Exploring Offline Large Language Models for Clinical Information Extraction: A Study of Renal Histopathological Reports of Lupus Nephritis Patients.

Open source, lightweight and offline generative large language models (LLMs) hold promise for clinical information extraction due to their suitability to operate in secured environments using commodity hardware without token cost. By creating a simple lupus nephritis (LN) renal histopathology annotation schema and generating gold standard data, this study investigates prompt-based strategies using three state-of-the-art lightweight LLMs, namely BioMistral-DARE-7B (BioMistral), Llama-2-13B (Llama 2), and Mistral-7B-instruct-v0.2 (Mistral). We examine the performance of these LLMs within a zero-shot learning environment for renal histopathology report information extraction. Incorporating four prompting strategies, including combinations of batch prompt (BP), single task prompt (SP), chain of thought (CoT) and standard simple prompt (SSP), our findings indicate that both Mistral and BioMistral consistently demonstrated higher performance compared to Llama 2. Mistral recorded the highest performance, achieving an F1-score of 0.996 [95% CI: 0.993, 0.999] for extracting the numbers of various subtypes of glomeruli across all BP settings and 0.898 [95% CI: 0.871, 0.921] in extracting relational values of immune markers under the BP+SSP setting. This study underscores the capability of offline LLMs to provide accurate and secure clinical information extraction, which can serve as a promising alternative to their heavy-weight online counterparts.

Social Vulnerability and Compliance With World Health Organization Advice on Protective Behaviors Against COVID-19 in African and Asia Pacific Countries: Factor Analysis to Develop a Social Vulnerability Index.

BACKGROUND: COVID-19 protective behaviors are key interventions advised by the World Health Organization (WHO) to prevent COVID-19 transmission. However, achieving compliance with this advice is often challenging, particularly among socially vulnerable groups. OBJECTIVE: We developed a social vulnerability index (SVI) to predict individuals' propensity to adhere to the WHO advice on protective behaviors against COVID-19 and identify changes in social vulnerability as Omicron evolved in African countries between January 2022 and August 2022 and Asia Pacific countries between August 2021 and June 2022. METHODS: In African countries, baseline data were collected from 14 countries (n=15,375) during the first Omicron wave, and follow-up data were collected from 7 countries (n=7179) after the wave. In Asia Pacific countries, baseline data were collected from 14 countries (n=12,866) before the first Omicron wave, and follow-up data were collected from 9 countries (n=8737) after the wave. Countries' socioeconomic and health profiles were retrieved from relevant databases. To construct the SVI for each of the 4 data sets, variables associated with COVID-19 protective behaviors were included in a factor analysis using polychoric correlation with varimax rotation. Influential factors were adjusted for cardinality, summed, and min-max normalized from 0 to 1 (most to least vulnerable). Scores for compliance with the WHO advice were calculated using individuals' self-reported protective behaviors against COVID-19. Multiple linear regression analyses were used to assess the associations between the SVI and scores for compliance to WHO advice to validate the index. RESULTS: In Africa, factors contributing to social vulnerability included literacy and media use, trust in health care workers and government, and country income and infrastructure. In Asia Pacific, social vulnerability was determined by literacy, country income and infrastructure, and population density. The index was associated with compliance with the WHO advice in both time points in African countries but only during the follow-up period in Asia Pacific countries. At baseline, the index values in African countries ranged from 0.00 to 0.31 in 13 countries, with 1 country having an index value of 1.00. The index values in Asia Pacific countries ranged from 0.00 to 0.23 in 12 countries, with 2 countries having index values of 0.79 and 1.00. During the follow-up phase, the index values decreased in 6 of 7 African countries and the 2 most vulnerable Asia Pacific countries. The index values of the least vulnerable countries remained unchanged in both regions. CONCLUSIONS: In both regions, significant inequalities in social vulnerability to compliance with WHO advice were observed at baseline, and the gaps became larger after the first Omicron wave. Understanding the dimensions that influence social vulnerability to protective behaviors against COVID-19 may underpin targeted interventions to enhance compliance with WHO recommendations and mitigate the impact of future pandemics among vulnerable groups.

Report from the World Health Organization's immunization and vaccines-related implementation research advisory committee (IVIR-AC) meeting, virtual gathering, 26 February-1 March 2024.

The Immunization and Vaccine-related Implementation Research Advisory Committee (IVIR-AC) is the World Health Organization's key standing advisory body to conduct an independent review of research, particularly of transmission and economic modeling analyses that estimate the impact and value of vaccines. From 26th February-1st March 2024, at its first of two semi-annual meetings, IVIR-AC provided feedback and recommendations across four sessions; this report summarizes the proceedings and recommendations from that meeting. Session topics included modeling of the impact and cost-effectiveness of the R21/Matrix-M malaria vaccine, meta-analysis of economic evaluations of vaccines, a global analysis estimating the impact of vaccination over the last 50 years, and modeling the impact of different RTS,S malaria vaccine dose schedules in seasonal settings.

Tracking diarrhea viruses and mpox virus using the wastewater surveillance network in Hong Kong.

The wastewater surveillance network successfully established for COVID-19 showed great potential to monitor other infectious viruses, such as norovirus, rotavirus and mpox virus. In this study, we established and validated detection methods for these viruses in wastewater. We developed a supernatant-based method to detect RNA viruses from wastewater samples and applied it to the monthly diarrhea viruses (norovirus genogroup I & II, and rotavirus) surveillance in wastewater treatment plants (WWTPs) at a city-wide level for 16 months. Significant correlations were observed between the diarrhea viruses concentrations in wastewater and detection rates in faecal specimens by clinical surveillance. The highest norovirus concentration in wastewater was obtained in winter, consistent with the seasonal pattern of norovirus outbreak in Hong Kong. Additionally, we established a pellet-based method to monitor DNA viruses in wastewater and detected weak signals for mpox virus in wastewater from a WWTP serving approximately 16,700 people, when the first mpox patient in Hong Kong was admitted to the hospital within the catchment area. Genomic sequencing provided confirmatory evidence for the validity of the results. Our findings emphasized the efficacy of the wastewater surveillance network in WWTPs as a cost-effective tool to track the transmission trend of diarrhea viruses and to provide sensitive detection of novel emerging viruses such as mpox virus in low-prevalence areas. The developed methods and surveillance results provide confidence for establishing robust wastewater surveillance programs to control infectious diseases in the post-pandemic era.

Enhanced prediction of abnormal glucose tolerance using an extended non-invasive risk score incorporating routine renal biochemistry.

INTRODUCTION: Type 2 diabetes is preventable in subjects with impaired glucose tolerance based on 2-hour plasma glucose (2hPG) during 75 g oral glucose tolerance test (OGTT). We incorporated routine biochemistry to improve the performance of a non-invasive diabetes risk score to identify individuals with abnormal glucose tolerance (AGT) defined by 2hPG≥7.8 mmol/L during OGTT. RESEARCH DESIGN AND METHODS: We used baseline data of 1938 individuals from the community-based "Better Health for Better Hong Kong - Hong Kong Family Diabetes Study (BHBHK-HKFDS) Cohort" recruited in 1998-2003. We incorporated routine biochemistry in a validated non-invasive diabetes risk score, and evaluated its performance using area under receiver operating characteristics (AUROC) with internal and external validation. RESULTS: The AUROC of the original non-invasive risk score to predict AGT was 0.698 (95% CI, 0.662 to 0.733). Following additional inclusion of fasting plasma glucose, serum potassium, creatinine, and urea, the AUROC increased to 0.778 (95% CI, 0.744 to 0.809, p<0.001). Net reclassification improved by 31.9% (p<0.001) overall, by 30.8% among people with AGT and 1.1% among people without AGT. The extended model showed good calibration (χ2=11.315, p=0.1845) and performance on external validation using an independent data set (AUROC=0.722, 95% CI, 0.680 to 0.764). CONCLUSIONS: The extended risk score incorporating clinical and routine biochemistry can be integrated into an electronic health records system to select high-risk subjects for evaluation of AGT using OGTT for prevention of diabetes.

Estimating the Epidemic Size of Superspreading Coronavirus Outbreaks in Real Time: Quantitative Study.

BACKGROUND: Novel coronaviruses have emerged and caused major epidemics and pandemics in the past 2 decades, including SARS-CoV-1, MERS-CoV, and SARS-CoV-2, which led to the current COVID-19 pandemic. These coronaviruses are marked by their potential to produce disproportionally large transmission clusters from superspreading events (SSEs). As prompt action is crucial to contain and mitigate SSEs, real-time epidemic size estimation could characterize the transmission heterogeneity and inform timely implementation of control measures. OBJECTIVE: This study aimed to estimate the epidemic size of SSEs to inform effective surveillance and rapid mitigation responses. METHODS: We developed a statistical framework based on back-calculation to estimate the epidemic size of ongoing coronavirus SSEs. We first validated the framework in simulated scenarios with the epidemiological characteristics of SARS, MERS, and COVID-19 SSEs. As case studies, we retrospectively applied the framework to the Amoy Gardens SARS outbreak in Hong Kong in 2003, a series of nosocomial MERS outbreaks in South Korea in 2015, and 2 COVID-19 outbreaks originating from restaurants in Hong Kong in 2020. RESULTS: The accuracy and precision of the estimation of epidemic size of SSEs improved with longer observation time; larger SSE size; and more accurate prior information about the epidemiological characteristics, such as the distribution of the incubation period and the distribution of the onset-to-confirmation delay. By retrospectively applying the framework, we found that the 95% credible interval of the estimates contained the true epidemic size after 37% of cases were reported in the Amoy Garden SARS SSE in Hong Kong, 41% to 62% of cases were observed in the 3 nosocomial MERS SSEs in South Korea, and 76% to 86% of cases were confirmed in the 2 COVID-19 SSEs in Hong Kong. CONCLUSIONS: Our framework can be readily integrated into coronavirus surveillance systems to enhance situation awareness of ongoing SSEs.

Cervical screening among Chinese females in the era of HPV vaccination: a population-based survey on screening uptake and regular screening following an 18-year organized screening program.

OBJECTIVE: China has a substantial disease burden of cervical cancer. To further understand preventive measures for reducing cervical cancer in China, this study aimed to correlate screening attendance and regular screening with human papillomavirus (HPV) vaccination among Chinese females. METHODS: This prospective questionnaire-based survey recruited Chinese females aged 25 or above in Hong Kong by random digit dialing telephone interviews in 2022. The survey studied women's practice of cervical screening and adherence to regular screening. Variables including HPV vaccination status and attendance of physical check-ups were involved in the questionnaire. Screening uptake and screening adherence were the main outcomes, which were measured as the proportion of women who reported having attended a cervical screening and screened regularly, respectively. RESULTS: Out of 906 valid respondents, the reported cervical screening uptake was over 70% among females aged 30 or above and particularly over 80% among women aged 35-59; however, the uptake was only 46% among those aged 25-29. Adherence to regular screening was 50%-60% across ages 25-59 years and dropped to approximately 40% for women older than 60 years. Both screening uptake and adherence were associated with HPV vaccination, with adjusted odds ratios of 2.37 and 2.23, respectively. A large proportion of regularly screened women may be overscreened for screening more frequently than recommended. CONCLUSION: Responded Chinese females showed good cervical screening uptake but were moderately adherent to regular screening. Policymakers should emphasize the importance of regular screening and the recommended screening frequency by HPV vaccination status for better healthcare resource use.

Serological assays for differentiating natural COVID-19 infection from vaccine induced immunity.

BACKGROUND: Natural SARS-CoV-2 infection may elicit antibodies to a range of viral proteins including non-structural protein ORF8. RNA, adenovirus vectored and sub-unit vaccines expressing SARS-CoV-2 spike would be only expected to elicit S-antibodies and antibodies to distinct domains of nucleocapsid (N) protein may reliably differentiate infection from vaccine-elicited antibody. However, inactivated whole virus vaccines may potentially elicit antibody to wider range of viral proteins, including N protein. We hypothesized that antibody to ORF8 protein will discriminate natural infection from vaccination irrespective of vaccine type. METHODS: We optimized and validated the anti-ORF8 and anti-N C-terminal domain (NCTD) ELISA assays using sera from pre-pandemic, RT-PCR confirmed natural infection sera and BNT162b2 (BNT) or CoronaVac vaccinees. We then applied these optimized assays to a cohort of blood donor sera collected in April-July 2022 with known vaccination and self-reported infection status. RESULTS: We optimized cut-off values for the anti-ORF8 and anti-N-CTD IgG ELISA assays using receiver-operating-characteristic (ROC) curves. The sensitivity of the anti-ORF8 and anti-N-CTD ELISA for detecting past infection was 83.2% and 99.3%, respectively. Specificity of anti-ORF8 ELISA was 96.8 % vs. the pre-pandemic cohort or 93% considering the pre-pandemic and vaccine cohorts together. The anti-N-CTD ELISA specificity of 98.9% in the pre-pandemic cohort, 93% in BNT vaccinated and only 4 % in CoronaVac vaccinated cohorts. Anti-N-CTD antibody was longer-lived than anti-ORF8 antibody after natural infection. CONCLUSIONS: Anti-N-CTD antibody assays provide good discrimination between natural infection and vaccination in BNT162b2 vaccinated individuals. Anti-ORF8 antibody can help discriminate infection from vaccination in either type of vaccine and help estimate infection attack rates (IAR) in communities.

Avian Influenza A(H5N1) Neuraminidase Inhibition Antibodies in Healthy Adults after Exposure to Influenza A(H1N1)pdm09.

We detected high titers of cross-reactive neuraminidase inhibition antibodies to influenza A(H5N1) virus clade 2.3.4.4b in 96.8% (61/63) of serum samples from healthy adults in Hong Kong in 2020. In contrast, antibodies at low titers were detected in 42% (21/50) of serum samples collected in 2009. Influenza A(H1N1)pdm09 and A(H5N1) titers were correlated.

Higher Short-Chain Fermentable Carbohydrates Are Associated with Lower Body Fat and Higher Insulin Sensitivity in People with Prediabetes.

The quality of carbohydrates has metabolic consequences in people with prediabetes. However, the causality of short-chain fermentable carbohydrate intakes and metabolic parameters has not been explored in the prediabetic or diabetic population. We investigated associations between different types of carbohydrates, including fermentable oligosaccharides, disaccharides, monosaccharides, polyols (FODMAPs), and polysaccharides (dietary fibre), and body composition and glucose/insulin responses in subjects with prediabetes. In this prospective cross-sectional study, 177 subjects with impaired glucose tolerance (IGT) (mean age: 60 (54-62) years, 41% men) underwent an assessment of body composition and completed six-point oral glucose tolerance tests (OGTT), Homeostatic Model Assessment of Insulin Resistance (HOMA2-IR), insulin sensitivity, detailed 3-day food records, and physical activity questionnaire. Daily habitual FODMAP intake decreased progressively with increasing BMI, ranging from 7.9 (6.2-12.7) g/d in subjects with normal BMI and 6.6 (4.6-9.9) g/d in subjects with overweight to 5.8 (3.8-9.0) g/d in subjects with obesity (p = 0.038). After adjustment for age and gender, galactooligosaccharides (GOSs) were negatively correlated with body fat (Standardised Beta coefficient ß = -0.156, p = 0.006) and positively associated with insulin sensitivity (ß = 0.243, p = 0.001). This remained significant after adjustment for macronutrients, fibre, and physical activity (p = 0.035 and p = 0.010, respectively). In individuals with IGT, higher dietary GOS intake was associated with lower body fat and higher insulin sensitivity independent of macronutrients and fibre intake, calling for interventional studies to evaluate the effect of FODMAP intake in prediabetes.

COVID-19 Vaccination Willingness and Reasons for Vaccine Refusal.

Importance: Hong Kong was held as an exemplar for pandemic response until it recorded the world's highest daily COVID-19 mortality, which was likely due to vaccine refusal. To prevent this high mortality in future pandemics, information on underlying reasons for vaccine refusal is necessary. Objectives: To track the evolution of COVID-19 vaccination willingness and uptake from before vaccine rollout to mass vaccination, to examine factors associated with COVID-19 vaccine refusal and compare with data from Singapore, and to assess the population attributable fraction for vaccine refusal. Design, Setting, and Participants: This cohort study used data from randomly sampled participants from 14 waves of population-based studies in Hong Kong (February 2020 to May 2022) and 2 waves of population-based studies in Singapore (May 2020 to June 2021 and October 2021 to January 2022), and a population-wide registry of COVID-19 vaccination appointments. Data were analyzed from February 23, 2021, to May 30, 2022. Exposures: Trust in COVID-19 vaccine information sources (ie, health authorities, physicians, traditional media, and social media); COVID-19 vaccine confidence on effectiveness, safety, and importance; COVID-19 vaccine misconceptions on safety and high-risk groups; political views; and COVID-19 policies (ie, workplace vaccine mandates and vaccine pass). Main Outcomes and Measures: Primary outcomes were the weighted prevalence of COVID-19 vaccination willingness over the pandemic, adjusted incidence rate ratios, and population attributable fractions of COVID-19 vaccine refusal. A secondary outcome was change in daily COVID-19 vaccination appointments. Results: The study included 28 007 interviews from 20 waves of longitudinal data, with 1114 participants in the most recent wave (median [range] age, 54.2 years [20-92] years; 571 [51.3%] female). Four factors-mistrust in health authorities, low vaccine confidence, vaccine misconceptions, and political views-could jointly account for 82.2% (95% CI, 62.3%-100.0%) of vaccine refusal in adults aged 18 to 59 years and 69.3% (95% CI, 47.2%-91.4%) of vaccine refusal in adults aged 60 years and older. Workplace vaccine mandates were associated with 62.2% (95% CI, 9.9%-139.2%) increases in daily COVID-19 vaccination appointments, and the Hong Kong vaccine pass was associated with 124.8% (95% CI, 65.9%-204.6%) increases in daily COVID-19 vaccination appointments. Conclusions and Relevance: These findings suggest that trust in health authorities was fundamental to overcoming vaccine hesitancy. As such, engendering trust in health care professionals, experts, and public health agencies should be incorporated into pandemic preparedness and response.

Development and application of influenza virus wastewater surveillance in Hong Kong.

Wastewater surveillance is considered as a powerful tool in providing cost-effective, population-wide and near real-time surveillance results for controlling infectious diseases (i.e., SARS-CoV-2, influenza virus), complementary to clinical surveillance. To facilitate the utility of this emerging tool, we developed two preanalytical protocols (supernatant-based and pellet-based) for influenza A/B virus (IAV/IBV) wastewater surveillance and applied them to the established wastewater surveillance network for large-scale longitudinal monitoring in Hong Kong. We tested 724 wastewater samples from 24 stationary sites for weekly surveillance for 8 months and 458 wastewater samples from 11 wastewater treatment plants (WWTPs) for more frequent (three times per week) city-wide surveillance for 4 months when influenza season commenced. We found the city-wide IAV virus concentration in wastewater were associated with the detection rate and influenza-like illness plus rates (ILI+) of clinical respiratory specimens and increased significantly after the cancelling of mask mandate that was in place for COVID-19. IBV was at low detection rates and low virus concentration levels, consistent with the low detection rates observed by clinical surveillance. In addition, we conducted virus subtype identification in selected wastewater samples, and observed the H1pdm was the major circulation subtype. Moreover, the obtained virus signals were confirmed by Sanger sequencing of PCR products, suggesting the feasibility and applicability of established methods for rapid detection of influenza virus types and subtypes in wastewater surveillance. This study demonstrates the applicability of IAV/IBV wastewater surveillance to current wastewater infrastructures and it could be used as a rapid and cost-effective surveillance strategy to track virus transmission patterns in the community for timely public health actions in the future.

Dissecting human population variation in single-cell responses to SARS-CoV-2.

Humans display substantial interindividual clinical variability after SARS-CoV-2 infection1-3, the genetic and immunological basis of which has begun to be deciphered4. However, the extent and drivers of population differences in immune responses to SARS-CoV-2 remain unclear. Here we report single-cell RNA-sequencing data for peripheral blood mononuclear cells-from 222 healthy donors of diverse ancestries-that were stimulated with SARS-CoV-2 or influenza A virus. We show that SARS-CoV-2 induces weaker, but more heterogeneous, interferon-stimulated gene activity compared with influenza A virus, and a unique pro-inflammatory signature in myeloid cells. Transcriptional responses to viruses display marked population differences, primarily driven by changes in cell abundance including increased lymphoid differentiation associated with latent cytomegalovirus infection. Expression quantitative trait loci and mediation analyses reveal a broad effect of cell composition on population disparities in immune responses, with genetic variants exerting a strong effect on specific loci. Furthermore, we show that natural selection has increased population differences in immune responses, particularly for variants associated with SARS-CoV-2 response in East Asians, and document the cellular and molecular mechanisms by which Neanderthal introgression has altered immune functions, such as the response of myeloid cells to viruses. Finally, colocalization and transcriptome-wide association analyses reveal an overlap between the genetic basis of immune responses to SARS-CoV-2 and COVID-19 severity, providing insights into the factors contributing to current disparities in COVID-19 risk.

Higher dietary magnesium and potassium intake are associated with lower body fat in people with impaired glucose tolerance.

Introduction: Obesity and diabetes are public health concerns worldwide, but few studies have examined the habitual intake of minerals on body composition in people with prediabetes. Methods: In this prospective cross-sectional study, 155 Chinese subjects with IGT [median age: 59 (53-62) years, 58% female] had an assessment of body composition including body fat percentage, oral glucose tolerance tests (OGTT), Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) and 3-day food records from nutritional programme analysis. Results: Dietary intake of minerals was negatively correlated with body fat. People with obesity had the lowest daily consumption of iron median (IQR) 10.3 (6.9-13.3) mg, magnesium 224 (181-282) mg, and potassium 1973 (1563-2,357) mg when compared to overweight [10.5 (8.0-14.5) mg, 273 (221-335) mg, and 2,204 (1720-2,650) mg] and normal weight individuals [13.2 (10.0-18.6) mg, 313 (243-368) mg, and 2,295 (1833-3,037) mg] (p = 0.008, <0.0001, and 0.013 respectively). Amongst targeted minerals, higher dietary magnesium and potassium intake remained significantly associated with lower body fat after the adjustment of age, gender, macronutrients, fibre, and physical activity. Conclusion: Dietary magnesium and potassium intake may be associated with lower body fat in people with impaired glucose tolerance. Inadequate dietary mineral intake may play contribute to obesity and metabolic disorders independent of macronutrients and fibre consumption.

Effectiveness of chatbots on COVID vaccine confidence and acceptance in Thailand, Hong Kong, and Singapore.

Chatbots have become an increasingly popular tool in the field of health services and communications. Despite chatbots' significance amid the COVID-19 pandemic, few studies have performed a rigorous evaluation of the effectiveness of chatbots in improving vaccine confidence and acceptance. In Thailand, Hong Kong, and Singapore, from February 11th to June 30th, 2022, we conducted multisite randomised controlled trials (RCT) on 2,045 adult guardians of children and seniors who were unvaccinated or had delayed vaccinations. After a week of using COVID-19 vaccine chatbots, the differences in vaccine confidence and acceptance were compared between the intervention and control groups. Compared to non-users, fewer chatbot users reported decreased confidence in vaccine effectiveness in the Thailand child group [Intervention: 4.3 % vs. Control: 17%, P = 0.023]. However, more chatbot users reported decreased vaccine acceptance [26% vs. 12%, P = 0.028] in Hong Kong child group and decreased vaccine confidence in safety [29% vs. 10%, P = 0.041] in Singapore child group. There was no statistically significant change in vaccine confidence or acceptance in the Hong Kong senior group. Employing the RE-AIM framework, process evaluation indicated strong acceptance and implementation support for vaccine chatbots from stakeholders, with high levels of sustainability and scalability. This multisite, parallel RCT study on vaccine chatbots found mixed success in improving vaccine confidence and acceptance among unvaccinated Asian subpopulations. Further studies that link chatbot usage and real-world vaccine uptake are needed to augment evidence for employing vaccine chatbots to advance vaccine confidence and acceptance.

Resurgence of Omicron BA.2 in SARS-CoV-2 infection-naive Hong Kong.

Hong Kong experienced a surge of Omicron BA.2 infections in early 2022, resulting in one of the highest per-capita death rates of COVID-19. The outbreak occurred in a dense population with low immunity towards natural SARS-CoV-2 infection, high vaccine hesitancy in vulnerable populations, comprehensive disease surveillance and the capacity for stringent public health and social measures (PHSMs). By analyzing genome sequences and epidemiological data, we reconstructed the epidemic trajectory of BA.2 wave and found that the initial BA.2 community transmission emerged from cross-infection within hotel quarantine. The rapid implementation of PHSMs suppressed early epidemic growth but the effective reproduction number (Re) increased again during the Spring festival in early February and remained around 1 until early April. Independent estimates of point prevalence and incidence using phylodynamics also showed extensive superspreading at this time, which likely contributed to the rapid expansion of the epidemic. Discordant inferences based on genomic and epidemiological data underscore the need for research to improve near real-time epidemic growth estimates by combining multiple disparate data sources to better inform outbreak response policy.