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Background: We hypothesized that mass distribution of a broad-spectrum antibiotic agent to preschool children would reduce mortality in areas of sub-Saharan Africa that are currently far from meeting the Sustainable Development Goals of the United Nations.Methods: In this cluster-randomized trial, we assigned communities in Malawi, Niger, and Tanzania to four twice-yearly mass distributions of either oral azithromycin (approximately 20 mg per kilogram of body weight) or placebo. Children 1 to 59 months of age were identified in twice-yearly censuses and were offered participation in the trial. Vital status was determined at subsequent censuses. The primary outcome was aggregate all-cause mortality; country-specific rates were assessed in prespecified subgroup analyses.Results: A total of 1533 communities underwent randomization, 190,238 children were identified in the census at baseline, and 323,302 person-years were monitored. The mean (±SD) azithromycin and placebo coverage over the four twice-yearly distributions was 90.4±10.4%. The overall annual mortality rate was 14.6 deaths per 1000 person-years in communities that received azithromycin (9.1 in Malawi, 22.5 in Niger, and 5.4 in Tanzania) and 16.5 deaths per 1000 person-years in communities that received placebo (9.6 in Malawi, 27.5 in Niger, and 5.5 in Tanzania). Mortality was 13.5% lower overall (95% confidence interval [CI], 6.7 to 19.8) in communities that received azithromycin than in communities that received placebo (P<0.001); the rate was 5.7% lower in Malawi (95% CI, -9.7 to 18.9), 18.1% lower in Niger (95% CI, 10.0 to 25.5), and 3.4% lower in Tanzania (95% CI, -21.2 to 23.0). Children in the age group of 1 to 5 months had the greatest effect from azithromycin (24.9% lower mortality than that with placebo; 95% CI, 10.6 to 37.0). Serious adverse events occurring within a week after administration of the trial drug or placebo were uncommon, and the rate did not differ significantly between the groups. Evaluation of selection for antibiotic resistance is ongoing.Conclusions: Among postneonatal, preschool children in sub-Saharan Africa, childhood mortality was lower in communities randomly assigned to mass distribution of azithromycin than in those assigned to placebo, with the largest effect seen in Niger. Any implementation of a policy of mass distribution would need to strongly consider the potential effect of such a strategy on antibiotic resistance. (Funded by the Bill and Melinda Gates Foundation; MORDOR ClinicalTrials.gov number, NCT02047981 .). [ABSTRACT FROM AUTHOR]

Compartmental model diagrams have been used for nearly a century to depict causal relationships in infectious disease epidemiology. Causal directed acyclic graphs (DAGs) have been used more broadly in epidemiology since the 1990s to guide analyses of a variety of public health problems. Using an example from chronic disease epidemiology, the effect of type 2 diabetes on dementia incidence, we illustrate how compartmental model diagrams can represent the same concepts as causal DAGs, including causation, mediation, confounding, and collider bias. We show how to use compartmental model diagrams to explicitly depict interaction and feedback cycles. While DAGs imply a set of conditional independencies, they do not define conditional distributions parametrically. Compartmental model diagrams parametrically (or semiparametrically) describe state changes based on known biological processes or mechanisms. Compartmental model diagrams are part of a long-term tradition of causal thinking in epidemiology and can parametrically express the same concepts as DAGs, as well as explicitly depict feedback cycles and interactions. As causal inference efforts in epidemiology increasingly draw on simulations and quantitative sensitivity analyses, compartmental model diagrams may be of use to a wider audience. Recognizing simple links between these two common approaches to representing causal processes may facilitate communication between researchers from different traditions.

Purpose: To analyse predictors of clinical outcome in fungal keratitis., Methods: Data was collected during a prospective, randomized, controlled, double-masked clinical trial of treatment for fungal keratitis. Clinical features at presentation and demographics were collected at the enrollment visit for all patients. Pre-specified clinical outcomes included 3-month visual acuity and infiltrate/scar size, time to re-epithelialization, and corneal perforation. A separate multivariable model with each outcome as the dependent variable included all predictor variables., Results: Predictors for worse 3-month visual acuity include older age (P=0.024), worse presentation visual acuity (P<0.001), larger infiltrate size at presentation (P<0.001), and pigmented ulcer (P=0.030). Larger infiltrate size at presentation was a significant predictor of worse 3-month infiltrate/scar size (P<0.001). Larger epithelial defect size was a significant predictor of perforation (P=0.0013). Predictors of longer time to re-epithelialization include infiltrate size at presentation (P<0.001) and older age (P=0.025)., Conclusion: Ulcer severity at presentation is highly predictive of worse outcomes. Presentation of clinical characteristics such as baseline acuity and infiltrate scar can provide important information to clinicians about prognosis, and may help guide management and treatment decisions. Prevention of corneal ulcer remains important, as it is difficult to change the course of the ulcer once it has begun.

HIV affects the pathogenesis and the transmission of Mycobacterium tuberculosis. We used a discrete event simulation model to predict the potential impact of HIV on increasing the probability and the expected severity of tuberculosis outbreaks. Our predictions reveal that an HIV epidemic can significantly increase the frequency and severity of tuberculosis outbreaks, but that this amplification effect of HIV on tuberculosis outbreaks is very sensitive to the tuberculosis treatment rate. At moderate or low treatment rates, even a moderate HIV epidemic can cause the average size of tuberculosis outbreaks to almost double in comparison with the expected outbreak size when HIV is absent. However, we determined that the amplification effect of HIV can be substantially reduced if the treatment rate of tuberculosis is very high. We discuss the significant implications of these results for the global control of tuberculosis. Our results also reveal that occasionally a "normal-virulence" strain of M. tuberculosis can be expected to generate a large outbreak. We discuss the implications of these results in understanding the virulence of M. tuberculosis and in the planned elimination of tuberculosis in the United States.

Objectives: This study determined infection risk for HIV, hepatitis B virus (HBV), and hepatitis C virus (HCV) from needle reuse at a phlebotomy center that possibly exposed 3810 patients to infection., Methods: We used a model for the risk of infection per blood draw, supplemented by subsequent testing results from 1699 patients., Results: The highest risk of transmission was for HBV infection: 1.1 x 10(-6) in the best case and 1.2 x 10(-3) in the (unlikely) worst case. Subsequent testing yielded prevalence rates of 0.12%, 0.41%, and 0.88% for HIV, HBV, and HCV, respectively, lower than National Health and Nutrition Examination Survey III prevalence estimates., Conclusions: The infection risk was very low; few, if any, transmissions are likely to have occurred.

A mathematical model of enzootic Lyme-disease transmission in a natural focus is presented. This model is based on the life history of the vector tick Ixodes scapularis Say and the primary reservoir host Peromyscus leucopus. Using this model, the threshold condition for the disease to be able to invade a nonenzootic region is determined as a function of the various possible transmission chains operating throughout the year. These expressions show that the transmission chain in which ticks acquire the disease from mice in the fall and transmit it back to mice as nymphs in the spring is the most important chain (contributing approximately 87% of the elasticity of the threshold for the parameter choices examined). Equilibrium disease levels were examined under the assumption of a constant tick population; these levels were determined as a function of tick and mouse density, the vertical transmission rate, the infectivity of mice, and the survivorship parameters of the ticks and of the tick-host contact rates. Vertical transmission has a disproportionately large effect, since unfed infected larval ticks have two opportunities to feed on mice, rather than only one opportunity (as for a newly infected unfed nymph). Finally, a global sensitivity analysis based on Latin hypercube sampling is performed, in which is shown the importance of quantifying the natural history of infection in mice, and of elucidating the contribution of other hosts for I. scapularis than mice.

Previously we have formulated transmission models of untreated tuberculosis epidemics (Blower et al., Nature, Medicine 1 (1995), 815-821); in this paper, we present time-dependent uncertainty and sensitivity analyses in order to quantitatively understand the transmission dynamics of tuberculosis epidemics in the absence of treatment. The time-dependent uncertainty analysis enabled us to evaluate the variability in the epidemiological outcome variables of the model during the progression of a tuberculosis epidemic. Calculated values (from the uncertainty analysis) for the disease incidence, disease prevalence, and mortality rates were approximately consistent with historical data. The time-dependent sensitivity analysis revealed that only a few of the model's input parameters significantly affected the severity of a tuberculosis epidemic; these parameters were the disease reactivation rate, the fraction of infected individuals who develop tuberculosis soon after infection, the number of individuals that an infectious individual infects per year, the disease death rate, and the population recruitment rate. Our analysis demonstrates that it is possible to improve our understanding of the behavior of tuberculosis epidemics by applying time-dependent uncertainty and sensitivity analysis to a transmission model., (Copyright 1998 Academic Press.)

Genital herpes, caused by herpes simplex virus, is the most prevalent sexually transmitted disease worldwide. In many developing countries genital herpes is untreated, and in the United States only 10% of cases are treated. We present a mathematical model that we use as a health policy tool to predict the levels of antiviral drug resistance that would emerge, if treatment rates were increased, and to identify the key factors in determining the emergence of drug resistance. We use our results to suggest control measures for herpes epidemics that would prevent the emergence of substantial levels of antiviral drug resistance.

To predict the incidence of AIDS from 1978 through 1998 in San Francisco, we developed a model that combined annual HIV seroconversion rates for homosexual and bisexual men and for heterosexual injecting drug users with estimates of the incubation period distribution between HIV seroconversion and AIDS diagnosis and with estimates of the size of the at-risk populations. Our model assumed the availability of antiretroviral therapy at the efficacy level of zidovudine monotherapy. The annual number of new AIDS cases is estimated to have peaked at 3332 in 1992, and is projected to decline to 1196 annually by 1998. Although the projected number of cases decreased steadily during this period for homosexual and bisexual men, the projected number of cases for injection drug users, women, and persons with other risks increased between 1993 and 1998. The decline in the incidence of AIDS in San Francisco reflects the dramatic reductions in new HIV infections that occurred a decade previously and that were achieved as a result of significant changes in high-risk behaviors, primarily among homosexual and bisexual men. Changes in HIV seroincidence must be factored in before attributing the decrease in AIDS incidence to more effective combination antiretroviral treatment.

In developed countries the major tuberculosis epidemics declined long before the disease became curable in the 1940s. We present a theoretical framework for assessing the intrinsic transmission dynamics of tuberculosis. We demonstrate that it takes one to several hundred years for a tuberculosis epidemic to rise, fall and reach a stable endemic level. Our results suggest that some of the decline of tuberculosis is simply due to the natural behaviour of an epidemic. Although other factors must also have contributed to the decline, these causal factors were constrained to operate within the slow response time dictated by the intrinsic dynamics.