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L Sattenspiel

Publications and source records attributed to L Sattenspiel.

9 recordsLinked to original sources
PubMed2000

Tropical environments, human activities, and the transmission of infectious diseases.

Throughout recent history, the tropical regions of the world have been affected more severely by infectious diseases than the temperate world. Much of the success of infectious diseases in that region is due to both biological and environmental factors that encourage high levels of biodiversity in hosts, vectors, and pathogens, and social factors that compromise efforts to control diseases. Several of these factors are described. Discussion then shifts to specific types of host-pathogen relationships. The most important of these in the tropics is the relationship between humans, a pathogen, and a vector that carries the pathogen from one human to another. Mosquitoes are the vector responsible for the transmission of many vector-borne human diseases. Characteristics of mosquito-human interactions are described, including cultural behaviors humans have developed that both increase the chances of transmission and help to limit that transmission. The transmission of water-borne diseases, fecal-oral transmission, zoonotic diseases, respiratory illnesses, and sexually transmitted diseases are also discussed. Attention is paid to how diseases with these modes of transmission differ in characteristics and importance in tropical human populations compared to those in temperate regions. Following this general discussion, three case studies are presented in some detail. The diseases chosen for the case studies include cholera, lymphatic filariasis, and dracunculiasis (guinea worm). These three case studies taken together provide examples of the diversity of human host-pathogen interactions as well as ways that human activities have both promoted their spread and helped to control them. The transmission of all three diseases is related to the nature and quality of water sources. The transmission of cholera, a water-borne disease, is related to sanitation practices, physical characteristics of the environment such as temperature and humidity, and modern shipping practices. Lymphatic filariasis, a mosquito-borne disease, has increased in frequency in parts of Africa in recent decades as a consequence of large-scale agricultural development projects that have shifted the nature and quantity of water sources and potential mosquito breeding sites. Dracunculiasis is transmitted by a small crustacean that contaminates sources of drinking water. Because its transmission can be prevented by a simple change in human behavior, filtering all water with a small piece of cloth before using it, dracunculiasis has been the focus of a major eradication effort that is near success.

Agriculture↗
PubMed1998

Structured epidemic models and the spread of influenza in the central Canadian subarctic.

Patterns of transmission of infectious diseases within and among populations are strongly affected by population structure, which can either facilitate or limit interactions among people from different groups. Results from several theoretical studies show that nonrandom mixing among subgroups can affect the time when an infectious disease is introduced to the population, the speed of propagation of the disease, and the severity of an epidemic. Because many of these models focus on the effects of population structure, they are functionally similar to models used to describe the genetic structure of a population. One major difference between genetic models and epidemic models is that genetic models, with a time scale of the order of generations, incorporate migrations (or permanent movement) among subgroups, whereas epidemic models, with a time scale of the order of days or weeks, must incorporate short-term mobility among subgroups. Such mobility can be included in models for epidemic spread by explicitly incorporating the process by which residents from different locations interact with one another. We present a derivation of a mobility model for epidemic processes and apply it to the spread of the 1918-1919 influenza epidemic among the Cree and Métis people associated with three Hudson's Bay Company posts in the central Canadian Subarctic. The model distinguishes mobility from population effects. Results indicate that social organization (population effects) and social responses to the epidemic were more important than movement patterns (mobility) in explaining the differential impact of this virgin soil epidemic on the three study communities.

Canada↗
PubMed1993

Geographic spread of measles on the island of Dominica, West Indies.

Because of the short incubation period of most acute infectious diseases, short-term and daily mobility are more important than permanent and seasonal migration for the spread of these diseases. Yet most studies of population mobility focus on permanent or semipermanent change of residence. Here, we describe the results from a field study conducted on the island of Dominica, West Indies, during the summers of 1989 and 1990 and the winter of 1991. The study was designed to collect data on short-term mobility rather than migration. These mobility data are linked with data on the patterns of measles transmission during a 1984 epidemic. Three-hundred five individuals from all parts of the island were interviewed about their daily travel patterns, their travel off the island, and the travel of members of their immediate family. In addition to these respondents, interviews were conducted with representatives of most of the major occupations that involve travel in the course of a workday. Data were also collected on the number and type of motor vehicles traveling along various routes on the island and on travel of native residents to the capital city, Roseau, to buy or sell at the major weekly market. Analysis of the interviews shows that travel within the island is clearly nonrandom. For example, almost everyone interviewed traveled to Roseau at least once a month, but 40% of the respondents had never been to any of the major villages in the Grand Bay Health District, which is only about a half-hour from Roseau. Patterns of disease transmission have been directly affected by these mobility patterns. The measles epidemic in 1984 apparently did not reach the Grand Bay Health District, even though all other areas of the island experienced significant rates of infection. Analysis of reasons for the relative isolation of the Grand Bay Health District indicates the importance of transportation patterns, as well as social, cultural, and geographic factors, to the disease transmission patterns throughout the island.

Adolescent↗
PubMed1990

The effects of population structure on the spread of the HIV infection.

A model for the spread of human immunodeficiency virus (HIV) in a population of male homosexuals is presented. The population is divided into five groups on the basis of degree of sexual activity. Within each group, the individuals are classified as 1) susceptible; 2) infective; or 3) removed because of a lack of sexual activity associated with advanced acquired immunodeficiency disease (AIDS). The infective individuals are further subdivided into four stages of infection. Analyses of the model address two questions with regard to the spread of HIV: (1) What is the effect of level of sexual activity on an individual's risk for infection, and (2) What is the effect that assumptions about mixing between groups have on both individual risk and transmission throughout a population? Results from analyses using a number of different parameter estimates show that increased levels of sexual activity increase the likelihood that an individual will become infected. In addition, the initial spread of the disease is markedly affected by variation in the amount of contact among individuals from different subpopulations. The steady-state incidence of the disease is not markedly affected by variation in the contact patterns, but the size of the steady-state population and therefore the proportion of infected individuals in the population does vary significantly with changes in the degree of mixing among subpopulations. These results show clearly the sensitivity of model outcomes to variation in the patterns of contact among individuals and the need for better data on such interactions to aid in understanding and predicting the spread of HIV.

HIV Infections↗
PubMed1988

Spread and maintenance of a disease in a structured population.

The patterns of interactions among different groups of individuals in a structured population is an important factor affecting the ease of establishment of a disease and the rate of spread of the disease in a population. A model for the spread of a disease in such a population is described. The model considers two levels of interaction: interactions between individuals within a subpopulation because of geographic proximity, and interactions between individuals of the same or different sub-populations because of attendance at common social functions. Analysis of the model leads to sufficient conditions which determine maximum subpopulation sizes which allow the disease to be maintained in the population. These conditions are inequalities relating the removal rate of infectives to the infection rate of susceptibles. Results are discussed for both idealized movement patterns and for the spread of hepatitis A among day care centers in Albuquerque, New Mexico. In addition, the basic structures of the contact matrices necessary to extend the model to deal with vector-borne diseases and with sexually transmitted diseases are discussed.

Hepatitis A↗
PubMed1988

Sexual partner selectiveness effects on homosexual HIV transmission dynamics.

Deterministic simulation models are used to show that HIV transmission dynamics in homosexual populations can be strongly affected by sexual partner selectiveness. The type of selectiveness or biased mixing examined is where individuals with similar new partnership formation rates are more likely to form a pair than would be expected by chance. The effect of such selectiveness could be strong even when the total number and distribution of new sexual partnerships and sex acts remains constant. This means that in order to predict the future course of HIV transmission and identify the populations at highest risk, we must have information not only on the frequency of new sexual partnerships and types of sex acts, but also on who has sex with whom. Given high sexual partner selectiveness, some groups of homosexuals with low rates of sex and new sex partners would take many decades before a single introduction would generate an epidemic. Epidemics in these groups can be markedly accelerated by only modest contact with higher risk groups. Even in very low activity groups, which if isolated would have no epidemic, an important proportion of their members can be infected when they are not selective. The relative risks of AIDS in groups making high numbers of new sexual partnerships compared to groups making low numbers are markedly affected by sexual partner selectiveness. The models developed were examined using information collected in 1984 from the Coping and Change Study in collaboration with the Chicago Multicenter AIDS Cohort Study. This population was divided into activity groups by the rate at which individuals established new sexual partnerships and then a structure of new sexual partnerships between these activity groups was defined consistent with available data. Even without introducing any behavior change in the models, the proportion of the homosexual population infected was seen to level off temporarily at around 50% after several years as a consequence of saturation in the high risk groups when lower risk groups were not yet being consumed by the epidemic process. Most sex in the study population is casual or anonymous. The sample selection procedures were biased toward individuals who engage in such sex. There is, however, a large group of individuals that avoids the casual and anonymous sex scene. Simulated epidemics indicated that under a variety of conditions, the population that does not engage in casual and anonymous sex could experience an epidemic of HIV infection quite some time after the epidemic in the population that does has waned.(ABSTRACT TRUNCATED AT 400 WORDS)

Acquired Immunodeficiency Syndrome↗
PubMed1987

Epidemics in nonrandomly mixing populations: a simulation.

Two stochastic, discrete-time simulation models for the spread of an epidemic through a population are presented. The models explore the effects of nonrandom mixing within the population and are based on an SIR epidemic model without vital statistics. They consider a population of preschool children, some of whom attend child care facilities. Disease transmission occurs both within the home neighborhood and at the child care facility used, if any. The two models differ in population size used, population density, the proportions of children using different kinds of care, and the functions used for calculating the probability of disease transmission. Results are presented for seven different variables--length of the epidemic in weeks, number of cases, number of cases in each kind of care (two day care centers, private homes, and children staying at home), and the number of private home providers affected by the epidemic. In addition, the distribution of total epidemic size and the progress of an epidemic are estimated from 25 epidemic trials. The effects of the location of homes of initial cases, the type of care used by initial cases, and the density of the population are discussed. Results from the simulation confirmed the importance of type of care on the risk for disease transmission. Results from all runs of the simulation showed that children who attended a day care center were most likely to become infected, children who went to a private home were intermediate, and children who did not use any day care facility were at the lowest risk. The size and length of the epidemics were related to the presence of the disease in day care centers, regardless of the location of the initial case, and the time at which the disease entered the center(s). The simulations also showed that the geographical distribution of the homes of children attending a particular center was a critical feature involved in the production of epidemics. The center with more widely distributed homes of students was less likely to experience a major epidemic than the center with clustering of student's homes within a neighborhood. This indicates that it is not simply attendance at a day care center that is critical for disease spread, but that the nature of the population of children attending a center is also of critical importance in the actual risk for disease spread within the center. These results are discussed with reference to the spread of hepatitis A among day care centers in Albuquerque, New Mexico.

Child Day Care Centers↗
PubMedDate not supplied

A structured epidemic model incorporating geographic mobility among regions.

A model for the spread of infectious diseases among discrete geographic regions is presented that incorporates a mobility process that describes how contact occurs between individuals from different regions. The general formulation of the mobility process is described, and it is shown that the formulation encapsulates a range of mobility behavior from complete isolation of all regions (no mobility) to permanent migration between regions. It is then shown how this mobility process fits into an SIR epidemic model, and two examples are given extending its use. The examples include a model for disease transmission in a population with two distinct mobility patterns operating and a model developed to describe a 1984 measles epidemic on the Caribbean island of Dominica.

Communicable Diseases↗