[The venereal morbidity in Russia in 1914-1924].

It is accepted to explain increasing of venereal diseases during years of the Revolution by degradation of morality and general disorder of system of state administration and sanitary services in Russia. The cross-verification of information presented in scientific publications and primary information sources makes it possible to look into following issues: degree of venereal (syphilitic) contamination of population of pre-revolutionary Russia; influence on sanitary statistics by erroneous diagnostics and convictions of Zemstvo medicine about predominantly non-sexual path of transmission of syphilis pathogen in Russian countryside; dynamics and sources of venereal morbidity in wartime. The high indicators of pre-revolutionary statistics of venereal infections could be affected by diagnostic errors. The "village syphilis" encountered in public milieu could be completely different disease not sexually transmitted and not chronic form of disease. The primary documents allow to discuss increasing of the number of venereal patients during war years, that however, does not reach catastrophic numbers that can be found even in scientific publications. This is also confirmed by data of Chief Military Sanitary Board of the Red Army for 1920s and statistical materials of People's Commissariat of Health Care of the RSFSR. The high morbidity was demonstrated by same Gubernias that were problematic before the Revolution and only later by those ones through which during the war years passed army masses. In Russia, total level of syphilis morbidity after the end of Civil War occurred to be more than twice lower than in pre-war 1913 and continued to decrease under impact of sanitary measures of Soviet public health.

Multiple pandemic waves vs multi-period/multi-phasic epidemics: Global shape of the COVID-19 pandemic.

The overall course of the COVID-19 pandemic in Western countries has been characterized by complex sequences of phases. In the period before the arrival of vaccines, these phases were mainly due to the alternation between the strengthening/lifting of social distancing measures, with the aim to balance the protection of health and that of the society as a whole. After the arrival of vaccines, this multi-phasic character was further emphasized by the complicated deployment of vaccination campaigns and the onset of virus' variants. To cope with this multi-phasic character, we propose a theoretical approach to the modeling of overall pandemic courses, that we term multi-period/multi-phasic, based on a specific definition of phase. This allows a unified and parsimonious representation of complex epidemic courses even when vaccination and virus' variants are considered, through sequences of weak ergodic renewal equations that become fully ergodic when appropriate conditions are met. Specific hypotheses on epidemiological and intervention parameters allow reduction to simple models. The framework suggest a simple, theory driven, approach to data explanation that allows an accurate reproduction of the overall course of the COVID-19 epidemic in Italy since its beginning (February 2020) up to omicron onset, confirming the validity of the concept.

Wastewater-borne viruses and bacteria, surveillance and biosensors at the interface of academia and field deployment.

Wastewater is a complex, but an ideal, matrix for disease monitoring and surveillance as it represents the entire load of enteric pathogens from a local catchment area. It captures both clinical and community disease burdens. Global interest in wastewater surveillance has been growing rapidly for infectious diseases monitoring and for providing an early warning of potential outbreaks. Although molecular detection methods show high sensitivity and specificity in pathogen monitoring from wastewater, they are strongly limited by challenges, including expensive laboratory settings and prolonged sample processing and analysis. Alternatively, biosensors exhibit a wide range of practical utility in real-time monitoring of biological and chemical markers. However, field deployment of biosensors is primarily challenged by prolonged sample processing and pathogen concentration steps due to complex wastewater matrices. This review summarizes the role of wastewater surveillance and provides an overview of infectious viral and bacterial pathogens with cutting-edge technologies for their detection. It emphasizes the practical utility of biosensors in pathogen monitoring and the major bottlenecks for wastewater surveillance of pathogens, and overcoming approaches to field deployment of biosensors for real-time pathogen detection. Furthermore, the promising potential of novel machine learning algorithms to resolve uncertainties in wastewater data is discussed.

Enhancing the capacity of community health workers in prevention and control of epidemics and pandemics in Wakiso district, Uganda: evaluation of a pilot project.

BACKGROUND: Community Health Workers (CHWs) play a crucial role in outbreak response, including health education, contact tracing, and referral of cases if adequately trained. A pilot project recently trained 766 CHWs in Wakiso district Uganda on epidemic and pandemic preparedness and response including COVID-19. This evaluation was carried out to generate evidence on the outcomes of the project that can inform preparations for future outbreaks in the country. METHODS: This was a qualitative evaluation carried out one year after the project. It used three data collection methods: 30 in-depth interviews among trained CHWs; 15 focus group discussions among community members served by CHWs; and 11 key informant interviews among community health stakeholders. The data was analysed using a thematic approach in NVivo (version 12). RESULTS: Findings from the study are presented under four themes. (1) Improved knowledge and skills on managing epidemics and pandemics. CHWs distinguished between the two terminologies and correctly identified the signs and symptoms of associated diseases. CHWs reported improved communication, treatment of illnesses, and report writing skills which were of great importance including for managing COVID-19 patients. (2) Enhanced attitudes towards managing epidemics and pandemics as CHWs showed dedication to their work and more confidence when performing tasks specifically health education on prevention measures for COVID-19. (3) Improved health practices such as hand washing, vaccination uptake, and wearing of masks in the community and amongst CHWs. (4) Enhanced performance in managing epidemics and pandemics which resulted in increased work efficiency of CHWs. CHWs were able to carry out community mobilization through door-to-door household visits and talks on community radios as part of the COVID-19 response. CHWs were also able to prioritize health services for the elderly, and support the management of patients with chronic diseases such as HIV, TB and diabetes by delivering their drugs. CONCLUSIONS: These findings demonstrate that CHWs can support epidemic and pandemic response when their capacity is enhanced. There is need to invest in routine training of CHWs to contribute to outbreak preparedness and response.

Predicting plant disease epidemics using boosted regression trees.

Plant epidemics are often associated with weather-related variables. It is difficult to identify weather-related predictors for models predicting plant epidemics. In the article by Shah et al., to predict Fusarium head blight (FHB) epidemics of wheat, they explored a functional approach using scalar-on-function regression to model a binary outcome (FHB epidemic or non-epidemic) with respect to weather time series spanning 140 days relative to anthesis. The scalar-on-function models fit the data better than previously described logistic regression models. In this work, given the same dataset and models, we attempt to reproduce the article by Shah et al. using a different approach, boosted regression trees. After fitting, the classification accuracy and model statistics are surprisingly good.

A simple modification to the classical SIR model to estimate the proportion of under-reported infections using case studies in flu and COVID-19.

Background: Under-reporting and, thus, uncertainty around the true incidence of health events is common in all public health reporting systems. While the problem of under-reporting is acknowledged in epidemiology, the guidance and methods available for assessing and correcting the resulting bias are obscure. Objective: We aim to design a simple modification to the Susceptible - Infected - Removed (SIR) model for estimating the fraction or proportion of reported infection cases. Methods: The suggested modification involves rescaling of the classical SIR model producing its mathematically equivalent version with explicit dependence on the reporting parameter (true proportion of cases reported). We justify the rescaling using the phase plane analysis of the SIR model system and show how this rescaling parameter can be estimated from the data along with the other model parameters. Results: We demonstrate how the proposed method is cross-validated using simulated data with known disease cases and then apply it to two empirical reported data sets to estimate the fraction of reported cases in Missoula County, Montana, USA, using: (1) flu data for 2016-2017 and (2) COVID-19 data for fall of 2020. Conclusions: We establish with the simulated and COVID-19 data that when most of the disease cases are presumed reported, the value of the additional reporting parameter in the modified SIR model is close or equal to one, so that the original SIR model is appropriate for data analysis. Conversely, the flu example shows that when the reporting parameter is close to zero, the original SIR model is not accurately estimating the usual rate parameters, and the re-scaled SIR model should be used. This research demonstrates the role of under-reporting of disease data and the importance of accounting for under-reporting when modeling simulated, endemic, and pandemic disease data. Correctly reporting the "true" number of disease cases will have downstream impacts on predictions of disease dynamics. A simple parameter adjustment to the SIR modeling framework can help alleviate bias and uncertainty around crucial epidemiological metrics (e.g.: basic disease reproduction number) and public health decision making.

An SIS epidemic model with individual variation.

We study an extension of the stochastic SIS (Susceptible-Infectious-Susceptible) model in continuous time that accounts for variation amongst individuals. By examining its limiting behaviour as the population size grows we are able to exhibit conditions for the infection to become endemic.

[Medical practice in classical Greece : The neurological and psychiatric case reports of the Hippocratic Corpus]. / Medizinische Praxis im klassischen Griechenland : Die neurologischen und psychiatrischen Fallberichte des Corpus Hippocraticum.

OBJECTIVE: Which theoretical and practical competences do the neurological and psychiatric case histories of the Hippocratic Corpus convey? MATERIAL AND METHODS: The 431 Hippocratic case histories have been studied for reports and communication on the diagnostics, treatment and prognosis of single persons and groups of patients suffering from neurological and psychiatric diseases. RESULTS: In the 7 books of the Hippocratic Epidemics, a total of 128 patients with neurological and psychiatric symptoms are described. Epidemic fever and its variants were the leading predisposing conditions and the main symptoms were delirium, coma, insomnia, headache, speech disorders and convulsions. A number of patients with phrenitis and opisthotonos are also reported. The majority of the sick persons were male, were teenagers or adults and 47 of them are mentioned by name. The patient's information about the course is often just as informative as the doctor's observations. Treatment was limited to physical and dietary measures. DISCUSSION: The Hippocratic physician diagnosed and attempted to treat a large number of neurological and psychiatric diseases. The often almost continuous observations of the patients led to astonishingly precise predictions of the course and the prospects of recovery. Numerous symptoms described in the case studies, including carphologia and opisthotonus, have entered the neurological vocabulary. The retrospective etiological analysis of the reports leads to the almost explicit identification of neurosyphilis and encephalitis lethargica. The therapeutic measures described by the author were, as the changeable course of the diseases shows, only of limited effectiveness despite a very differentiated application over time, both against the underlying diseases and the neurological and psychiatric complications.

Photoluminescence-based biosensor for the detection of antibodies against SARS-CoV-2 virus proteins by ZnO tetrapod structure integrated within microfluidic system.

This paper reports on development of an optical biosensor for the detection of antibodies against SARS-CoV-2 virus proteins in blood serum. ZnO nanotetrapods with high surface area and stable room temperature photoluminescence (PL) were selected as transducers. Structure and optical properties of the ZnO tetrapods have been studied by XRD, SEM and Raman spectroscopy. Crystallinity, dimensions and emission peaks of the ZnO tetrapods were determined. The ZnO tetrapods were fixed on glass chip. Silanization of ZnO tetrapods surface resulted in forming of functional surface groups suitable for the immobilization of bioselective layer. Two types of recombinant proteins (rS and rN) have been used to form bioselective layer on the surface of the ZnO tetrapods. Flow through microfluidic system, integrated with optical system, has been used for the determination of antibodies against SARS-CoV-2 virus proteins present in blood samples. The SARS-CoV-2 probes, prepared in PBS solution, have been injected into the measurement chamber with a constant pumping speed. Steady-state photoluminescence spectra and photoluminescence kinetics have been studied before and after injection of the probes. The biosensor signal has been tested to anti-SARS-CoV-2 antibodies in the range of 0.001 nM-1 nM. Control measurements have been performed with blood serum of healthy person. ZnO-SARS-CoV-2-rS and ZnO-SARS-CoV-2-rN biosensors showed high stability and sensitivity to anti-SARS-CoV-2 antibodies in the range of 0.025-0.5 nM (LOD 0.01 nM) and 0.3-1 nM (LOD 0.3 nM), respectively. Gibbs free energy of interaction between ZnO/SARS-CoV-2-rS and ZnO/SARS-CoV-2-rN bioselective layers with anti-SARS-CoV-2 antibodies showed -35.5 and -21.4 kJ/mol, respectively. Average detection time of biosensor integrated within microfluidic system was 15-20 min. The detection time and pumping speed (50 µL/min) were optimized to make detection faster. The developed system and ZnO-SARS-CoV-2-rS nanostructures have good potential for detection of anti-SARS-CoV-2 antibodies from patient's probes.

Environmental Materialities and the History of Pandemics.

Over the last several decades, a growing group of environmental and medical historians have argued that engagement with the materiality of disease is critical to eroding the false boundaries between environment and health, and especially to the historical study of major epidemics and pandemics. This article evaluates the ways in which environmental and medical historians have engaged materiality when thinking through questions of infectious disease. It argues that far from eschewing cultural constructions of disease and analysis of medical systems, these works demonstrate that engagement with materiality in the study of disease articulates the stakes of medical regimes and practices of healing, and renders legible the multiple scales at which epidemics occur. Addressing key controversies in the use of sources, it provides examples of works that incorporate material objects, biological ideas and actors, and non-humans without falling prey to the extremes of "biological determinism" or "constructivism." It argues that commonalities in the methods employed by these works - utilization of scientific frameworks and data, multispecies analysis, attention to scale, and spatial thinking - reveal unseen and untold aspects of past pandemics. It concludes with a brief example of how these frameworks come together in practice through a case study on the history of enteric fever in Dublin, Ireland.

Modelling the impact of precaution on disease dynamics and its evolution.

In this paper, we introduce the notion of practically susceptible population, which is a fraction of the biologically susceptible population. Assuming that the fraction depends on the severity of the epidemic and the public's level of precaution (as a response of the public to the epidemic), we propose a general framework model with the response level evolving with the epidemic. We firstly verify the well-posedness and confirm the disease's eventual vanishing for the framework model under the assumption that the basic reproduction number R 0 < 1 . For R 0 > 1 , we study how the behavioural response evolves with epidemics and how such an evolution impacts the disease dynamics. More specifically, when the precaution level is taken to be the instantaneous best response function in literature, we show that the endemic dynamic is convergence to the endemic equilibrium; while when the precaution level is the delayed best response, the endemic dynamic can be either convergence to the endemic equilibrium, or convergence to a positive periodic solution. Our derivation offers a justification/explanation for the best response used in some literature. By replacing "adopting the best response" with "adapting toward the best response", we also explore the adaptive long-term dynamics.

Comparison of the Stress and Anxiety to Viral Epidemic-9 and SAVE-6 scales among healthcare workers in Peru.

Introduction: Peru is a country that has a high incidence of viral outbreaks and epidemics, which is why it is necessary to validate a scale that measures anxiety and stress in professionals who are on the front lines of these events. Therefore, our objective was to validate the Peruvian-Spanish version of the Stress and Anxiety to Viral Epidemics-9 items (SAVE-9) scale and to concurrently compare its validity and internal consistency with the SAVE-6 scale among healthcare workers (HCWs). Materials and methods: We conducted a cross-sectional study based on data collected from a self-reported survey in paper-and-pencil format between April and July 2023. A total of 203 HCWs participated in the research. We developed a confirmatory factor analysis (CFA) and item response theory (IRT). We calculated Cronbach's α coefficient and McDonald's ω to assess the internal consistency of the scales. Results: The results show that SAVE-9 (a two-factor model) and SAVE-6 (a one-factor model) provided an excellent fit in the confirmatory factor analysis. Both scales demonstrated strong internal consistency (Cronbach's α 0.85 and 0.86, respectively). Significant correlations were found between the SAVE-9 and SAVE-6 scales and Generalized Anxiety Disorder-7 items scale (r = 0.44 and r = 0.38, respectively, p < 0.001) as well as the Patient Health Questionnaire-9 items (r = 0.39 and r = 0.35, respectively, p < 0.001). The optimal cutoff points for SAVE-9 and SAVE-6 were identified for assessing anxiety, aligned with a GAD-7 score ≥5 points. Conclusion: The Peruvian-Spanish SAVE-9 and SAVE-6 scales are reliable and valid rating scales to assess the anxiety response of HCWs in response to viral epidemics. Though COVID-19 is diminished, these scales will be useful for other viral epidemics in the future.

Mathematical models and analysis tools for risk assessment of unnatural epidemics: a scoping review.

Predicting, issuing early warnings, and assessing risks associated with unnatural epidemics (UEs) present significant challenges. These tasks also represent key areas of focus within the field of prevention and control research for UEs. A scoping review was conducted using databases such as PubMed, Web of Science, Scopus, and Embase, from inception to 31 December 2023. Sixty-six studies met the inclusion criteria. Two types of models (data-driven and mechanistic-based models) and a class of analysis tools for risk assessment of UEs were identified. The validation part of models involved calibration, improvement, and comparison. Three surveillance systems (event-based, indicator-based, and hybrid) were reported for monitoring UEs. In the current study, mathematical models and analysis tools suggest a distinction between natural epidemics and UEs in selecting model parameters and warning thresholds. Future research should consider combining a mechanistic-based model with a data-driven model and learning to pursue time-varying, high-precision risk assessment capabilities.

Molecular Evolution of GII.P31/GII.4_Sydney_2012 Norovirus over a Decade in a Clinic in Japan.

Norovirus (NoV) genogroup II, polymerase type P31, capsid genotype 4, Sydney_2012 variant (GII.P31/GII.4_Sydney_2012) has been circulating at high levels for over a decade, raising the question of whether this strain is undergoing molecular alterations without demonstrating a substantial phylogenetic difference. Here, we applied next-generation sequencing to learn more about the genetic diversity of 14 GII.P31/GII.4_Sydney_2012 strains that caused epidemics in a specific region of Japan, with 12 from Kyoto and 2 from Shizuoka, between 2012 and 2022, with an emphasis on amino acid (aa) differences in all three ORFs. We found numerous notable aa alterations in antigenic locations in the capsid region (ORF2) as well as in other ORFs. In all three ORFs, earlier strains (2013-2016) remained phylogenetically distinct from later strains (2019-2022). This research is expected to shed light on the evolutionary properties of dominating GII.P31/GII.4_Sydney_2012 strains, which could provide useful information for viral diarrhea prevention and treatment.

Pathways to prevention: insights on stemming HIV outbreaks in Larkana, Pakistan.

In the past two decades, Pakistan has faced multiple human immunodeficiency virus outbreaks, with Larkana appearing to be the hub of such outbreaks. While the previous Larkana outbreaks happened in high-risk populations, the alarming outbreak in 2019 occurred in a low-risk paediatric population, raising several concerning questions. Human immunodeficiency virus infections spilling into the general population is indicative of a steady increase in the number of cases, and the failure of control strategies to stem the concentrated epidemic from evolving. Although several causative factors have been identified from previous outbreaks, the one that occurred in 2019 may have been influenced by an additional, hitherto unexplored factor; child sexual abuse. The current narrative review was planned to summarise human immunodeficiency virus risk factors and causes identified in previous Larkana epidemics, to explore potential reasons for the outbreaks in children, and to discuss possible steps needed for stemming human immunodeficiency virus outbreaks in Pakistan.

Vaccine-Preventable Disease Outbreaks among Healthcare Workers: A Scoping Review.

BACKGROUND: Outbreaks of vaccine preventable diseases (VPDs) in health care workers (HCWs) can result in morbidity and mortality and cause significant disruptions to health care services, patients and visitors as well as an added burden on the health system. This scoping review is aimed to describe the epidemiology of VPD outbreaks in HCW, caused by diseases which are prevented by the ten vaccines recommended by World Health Organization (WHO) for HCWs. METHODS: In April 2022 CINAHL, MEDLINE, Global Health and EMBASE were searched for all articles reporting on VPD outbreaks in HCWs since the year 2000. Articles were included regardless of language and study type. Clinical and epidemiological characteristics of VPD outbreaks were described. RESULTS: Our search found 9363 articles, of which 216 met inclusion criteria. Studies describing six of the ten VPDs were found: influenza, measles, varicella, tuberculosis, pertussis and rubella. Most articles (93%) were from high- and upper middle-income countries. While most outbreaks occurred in hospitals, several influenza outbreaks were reported in long term care facilities. Based on available data, vaccination rates amongst HCWs were rarely reported. CONCLUSION: We describe several VPD outbreaks in HCWs from 2000 to April 2022. The review emphasises the need to understand the factors influencing outbreaks in HCWs and highlight importance of vaccination amongst HCWs.