Biomedical subjects

I M Longini

Publications and source records attributed to I M Longini.

At least 37 records · Page 2Linked to original sources

PubMed1994

Exposure efficacy and change in contact rates in evaluating prophylactic HIV vaccines in the field.

Field studies of the efficacy of prophylactic vaccines in reducing susceptibility rely on the assumption of equal exposure to infection in the vaccinated and unvaccinated groups. Differential exposure to infection could, however, be the goal of other types of intervention programme, or it could occur secondary to belief in the protective effects of a prophylactic measure, such as vaccination. We call this differential exposure the exposure efficacy, or behaviour efficacy. To study the relative contribution of unequal exposure to infection and differential susceptibility to the estimate of vaccine efficacy, we formulate a simple model that explicitly includes both susceptibility and exposure to infection. We illustrate this on the example of randomized field trials of prophylactic human immunodeficiency virus vaccines. Increased exposure to infection in the vaccinated group may bias the estimated reduction in susceptibility. The bias in the estimate depends on the choice of efficacy parameter, the amount of information used in the analysis, the distribution and level of protection in the population, and the imbalance in exposure to infection. Sufficient increase in contacts in the vaccinated could result in the vaccine being interpreted as having an immunosuppressive effect. Estimates of vaccine efficacy are generally more robust to imbalances in exposure to infection when the detailed history of exposure to infection can be used in the analysis or at high levels of protection. The bias also depends on the relationship between the distribution of vaccine protection and the distribution of behaviour change, which could differ between blinded and unblinded trials.

AIDS Vaccines↗

PubMed1994

Probability of female-to-male transmission of HIV-1 in Thailand.

The epidemic of human immunodeficiency virus type 1 (HIV-1) infection in Thailand has allowed an estimate to be made of the probability of female-to-male HIV-1 transmission per sexual contact. In a study of 1115 21-year-old male military conscripts, of whom 77 (6.9%) were HIV-1 seropositive, sex with female prostitutes was identified as the principal mode of HIV-1 transmission. With a mathematical model including data on conscript's age at first sexual contact, frequency of sex with female prostitutes, and province of origin; as well as province-specific HIV-1 seroprevalence of prostitutes, we estimated the probability of HIV-1 transmission per sexual contact to be 0.031 (95% confidence limits [CL] 0.025-0.040). Allowing for random error in the self-reported frequency of contacts, the estimate was 0.056 (95% CL 0.041-0.075). The transmission probability was significantly greater among men with a history of sexually-transmitted diseases. These estimates are substantially higher than analogous estimates made in North America. This high per-act probability of heterosexual transmission helps to explain the rapid spread of HIV-1 in the emerging epidemic in Thailand and perhaps in other countries where HIV-1 transmission is predominantly heterosexual.

Adult↗

PubMed1994

The ecological effects of individual exposures and nonlinear disease dynamics in populations.

To describe causally predictive relationships, model parameters and the data used to estimate them must correspond to the social context of causal actions. Causes may act directly upon the individual, during a contact between individuals, or upon a group dynamic. Assuming that outcomes in different individuals are independent puts the causal action directly upon individuals. Analyses making this assumption are thus inappropriate for infectious diseases, for which risk factors alter the outcome of contacts between individuals. Transmission during contact generates nonlinear infection dynamics. These dynamics can so attenuate exposure-infection relationships at the individual level that even risk factors causing the vast majority of infections can be missed by individual-level analyses. On the other hand, these dynamics amplify causal associations between exposure and infection at the ecological level. The amplification and attenuation derive from chains of transmission initiated by exposed individuals but involving unexposed individuals. A study of household exposure to the only vector of dengue in Mexico illustrates the phenomenon. An individual-level analysis demonstrated almost no association between exposure and infection. Ecological analysis, in contrast, demonstrated a strong association. Transmission models that are devoid of any sources of the ecological fallacy are used to illustrate how nonlinear dynamics generate such results.

Dengue↗

PubMed1994

Role of the primary infection in epidemics of HIV infection in gay cohorts.

A review of the data on infectivity per contact for transmission of the HIV suggests that the infectivity may be on the order of 0.1-0.3 per anal intercourse in the period of the initial infection, 10(-4) to 10(-3) in the long asymptomatic period, and 10(-3) to 10(-2) in the period leading into AIDS. The pattern of high contagiousness during the primary infection followed by a large drop in infectiousness may explain the pattern of epidemic spread seen in male homosexual cohorts in the early years of the epidemic. Simulations of cohorts of homosexual males, using that range of parameter values, indicate the following: (a) The initial fast rise and then more or less rapid flattening of the incidence curve of seropositives is primarily due to rapid initial spread, yielding a group of infecteds all of whom pass into the low infectivity asymptomatic period at close to the same time. All this occurs only if the basic reproduction number for the primary infection is > 1. (b) The behavioral changes that have been reported all started after the incidence of new infections began to fall, too late to have a major effect on the initial rise. The behavioral changes had a major effect in slowing down the subsequent rise in the number of seropositives. (c) High activity groups play an important role in the early rapid rise of the epidemic. However, it is not likely that the rapid decrease in rate of growth of seropositives is solely due to saturation of these very high activity groups. Although the evidence for this interpretation of the role of the primary infection is not conclusive, its implications for prevention and for vaccine trials are so markedly different from those of other interpretations that we consider it to be an important hypothesis for further testing.

Cohort Studies↗

PubMed1994

Estimation of incidence of HIV infection using cross-sectional marker surveys.

Methods of estimating the probability density function of infection times for a population, using serial cross-sectional measurements of a marker of disease progression, are presented. The infection time distribution may be calculated back to the beginning of the epidemic, if it is possible to sample individuals who were infected at the beginning of the epidemic; otherwise, under a Markov assumption, the infection time distribution may be calculated conditional on infection after sampling has begun. In either case, the proportion of prevalent cases infected in an arbitrary time interval between the onset and termination of sampling may be measured. Data from the San Francisco Men's Health Study are analyzed; the infection time distribution compares well with that estimated by Bacchetti (1990, Journal of the American Statistical Association 85, 1002-1008) using stored sera from several San Francisco cohort studies.

Biomarkers↗

PubMed1993

Effect of routine use of therapy in slowing the clinical course of human immunodeficiency virus (HIV) infection in a population-based cohort.

Clinical trials have shown that the prophylactic use of zidovudine and aerosolized pentamidine (or other antibiotics used as prophylaxis against Pneumocystis carinii pneumonia) in acquired immunodeficiency syndrome (AIDS)-free human immunodeficiency virus (HIV)-infected persons delays the development of AIDS, but the effectiveness of such therapy in general use in the population still remains largely undocumented. To help answer this question, the authors estimate the effectiveness of this therapy in a population-based cohort of HIV-infected homosexual and bisexual men in San Francisco. The authors use a continuous-time Markov process to model the decline of CD4+ T-lymphocytes (T4-cells) measured in cells/microliter in HIV-infected persons. The model partitions the HIV (type 1) infection period into six progressive T4-cell count intervals (stages), followed by a seventh stage: AIDS diagnosis. The authors use maximum likelihood methods to fit the model to the observed transitions for 428 HIV-infected men during June 1984 to March 1991, from the San Francisco Men's Health Study. Since zidovudine was not widely used before 1988, the model has a component that controls for calendar time-related biases. The fitted model provides statistical estimates and confidence intervals for measuring therapy effectiveness. The authors estimate that prophylactic therapy reduces the progression rate from stage 4 (T4-cell count, 350-499) to stage 5 (T4-cell count, 200-349) by a factor of 0.26 (95% confidence interval (CI) -0.22 to 0.55); from stage 5 to stage 6 (T4-cell count < 200) by a factor of 0.33 (95% CI 0.04-0.54); and from stage 6 to 7 (AIDS) by a factor of 0.62 (95% CI 0.47-0.73). In addition, therapy started by an HIV-infected person in stage 4 is estimated to reduce the risk of developing AIDS by a factor of 0.83 (95% CI 0.46-0.94) at 6 months and 0.68 (95% CI 0.35-0.89) at 24 months after entering stage 4. Therapy started by HIV-infected persons in more advanced stages is estimated to reduce the risk of developing AIDS by factors ranging from 0.70 (95% CI 0.39-0.90), early in stage 5, to 0.28 (95% CI 0.14-0.45), late in stage 6. Thus, the prophylactic use of zidovudine and pentamidine in routine medical care has a strong, consistent, and significant effect in slowing the clinical course of HIV infection in a population-based cohort.

AIDS-Related Opportunistic Infections↗

PubMed1993

Measuring vaccine efficacy from epidemics of acute infectious agents.

A good measure of field vaccine efficacy should evaluate the direct protective effect of vaccination on the person who receives the vaccine. The conventional estimator for vaccine efficacy depends on population level factors that are either unrelated or indirectly related to the direct biological action of the vaccine on persons, including population structure, duration of the study, the fraction vaccinated, and herd immunity, that is, indirect effects. Indirect effects can cause the conventional vaccine efficacy estimator to be inaccurate. We review alternative vaccine efficacy estimators that control for indirect effects at the population level. Thus, they are more accurate than the conventional estimator. We use epidemic simulations to explore the robustness of the conventional and proposed estimators under different field conditions. In addition, we apply the different vaccine efficacy estimators to data from a measles epidemic in Muyinga, Burundi.

Burundi↗

PubMed1993

Estimates of the US health impact of influenza.

OBJECTIVES: Data from the Tecumseh Community Health Study were used to estimate excess morbidity owing to influenza, and results were compared with estimates made previously using different methodology for an Institute of Medicine report. METHODS: Study participants from Tecumseh, Michigan, were classified as infected or noninfected based on laboratory results. The excess numbers of respiratory illnesses, respiratory illness days, and bed and restricted activity days experienced by the infected compared with the noninfected were estimated. RESULTS: The number of excess influenza-related respiratory illnesses was lower than that estimated in the Institute of Medicine report, in which all illnesses of certain characteristics occurring during an influenza season were attributed to influenza. It is now estimated that the US population under 20 years of age experiences a yearly average of 13.8 to 16.0 million influenza-related excess respiratory illnesses; for older individuals, the yearly estimate is 4.1 to 4.4 million excess illnesses. CONCLUSIONS: For public health purposes, estimates of excess morbidity as well as of total morbidity associated with influenza should be used in setting health priorities.

Adolescent↗

PubMed1992

Interpretation and estimation of vaccine efficacy under heterogeneity.

Interpretation and estimation of vaccine efficacy is complicated when the vaccine effect is heterogeneous across vaccinated strata. If a person has a certain susceptibility, or probability of becoming infected conditional on a specified exposure to infection, then one effect of a vaccine would be to reduce that susceptibility, possibly to zero. Vaccine efficacy is a function of the relative susceptibilities in the vaccinated and unvaccinated persons. Under heterogeneity of vaccine effect, a general expression for a summary vaccine efficacy parameter is a function of the vaccine efficacy in the different vaccinated strata weighted by the fraction of the vaccinated subpopulations in each stratum. Interpretation and estimability of the summary vaccine efficacy parameter depends on whether the strata are identifiable, and whether the heterogeneity is host- or vaccine-related. Bounds are derived for the summary vaccine efficacy when the strata are not identifiable for the case of an outbreak of an acute infectious disease. The upper bound assumes that everyone is equally affected by the vaccine, and the lower bound assumes that some are completely protected while others have no protection. The biologic interpretation of the two bounds is different.

Disease Susceptibility↗

PubMed1992

Estimating the stage-specific numbers of HIV infection using a Markov model and back-calculation.

The back-calculation method has been used to estimate the number of HIV infections from AIDS incidence data in a particular population. We present an extension of back calculation that provides estimates of the numbers of HIV infectives in different stages of infection. We model the staging process with a time-dependent Markov process that partitions the HIV infectious period into the following progressive stages and/or substages: stage 1, infected but antibody negative; substages 2-3; antibody positive but asymptomatic; substages 4-6, pre-AIDS symptoms and/or abnormal haematologic indicator, stage 7, clinical AIDS. We also model an eight stage, decreased due to AIDS. The model allows for time-dependent treatment effects that slow the rate of progression in substages 4-7. We use the estimated AIDS incubation period distribution for the Markov model in back calculation from AIDS incidence data to estimate the total number of HIV infections and the parameters of the infection probability distribution. We then use these estimates in the Markov model to estimate the stage-specific numbers of HIV infections over the course of the epidemic in the population under study. Example calculations employ data for epidemic in San Francisco City, Clinic Cohort.

Cause of Death↗

PubMed1992

A discrete-time model for the statistical analysis of infectious disease incidence data.

A discrete-time model is devised for the per-time-unit distribution of infectious disease cases in a sample of households. Using the time at which an individual is identified (e.g., when illness symptoms appear) as a marker for being infected, the probabilities of becoming infected from the community or from a single infectious household member are estimated for various risk factor levels. Maximum likelihood procedures for estimating the model parameters are given. An individual may be classified with regard to level of susceptibility and level of infectiousness. The model is fitted to a combination of symptom and viral culture data from a rhinovirus epidemic in Tecumseh, Michigan. In general, it is observed that decreasing risk of infection is associated with increasing age.

Adult↗

PubMed1991

Assessing risk factors for transmission of infection.

Commonly used measures of effect, such as risk ratios and odds ratios, may be quite biased when used to assess the effect of factors that alter transmission risks given exposure to infected individuals. This is demonstrated in a simulation model involving a higher-risk behavior and a lower-risk behavior affecting the sexual transmission of human immunodeficiency virus. The bias arises because population contact patterns between higher-risk and lower-risk persons change their relative probabilities of exposure to an infected individual as an epidemic progresses. The assessment of contact patterns is thus central to risk assessment for contagious diseases. A new formulation of selective mixing presented here, together with a structured mixing specification of the social settings of contact, provides a theoretic framework for the investigation of contact pattern determinants.

Bias↗

PubMed1991

Determinants and predictors of dengue infection in Mexico.

A national serosurvey was conducted in Mexico from March to October 1986 to identify predictors of dengue transmission and target areas at high risk of severe annual epidemics. A total of 3,408 households in 70 localities with populations less than 50,000 were randomly sampled, and serology was obtained from one subject under age 25 years in each household. When comparing exposure and infection frequencies across the 70 communities, the authors found that median temperature during the rainy season was the strongest predictor of dengue infection, with an adjusted fourfold risk in the comparison of 30 degrees C with 17 degrees C. High temperatures increase vector efficiency by reducing the period of viral replication in mosquitoes. The proportion of houses in a community with larva on the premises was significantly associated with the community proportion infected (odds ratio (OR)adj = 1.9; 95% confidence interval (CI) 1.4-2.5), as was the proportion of households with uncovered water containers present (ORadj = 1.9; 95% CI 1.4-2.7). Because these factors have effects beyond the individual household and subjects infected from them create a risk for other subjects, both analyses of effects and organization of control efforts must be at the community level. A predictive model was constructed using the community level risk factors to classify communities as being at high, medium, or low risk of experiencing an epidemic; 57% of these communities were correctly classified using this model.

Adult↗

PubMed1991

Direct and indirect effects in vaccine efficacy and effectiveness.

In 1915, Greenwood and Yule noted that for valid vaccine efficacy studies, exposure to infection in the vaccinated and the unvaccinated must be equal (Proc R Soc Med 1915;8(part 2):113-94). The direct effect of a vaccine, however, needs to be defined by the protection it confers given a specific amount of exposure to infection, not just a comparable exposure. In this paper, two classes of parameters are distinguished along lines differing from the conventional distinction between efficacy and effectiveness. Efficacy parameters attempt to control for exposure to infection and represent direct effects on individuals. Direct effectiveness parameters represent a mixture of direct effects on individuals and indirect effects in the population.

Environmental Exposure↗

PubMed1991

Estimation of vaccine efficacy in outbreaks of acute infectious diseases.

In a previous paper we defined the efficacy of a vaccine as 1-beta 1/beta 0, where beta 0 is the instantaneous probability of transmission of infection to an unvaccinated person exposed to a single infectious person, and beta 1 is similarly defined for a vaccinated person. We showed that under the conditions of an outbreak of an acute, directly transmitted infectious disease in a homogeneous and randomly mixing population, an estimate of this measure of vaccine efficacy is 1-[1n(1-A1)/1n(1-A0)], where A0 and A1 are the observed final attack rates among unvaccinated and vaccinated persons, respectively. In the present work we present an approximation for the standard error of this estimator, accounting for both the sampling and process variation. We extend the results of our previous paper to a stratified population, where the strata correspond to different levels of susceptibility and may have different vaccination coverage. We also consider populations that consist of small units (for example, households) where individuals mix primarily in these units. In this case, definition of vaccine efficacy is in terms of the within-unit transmission probabilities and is estimable by using transmission models for infectious diseases. We apply the estimation methods described above to data from influenza and measles outbreaks. We also examine, via a stochastic simulation study, the robustness of the vaccine efficacy estimators under various population structures and mixing patterns.

Adolescent↗

PubMed1991

A simulation model of AIDS in San Francisco: I. Model formulation and parameter estimation.

A model is formulated for the spread of the human immunodeficiency virus (HIV) and the subsequent development of acquired immunodeficiency syndrome (AIDS) in the population of homosexual men in San Francisco. The dynamic simulation model includes sexually very active and active subpopulations, migration, and a staged progression of HIV-infected persons to AIDS and death. Numerous data sources are used to estimate parameter values in the model. In a companion paper, simulations using the model and parameter estimates are found that are consistent with HIV and AIDS incidence data.

Acquired Immunodeficiency Syndrome↗

PubMed1991

Measures of the effects of vaccination in a randomly mixing population.

Vaccine efficacy in the field is often derived from the relative attack rates in the vaccinated and unvaccinated after an outbreak. In this paper, vaccine efficacy is defined in terms of the probability that the infectious agent is transmitted from an infected to a susceptible person, and a method for estimating it from the usual attack rate data is given. We explore two mechanisms of vaccine action defined by Smith et al, but include an underlying dynamic epidemic model of an acute directly transmitted disease. We show analytically that under the model in which the vaccine mechanism reduces the probability of infection given a certain exposure, vaccine efficacy based on the relative attack rates underestimates the protective effect of the vaccine based on the relative transmission probabilities. Under the other model in which the vaccine mechanism offers complete protection to a certain proportion of those vaccinated, and no protection to the other vaccinated proportion, the vaccine efficacy based on the relative attack rates will equal that based on the transmission probabilities. Parameters for the effectiveness of a vaccination programme are defined in terms of the direct and indirect benefit to a single person as well as the total and average benefit to the entire population, and derived from the dynamic model for an outbreak of an acute directly transmitted disease. These effects can also be estimated without an actual separate unvaccinated population, independent of assumptions about the vaccine mechanism. The variation of these measures as functions of the fraction of vaccinated people in the population is explored numerically.

Cohort Studies↗

PubMed1991

The dynamics of CD4+ T-lymphocyte decline in HIV-infected individuals: a Markov modeling approach.

We modeled the decline of CD4+ T-lymphocytes (T4 cells) in HIV-infected individuals with a continuous-time Markov process. The model partitions the HIV infection period into six progressive T4-cell count intervals (states), followed by a seventh state: a definitive HIV-infection end point, i.e., AIDS diagnosis or Walter Reed stage 6 (opportunistic infections). The Markov model was used to estimate the state-specific progression rates from data as functions of important progression cofactors. We applied the model to data on 1,796 HIV-positive individuals in the U.S. Army. The estimated mean waiting time from seroconversion to when the T4-cell count persistently drops below 500/mm3, but is greater than 349/mm3, is 4.1 years, and the waiting time to a T4-cell count of less than 200/mm3 is estimated at 8.0 years. The estimated rate of T4-cell decline was higher for HIV-infected individuals with initially high numbers of T4 cells, but the estimated rate of decline remains relatively uniform when the T4-cell count dropped persistently below 500/mm3. The opportunistic infection incubation period, i.e., the time from seroconversion to opportunistic infection diagnosis, is estimated at 9.6 years. Age is found to be an important cofactor. The estimated mean opportunistic infection incubation periods are 11.1, 10.0, and 8.9 years for the youngest (less than or equal to 25 years old), the middle (26-30 years old), and the oldest (greater than 30 years old) age groups, respectively.(ABSTRACT TRUNCATED AT 250 WORDS)

Acquired Immunodeficiency Syndrome↗