVID-19.

Bayesian inference for the onset time and epidemiological characteristics of emerging infectious diseases.

Background: Emerging infectious diseases pose a significant threat to global public health. Timely detection and response are crucial in mitigating the spread of such epidemics. Inferring the onset time and epidemiological characteristics is vital for accelerating early interventions, but accurately predicting these parameters in the early stages remains challenging. Methods: We introduce a Bayesian inference method to fit epidemic models to time series data based on state-space modeling, employing a stochastic Susceptible-Exposed-Infectious-Removed (SEIR) model for transmission dynamics analysis. Our approach uses the particle Markov chain Monte Carlo (PMCMC) method to estimate key epidemiological parameters, including the onset time, the transmission rate, and the recovery rate. The PMCMC algorithm integrates the advantageous aspects of both MCMC and particle filtering methodologies to yield a computationally feasible and effective means of approximating the likelihood function, especially when it is computationally intractable. Results: To validate the proposed method, we conduct case studies on COVID-19 outbreaks in Wuhan, Shanghai and Nanjing, China, respectively. Using early-stage case reports, the PMCMC algorithm accurately predicted the onset time, key epidemiological parameters, and the basic reproduction number. These findings are consistent with empirical studies and the literature. Conclusion: This study presents a robust Bayesian inference method for the timely investigation of emerging infectious diseases. By accurately estimating the onset time and essential epidemiological parameters, our approach is versatile and efficient, extending its utility beyond COVID-19.

Evaluating Two Sampling Methods for Mycoplasma Bovis Diagnosis in American Bison (Bison bison).

Mycoplasma bovis is a bacterial pathogen endemic to cattle. In the early 2000s, M. bovis emerged as a cause of respiratory disease in American bison (Bison bison), causing significant morbidity and mortality. Bison herds that experience an outbreak of M. bovis are at higher risk for subsequent outbreaks, suggesting that chronic, subclinical infections can be established. Antemortem testing is therefore crucial to disease management; however, the precise sampling method to maximize detection of M. bovis in bison is unknown. We evaluated two sample types-superficial nasal swabs and deep nasopharyngeal swabs-collected from apparently healthy or symptomatic bison from January 2021 through December 2022. We used real-time PCR to detect M. bovis in 76/938 bison (8.1%) from 11 herds. For bison testing positive on at least one swab type, M. bovis was detected in 63/76 (82.8%) deep nasopharyngeal swabs and 29/73 (38.1%) superficial nasal swabs. Agreement between swabs for positive bison was 21% (n=16, kappa coefficient 0.319). We conclude that deep nasopharyngeal swabbing is more sensitive than superficial nasal swabbing for detection of M. bovis in bison and that low agreement between methods may be related to stage of infection. We further tested pooled samples by PCR and found that pooling of up to five samples can be effective to increase throughput and minimize costs. Management of wild bison relies on the ability to relocate animals to maintain gene flow and healthy populations. Sensitive and specific diagnostic tests are needed to inform decisions and minimize risk of transmission, especially from subclinical carriers. This study provides valuable insight that will inform best practices for M. bovis testing, thereby supporting the conservation of bison as healthy wildlife, which in turn promotes ecological restoration, safeguards cultural practices of Tribal Nations, and upholds the bison as a unique American icon.

Climate change, its impact on emerging infectious diseases and new technologies to combat the challenge.

ABSTRACTImproved sanitation, increased access to health care, and advances in preventive and clinical medicine have reduced the mortality and morbidity rates of several infectious diseases. However, recent outbreaks of several emerging infectious diseases (EIDs) have caused substantial mortality and morbidity, and the frequency of these outbreaks is likely to increase due to pathogen, environmental, and population effects driven by climate change. Extreme or persistent changes in temperature, precipitation, humidity, and air pollution associated with climate change can, for example, expand the size of EID reservoirs, increase host-pathogen and cross-species host contacts to promote transmission or spillover events, and degrade the overall health of susceptible host populations leading to new EID outbreaks. It is therefore vital to establish global strategies to track and model potential responses of candidate EIDs to project their future behaviour and guide research efforts on early detection and diagnosis technologies and vaccine development efforts for these targets. Multi-disciplinary collaborations are demanding to develop effective inter-continental surveillance and modelling platforms that employ artificial intelligence to mitigate climate change effects on EID outbreaks. In this review, we discuss how climate change has increased the risk of EIDs and describe novel approaches to improve surveillance of emerging pathogens that pose the risk for EID outbreaks, new and existing measures that could be used to contain or reduce the risk of future EID outbreaks, and new methods to improve EID tracking during further outbreaks to limit disease transmission.

Health activism, vaccine, and mpox discourse: BERTopic based mixed-method analyses of tweets from sexual minority men and gender diverse (SMMGD) individuals in the U.S.

Objectives: To synthesize discussions among sexual minority men and gender diverse (SMMGD) individuals on mpox, given limited representation of SMMGD voices in existing mpox literature. Methods: BERTopic (a topic modeling technique) was employed with human validations to analyze mpox-related tweets (n = 8,688; October 2020-September 2022) from 2,326 self-identified SMMGD individuals in the U.S.; followed by content analysis and geographic analysis. Results: BERTopic identified 11 topics: health activism (29.81%); mpox vaccination (25.81%) and adverse events (0.98%); sarcasm, jokes, emotional expressions (14.04%); COVID-19 and mpox (7.32%); government/public health response (6.12%); mpox symptoms (2.74%); case reports (2.21%); puns on the virus' naming (i.e., monkeypox; 0.86%); media publicity (0.68%); mpox in children (0.67%). Mpox health activism negatively correlated with LGB social climate index at U.S. state level, ρ = -0.322, p = 0.031. Conclusions: SMMGD discussions on mpox encompassed utilitarian (e.g., vaccine access, case reports, mpox symptoms) and emotionally-charged themes-advocating against homophobia, misinformation, and stigma. Mpox health activism was more prevalent in states with lower LGB social acceptance. Public Health Implications: Findings illuminate SMMGD engagement with mpox discourse, underscoring the need for more inclusive health communication strategies in infectious disease outbreaks to control associated stigma.

Paranannizziopsis spp. Infection in Wild Vipers, Europe.

We describe the detection of Paranannizziopsis sp. fungus in a wild population of vipers in Europe. Fungal infections were severe, and 1 animal likely died from infection. Surveillance efforts are needed to better understand the threat of this pathogen to snake conservation.

Persistence of IgG and neutralizing antibodies in Crimean-Congo hemorrhagic fever survivors.

The World Health Organization classified Crimean-Congo hemorrhagic fever (CCHF) as a high-priority infectious disease and emphasized the performance of research studies and product development against it. Little information is available about the immune response due to natural CCHF virus (CCHFV) infection in humans. Here, we investigated the persistence of IgG and neutralizing antibodies in serum samples collected from 61 Iranian CCHF survivors with various time points after recovery (<12, 12-60, and >60 months after disease). The ELISA results showed IgG seropositivity in all samples while a pseudotyped based neutralization assay findings revealed the presence of neutralizing antibody in 29 samples (46.77%). For both IgG and neutralizing antibodies, a decreasing trend of titer was observed with the increase in the time after recovery. Not only the mean titer of IgG (772.80 U/mL) was higher than mean neutralizing antibody (25.64) but also the IgG persistence was longer. In conclusion, our findings provide valuable information about the long-term persistence of humoral immune response in CCHF survivors indicating that IgG antibody can be detected at least 8 years after recovery and low titers of neutralizing antibody can be detected in CCHF survivors.

Disease X epidemic control using a stochastic model and a deterministic approximation: Performance comparison with and without parameter uncertainties.

BACKGROUND: The spread of infectious diseases can be modeled using deterministic or stochastic models. A deterministic approximation of a stochastic model can be appropriate under some conditions, but is unable to capture the discrete nature of populations. We look into the choice of a model from the perspective of decision making. METHOD: We consider an emerging disease (Disease X) in a closed population modeled by a stochastic SIR model or its deterministic approximation. The objective of the decision maker is to minimize the cumulative number of symptomatic infected-days over the course of the epidemic by picking a vaccination policy. We consider four decision making scenarios: based on the stochastic model or the deterministic model, and with or without parameter uncertainty. We also consider different sample sizes for uncertain parameter draws and stochastic model runs. We estimate the average performance of decision making in each scenario and for each sample size. RESULTS: The model used for decision making has an influence on the picked policies. The best achievable performance is obtained with the stochastic model, knowing parameter values, and for a large sample size. For small sample sizes, the deterministic model can outperform the stochastic model due to stochastic effects. Resolving uncertainties may bring more benefit than switching to the stochastic model in our example. CONCLUSION: This article illustrates the interplay between the choice of a type of model, parameter uncertainties, and sample sizes. It points to issues to be considered when optimizing a stochastic model.

Bovine astrovirus and its role in lymphocytic encephalitis in cattle in Ontario, Canada, 1988-2019.

Astroviruses have been found in cattle and other species with encephalitis. Our objective was to determine the frequency of neurotropic bovine astrovirus (BoAstV) in cases of encephalitis in cattle ≥ 4-mo-old. Of 56 cases of idiopathic lymphocytic encephalitis examined retrospectively (1988-2019), fixed brain from 11 cases (19%) tested positive by semi-quantitative RT-PCR for BoAstV CH13/NeuroS1. None of the control cases tested positive, including 32 with other forms of encephalitis and 40 with no neurologic disease. Most astrovirus-positive cases were 1-2-y-old, with a range of 7 mo to 7 y, and affected both beef and dairy breeds with wide geographic distribution. BoAstV-positive cases had acute onset of neurologic signs of 12 h to 7 d before death or euthanasia. Affected cattle had lymphocytic inflammation throughout the brain including cerebrum, thalamus, midbrain, cerebellum, medulla oblongata, and spinal cord, and affecting gray and white matter. Further PCR testing identified a possible cause in 9 of the 45 (20%) remaining idiopathic cases of lymphocytic encephalitis, including eastern equine encephalitis virus, Listeria monocytogenes, bovine viral diarrhea virus, bovine alphaherpesvirus 1, and ovine gammaherpesvirus 2 (malignant catarrhal fever); we found no cases of infection by West Nile virus, rabies virus, or Chlamydia spp. No cause was identified in 36 of 56 (64%) cases of lymphocytic encephalitis. We frequently identified neurotropic BoAstV in cases of lymphocytic encephalitis that had no previously identified cause. Neurotropic BoAstV infections had gone undetected for decades, but the frequency of BoAstV infections has not increased among contemporary cases.

Pathogen evolution following spillover from a resident to a migrant host population depends on interactions between host pace of life and tolerance to infection.

Changes to migration routes and phenology create novel contact patterns among hosts and pathogens. These novel contact patterns can lead to pathogens spilling over between resident and migrant populations. Predicting the consequences of such pathogen spillover events requires understanding how pathogen evolution depends on host movement behaviour. Following spillover, pathogens may evolve changes in their transmission rate and virulence phenotypes because different strategies are favoured by resident and migrant host populations. There is conflict in current theoretical predictions about what those differences might be. Some theory predicts lower pathogen virulence and transmission rates in migrant populations because migrants have lower tolerance to infection. Other theoretical work predicts higher pathogen virulence and transmission rates in migrants because migrants have more contacts with susceptible hosts. We aim to understand how differences in tolerance to infection and host pace of life act together to determine the direction of pathogen evolution following pathogen spillover from a resident to a migrant population. We constructed a spatially implicit model in which we investigate how pathogen strategy changes following the addition of a migrant population. We investigate how differences in tolerance to infection and pace of life between residents and migrants determine the effect of spillover on pathogen evolution and host population size. When the paces of life of the migrant and resident hosts are equal, larger costs of infection in the migrants lead to lower pathogen transmission rate and virulence following spillover. When the tolerance to infection in migrant and resident populations is equal, faster migrant paces of life lead to increased transmission rate and virulence following spillover. However, the opposite can also occur: when the migrant population has lower tolerance to infection, faster migrant paces of life can lead to decreases in transmission rate and virulence. Predicting the outcomes of pathogen spillover requires accounting for both differences in tolerance to infection and pace of life between populations. It is also important to consider how movement patterns of populations affect host contact opportunities for pathogens. These results have implications for wildlife conservation, agriculture and human health.

The emergence of Rocky Mountain spotted fever in the southwestern United States and northern Mexico requires a binational One Health approach.

Rocky Mountain spotted fever (RMSF) is an international and quintessential One Health problem. This paper synthesizes recent knowledge in One Health, binational RMSF concerns, and veterinary and human medical perspectives to this fatal, reemerging problem. RMSF, a life-threatening tick-borne disease caused by the bacterium Rickettsia rickettsii, emerged during the first decade of the 21st century in impoverished communities in the southwestern US and northern Mexico. Lack of an index of suspicion, delay in diagnosis, and delayed initiation of antibiotic treatment contribute to fatality. Campaigns targeting dog neutering, restraint to residents' properties, and on-dog and on-premises treatment with acaricides temporarily reduce prevalence but are often untenable economically. Contemporary Mexican RMSF is hyperendemic in small communities and cities, whereas epidemics occur in the western US primarily in small tribal communities. In in both locations, the epidemics are fueled by free-roaming dogs and massive brown dog tick populations. In the US, RMSF has a case fatality rate of 5% to 7%; among thousands of annual cases in Mexico, case fatality often exceeds 30%.1,2 Numerous case patients in US border states have recent travel histories to northern Mexico. Veterinarians and physicians should alert the public to RMSF risk, methods of prevention, and the importance of urgent treatment with doxycycline if symptomatic. One Health professionals contribute ideas to manage ticks and rickettsial disease and provide broad education for the public and medical professionals. Novel management approaches include vaccine development and deployment, acaricide resistance monitoring, and modeling to guide targeted dog population management and other interventions.

Update on Mpox: What the Primary Care Clinician Should Know.

Mpox is a viral infection, which primarily caused sporadic outbreaks in West and Central Africa until causing a global epidemic in 2022. The disease has disproportionately affected people with human immunodeficiency virus and men who have sex with men. Transmission is through close physical contact, including sexual contact. Infection presents with a characteristic rash, with frequent anogenital involvement-polymerase chain reaction of skin lesions is diagnostic. Vaccination is available for primary prevention and postexposure prophylaxis. Treatment consists of supportive care, with antiviral medications available via clinical trials and/or for patients with severe disease.

Value of information dynamics in Disease X vaccine clinical trials.

BACKGROUND: Solutions have been proposed to accelerate the development and rollout of vaccines against a hypothetical disease with epidemic or pandemic potential called Disease X. This may involve resolving uncertainties regarding the disease and the new vaccine. However the value for public health of collecting this information will depend on the time needed to perform research, but also on the time needed to produce vaccine doses. We explore this interplay, and its effect on the decision on whether or not to perform research. METHOD: We simulate numerically the emergence and transmission of a disease in a population using a susceptible-infected-recovered (SIR) compartmental model with vaccination. Uncertainties regarding the disease and the vaccine are represented by parameter prior distributions. We vary the date at which vaccine doses are available, and the date at which information about parameters becomes available. We use the expected value of perfect information (EVPI) and the expected value of partially perfect information (EVPPI) to measure the value of information. RESULTS: As expected, information has less or no value if it comes too late, or (equivalently) if it can only be used too late. However we also find non trivial dynamics for shorter durations of vaccine development. In this parameter area, it can be optimal to implement vaccination without waiting for information depending on the respective durations of dose production and of clinical research. CONCLUSION: We illustrate the value of information dynamics in a Disease X outbreak scenario, and present a general approach to properly take into account uncertainties and transmission dynamics when planning clinical research in this scenario. Our method is based on numerical simulation and allows us to highlight non trivial effects that cannot otherwise be investigated.

Human Tick-Borne Diseases and Advances in Anti-Tick Vaccine Approaches: A Comprehensive Review.

This comprehensive review explores the field of anti-tick vaccines, addressing their significance in combating tick-borne diseases of public health concern. The main objectives are to provide a brief epidemiology of diseases affecting humans and a thorough understanding of tick biology, traditional tick control methods, the development and mechanisms of anti-tick vaccines, their efficacy in field applications, associated challenges, and future prospects. Tick-borne diseases (TBDs) pose a significant and escalating threat to global health and the livestock industries due to the widespread distribution of ticks and the multitude of pathogens they transmit. Traditional tick control methods, such as acaricides and repellents, have limitations, including environmental concerns and the emergence of tick resistance. Anti-tick vaccines offer a promising alternative by targeting specific tick proteins crucial for feeding and pathogen transmission. Developing vaccines with antigens based on these essential proteins is likely to disrupt these processes. Indeed, anti-tick vaccines have shown efficacy in laboratory and field trials successfully implemented in livestock, reducing the prevalence of TBDs. However, some challenges still remain, including vaccine efficacy on different hosts, polymorphisms in ticks of the same species, and the economic considerations of adopting large-scale vaccine strategies. Emerging technologies and approaches hold promise for improving anti-tick vaccine development and expanding their impact on public health and agriculture.

Development of Emerging Infectious Diseases Preventive Health Behavior (EID-PHB) Scale and Validation of the Complex Models.

Introduction: Emerging Infectious Diseases are one of the world's leading causes of death, and preventive measures must be implemented to minimize human casualties. Research on preventive behavior relies on the preventive behavior scale and it has an impact on the findings. Purpose: This study aimed to develop an Emerging Infectious Diseases Preventive Health Behavior (EID-PHB) Scale and verify the validity and reliability of the complex models. Methods: Initial items were generated through a literature review and interviews, based on the proposed conceptual framework of transmission-based precautions. 14 experts reviewed the preliminary items for content validity and 20 adults for face validity. Data were collected online by a research company from April 28 to May 3, 2023. A total of 533 participants completed the survey, and subjects were assigned through simple random sampling. The first sample (n = 330) was used for item analysis and Exploratory Factor Analysis (EFA), and the second sample (n = 203) was used for Confirmatory Factor Analysis (CFA), convergent validity, discriminant validity, criterion validity, and reliability. The test-retest reliability was assessed in 34 adults. Results: The final instrument derived six components (droplet, contact, airborne, bloodborne, environmental prevention, and psychological coping), nine indicators, and 34 items. The CFA indicated that all the complex models had a good fit and the integrated factors were confirmed through validity tests. The Cronbach's alpha for the 34 items was 0.92, and the criterion validity was verified (r = 0.85, p < 0.001). Conclusion: The EID-PHB is a valid and reliable tool that can be used to determine preventive behaviors against emerging infectious diseases. This tool is expected to provide a conceptual framework for future research, contribute to the clinical practice and education, and establish strategies and policies for improving individual and public health.