Lee Worden

Spatial heterogeneity in projected leprosy trends in India

BackgroundLeprosy is caused by infection with Mycobacterium leprae and is characterized by peripheral nerve damage and skin lesions. The disease is classified into paucibacillary (PB) and multibacillary (MB) leprosy. The 2012 London Declaration formulated the following targets for leprosy control: (1) global interruption of transmission or elimination by 2020, and (2) reduction of grade-2 disabilities in newly detected cases to below 1 per million population at a global level by 2020. Leprosy is treatable, but diagnosis, access to treatment and treatment adherence (all necessary to curtail transmission) represent major challenges. Globally, new case detection rates for leprosy have remained fairly stable in the past decade, with India responsible for more than half of cases reported annually.MethodsWe analyzed publicly available data from the Indian Ministry of Health and Family Welfare, and fit linear mixed-effects regression models to leprosy case detection trends reported at the district level. We assessed correlation of the new district-level case detection rate for leprosy with several state-level regressors: TB incidence, BCG coverage, fraction of cases exhibiting grade 2 disability at diagnosis, fraction of cases in children, and fraction multibacillary.ResultsOur analyses suggest an endemic disease in very slow decline, with substantial spatial heterogeneity at both district and state levels. Enhanced active case finding was associated with a higher case detection rate.ConclusionsTrend analysis of reported new detection rates from India does not support a thesis of rapid progress in leprosy control.

Assessing Measles Transmission in the United States Following a Large Outbreak in California.

The recent increase in measles cases in California may raise questions regarding the continuing success of measles control. To determine whether the dynamics of measles is qualitatively different in comparison to previous years, we assess whether the 2014-2015 measles outbreak associated with an Anaheim theme park is consistent with subcriticality by calculating maximum-likelihood estimates for the effective reproduction numbe given this year’s outbreak, using the Galton-Watson branching process model. We find that the dynamics after the initial transmission event are consistent with prior transmission, but does not exclude the possibilty that the effective reproduction number has increased.

The Effect of Contact Investigations and Public Health Interventions in the Control and Prevention of Measles Transmission: A Simulation Study

Background Measles cases continue to occur despite its elimination status in the United States. To control transmission, public health officials confirm the measles diagnosis, identify close contacts of infectious cases, deliver public health interventions (i.e., post-exposure prophylaxis) among those who are eligible, and follow-up with the close contacts to determine overall health outcomes. A stochastic network simulation of measles contact tracing was conducted using existing agent-based modeling software and a synthetic population with high levels of immunity in order to estimate the impact of different interventions in controlling measles transmission. Methods and Findings The synthetic population was created to simulate California`s population in terms of population demographics, household, workplace, school, and neighborhood characteristics using California Department of Finance 2010 census data. Parameters for the model were obtained from a review of the literature, California measles case surveillance data, and expert opinion. Eight different scenarios defined by the use of three different public health interventions were evaluated: (a) post-exposure measles, mumps, and rubella (MMR) vaccine, (b) post-exposure immune globulin (IG), and (c) voluntary isolation and home quarantine in the presence or absence of public health response delays. Voluntary isolation and home quarantine coupled with one or two other interventions had the greatest reduction in the number of secondary cases infected by the index case and the probability of escape situations (i.e., the outbreak continues after 90 days). Conclusions Interrupting contact patterns via voluntary isolation and home quarantine are particularly important in reducing the number of secondary cases infected by the index case and the probability of uncontrolled outbreaks.

Evaluating Subcriticality during the Ebola Epidemic in West Africa

The 2014–2015 Ebola outbreak is the largest and most widespread to date. In order to estimate ongoing transmission in the affected countries, we estimated the weekly average number of secondary cases caused by one individual infected with Ebola throughout the infectious period for each affected West African country using a stochastic hidden Markov model fitted to case data from the World Health Organization. If the average number of infections caused by one Ebola infection is less than 1.0, the epidemic is subcritical and cannot sustain itself. The epidemics in Liberia and Sierra Leone have approached subcriticality at some point during the epidemic; the epidemic in Guinea is ongoing with no evidence that it is subcritical. Response efforts to control the epidemic should continue in order to eliminate Ebola cases in West Africa.

Short-term leprosy forecasting from an expert opinion survey

We conducted an expert survey of leprosy (Hansen’s Disease) and neglected tropical disease experts in February 2016. Experts were asked to forecast the next year of reported cases for the world, for the top three countries, and for selected states and territories of India. A total of 103 respondents answered at least one forecasting question. We elicited lower and upper confidence bounds. Comparing these results to regression and exponential smoothing, we found no evidence that any forecasting method outperformed the others. We found evidence that experts who believed it was more likely to achieve global interruption of transmission goals and disability reduction goals had higher error scores for India and Indonesia, but lower for Brazil. Even for a disease whose epidemiology changes on a slow time scale, forecasting exercises such as we conducted are simple and practical. We believe they can be used on a routine basis in public health.

Early projections of Ebola outbreak size and duration with and without vaccine use in Equateur, Democratic Republic of Congo, as of May 21, 2018

Background As of May 27, 2018, 54 cases of Ebola virus disease (EVD) were reported in Équateur Province, Democratic Republic of Congo. We used reported case counts and time series from prior outbreaks to estimate the current outbreak size and duration with and without vaccine use. Methods We modeled Ebola virus transmission using a stochastic branching process model with a negative binomial distribution, using both estimates of reproduction number R declining from supercritical to subcritical derived from past Ebola outbreaks, as well as a particle filtering method to generate a probabilistic projection of the future course of the outbreak conditioned on its reported trajectory to date; modeled using 0%, 44%, and 62% estimates of vaccination coverage. Additionally, we used the time series for 18 prior Ebola outbreaks from 1976 to 2016 to parameterize a regression model predicting the outbreak size from the number of observed cases from April 4 to May 27. Results With the stochastic transmission model, we projected a median outbreak size of 78 EVD cases (95% credible interval: 52, 125.4), 86 cases (95% credible interval: 53, 174.3), and 91 cases (95% credible interval: 52, 843.5), using 62%, 44%, and 0% estimates of vaccination coverage. With the regression model, we estimated a median size of 85.0 cases (95% prediction interval: 53.5, 216.6). Conclusions This outbreak has the potential to be the largest outbreak in DRC since 2007. Vaccines are projected to limit outbreak size and duration but are only part of prevention, control, and care strategies.

Multiple Exposures, Reinfection, and Risk of Progression to Active Tuberculosis

A recent study reported on a tuberculosis outbreak in a largely Inuit village. Among recently infected individuals, exposure to additional active cases was associated with an increasing probability of developing active disease within a year. Using binomial risk models, we evaluated two potential mechanisms by which multiple infections during the first year following initial infection could account for increasing disease risk with increasing exposures. In the reinfection model, multiple exposures have an independent risk of becoming an infection, and infections contribute independently to active disease. In the threshold model, disease risk follows a sigmoidal function with small numbers of exposures conferring a low risk of active disease and large numbers of exposures conferring a high risk. To determine the dynamic impact of reinfection during the early phase of infection, we performed simulations from a modified Reed-Frost model of TB dynamics following spread from an initial number of cases. We parameterized this model with the maximum likelihood estimates from the reinfection and threshold models in addition to the observed distribution of exposures among recent infections. We find that both models can plausibly account for the observed increase in disease risk with increasing exposures, but the threshold model confers a better fit than a nested model without a threshold (p=0.04). Our simulations indicate that multiple exposures during this critical time period can lead to dramatic increases in outbreak size. In order to decrease TB burden in high-prevalence settings, it may be necessary to implement measures aimed at preventing repeated exposures, in addition to preventing primary infection.

Anatomy of a Hotspot: Chain and Seroepidemiology of Ebola Virus Transmission, Sukudu, Sierra Leone, 2015–16

Studies have yet to include minimally symptomatic Ebola virus (EBOV) infections and unrecognized Ebola virus disease (EVD) in Ebola-related transmission chains and epidemiologic risk estimates. We conducted a cross-sectional, sero-epidemiological survey from October 2015 to January 2016 among 221 individuals living in quarantined households from November 2014 to February 2015 during the Ebola outbreak in the village of Sukudu, Sierra Leone. Of 48 EBOV-infected persons, 25% (95% confidence interval [CI], 14%-40%) had minimally symptomatic EBOV infections and 4% (95% CI, 1%-14%) were unrecognized EVD cases. The pattern of minimally symptomatic EBOV infections in the transmission chain was nonrandom (P < .001, permutation test). Not having lived in the same house as an EVD case was significantly associated with minimally symptomatic infection. This is the first study to investigate a chain of EBOV transmission inclusive of minimally symptomatic EBOV infections and unrecognized EVD. Our findings provide new insights into Ebola transmission dynamics and quarantine practices.

Mass Azithromycin Distribution and Community Microbiome: A Cluster-Randomized Trial

Abstract Background Mass distributions of oral azithromycin have long been used to eliminate trachoma, and they are now being proposed to reduce childhood mortality. The observed benefit appears to be augmented with each additional treatment, suggesting a possible community-level effect. Here, we assess whether 2 biannual mass treatments of preschool children affect the community’s gut microbiome at 6 months after the last distribution. Methods In this cluster-randomized controlled trial, children aged 1–60 months in the Dossa region of Niger were randomized at the village level to receive a single dose of azithromycin or placebo every 6 months. Fecal samples were collected 6 months after the second treatment for metagenomic deep sequencing. The prespecified primary outcome was the Euclidean PERMANOVA of the gut microbiome, or effectively the distance between the genus-level centroid at the community level, with the secondary outcome being the Simpson’s α diversity. Results In the azithromycin arm, the gut microbial structures were significantly different than in the placebo arm (Euclidean PERMANOVA, P < .001). Further, the diversity of the gut microbiome in the azithromycin arm was significantly lower than in the placebo arm (inverse Simpson’s index, P = .005). Conclusions Two mass azithromycin administrations, 6 months apart, in preschool children led to long-term alterations of the gut microbiome structure and community diversity. Here, long-term microbial alterations in the community did not imply disease but were associated with an improvement in childhood mortality. Clinical Trials Registration NCT02048007.

Spatial distribution of leprosy in India: an ecological study

BackgroundAs leprosy elimination becomes an increasingly realistic goal, it is essential to determine the factors that contribute to its persistence. We evaluate social and economic factors as predictors of leprosy annual new case detection rates within India, where the majority of leprosy cases occur.MethodsWe used correlation and linear mixed effect regressions to assess whether poverty, illiteracy, nighttime satellite radiance (an index of development), and other covariates can explain district-wise annual new case detection rate and Grade 2 disability diagnoses.ResultsWe find only weak evidence of an association between poverty and annual new case detection rates at the district level, though illiteracy and satellite radiance are statistically significant predictors of leprosy at the district level. We find no evidence of rapid decline over the period 2008–2015 in either new case detection or new Grade 2 disability.ConclusionsOur findings suggest a somewhat higher rate of leprosy detection, on average, in poorer districts; the overall effect is weak. The divide between leprosy case detection and true incidence of clinical leprosy complicates these results, particularly given that the detection rate is likely disproportionately lower in impoverished settings. Additional information is needed to distinguish the determinants of leprosy case detection and transmission during the elimination epoch.