District-Level Forecast of Achieving Trachoma Elimination as a Public Health Problem By 2030: An Ensemble Modelling Approach.

Assessing the feasibility of 2030 as a target date for global elimination of trachoma, and identification of districts that may require enhanced treatment to meet World Health Organization (WHO) elimination criteria by this date are key challenges in operational planning for trachoma programmes. Here we address these challenges by prospectively evaluating forecasting models of trachomatous inflammation-follicular (TF) prevalence, leveraging ensemble-based approaches. Seven candidate probabilistic models were developed to forecast district-wise TF prevalence in 11 760 districts, trained using district-level data on the population prevalence of TF in children aged 1-9 years from 2004 to 2022. Geographical location, history of mass drug administration treatment, and previously measured prevalence data were included in these models as key predictors. The best-performing models were included in an ensemble, using weights derived from their relative likelihood scores. To incorporate the inherent stochasticity of disease transmission and challenges of population-level surveillance, we forecasted probability distributions for the TF prevalence in each geographic district, rather than predicting a single value. Based on our probabilistic forecasts, 1.46% (95% confidence interval [CI]: 1.43-1.48%) of all districts in trachoma-endemic countries, equivalent to 172 districts, will exceed the 5% TF control threshold in 2030 with the current interventions. Global elimination of trachoma as a public health problem by 2030 may require enhanced intervention and/or surveillance of high-risk districts.

Association of weather variables with pathogens contributing to conjunctivitis worldwide.

PURPOSE: To identify weather variables associated with pathogens contributing to infectious conjunctivitis globally. METHODS: Sample collection and pathogen identification from patients with acute infectious conjunctivitis was performed from 2017 to 2023. We linked pathogens identified from 13 sites across 8 countries with publicly available weather data by geographic coordinates. Mixed effects logistic regression analysis was performed to estimate the associations between temperature, precipitation, and relative humidity exposures, and the prevalence of infection types (RNA virus, DNA virus, bacteria, and fungus). RESULTS: 498 cases from the United States, India, Nepal, Thailand, Burkina Faso, Niger, Vietnam, and Israel were included in the analysis. 8-day average precipitation (mm) was associated with increased odds of RNA virus infection (odds ratio (OR)=1.47, 95% confidence interval (CI): 1.12 to 1.93, P=0.01) and decreased odds of DNA infection (OR=0.62, 95% CI: 0.46 to 0.82, P<0.001). Relative humidity (%) was associated with increased odds of RNA virus infections (OR=2.64, 95% CI: 1.51 to 4.61, P<0.001), and fungal infections (OR=2.35, 95% CI: 1.19 to 4.66, P=0.01), but decreased odds of DNA virus (OR=0.58, 95%CI: 0.37 to 0.90, P=0.02) and bacterial infections (OR=0.42, 95% CI: 0.25 to 0.71, P<0.001). Temperature (°C) was not associated with ocular infections for any pathogen type. CONCLUSIONS: This study suggests that weather factors affect pathogens differently. Particularly, humidity and precipitation were predictors for pathogens contributing to conjunctivitis worldwide. Additional work is needed to clarify the effects of shifts in weather and environmental factors on ocular infectious diseases.

Use of Large Language Models to Assess the Likelihood of Epidemics From the Content of Tweets: Infodemiology Study.

BACKGROUND: Previous work suggests that Google searches could be useful in identifying conjunctivitis epidemics. Content-based assessment of social media content may provide additional value in serving as early indicators of conjunctivitis and other systemic infectious diseases. OBJECTIVE: We investigated whether large language models, specifically GPT-3.5 and GPT-4 (OpenAI), can provide probabilistic assessments of whether social media posts about conjunctivitis could indicate a regional outbreak. METHODS: A total of 12,194 conjunctivitis-related tweets were obtained using a targeted Boolean search in multiple languages from India, Guam (United States), Martinique (France), the Philippines, American Samoa (United States), Fiji, Costa Rica, Haiti, and the Bahamas, covering the time frame from January 1, 2012, to March 13, 2023. By providing these tweets via prompts to GPT-3.5 and GPT-4, we obtained probabilistic assessments that were validated by 2 human raters. We then calculated Pearson correlations of these time series with tweet volume and the occurrence of known outbreaks in these 9 locations, with time series bootstrap used to compute CIs. RESULTS: Probabilistic assessments derived from GPT-3.5 showed correlations of 0.60 (95% CI 0.47-0.70) and 0.53 (95% CI 0.40-0.65) with the 2 human raters, with higher results for GPT-4. The weekly averages of GPT-3.5 probabilities showed substantial correlations with weekly tweet volume for 44% (4/9) of the countries, with correlations ranging from 0.10 (95% CI 0.0-0.29) to 0.53 (95% CI 0.39-0.89), with larger correlations for GPT-4. More modest correlations were found for correlation with known epidemics, with substantial correlation only in American Samoa (0.40, 95% CI 0.16-0.81). CONCLUSIONS: These findings suggest that GPT prompting can efficiently assess the content of social media posts and indicate possible disease outbreaks to a degree of accuracy comparable to that of humans. Furthermore, we found that automated content analysis of tweets is related to tweet volume for conjunctivitis-related posts in some locations and to the occurrence of actual epidemics. Future work may improve the sensitivity and specificity of these methods for disease outbreak detection.

Eye Trauma in Mixed Martial Arts and Boxing.

PURPOSE: To evaluate and compare eye and face trauma in mixed martial arts (MMA) and boxing. DESIGN: Retrospective cohort study. METHODS: Data from boxing and MMA competitions were extracted from the Nevada Athletic Commission (NAC) between 2000 and 2020. Details of competitions, contestants, outcomes, and injuries were extracted. RESULTS: In total 1539 boxing injuries (from 4313 contests) and 1442 MMA injuries (from 2704 contests) were identified. Boxing had higher eye injury rates compared to MMA ( p < 0.0001), with an odds ratio of 1.268 (95% CI, 1.114-1.444). Eye trauma represented 47.63% of boxing injuries and 25.59% of MMA injuries, with periocular lacerations being the most common eye injury in both. Orbital fractures represented 17.62% of eye injuries in MMA and 3.14% in boxing contests. However, 2%-3% were retinal in both sports, and 3.27% were glaucomatous in boxing. MMA contestants had an odds ratio of 1.823 (95% CI, 1.408-2.359) for requiring physician evaluation following an eye injury compared with boxing. MMA contestants also had a higher rate of face ( p < 0.0001) and body ( p < 0.0001) injuries. For both sports, an increased number of rounds and being the losing fighter were associated with increased odds of eye and face injury. CONCLUSION: Although boxing has a higher rate of eye injuries, MMA eye injuries are more likely to require physician evaluation. MMA contestants also have a higher rate of orbital fractures and face and body trauma. A detailed postfight examination and long-term follow-up of ocular injury in combat sports will be vital in proposing reforms to prevent eye trauma.

A Google Trends Approach to Identify Distinct Diurnal and Day-of-Week Web-Based Search Patterns Related to Conjunctivitis and Other Common Eye Conditions: Infodemiology Study.

BACKGROUND: Studies suggest diurnal patterns of occurrence of some eye conditions. Leveraging new information sources such as web-based search data to learn more about such patterns could improve the understanding of patients' eye-related conditions and well-being, better inform timing of clinical and remote eye care, and improve precision when targeting web-based public health campaigns toward underserved populations. OBJECTIVE: To investigate our hypothesis that the public is likely to consistently search about different ophthalmologic conditions at different hours of the day or days of week, we conducted an observational study using search data for terms related to ophthalmologic conditions such as conjunctivitis. We assessed whether search volumes reflected diurnal or day-of-week patterns and if those patterns were distinct from each other. METHODS: We designed a study to analyze and compare hourly search data for eye-related and control search terms, using time series regression models with trend and periodicity terms to remove outliers and then estimate diurnal effects. We planned a Google Trends setting, extracting data from 10 US states for the entire year of 2018. The exposure was internet search, and the participants were populations who searched through Google's search engine using our chosen study terms. Our main outcome measures included cyclical hourly and day-of-week web-based search patterns. For statistical analyses, we considered P<.001 to be statistically significant. RESULTS: Distinct diurnal (P<.001 for all search terms) and day-of-week search patterns for eye-related terms were observed but with differing peak time periods and cyclic strengths. Some diurnal patterns represented those reported from prior clinical studies. Of the eye-related terms, "pink eye" showed the largest diurnal amplitude-to-mean ratios. Stronger signal was restricted to and peaked in mornings, and amplitude was higher on weekdays. By contrast, "dry eyes" had a higher amplitude diurnal pattern on weekends, with stronger signal occurring over a broader evening-to-morning period and peaking in early morning. CONCLUSIONS: The frequency of web-based searches for various eye conditions can show cyclic patterns according to time of the day or week. Further studies to understand the reasons for these variations may help supplement the current clinical understanding of ophthalmologic symptom presentation and improve the timeliness of patient messaging and care interventions.

Forecasting Trachoma Control and Identifying Transmission-Hotspots.

BACKGROUND: Tremendous progress towards elimination of trachoma as a public health problem has been made. However, there are areas where the clinical indicator of disease, trachomatous inflammation-follicular (TF), remains prevalent. We quantify the progress that has been made, and forecast how TF prevalence will evolve with current interventions. We also determine the probability that a district is a transmission-hotspot based on its TF prevalence (ie, reproduction number greater than one). METHODS: Data on trachoma prevalence come from the GET2020 global repository organized by the World Health Organization and the International Trachoma Initiative. Forecasts of TF prevalence and the percent of districts with local control is achieved by regressing the coefficients of a fitted exponential distribution for the year-by-year distribution of TF prevalence. The probability of a district being a transmission-hotspot is extrapolated from the residuals of the regression. RESULTS: Forecasts suggest that with current interventions, 96.5% of surveyed districts will have TF prevalence among children aged 1-9 years <5% by 2030 (95% CI: 86.6%-100.0%). Districts with TF prevalence < 20% appear unlikely to be transmission-hotspots. However, a district having TF prevalence of over 28% in 2016-2019 corresponds to at least 50% probability of being a transmission-hotspot. CONCLUSIONS: Sustainable control of trachoma appears achievable. However there are transmission-hotspots that are not responding to annual mass drug administration of azithromycin and require enhanced treatment in order to reach local control.

Predicted Impact of COVID-19 on Neglected Tropical Disease Programs and the Opportunity for Innovation.

Due to the COVID-19 pandemic, many key neglected tropical disease (NTD) activities have been postponed. This hindrance comes at a time when the NTDs are progressing towards their ambitious goals for 2030. Mathematical modelling on several NTDs, namely gambiense sleeping sickness, lymphatic filariasis, onchocerciasis, schistosomiasis, soil-transmitted helminthiases (STH), trachoma, and visceral leishmaniasis, shows that the impact of this disruption will vary across the diseases. Programs face a risk of resurgence, which will be fastest in high-transmission areas. Furthermore, of the mass drug administration diseases, schistosomiasis, STH, and trachoma are likely to encounter faster resurgence. The case-finding diseases (gambiense sleeping sickness and visceral leishmaniasis) are likely to have fewer cases being detected but may face an increasing underlying rate of new infections. However, once programs are able to resume, there are ways to mitigate the impact and accelerate progress towards the 2030 goals.

Trachoma Prevalence After Discontinuation of Mass Azithromycin Distribution.

BACKGROUND: As the World Health Organization seeks to eliminate trachoma by 2020, countries are beginning to control the transmission of trachomatous inflammation-follicular (TF) and discontinue mass drug administration (MDA) with oral azithromycin. We evaluated the effect of MDA discontinuation on TF1-9 prevalence at the district level. METHODS: We extracted from the available data districts with an impact survey at the end of their program cycle that initiated discontinuation of MDA (TF1-9 prevalence <5%), followed by a surveillance survey conducted to determine whether TF1-9 prevalence remained below the 5% threshold, warranting discontinuation of MDA. Two independent analyses were performed, 1 regression based and 1 simulation based, that assessed the change in TF1-9 from the impact survey to the surveillance survey. RESULTS: Of the 220 districts included, TF1-9 prevalence increased to >5% from impact to surveillance survey in 9% of districts. Regression analysis indicated that impact survey TF1-9 prevalence was a significant predictor of surveillance survey TF1-9 prevalence. The proportion of simulations with >5% TF1-9 prevalence in the surveillance survey was 2%, assuming the survey was conducted 4 years after MDA. CONCLUSION: An increase in TF1-9 prevalence may represent disease resurgence but could also be due to measurement error. Improved diagnostic tests are crucial to elimination of TF1-9 as a public health problem.

Google Searches and Detection of Conjunctivitis Epidemics Worldwide.

PURPOSE: Epidemic and seasonal infectious conjunctivitis outbreaks can impact education, workforce, and economy adversely. Yet conjunctivitis typically is not a reportable disease, potentially delaying mitigating intervention. Our study objective was to determine if conjunctivitis epidemics could be identified using Google Trends search data. DESIGN: Search data for conjunctivitis-related and control search terms from 5 years and countries worldwide were obtained. Country and term were masked. Temporal scan statistics were applied to identify candidate epidemics. Candidates then were assessed for geotemporal concordance with an a priori defined collection of known reported conjunctivitis outbreaks, as a measure of sensitivity. PARTICIPANTS: Populations by country that searched Google's search engine using our study terms. MAIN OUTCOME MEASURES: Percent of known conjunctivitis outbreaks also found in the same country and period by our candidate epidemics, identified from conjunctivitis-related searches. RESULTS: We identified 135 candidate conjunctivitis epidemic periods from 77 countries. Compared with our a priori defined collection of known reported outbreaks, candidate conjunctivitis epidemics identified 18 of 26 (69% sensitivity) of the reported country-wide or island nationwide outbreaks, or both; 9 of 20 (45% sensitivity) of the reported region or district-wide outbreaks, or both; but far fewer nosocomial and reported smaller outbreaks. Similar overall and individual sensitivity, as well as specificity, were found on a country-level basis. We also found that 83% of our candidate epidemics had start dates before (of those, 20% were more than 12 weeks before) their concurrent reported outbreak's report issuance date. Permutation tests provided evidence that on average, conjunctivitis candidate epidemics occurred geotemporally closer to outbreak reports than chance alone suggests (P < 0.001) unlike control term candidates (P = 0.40). CONCLUSIONS: Conjunctivitis outbreaks can be detected using temporal scan analysis of Google search data alone, with more than 80% detected before an outbreak report's issuance date, some as early as the reported outbreak's start date. Future approaches using data from smaller regions, social media, and more search terms may improve sensitivity further and cross-validate detected candidates, allowing identification of candidate conjunctivitis epidemics from Internet search data potentially to complementarily benefit traditional reporting and detection systems to improve epidemic awareness.

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

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.

Pilot study comparing a new virtual reality-based visual field test to standard perimetry in children.

PURPOSE: To assess the feasibility and performance of Vivid Vision Perimetry (VVP), a new virtual reality (VR)-based visual field platform. METHODS: Children 7-18 years of age with visual acuity of 20/80 or better undergoing Humphrey visual field (HVF) testing were recruited to perform VVP, a VR-based test that uses suprathreshold stimuli to test 54 field locations and calculates a fraction seen score. Pearson correlation coefficients were calculated to evaluate correlation between HVF mean sensitivity and VVP mean fraction seen scores. Participants were surveyed regarding their experience. RESULTS: A total of 37 eyes of 23 participants (average age, 12.9 ± 3.1 years; 48% female) were included. All participants successfully completed VVP testing. Diagnoses included glaucoma (12), glaucoma suspect (7), steroid-induced ocular hypertension (3), and craniopharyngioma (1). Sixteen participants had prior HVF experience, and none had prior VVP experience, although 7 had previously used VR. Of the 23 HVF tests performed, 9 (39%) were unreliable due to fixation losses, false positives, or false negatives. Similarly, 35% of VVP tests were unreliable (as defined by accuracy of blind spot detection). Excluding unreliable HVF tests, the correlation between HVF average mean sensitivity and VVP mean fraction seen score was 0.48 (P = 0.02; 95% CI, 0.09-0.74). When asked about preference for the VVP or HVF examination, all participants favored the VVP, and 70% were "very satisfied" with VVP. CONCLUSIONS: In our cohort of 23 pediatric subjects, VVP proved to be a clinically feasible VR-based visual field testing, which was uniformly preferred over HVF.

Large Language Models Can Enable Inductive Thematic Analysis of a Social Media Corpus in a Single Prompt: Human Validation Study.

BACKGROUND: Manually analyzing public health-related content from social media provides valuable insights into the beliefs, attitudes, and behaviors of individuals, shedding light on trends and patterns that can inform public understanding, policy decisions, targeted interventions, and communication strategies. Unfortunately, the time and effort needed from well-trained human subject matter experts makes extensive manual social media listening unfeasible. Generative large language models (LLMs) can potentially summarize and interpret large amounts of text, but it is unclear to what extent LLMs can glean subtle health-related meanings in large sets of social media posts and reasonably report health-related themes. OBJECTIVE: We aimed to assess the feasibility of using LLMs for topic model selection or inductive thematic analysis of large contents of social media posts by attempting to answer the following question: Can LLMs conduct topic model selection and inductive thematic analysis as effectively as humans did in a prior manual study, or at least reasonably, as judged by subject matter experts? METHODS: We asked the same research question and used the same set of social media content for both the LLM selection of relevant topics and the LLM analysis of themes as was conducted manually in a published study about vaccine rhetoric. We used the results from that study as background for this LLM experiment by comparing the results from the prior manual human analyses with the analyses from 3 LLMs: GPT4-32K, Claude-instant-100K, and Claude-2-100K. We also assessed if multiple LLMs had equivalent ability and assessed the consistency of repeated analysis from each LLM. RESULTS: The LLMs generally gave high rankings to the topics chosen previously by humans as most relevant. We reject a null hypothesis (P<.001, overall comparison) and conclude that these LLMs are more likely to include the human-rated top 5 content areas in their top rankings than would occur by chance. Regarding theme identification, LLMs identified several themes similar to those identified by humans, with very low hallucination rates. Variability occurred between LLMs and between test runs of an individual LLM. Despite not consistently matching the human-generated themes, subject matter experts found themes generated by the LLMs were still reasonable and relevant. CONCLUSIONS: LLMs can effectively and efficiently process large social media-based health-related data sets. LLMs can extract themes from such data that human subject matter experts deem reasonable. However, we were unable to show that the LLMs we tested can replicate the depth of analysis from human subject matter experts by consistently extracting the same themes from the same data. There is vast potential, once better validated, for automated LLM-based real-time social listening for common and rare health conditions, informing public health understanding of the public's interests and concerns and determining the public's ideas to address them.

Evaluating for unrecognized deficits in perimetry associated with functional upper eyelid malposition.

Objective: To investigate whether functional upper eyelid malposition is associated with unrecognized deficits in automated perimetry among glaucoma patients by examining patients undergoing eyelid surgery who had not been identified as requiring eyelid taping during glaucoma field testing. Methods: In this retrospective pre-post study, an automated database search followed by manual chart review was used to identify eligible patients from January 2012 to March 2020. Included patients had reliable visual field testing within two years before and after functional upper blepharoplasty or ptosis repair and no comorbid ocular diagnoses. As part of routine practice, glaucoma visual field technicians taped patients with pupil-obstructing eyelid malposition; taped examinations were excluded from analysis. Clinical and demographic characteristics, mean deviation, and pattern standard deviation were evaluated within a two year period before and after eyelid surgery. Results: The final analysis included 60 eyes of 38 patients. Change in visual field parameters after eyelid surgery did not reach statistical significance in crude or adjusted analyses. Among patients with ptosis, the margin reflex distance-1 was not associated with change in mean deviation after surgery (Pearson R2 â€‹= â€‹0.0061; P â€‹= â€‹0.700). Five of 17 eyes excluded from analysis due to unreliable pre-operative visual fields demonstrated substantial improvement after surgery. Conclusions: Functional upper eyelid malposition does not appear to cause spurious visual field abnormalities among glaucoma patients with reliable visual fields who were determined not to require eyelid taping at the time of their visual fields. Unreliable visual fields could be a sign of eyelid interference in this population.

Assessment of Remote Training, At-Home Testing, and Test-Retest Variability of a Novel Test for Clustered Virtual Reality Perimetry.

OBJECTIVE: To assess the feasibility of remotely training glaucoma patients to take a 10-session clustered virtual reality (VR) visual field (VF) test (Vivid Vision Perimetry [VVP-10]) at home, analyze results for test-retest variability, and assess correspondence with conventional perimetry. DESIGN: Cross-sectional study. SUBJECTS: Twenty-one subjects with glaucoma were enrolled and included in the feasibility assessment of remote training. Thirty-six eyes were used for test-retest analysis and determination of concordance with the Humphrey Field Analyzer (HFA). METHODS: Subjects were provided with a mobile VR headset containing the VVP-10 test software and trained remotely via video conferencing. Subjects were instructed to complete 10 sessions over a 14-day period. MAIN OUTCOME MEASURES: Feasibility was determined by the number of subjects who were able to independently complete VVP-10 over the 14-day period after 1 remote training session. The intraclass correlation coefficient (ICC) for average fraction seen across 10 sessions and the standard error (SE) of the mean were primary outcome measures for assessing test-retest variability. Correlation with HFA mean sensitivity (MS) across eyes, was a secondary outcome measure. RESULTS: Twenty subjects (95%) successfully completed the VVP-10 test series after 1 training session. The ICC for VVP-10 was 0.95 (95% confidence interval [CI], 0.92-0.97). The mean SE in units of fraction seen was 0.012. The Spearman correlations between VVP-10 average fraction seen and HFA MS were 0.87 (95% CI, 0.66-0.98) for moderate-to-advanced glaucoma eyes, and decreased to 0.67 (95% CI, 0.28-0.94) when all eyes were included. CONCLUSIONS: Remote training of patients at home is feasible, and subsequent remote clustered VF testing using VVP-10 by patients on their own, without any further interactions with caregivers or study staff, was possible. At-home VVP-10 results demonstrated low test-retest variability. Future studies must be conducted to determine if VVP-10, taken at home as convenient for the patient, may be a viable supplement to provide equivalent or complementary results to that of standard in-clinic assessment of visual function in glaucoma. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Coxsackievirus A24 causing acute conjunctivitis in a 2023 outbreak in Vietnam.

OBJECTIVES: To determine the associated pathogen during the 2023 conjunctivitis outbreak in Vietnam METHODS: RNA-sequencing was used to identify pathogens before and during the outbreak. RESULTS: 24 patients with infectious conjunctivitis between March and October 2023 from Hai Yen Vision Institute in Vietnam were swabbed. Coxsackievirus A24v was the most common pathogen identified. Phylogenetic analysis of these strains demonstrates similarities to the Coxsackievirus identified in the 2022 India outbreak. Human adenovirus D was also circulating. Ocular findings of tearing, purulence, and itching were common in this outbreak. CONCLUSIONS: Multiple viruses can co-circulate during conjunctivitis outbreaks. Hemorrhagic conjunctivitis, commonly associated with coxsackievirus conjunctivitis, was not a common clinical sign in this outbreak. Repeat genetic surveillance, with the notable inclusion of RNA virus detection strategies, is important for outbreak detection.

Biomarker Detection and Validation for Corneal Involvement in Patients With Acute Infectious Conjunctivitis.

Importance: Infectious conjunctivitis can lead to corneal involvement and result in ocular morbidity. The identification of biomarkers associated with corneal involvement has the potential to improve patient care. Objective: To identify biomarkers in patients with acute infectious conjunctivitis. Design, Setting, and Participants: This cross-sectional study took place from December 2016 to March 2024. Analyses were performed in 3 phases. First, logistic regression and machine learning algorithms were used to predict the probability of demonstrating corneal involvement in patients with presumed infectious conjunctivitis. Second, quantitative reverse transcription polymerase chain reaction (RT-qPCR) was used to confirm the most important biomarker gene identified by the algorithm. Third, the biomarker gene was validated in prospectively collected conjunctival samples of adult patients from 3 outpatient centers in Thailand and 1 in India. Patients with signs and symptoms of infectious conjunctivitis and onset within less than 14 days were eligible. Exclusion criteria were the inability to consent, presumed toxicity, or allergic conjunctivitis. Exposures: Acute infectious conjunctivitis. Main Outcomes and Measures: The identification and validation of ocular surface gene expression associated with corneal findings on slitlamp examination. Results: Thirteen genes exhibited a 1.5-log2 fold change in expression in patients with corneal involvement compared to patients without corneal involvement. Using the 13 genes to train and cross validate, logistic regression produced the highest mean area under the receiver operating characteristic curve (AUROC; 0.85; 95% CI, 0.84-0.86) for corneal involvement. The removal of apolipoprotein E (APOE) from the gene ensemble led to a decline in predictive performance of the logistic regression classifier (from mean AUROC 0.85 [95% CI, 0.84-0.86] to 0.74 [95% CI, 0.73-0.75]; adjusted P = .001 [Tukey test]). Orthogonal testing of APOE expression level with RT-qPCR showed that APOE expression was higher in patients with corneal involvement compared to patients without (median [IQR], 0.23 [0.04-0.47] vs 0.04 [0.02-0.06]; P = .004 [Mann-Whitney U test]). Using a Youden index of 0.23 Δ threshold cycle, APOE had a sensitivity of 56% (95% CI, 33-77) and a specificity of 88% (95% CI, 79-93) in 106 samples with conjunctivitis at Aravind, India (P < .001 [Fisher exact test]). When applied to a different patient population in Thailand, the same criteria could discriminate between disease states (58 samples; sensitivity, 47%; 95% CI, 30-64 and specificity, 93%; 95% CI, 77-99; P = .001 [Fisher exact test]). Conclusions and Relevance: The results from this study suggest that the host conjunctival immune response can be meaningfully interrogated to identify biomarkers for ocular surface diseases.

Apollo Rising: Acute Conjunctivitis Outbreak in India, 2022.

Purpose: To identify pathogens associated with the 2022 conjunctivitis outbreak in Tamil Nadu, India. Methods: This prospective study was conducted in November of 2022. Patients with presumed acute infectious conjunctivitis presenting to the Aravind Eye Clinic in Madurai, India were eligible. Anterior nares and conjunctival samples from participants were obtained and processed for metagenomic RNA deep sequencing (RNA-seq). Results: Samples from 29 patients were sequenced. A pathogen was identified in 28/29 (97%) patients. Coxsackievirus A24v, a highly infectious RNA virus, was the predominant pathogen and detected in 23/29 patients. Human adenovirus D (HAdV-D), a DNA virus commonly associated with conjunctivitis outbreaks, was detected in the remaining patients (5/29). Hemorrhagic conjunctiva was documented in both HAdV-D and coxsackievirus A24v affected patients but was not the predominant clinical presentation. Phylogenetic analysis of coxsackievirus A24v revealed a recent divergence from the 2015 outbreak. Conclusions: Coxsackievirus A24v and HAdV-D were co-circulating during the 2022 conjunctivitis outbreak in Tamil Nadu, India. Clinical findings were similar between patients with HAD-V and coxsackievirus A24v associated conjunctivitis. As high-throughput technologies become more readily accessible and cost-effective, unbiased pathogen surveillance may prove useful for outbreak surveillance and control.