Michael Deiner

Netrin-1 and DCC Mediate Axon Guidance Locally at the Optic Disc: Loss of Function Leads to Optic Nerve Hypoplasia

Embryonic retinal ganglion cell (RGC) axons must extend toward and grow through the optic disc to exit the eye into the optic nerve. In the embryonic mouse eye, we found that immunoreactivity for the axon guidance molecule netrin-1 was specifically on neuroepithelial cells at the disk surrounding exiting RGC axons, and RGC axons express the netrin receptor, DCC (deleted in colorectal cancer). In vitro, anti-DCC antibodies reduced RGC neurite outgrowth responses to netrin-1. In netrin-1- and DCC-deficient embryos, RGC axon pathfinding to the disc was unaffected; however, axons failed to exit into the optic nerve, resulting in optic nerve hypoplasia. Thus, netrin-1 through DCC appears to guide RGC axons locally at the optic disc rather than at long range, apparently reflecting the localization of netrin-1 protein to the vicinity of netrin-1-producing cells at the optic disc.

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.

Surveillance Tools Emerging From Search Engines and Social Media Data for Determining Eye Disease Patterns

IMPORTANCE Internet-based search engine and social media data may provide a novel complementary source for better understanding the epidemiologic factors of infectious eye diseases, which could better inform eye health care and disease prevention. OBJECTIVE To assess whether data from internet-based social media and search engines are associated with objective clinic-based diagnoses of conjunctivitis. DESIGN, SETTING, AND PARTICIPANTS Data from encounters of 4143 patients diagnosed with conjunctivitis from June 3, 2012, to April 26, 2014, at the University of California San Francisco (UCSF) Medical Center, were analyzed using Spearman rank correlation of each weekly observation to compare demographics and seasonality of nonallergic conjunctivitis with allergic conjunctivitis. Data for patient encounters with diagnoses for glaucoma and influenza were also obtained for the same period and compared with conjunctivitis. Temporal patterns of Twitter and Google web search data, geolocated to the United States and associated with these clinical diagnoses, were compared with the clinical encounters. The a priori hypothesis was that weekly internet-based searches and social media posts about conjunctivitis may reflect the true weekly clinical occurrence of conjunctivitis. MAIN OUTCOMES AND MEASURES Weekly total clinical diagnoses at UCSF of nonallergic conjunctivitis, allergic conjunctivitis, glaucoma, and influenza were compared using Spearman rank correlation with equivalent weekly data on Tweets related to disease or disease-related keyword searches obtained from Google Trends. RESULTS Seasonality of clinical diagnoses of nonallergic conjunctivitis among the 4143 patients (2364 females [57.1%] and 1776 males [42.9%]) with 5816 conjunctivitis encounters at UCSF correlated strongly with results of Google searches in the United States for the term pink eye (ρ, 0.68 [95% CI, 0.52 to 0.78]; P < .001) and correlated moderately with Twitter results about pink eye (ρ, 0.38 [95% CI, 0.16 to 0.56]; P < .001) and with clinical diagnosis of influenza (ρ, 0.33 [95% CI, 0.12 to 0.49]; P < .001), but did not significantly correlate with seasonality of clinical diagnoses of allergic conjunctivitis diagnosis at UCSF (ρ, 0.21 [95% CI, -0.02 to 0.42]; P = .06) or with results of Google searches in the United States for the term eye allergy (ρ, 0.13 [95% CI, -0.06 to 0.32]; P = .19). Seasonality of clinical diagnoses of allergic conjunctivitis at UCSF correlated strongly with results of Google searches in the United States for the term eye allergy (ρ, 0.44 [95% CI, 0.24 to 0.60]; P < .001) and eye drops (ρ, 0.47 [95% CI, 0.27 to 0.62]; P < .001). CONCLUSIONS AND RELEVANCE Internet-based search engine and social media data may reflect the occurrence of clinically diagnosed conjunctivitis, suggesting that these data sources can be leveraged to better understand the epidemiologic factors of conjunctivitis.

Mechanism of Paddle Cilia Formation in Molluscan Veligers

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Probabilistic forecasts of trachoma transmission at the district level: A statistical model comparison

The World Health Organization and its partners are aiming to eliminate trachoma as a public health problem by 2020. In this study, we compare forecasts of TF prevalence in 2011 for 7 different statistical and mechanistic models across 9 de-identified trachoma endemic districts, representing 4 unique trachoma endemic countries. We forecast TF prevalence between 1–6 years ahead in time and compare the 7 different models to the observed 2011 data using a log-likelihood score. An SIS model, including a district-specific random effect for the district-specific transmission coefficient, had the highest log-likelihood score across all 9 districts and was therefore the best performing model. While overall the deterministic transmission model was the least well performing model, although it did comparably well to the other models for 8 of 9 districts. We perform a statistically rigorous comparison of the forecasting ability of a range of mathematical and statistical models across multiple endemic districts between 1 and 6 years ahead of the last collected TF prevalence data point in 2011, assessing results against surveillance data. This study is a step towards making statements about likelihood and time to elimination with regard to the WHO GET2020 goals.

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.

Models of Trachoma Transmission and Their Policy Implications: From Control to Elimination

Abstract Despite great progress in eliminating trachoma from the majority of worldwide districts, trachoma control seems to have stalled in some endemic districts. Can mathematical models help suggest the way forward? We review specific achievements of models in trachoma control in the past. Models showed that, even with incomplete coverage, mass drug administration could eliminate disease through a spillover effect, somewhat analogous to how incomplete vaccine campaigns can eliminate disease through herd protection. Models also suggest that elimination can always be achieved if enough people are treated often enough with an effective enough drug. Other models supported the idea that targeting ages at highest risk or continued improvements in hygiene and sanitation can contribute meaningfully to trachoma control. Models of intensive targeting of a core group may point the way to final eradication even in areas with substantial transmission and within-community heterogeneity.

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.

Facebook and Twitter vaccine sentiment in response to measles outbreaks

Social media posts regarding measles vaccination were classified as pro-vaccination, expressing vaccine hesitancy, uncertain, or irrelevant. Spearman correlations with Centers for Disease Control and Prevention–reported measles cases and differenced smoothed cumulative case counts over this period were reported (using time series bootstrap confidence intervals). A total of 58,078 Facebook posts and 82,993 tweets were identified from 4 January 2009 to 27 August 2016. Pro-vaccination posts were correlated with the US weekly reported cases (Facebook: Spearman correlation 0.22 (95% confidence interval: 0.09 to 0.34), Twitter: 0.21 (95% confidence interval: 0.06 to 0.34)). Vaccine-hesitant posts, however, were uncorrelated with measles cases in the United States (Facebook: 0.01 (95% confidence interval: −0.13 to 0.14), Twitter: 0.0011 (95% confidence interval: −0.12 to 0.12)). These findings may result from more consistent social media engagement by individuals expressing vaccine hesitancy, contrasted with media- or event-driven episodic interest on the part of individuals favoring current policy.

Identifying a sufficient core group for trachoma transmission

Background In many infectious diseases, a core group of individuals plays a disproportionate role in transmission. If these individuals were effectively prevented from transmitting infection, for example with a perfect vaccine, then the disease would disappear in the remainder of the community. No vaccine has yet proven effective against the ocular strains of chlamydia that cause trachoma. However, repeated treatment with oral azithromycin may be able to prevent individuals from effectively transmitting trachoma. Methodology/Principal findings Here we assess several methods for identifying a core group for trachoma, assuming varying degrees of knowledge about the transmission process. We determine the minimal core group from a completely specified model, fitted to results from a large Ethiopian trial. We compare this benchmark to a core group that could actually be identified from information available to trachoma programs. For example, determined from the rate of return of infection in a community after mass treatments, or from the equilibrium prevalence of infection. Conclusions/Significance Sufficient groups are relatively easy for programs to identify, but will likely be larger than the theoretical minimum.