Characterization of differential susceptibility and differential infectivity epidemic models.

Heterogeneity in susceptibility and infectivity is a central issue in epidemiology. Although the latter has received some attention recently, the former is often neglected in modeling of epidemic systems. Moreover, very few studies consider both of these heterogeneities. This paper is concerned with the characterization of epidemic models with differential susceptibility and differential infectivity under a general setup. Specifically, we investigate the global asymptotic behavior of equilibria of these systems when the network configuration of the Susceptible-Infectious interactions is strongly connected. These results prove two conjectures by Bonzi et al. (J Math Biol 62:39-64, 2011) and Hyman and Li (Math Biosci Eng 3:89-100, 2006). Moreover, we consider the scenario in which the strong connectivity hypothesis is dropped. In this case, the model exhibits a wider range of dynamical behavior, including the rise of boundary and interior equilibria, all based on the topology of network connectivity. Finally, a model with multidirectional transitions between infectious classes is presented and completely analyzed.

Threshold behavior and exponential ergodicity of an sir epidemic model: the impact of random jamming and hospital capacity.

This article uses hospital capacity to determine the treatment rate for an infectious disease. To examine the impact of random jamming and hospital capacity on the spread of the disease, we propose a stochastic SIR model with nonlinear treatment rate and degenerate diffusion. Our findings demonstrate that the disease's persistence or eradication depends on the basic reproduction number [Formula: see text]. If [Formula: see text], the disease is eradicated with a probability of 1, while [Formula: see text] results in the disease being almost surely strongly stochastically permanent. We also demonstrate that if [Formula: see text], the Markov process has a unique stationary distribution and is exponentially ergodic. Additionally, we identify a critical capacity which determines the minimum hospital capacity required.

The impact of household structure on disease-induced herd immunity.

The disease-induced herd immunity level [Formula: see text] is the fraction of the population that must be infected by an epidemic to ensure that a new epidemic among the remaining susceptible population is not supercritical. For a homogeneously mixing population [Formula: see text] equals the classical herd immunity level [Formula: see text], which is the fraction of the population that must be vaccinated in advance of an epidemic so that the epidemic is not supercritical. For most forms of heterogeneous mixing [Formula: see text], sometimes dramatically so. For an SEIR (susceptible [Formula: see text] exposed [Formula: see text] infective [Formula: see text] recovered) model of an epidemic among a population that is partitioned into households, in which individuals mix uniformly within households and, in addition, uniformly at a much lower rate in the population at large, we show that [Formula: see text] unless variability in the household size distribution is sufficiently large. Thus, introducing household structure into a model typically has the opposite effect on disease-induced herd immunity than most other forms of population heterogeneity. We reach this conclusion by considering an approximation [Formula: see text] of [Formula: see text], supported by numerical studies using real-world household size distributions. For [Formula: see text], we prove that [Formula: see text] when all households have size n, and conjecture that this inequality holds for any common household size n. We prove results comparing [Formula: see text] and [Formula: see text] for epidemics which are highly infectious within households, and also for epidemics which are weakly infectious within households.

Hallucinating hallucinogens.

Fighting the designer drug epidemic with generative AI.

Epidemic Characteristics, Spatiotemporal Pattern, and Risk Factors of Other Infectious Diarrhea in Fujian Province From 2005 to 2021: Retrospective Analysis.

BACKGROUND: Other infectious diarrhea (OID) continues to pose a significant public health threat to all age groups in Fujian Province. There is a need for an in-depth analysis to understand the epidemiological pattern of OID and its associated risk factors in the region. OBJECTIVE: In this study, we aimed to describe the overall epidemic characteristics and spatiotemporal pattern of OID in Fujian Province from 2005 to 2021 and explore the linkage between sociodemographic and environmental factors and the occurrence of OID within the study area. METHODS: Notification data for OID in Fujian were extracted from the China Information System for Disease Control and Prevention. The spatiotemporal pattern of OID was analyzed using Moran index and Kulldorff scan statistics. The seasonality of and short-term impact of meteorological factors on OID were examined using an additive decomposition model and a generalized additive model. Geographical weighted regression and generalized linear mixed model were used to identify potential risk factors. RESULTS: A total of 388,636 OID cases were recorded in Fujian Province from January 2005 to December 2021, with an average annual incidence of 60.3 (SD 16.7) per 100,000 population. Children aged <2 years accounted for 50.7% (196,905/388,636) of all cases. There was a steady increase in OID from 2005 to 2017 and a clear seasonal shift in OID cases from autumn to winter and spring between 2005 and 2020. Higher maximum temperature, atmospheric pressure, humidity, and precipitation were linked to a higher number of deseasonalized OID cases. The spatial and temporal aggregations were concentrated in Zhangzhou City and Xiamen City for 17 study years. Furthermore, the clustered areas exhibited a dynamic spreading trend, expanding from the southernmost Fujian to the southeast and then southward over time. Factors such as densely populated areas with a large <1-year-old population, less economically developed areas, and higher pollution levels contributed to OID cases in Fujian Province. CONCLUSIONS: This study revealed a distinct distribution of OID incidence across different population groups, seasons, and regions in Fujian Province. Zhangzhou City and Xiamen City were identified as the major hot spots for OID. Therefore, prevention and control efforts should prioritize these specific hot spots and highly susceptible groups.

Identifying the patterns and sizes of the first lumpy skin disease outbreak clusters in Northern Thailand with a high degree of dairy farm aggregation using spatio-temporal models.

Lumpy skin disease (LSD) is one of the most important notifiable transboundary diseases affecting cattle in many parts of the world. In Thailand, LSD outbreaks in cattle farming areas have been reported in 69 out of 77 provinces, indicating a serious nationwide situation. Understanding the dynamics of spatial and temporal LSD epidemic patterns can provide important information on disease transmission and control. This study aims to identify spatial and temporal clusters in the first LSD outbreaks in dairy farming areas with a high degree of aggregation in Northern Thailand using spatio-temporal models. The data were obtained from an official LSD outbreak investigation conducted between June and August 2021 on dairy farms (n = 202). The outbreak of LSD was confirmed by employing clinical observations and laboratory analysis. The spatio-temporal models including space-time permutation (STP), Poisson, and Bernoulli were applied to the outbreak data with the settings of 10%, 25%, and 50%, respectively, for the maximum reported cluster size (MRCS). Overall, the number of most likely and secondary clusters varied depending on the model and MRCS settings. All MRCS settings in the STP model detected the most likely clusters in the same area and the Poisson models in different areas, with the largest being defined by a 50% MRCS. Although the sizes of the most likely clusters identified by the Bernoulli models were different, they all had the same cluster period. Based on the sizes of the detected clusters, strict LSD insect-vector control should be undertaken within one kilometer of the outbreak farm in areas where no LSD vaccination has been administered. This study determines the sizes and patterns of LSD outbreak clusters in the dairy farming area with a high degree of farm aggregation. The spatio-temporal study models used in this study, along with multiple adjusted MRCS, provide critical epidemiological information. These models also expand the options for assisting livestock authorities in facilitating effective LSD prevention and control programs. By prioritizing areas for resource allocation, these models can help improve the efficiency of such programs.

Respiratory Syncytial Virus in Outpatient Children with Bronchiolitis: Continuous Virus Circulation During the Nonepidemic Period.

We aimed to estimate the respiratory syncytial virus positivity rate among ambulatory children with bronchiolitis according to the bronchiolitis epidemic period as defined by the French Public Health Institute. The positivity rate was 28.9% during the nonepidemic period and 50.6% during the epidemic period, which suggests continuous virus circulation between bronchiolitis annual peaks.

Assessment of levels and trends of HIV infections among different subgroup populations of Gujarat State - Prioritization of the districts.

Background: In India, HIV prevalence varies by region and high-risk groups. General population rates have decreased in high prevalence states through HIV Sentinel Surveillance among pregnant women, while low-moderate prevalence states show variable trends. Gujarat, in western India, has mixed HIV prevalence according to 2017 Sentinel Surveillance data. Objectives: To study the level and trend of HIV positivity among pregnant women and high-risk groups (HRGs) across different districts of the state of Gujarat from year 2012-13 to 2016-17. To review the possible determinants of the HIV epidemic across the selected districts in the state of Gujarat. Materials and Methods: Data from the National AIDS Control Organization (NACO) spanning 2012-17 was analyzed for HIV trends in Gujarat. This included combined HIV testing data from pregnant women at Integrated and Counseling Testing Centers, blood unit testing data from selected districts, and HIV testing among high-risk populations through Targeted Intervention sites. Results: HIV cases in Kheda district declined post-2013-14 among pregnant women (0.38% to 0.21% in 2016-17), and in general ICTC clients (5.53% to 0.264% in 2017-18). MSM seropositivity dropped from 1.15% (2014-15) to 0.74% (2016-17), FSWs from 0.7% (2014-15) to 0.29% (2015-16). Contrastingly, blood donors exhibited an increasing trend, rising from 0.15% (2012-13) to 0.24% (2016-17). In Mehsana, ANC mother seropositivity rose to 0.6% (2013-14), fell to 0.32% (2015-16), and rose again to 0.48% (2016-17). General ICTC clients declined from 1.2% (2012-13) to 0.53% (2016-17). FSWs had 0.25% seropositivity (2015-16), while MSM saw a drop from 0.44% (2014-15) to 0.23% (2016-17). Blood donors' trend was inconsistent. Sabarkantha's pregnant women seropositivity dipped from 0.59% (2012-13) to 0.20% (2014-15), rising to 0.25% (2017-18). General ICTC client seropositivity decreased from 5.34% (2012-13) to 1.17% (2017-18). Conclusion: While declines in HIV prevalence are evident among certain groups such as pregnant women and general ICTC clients, there are fluctuations in seropositivity among high-risk populations like MSM, FSWs, and blood donors. These insights emphasize the need for targeted interventions and ongoing monitoring to effectively address the evolving HIV landscape in these districts.

Ending the HIV Epidemic.

Despite progress, there is still much work to be done.

Obesity and lifespan, a complex tango.

Obesity and aging share comorbidities, phenotypes, and deleterious effects on health that are associated with chronic diseases. However, distinct features set them apart, with underlying biology that should be explored and exploited, especially given the demographic shifts and the obesity epidemic that the world is facing.

Novel spatial profiles of some diffusive SIS epidemic models.

In this paper, we are concerned with two SIS epidemic reaction-diffusion models with mass action infection mechanism of the form SI, and study the spatial profile of population distribution as the movement rate of the infected individuals is restricted to be small. For the model with a constant total population number, our results show that the susceptible population always converges to a positive constant which is indeed the minimum of the associated risk function, and the infected population either concentrates at the isolated highest-risk points or aggregates only on the highest-risk intervals once the highest-risk locations contain at least one interval. In sharp contrast, for the model with a varying total population number which is caused by the recruitment of the susceptible individuals and death of the infected individuals, our results reveal that the susceptible population converges to a positive function which is non-constant unless the associated risk function is constant, and the infected population may concentrate only at some isolated highest-risk points, or aggregate at least in a neighborhood of the highest-risk locations or occupy the whole habitat, depending on the behavior of the associated risk function and even its smoothness at the highest-risk locations. Numerical simulations are performed to support and complement our theoretical findings.

A holistic approach in epidemics.

This paper explores the concept of a holistic approach in preventing and responding to epidemics. Epidemics are defined as the occurrence of an illness or health-related event exceeding normal expectations within a specific community or region. Holism emphasizes viewing systems as a whole rather than a collection of parts. In the context of epidemics, a holistic approach considers not only medical interventions but also social, economic, psychological and environmental factors that influence disease transmission and management. The impact of climate change on epidemic response, the understanding of the significance of animal health and agriculture, the consideration of art, culture and societal factors, the exploration of the use of technology and innovation, the addressing of limitations in resources and the provision of enhanced support for the mental and emotional well-being of individuals and affected communities, are parts of this holistic approach. By integrating them, innovative practices as well as cross-sectoral and interdisciplinary techniques can be employed. Such an approach has the potential to enhance epidemic prevention and response strategies, ultimately contributing to positive public health outcomes.

An overview and visual analysis of research on government regulation in healthcare.

Objective: During the period of COVID-19, government regulation (GR) played an important role in healthcare. This study examines the current research situation of GR in healthcare, discusses the research hotspots, the most productive authors and countries, and the most common journals, and analyzes the changes in GR in healthcare before and after the outbreak of COVID-19. Methods: This study followed PRISMA guidelines to collect literature on GR in healthcare. And the VOSviewer software was used to perform a quantitative analysis of these documents to obtain a visual map, including year, country, institution, journal, author, and research topic. Results: A total of 1,830 papers that involved 976 academic journals, 3,178 institutions, and 133 countries were identified from 1985 to 2023. The United States was the country with the highest production (n = 613), followed by the United Kingdom (n = 289). The institution with the largest number of publications was the University of London in the UK (n = 103); In the author collaboration network, the biggest cluster is Bomhoff M, Bouwman R, Friele R, et al. The top five journals in terms of the number of articles were BMC Health Services Research (n = 70), Plos One (n = 35), Health Policy (n = 33), Social Science & Medicine (n = 29), Health Policy and Planning (n = 29), and Frontiers in Public Health (n = 27). The existing literature mainly focused on "health policy," "public health," "China," "mental health," "India," "qualitative research," "legislation," and "governance," et al. Since 2020, research on "COVID-19" has also become a priority in the domain of healthcare. Conclusion: This study reveals the overall performance of the literature on GR published in healthcare. Healthcare needs GR, especially in response to the COVID-19 epidemic, which has played an irreplaceable role. The outbreak of COVID-19 not only tested the health systems of various countries, but also changed GR in healthcare. With the end of COVID-19, whether these changes will end remains to be further studied.

Global fight against HIV is at risk.

Will the United States remain committed to a landmark health program it started 20 years ago that saved more than 25 million lives around the world? For a younger generation of physicians, nurses, and researchers today, the depth of despair wrought by the HIV/AIDS epidemic at that time is almost unimaginable. Even more profoundly, for countries in Africa, the epidemic presented an existential threat. Without access to antiretroviral therapy or efficacious prevention tools, new infections continued unfettered, and people with HIV/ AIDS faced near-certain death. Yet, somehow out of this anguish came a ray of hope. In 2003, President George W. Bush announced the launch of the President's Emergency Plan for AIDS Relief (PEPFAR), committing billions of dollars to fight the epidemic in the poorest countries around the world. The initiative has been a shining example of global collaboration in the face of adversity. Yet, as of this September, the US Congress has yet to reauthorize PEPFAR. The Biden administration, individuals from both sides of the political divide, and former President Bush himself have urged Congress to support PEPFAR's lifesaving work. The scientific and public health communities must do the same before it is too late.

Improving social resilience amid the COVID-19 epidemic: A system dynamics model.

Social resilience is a key factor in disaster management, but compared to resilience in other fields, research on social resilience is still limited to assessment or evaluation, and there is still a lack of dynamic and procedural research, which is also a challenge. This article constructs a causal feedback model and a system dynamics model of social resilience during the COVID-19 epidemic, so as to analyze the dynamic characteristics and improvement path of social resilience. After verifying the effectiveness of the model, model simulation is conducted and the following important conclusions are drawn: social resilience dynamically changes during the research cycle and is influenced by social entity behavior and social mechanisms; The sensitivity factors for the two variables that measure social resilience, namely panic degree and damage degree, are the real-time information acquisition of public and the epidemic awareness of local government, respectively. Therefore, the path to enhancing social resilience should be pursued from both the public and government perspectives, including improving the public's ability to access real-time information, increasing the timeline of government information disclosure, and enhancing local governments' understanding and awareness of the epidemic.

A looming epidemic: combating the recurrent outbreaks of diphtheria in Nigeria.

Nigeria has endured several diphtheria outbreaks over the last few decades, mirroring a suboptimal population immunity across several demographics within the country. The country's northern region has been affected mainly by this infectious disease; it directly depicts the effect of poor DPT vaccine uptake amongst children in this region compared to other geopolitical zones in Nigeria. Whilst pharmaceutical intervention and surveillance activities have commenced as directed by the NCDC, to combat this public health menace, top leaders of the Nigerian healthcare system - public and private sectors, must understudy the predisposing factors gearing the recurrence of diphtheria in Nigeria and provide robust, research-based and scientific mechanisms to arrest the root causes of the incessant outbreaks. This article discusses the factors promoting the recurrent diphtheria outbreaks in Nigeria, the preexisting interventions with their existential deterrents, and new strategies recommended to curb the further resurgence of the disease.

A global examination of ecological niche modeling to predict emerging infectious diseases: a systematic review.

Introduction: As emerging infectious diseases (EIDs) increase, examining the underlying social and environmental conditions that drive EIDs is urgently needed. Ecological niche modeling (ENM) is increasingly employed to predict disease emergence based on the spatial distribution of biotic conditions and interactions, abiotic conditions, and the mobility or dispersal of vector-host species, as well as social factors that modify the host species' spatial distribution. Still, ENM applied to EIDs is relatively new with varying algorithms and data types. We conducted a systematic review (PROSPERO: CRD42021251968) with the research question: What is the state of the science and practice of estimating ecological niches via ENM to predict the emergence and spread of vector-borne and/or zoonotic diseases? Methods: We searched five research databases and eight widely recognized One Health journals between 1995 and 2020. We screened 383 articles at the abstract level (included if study involved vector-borne or zoonotic disease and applied ENM) and 237 articles at the full-text level (included if study described ENM features and modeling processes). Our objectives were to: (1) describe the growth and distribution of studies across the types of infectious diseases, scientific fields, and geographic regions; (2) evaluate the likely effectiveness of the studies to represent ecological niches based on the biotic, abiotic, and mobility framework; (3) explain some potential pitfalls of ENM algorithms and techniques; and (4) provide specific recommendation for future studies on the analysis of ecological niches to predict EIDs. Results: We show that 99% of studies included mobility factors, 90% modeled abiotic factors with more than half in tropical climate zones, 54% modeled biotic conditions and interactions. Of the 121 studies, 7% include only biotic and mobility factors, 45% include only abiotic and mobility factors, and 45% fully integrated the biotic, abiotic, and mobility data. Only 13% of studies included modifying social factors such as land use. A majority of studies (77%) used well-recognized ENM algorithms (MaxEnt and GARP) and model selection procedures. Most studies (90%) reported model validation procedures, but only 7% reported uncertainty analysis. Discussion: Our findings bolster ENM to predict EIDs that can help inform the prevention of outbreaks and future epidemics. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier (CRD42021251968).