Influenza epidemics in the USSR and Czechoslovakia in 1979-1984

In this work materials characterizing the appearance and development of influenza epidemic at the territories of the USSR and the Czech Socialist Republic are presented, the common features and differences of the epidemic process in both countries are recorded. The work shows that in both countries the appearance of this epidemic is caused by the same virus. In most cases the epidemic started earlier and lasted longer in the USSR, but morbidity rate during the epidemic was, on the whole, higher in the Czech Socialist Republic. Similarity in the course of the primary period of the epidemic processes from their appearance to their maximum rise was observed. In both countries the maximum rise of morbidity rate was registered on weeks 3-4 from the beginning of the epidemic.     

杉木种子涩籽地理流行趋势的研究

本文应用趋势面分析福建省杉木种子涩籽地理流行趋势,建立涩籽地理流行数学模型,阐述其流行规律,绘制山涩籽地理流行图,并将其划分成四个区：1．闽西南杉木涩籽流行递减区;2．闽东南杉木涩籽流行递增区;3．闽北杉木涩籽流行递减区：4,闽中北闽西北杉木涩籽流行渐稳区。同时建议将大型杉木种子园建在建瓯县。     

Network-based analysis of stochastic SIR epidemic models with random and proportionate mixing

In this paper, we outline the theory of epidemic percolation networks and their use in the analysis of stochastic susceptible-infectious-removed (SIR) epidemic models on undirected contact networks. We then show how the same theory can be used to analyze stochastic SIR models with random and proportionate mixing. The epidemic percolation networks for these models are purely directed because undirected edges disappear in the limit of a large population. In a series of simulations, we show that epidemic percolation networks accurately predict the mean outbreak size and probability and final size of an epidemic for a variety of epidemic models in homogeneous and heterogeneous populations. Finally, we show that epidemic percolation networks can be used to re-derive classical results from several different areas of infectious disease epidemiology. In an Appendix, we show that an epidemic percolation network can be defined for any time-homogeneous stochastic SIR model in a closed population and prove that the distribution of outbreak sizes given the infection of any given node in the SIR model is identical to the distribution of its out-component sizes in the corresponding probability space of epidemic percolation networks. We conclude that the theory of percolation on semi-directed networks provides a very general framework for the analysis of stochastic SIR models in closed populations.     

The epidemic process in mumps infection

Manifestations of the epidemic process of a parotitis infection can be explained by the theory of the self regulation of parasitic systems. A characteristic feature of epidemic parotitis is the formation of epidemic foci in the absence of parotitis cases and without the penetration of the infective agent from the outside. The epidemic wave of parotitis infection decreases as the virulence of the infective agent attenuates due to its passage through persons gaining immunity in the course of the epidemic. The avirulent infective agent persists in the body of some immune carriers till a sufficient stratum of susceptible subjects accumulates in the chain of the agent circulation. The analysis points to the autonomous character of the epidemic process not only among the urban and rural population, but also among separate social and age groups of the population within one town or settlement. The findings evidence an independent formation of the epidemic variant of the infective agent in individual schools and preschool institutions.     

Prediction of hot spot areas of hemorrhagic fever with renal syndrome in Hunan Province based on an information quantity model and logistical regression model

BackgroundChina’s “13^th 5-Year Plan” (2016–2020) for the prevention and control of sudden acute infectious diseases emphasizes that epidemic monitoring and epidemic focus surveys in key areas are crucial for strengthening national epidemic prevention and building control capacity. Establishing an epidemic hot spot areas and prediction model is an effective means of accurate epidemic monitoring and surveying. Objective: This study predicted hemorrhagic fever with renal syndrome (HFRS) epidemic hot spot areas, based on multi-source environmental variable factors. We calculated the contribution weight of each environmental factor to the morbidity risk, obtained the spatial probability distribution of HFRS risk areas within the study region, and detected and extracted epidemic hot spots, to guide accurate epidemic monitoring as well as prevention and control. Methods: We collected spatial HFRS data, as well as data on various types of natural and human social activity environments in Hunan Province from 2010 to 2014. Using the information quantity method and logistic regression modeling, we constructed a risk-area-prediction model reflecting the epidemic intensity and spatial distribution of HFRS. Results: The areas under the receiver operating characteristic curve of training samples and test samples were 0.840 and 0.816. From 2015 to 2019, HRFS case site verification showed that more than 82% of the cases occurred in high-risk areas.DiscussionThis research method could accurately predict HFRS hot spot areas and provided an evaluation model for Hunan Province. Therefore, this method could accurately detect HFRS epidemic high-risk areas, and effectively guide epidemic monitoring and surveyance.     

Brief communication: Rethinking the impact of the 1918 influenza pandemic on sex differentials in mortality

This study will assess the general impact of the 1918 influenza on overall mortality and its impact on mortality attributable to pulmonary tuberculosis in a small‐scale population. Using life table and decomposition methodologies, changes in mortality in Gibraltar used a scheme that identified a pre‐epidemic period (1904–1917), the epidemic year (1918), and the post‐epidemic period (1919–1927). Overall health in both sexes fell significantly in 1918 with a drop in life expectancy at birth, however, health quickly rebounded in the post‐epidemic period. In the case of women, there was a significant increase in life expectancy at birth after the epidemic. The impact of influenza on the magnitude of sex differentials in the life expectancy at birth fell during epidemic year but returned to a level comparable to that of the pre‐epidemic period. With respect to respiratory tuberculosis deaths, the immediate impact of influenza was restricted to only a significant increase in the rate among women (aged 15–54). In the post‐epidemic period, tuberculosis mortality rates returned to the pre‐epidemic state in both sexes. The findings from Gibraltar stand in contrast opposition to results reported for experience in the United States during the 1918 flu. Am J Phys Anthropol, 2009. © 2009 Wiley‐Liss, Inc.     

Measles epidemic from failure to immunize.

During 1988 through 1990, California experienced its worst measles epidemic in more than a decade, with 16,400 reported cases, 3,390 hospital admissions, and 75 deaths. More than half of the patients were younger than 5 years; the highest incidence was among infants younger than 12 months. The epidemic centered in low-income Hispanic communities in southern and central California. The major cause of the epidemic was low immunization levels among preschool-aged children and young adults. Rates of complications, admission to hospital, and death were surprisingly high. Outbreak control efforts met with indeterminate success. Problems with these efforts included insufficient funding early in the epidemic and disappointing public response to community-based immunization campaigns. The cost of medical care and outbreak control for the epidemic is conservatively estimated at $30.9 million. Unless the level of immunization in preschool-aged children is increased, this type of epidemic will probably recur.     

The impact of local heterogeneity on alternative control strategies for foot-and-mouth disease

The 2001 epidemic of foot-and-mouth disease (FMD) in the UK resulted in the death of nearly 10 million livestock at a cost that was estimated to be up to 8 billion pounds. Owing to the controversy surrounding the epidemic, the question of whether or not alternative policies would have resulted in significantly better control of the epidemic remains of great interest. A hexagonal lattice simulation of FMD in Cumbria is used to address the central question of whether or not better use could have been made of expert knowledge of FMD transmission to target pre-emptive culling, by assuming that the premises at greatest risk of becoming infected can be targeted for culling. The 2000 UK census and the epidemiological database collected during the epidemic are used to describe key characteristics of disease transmission, and the model is fit to the epidemic time-series. Under the assumptions of the model, the parameters that best fit the epidemic in Cumbria indicate that a policy based on expert knowledge would have exacerbated the epidemic compared with the policy as implemented. However, targeting more distant, high-risk farms could be more valuable under different epidemic conditions, notably, if risk factors of sufficient magnitude could be identified to aid in prioritizing vaccination or culling of farms at high risk of becoming infected.     

The duality of the qualitative determinacy of the epidemic process in anthroponoses as the main trait distinguishing them from the epidemic manifestations of zoonotic diseases in man

The present article substantiates the necessity of defining more accurately the notion "epidemic process" and using this term only in reference to anthroponotic diseases. Proceeding from the philosophical concept of the qualitative definiteness of material objects and phenomena, the author proposes to distinguish the epidemic process in anthroponoses from mass spread of zoonotic diseases among humans on the basis of using the systemic qualities of the epidemic process, and in particular the principle of the dual character of the qualitative definiteness of objects and phenomena as the distinctive feature of the epidemic process of anthroponoses. Distinction, based on this principle, between anthroponotic diseases and zoonotic diseases in groups of humans must be reflected in the definitions of these phenomena. The application of the term "epidemic process" only in reference to anthroponotic diseases is proposed, while zoonotic diseases in groups of humans should be considered as epidemic manifestations of zoonotic infections.     

Risk perception and effectiveness of uncoordinated behavioral responses in an emerging epidemic

Beyond control measures imposed by public authorities, human behavioral changes can be triggered by uncoordinated responses driven by the risk perception of an emerging epidemic. In order to account for spontaneous social distancing, a model based on an evolutionary game theory framework is here proposed. Behavioral changes are modeled through an imitation process in which the convenience of different behaviors depends on the perceived prevalence of infections. Effects of misperception of risk induced by partial or incorrect information concerning the state of the epidemic are considered as well. Our findings highlight that, if the perceived risk associated to an epidemic is sufficiently large, then even a small reduction in the number of potentially infectious contacts (as a response to the epidemic) can remarkably affect the infection spread. In particular, the earlier the warning about the epidemic appears, the larger the possible reduction of the peak prevalence, and of the final epidemic size. Moreover, the epidemic spread is delayed if individuals' perception of risk is based on a memory mechanism and the risk of infection is initially overestimated. In conclusion, this analysis allows noteworthy inferences about the role of risk perception and the effectiveness of spontaneous behavioral changes during an emerging epidemic.     

具有阶段结构和非线性接触率的SI传染病模型的渐近性态

研究了一类具有阶段结构和非线性接触率的传染病模型的渐近性态,得到了传染病最终消除和成为地方病的阀值．     

The feasibility of forecasting influenza epidemics in Cuba.

A large influenza epidemic took place in Havana during the winter of 1988. The epidemiologic surveillance unit of the Pedro Kourí Institute of Tropical Medicine detected the beginning of the epidemic wave. The Rvachev-Baroyan mathematical model of the geographic spread of an epidemic was used to forecast this epidemic under routine conditions of the public health system. The expected number of individuals who would attend outpatient services, because of influenza-like illness, was calculated and communicated to the health authorities within enough time to permit the introduction of available control measures. The approximate date of the epidemic peak, the daily expected number of individuals attending medical services, and the approximate time of the end of the epidemic wave were estimated. The prediction error was 12%. The model was sufficiently accurate to warrant its use as a practical forecasting tool in the Cuban public health system.     

具有种群动力的时滞SI模型

对一类具有幼年和成年两个生理阶段结构和时滞的Logistic种群动力的SI传染病模型进行了分析,得到了传染病最终消除和成为地方病的阈值．     

The Kermack-McKendrick epidemic model revisited

The Kermack-McKendrick epidemic model of 1927 is an age of infection model, that is, a model in which the infectivity of an individual depends on the time since the individual became infective. A special case, which is formulated as a two-dimensional system of ordinary differential ordinary differential equations, has often been called the Kermack-McKendrick model. One of the products of the SARS epidemic of 2002-2003 was a variety of epidemic models including general contact rates, quarantine, and isolation. These models can be viewed as age of infection epidemic models and analyzed using the approach of the full Kermack-McKendrick model. All these models share the basic properties that there is a threshold between disappearance of the disease and an epidemic outbreak, and that an epidemic will die out without infecting the entire population.     

Estimation of the reproduction number of dengue fever from spatial epidemic data

Dengue, a vector-borne disease, thrives in tropical and subtropical regions worldwide. A retrospective analysis of the 2002 dengue epidemic in Colima located on the Mexican central Pacific coast is carried out. We estimate the reproduction number from spatial epidemic data at the level of municipalities using two different methods: (1) Using a standard dengue epidemic model and assuming pure exponential initial epidemic growth and (2) Fitting a more realistic epidemic model to the initial phase of the dengue epidemic curve. Using Method I, we estimate an overall mean reproduction number of 3.09 (95% CI: 2.34,3.84) as well as local reproduction numbers whose values range from 1.24 (1.15,1.33) to 4.22 (2.90,5.54). Using Method II, the overall mean reproduction number is estimated to be 2.0 (1.75,2.23) and local reproduction numbers ranging from 0.49 (0.0,1.0) to 3.30 (1.63,4.97). Method I systematically overestimates the reproduction number relative to the refined Method II, and hence it would overestimate the intensity of interventions required for containment. Moreover, optimal intervention with defined resources demands different levels of locally tailored mitigation. Local epidemic peaks occur between the 24th and 35th week of the year, and correlate positively with the final local epidemic sizes (rho=0.92, P-value<0.001). Moreover, final local epidemic sizes are found to be linearly related to the local population size (P-value<0.001). This observation supports a roughly constant number of female mosquitoes per person across urban and rural regions.     

Functional outline of the epidemic process

The present study has shown that on the level of the parasitic system the epidemic process is a biological system, wherein the host population serves as the internal regulator, the mechanism of transmission serves as the external regulator and the parasite population, as the regulated object. The biological regulating mechanisms of the epidemic process have fundamental differences in the groups of infectious with various mechanisms of transmission, and the specific nature of the mechanism of transmission determines the peculiar features of the biological mechanism which governs the self-regulation of the epidemic process. In contrast, on a higher level of the organization of the epidemic process, i. e. on the level of the socio-ecological system, the epidemic process is a biosocial system, wherein the human society serves as the regulator, the parasitic system serves as the regulated object and the mechanism of transmission plays the role of the filter which determines the scope of social factors, most important in the regulation of the epidemic process in a given infection. The spontaneous regulation of the epidemic process is the freed forward channel from the regulator to the regulated object, and the controlled regulation is the feedback channel.     

Comparison of influenza outbreaks in the Republic of Kazakhstan and Russia induced by 2009 yearly new variant of A(H1N1) influenza virus

The aim of the work is the comparison of the epidemiology of influenza and acute respiratory virus infections(ARVI)in the Republic of Kazakhstan with the corresponding influenza epidemic in Russia induced by influenza pandemic virus A/California/07/2009 in 2009. Data on influenza and ARVI from the Republic of Kazakhstan and Federal Center of influenza was collected and investigated over the course of several weeks from hospitalized patients with the same diagnosis among all population and in age groups on 16 territories of Kazakhstan and in 49 major cities of Russia. The epidemic in Kazakhstan resembled the Russian epidemic in terms of its abnormally early beginning,expression of monoaetiology,the spread of the epidemic into all territories and start of the epidemics among adult population. High percentage of hospitalized people and lethal outcome were registered in this epidemic. Similarity of epidemic process character in corresponding border-line territories of both countries was found out.     

Evolutionary relationships of endemic/epidemic and sylvatic dengue viruses

Endemic/epidemic dengue viruses (DEN) that are transmitted among humans by the mosquito vectors Aedes aegypti and Aedes albopictus are hypothesized to have evolved from sylvatic DEN strains that are transmitted among nonhuman primates in West Africa and Malaysia by other Aedes mosquitoes. We tested this hypothesis with phylogenetic studies using envelope protein gene sequences of both endemic/epidemic and sylvatic strains. The basal position of sylvatic lineages of DEN-1, -2, and -4 suggested that the endemic/epidemic lineages of these three DEN serotypes evolved independently from sylvatic progenitors. Time estimates for evolution of the endemic/epidemic forms ranged from 100 to 1,500 years ago, and the evolution of endemic/epidemic forms represents relatively recent events in the history of DEN evolution. Analysis of envelope protein amino acid changes predicted to have accompanied endemic/epidemic emergence suggested a role for domain III in adaptation to new mosquito and/or human hosts.     

Large-sample analysis for a stochastic epidemic model and its parameter estimators

This paper considers the simplest stochastic model for the spread of an epidemic in a closed, homogeneously mixing population. Approximate methods are presented for calculating the probability distribution of the epidemic size (i.e. number of infected individuals). In fact, a functional central limit theorem and a large deviation principle for the epidemic size when the population increases are shown. These results enable us to both obtain a global approximation for the epidemic size and study asymptotic properties of other random variables depending on the complete history of the epidemic. As an application of our results, we derive two sequences of estimators for the contact rate and analyze their asymptotic behaviour.     

An SEI model for sarcoptic mange among chamois

We consider a simple model to study the dynamics of sarcoptic mange in a population of chamois. The epidemiological patterns observed during an epidemic in Italy are reconstructed and key parameters of the model are estimated from field data. In particular, we calculate the basic reproductive ratio R (0), a threshold value for chamois density for the occurrence of an epidemic and the speed of propagation of the epidemic wave. The model is then used to obtain indications on the effect of culling as a possible control measure in a closed population and extended to analyse the spatial diffusion of the epidemic. Our results are in agreement with mange epidemiology and observations, and suggest that intervention could be efficacious in reducing the impact of an epidemic.