The Tecumseh Community Health Study.
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Adoption↗
Biomedical subjects
I M Longini
Publications and source records attributed to I M Longini.
Models of epidemics and endemicity in genetically variable host populations.
A discrete time genetics model is developed for populations that are undergoing selection due to infectious disease. It is assumed that the generation time of the host and infectious agent are not-synchronous and that only the host population is evolving. Two classes of epidemic processes are considered. The first class is for infectious agents that confer immunity following infection, while the second class is for those that do not confer immunity. The necessary and sufficient conditions are found in order for the disease to persist in a stable polymorphic host population. These conditions are shown to depend on the density of susceptibles, the selection coefficients, and the severity and class of the disease process.
Alleles↗
The Tecumseh study. XII. Enteric agents in the community, 1976-1981.
Enteric illnesses in residents of Tecumseh, Michigan, were studied from 1976 to 1981. The frequency of illness among adults and children increased each year in the late autumn, usually in November. This peak of illness preceded the main period of appearance of the rotaviruses, which were less regularly associated with another peak of illness. Rotaviruses were identified in 3.8% of all stool specimens collected; in specimens from children under two years of age, the annual rate of rotavirus identification was 10.4%. All rotaviruses were identified during the period from late December to early April. Bacterial pathogens were isolated from 3.3% of stool specimens, with no concentration in any age group or season. However, most enteric illnesses in the community were not associated with recognized pathogens. Testing of blood specimens collected in 1976-1978 by complement fixation confirmed the seasonal pattern of rotavirus activity. Rotavirus infections were documented in all age groups, even in older adults, and were associated with symptomatic illness.
Adenoviruses, Human↗
Estimating household and community transmission parameters for influenza.
A maximum likelihood procedure is given for estimating household and community transmission parameters from observed influenza infection data. The estimator for the household transmission probability is an improvement over the classical secondary attack rate calculations because it factors out community-acquired infections from true secondary infections. The mathematical model used does not require the specification of infection onset times and, therefore, can be used with serologic data which detect asymptomatic infections. Infection data were derived by serology and virus isolation from the Tecumseh Respiratory Illness Study and the Seattle Flu Study for the years 1975-1979. Included were seasons of influenza B and influenza A subtypes H1N1 and H3N2. The transmission characteristics of influenza B and influenza A(H3N2) and A(H1N1) outbreaks during this period are compared. Influenza A(H1N1), A(H3N2) and influenza B are found to be in descending order both in terms of ease of spread in the household and intensity of the epidemic in the community. Children are found to be the main introducers of influenza into households. the degree of estimation error from the misclassification of infected and susceptible individuals is illustrated with a stochastic simulation model. This model simulates the expected number of detected infections at different levels of sensitivity and specificity for the serologic tests used. Other sources of estimation error, such as deviation from the model assumption of uniform community exposure and the possible presence of superspreaders, are also discussed.
Epidemiologic Methods↗
Household and community transmission parameters from final distributions of infections in households.
A model is devised for the distribution of the total number of cases in households from a homogeneous community. In the model, community-acquired infection serves as a source of initial infection within households as well as of possible further cases. In addition, infected household members can infect others in the household. Maximum likelihood procedures for the model parameters are given. The model is fitted to symptom data on influenza and the common cold. Influenza seems to spread more easily in the community than within the household, while the opposite may be the case for the common cold. The model, which does not require specification of the time of onset of infection for individuals, can be fitted to serological data; this would provide a more accurate measure of household infection than the symptom data used.
Common Cold↗
Modelling the female-to-male per-act HIV transmission probability in an emerging epidemic in Asia.
The per-sexual-act probability of transmission of the human immunodeficiency virus type 1 (HIV) from an infected person to a susceptible sex partner can be determined from a simple model if the number of contacts each study participant has with infected partners is known. The unusual epidemiologic situation in the emerging HIV epidemic in Thailand allowed this quantity to be estimated from a cross-sectional study of young men conscripted into the Thai military in 1991. Although the simple model does not fit the data, an errors-in-variables approach provides a model with adequate fit. Other sources of lack of fit, including heterogeneity of the transmission probability, are discussed. With adjustment for measurement error, the per-act probability is estimated to be 0.056, an order of magnitude higher than similar estimates in North America. Because data indicate that recently infected persons may be more infectious, and because extensive HIV transmission in Thailand began in 1988, this difference may be due, in part, to a higher proportion of recently infected individuals in the emerging Thai epidemic from 1988 to 1991.
Adult↗
Estimation of vaccine efficacy from epidemics of acute infectious agents under vaccine-related heterogeneity.
A stochastic epidemic model is formulated for the study of the protective effects of vaccination in a population that is stratified by vaccine-related factors. The epidemic model is transformed into a counting process, and then martingale-based methods are used to provide estimators of vaccine efficacy and their variances. Following an example, various extensions of the model are discussed.
Acute Disease↗
[Procedures for estimating transmission parameters from influenza epidemics: use of serological data].
A maximum likelihood procedure is given for estimating household and community transmission parameters from observed influenza infection data. The mathematical model used does not require the specification of infection onset times and, therefore, can be used with serological data which detect asymptomatic infections. Infection data was derived by serology and virus isolation from the Tecumseh Respiratory Illness Study and the Seattle Flu Study for the years 1975-1979. Influenza A (H1N1), A (H3N2), and B viruses were found to be in descending order both in terms of ease of spread in the household and intensity of the epidemic in the community except when two strains co-circulate. Children are found to be the main introducers of influenza into households.
Adult↗