Assessment of CD8+ T-cell mediated immunity in an influenza A(H3N2) human challenge model in Belgium: a single centre, randomised, double-blind phase 2 study.

BACKGROUND: Protection afforded by inactivated influenza vaccines can theoretically be improved by inducing T-cell responses to conserved internal influenza A antigens. We assessed whether, in an influenza controlled human infection challenge, susceptible individuals receiving a vaccine boosting T-cell responses would exhibit lower viral load and decreased symptoms compared with placebo recipients. METHODS: In this single centre, randomised, double-blind phase 2 study, healthy adult (aged 18-55 years) volunteers with microneutralisation titres of less than 20 to the influenza A(H3N2) challenge strain were enrolled at an SGS quarantine facility in Antwerp, Belgium. Participants were randomly assigned double-blind using a permuted-block list with a 3:2 allocation ratio to receive 0·5 mL intramuscular injections of modified vaccinia Ankara (MVA) expressing H3N2 nucleoprotein (NP) and matrix protein 1 (M1) at 1·5 × 108 plaque forming units (4·3 × 108 50% tissue culture infectious dose [TCID50]; MVA-NP+M1 group) or saline placebo (placebo group). At least 6 weeks later, participants were challenged intranasally with 0·5 mL of a 1 × 106 TCID50/mL dose of influenza A/Belgium/4217/2015 (H3N2). Nasal swabs were collected twice daily from day 2 until day 11 for viral PCR, and symptoms of influenza were recorded from day 2 until day 11. The primary outcome was to determine the efficacy of MVA-NP+M1 vaccine to reduce the degree of nasopharyngeal viral shedding as measured by the cumulative viral area under the curve using a log-transformed quantitative PCR. This study is registered with ClinicalTrials.gov, NCT03883113. FINDINGS: Between May 2 and Oct 24, 2019, 145 volunteers were enrolled and randomly assigned to the MVA-NP+M1 group (n=87) or the placebo group (n=58). Of these, 118 volunteers entered the challenge period (71 in the MVA-NP+M1 group and 47 in the placebo group) and 117 participants completed the study (71 in the MVA-NP+M1 group and 46 in the placebo group). 78 (54%) of the 145 volunteers were female and 67 (46%) were male. The primary outcome, overall viral load as determined by quantitative PCR, did not show a statistically significant difference between the MVA-NP+M1 (mean 649·7 [95% CI 552·7-746·7) and placebo groups (mean 726·1 [604·0-848·2]; p=0·17). All reported treatment emergent adverse events (TEAEs; 11 in the vaccination phase and 51 in the challenge phase) were grade 1 and 2, except for two grade 3 TEAEs in the placebo group in the challenge phase. A grade 4 second trimester fetal death, considered possibly related to the MVA-NP+M1 vaccination, and an acute psychosis reported in a placebo participant during the challenge phase were reported. INTERPRETATION: The use of an MVA vaccine to expand CD4+ or CD8+ T cells to conserved influenza A antigens in peripheral blood did not affect nasopharyngeal viral load in an influenza H3N2 challenge model in seronegative, healthy adults. FUNDING: Department of Health and Human Services; Administration for Strategic Preparedness and Response; Biomedical Advanced Research and Development Authority; and Barinthus Biotherapeutics.

Nowcasting and forecasting the 2022 U.S. mpox outbreak: Support for public health decision making and lessons learned.

In June of 2022, the U.S. Centers for Disease Control and Prevention (CDC) Mpox Response wanted timely answers to important epidemiological questions which can now be answered more effectively through infectious disease modeling. Infectious disease models have shown to be valuable tools for decision making during outbreaks; however, model complexity often makes communicating the results and limitations of models to decision makers difficult. We performed nowcasting and forecasting for the 2022 mpox outbreak in the United States using the R package EpiNow2. We generated nowcasts/forecasts at the national level, by Census region, and for jurisdictions reporting the greatest number of mpox cases. Modeling results were shared for situational awareness within the CDC Mpox Response and publicly on the CDC website. We retrospectively evaluated forecast predictions at four key phases (early, exponential growth, peak, and decline) during the outbreak using three metrics, the weighted interval score, mean absolute error, and prediction interval coverage. We compared the performance of EpiNow2 with a naïve Bayesian generalized linear model (GLM). The EpiNow2 model had less probabilistic error than the GLM during every outbreak phase except for the early phase. We share our experiences with an existing tool for nowcasting/forecasting and highlight areas of improvement for the development of future tools. We also reflect on lessons learned regarding data quality issues and adapting modeling results for different audiences.

Modelling the impact of vaccination and sexual behaviour adaptations on mpox cases in the USA during the 2022 outbreak.

BACKGROUND: The 2022 mpox outbreak has infected over 30 000 people in the USA, with cases declining since mid-August. Infections were commonly associated with sexual contact between men. Interventions to mitigate the outbreak included vaccination and a reduction in sexual partnerships. Understanding the contributions of these interventions to decreasing cases can inform future public health efforts. METHODS: We fit a dynamic network transmission model to mpox cases reported by Washington DC through 10 January 2023. This model incorporated both vaccine administration data and reported reductions in sexual partner acquisition by gay, bisexual or other men who have sex with men (MSM). The model output consisted of daily cases over time with or without vaccination and/or behavioural adaptation. RESULTS: We found that initial declines in cases were likely caused by behavioural adaptations. One year into the outbreak, vaccination and behavioural adaptation together prevented an estimated 84% (IQR 67% to 91%) of cases. Vaccination alone averted 79% (IQR 64% to 88%) of cases and behavioural adaptation alone averted 25% (IQR 10% to 42%) of cases. We further found that in the absence of vaccination, behavioural adaptation would have reduced the number of cases, but would have prolonged the outbreak. CONCLUSIONS: We found that initial declines in cases were likely caused by behavioural adaptation, but vaccination averted more cases overall and was key to hastening outbreak conclusion. Overall, this indicates that outreach to encourage individuals to protect themselves from infection was vital in the early stages of the mpox outbreak, but that combination with a robust vaccination programme hastened outbreak conclusion.

Evaluation of a panel of therapeutic antibody clinical candidates for efficacy against SARS-CoV-2 in Syrian hamsters.

The COVID-19 pandemic spurred the rapid development of a range of therapeutic antibody treatments. As part of the US government's COVID-19 therapeutic response, a research team was assembled to support assay and animal model development to assess activity for therapeutics candidates against SARS-CoV-2. Candidate treatments included monoclonal antibodies, antibody cocktails, and products derived from blood donated by convalescent patients. Sixteen candidate antibody products were obtained directly from manufacturers and evaluated for neutralization activity against the WA-01 isolate of SARS-CoV-2. Products were further tested in the Syrian hamster model using prophylactic (-24 h) or therapeutic (+8 h) treatment approaches relative to intranasal SARS-CoV-2 exposure. In vivo assessments included daily clinical scores and body weights. Viral RNA and viable virus titers were quantified in serum and lung tissue with histopathology performed at 3d and 7d post-virus-exposure. Sham-treated, virus-exposed hamsters showed consistent clinical signs with concomitant weight loss and had detectable viral RNA and viable virus in lung tissue. Histopathologically, interstitial pneumonia with consolidation was present. Therapeutic efficacy was identified in treated hamsters by the absence or diminution of clinical scores, body weight loss, viral loads, and improved semiquantitative lung histopathology scores. This work serves as a model for the rapid, systematic in vitro and in vivo assessment of the efficacy of candidate therapeutics at various stages of clinical development. These efforts provided preclinical efficacy data for therapeutic candidates. Furthermore, these studies were invaluable for the phenotypic characterization of SARS CoV-2 disease in hamsters and of utility to the broader scientific community.

Serial Interval and Incubation Period Estimates of Monkeypox Virus Infection in 12 Jurisdictions, United States, May-August 2022.

Using data from 12 US health departments, we estimated mean serial interval for monkeypox virus infection to be 8.5 (95% credible interval 7.3-9.9) days for symptom onset, based on 57 case pairs. Mean estimated incubation period was 5.6 (95% credible interval 4.3-7.8) days for symptom onset, based on 35 case pairs.

Novel modelling approaches to predict the role of antivirals in reducing influenza transmission.

To aid understanding of the effect of antiviral treatment on population-level influenza transmission, we used a novel pharmacokinetic-viral kinetic transmission model to test the correlation between nasal viral load and infectiousness, and to evaluate the impact that timing of treatment with the antivirals oseltamivir or baloxavir has on influenza transmission. The model was run under three candidate profiles whereby infectiousness was assumed to be proportional to viral titer on a natural-scale, log-scale, or dose-response model. Viral kinetic profiles in the presence and absence of antiviral treatment were compared for each individual (N = 1000 simulated individuals); subsequently, viral transmission mitigation was calculated. The predicted transmission mitigation was greater with earlier administration of antiviral treatment, and with baloxavir versus oseltamivir. When treatment was initiated 12-24 hours post symptom onset, the predicted transmission mitigation was 39.9-56.4% for baloxavir and 26.6-38.3% for oseltamivir depending on the infectiousness profile. When treatment was initiated 36-48 hours post symptom onset, the predicted transmission mitigation decreased to 0.8-28.3% for baloxavir and 0.8-19.9% for oseltamivir. Model estimates were compared with clinical data from the BLOCKSTONE post-exposure prophylaxis study, which indicated the log-scale model for infectiousness best fit the observed data and that baloxavir affords greater reductions in secondary case rates compared with neuraminidase inhibitors. These findings suggest a role for baloxavir and oseltamivir in reducing influenza transmission when treatment is initiated within 48 hours of symptom onset in the index patient.

Reducing Influenza Virus Transmission: The Potential Value of Antiviral Treatment.

Prompt antiviral treatment has the potential to reduce influenza virus transmission to close contacts, but rigorous data on the magnitude of treatment effects on transmission are limited. Animal model data indicate that rapid reductions in viral replication after antiviral treatment reduce the risk of transmission. Observational and clinical trial data with oseltamivir and other neuraminidase inhibitors indicate that prompt treatment of household index patients seems to reduce the risk of illness in contacts, although the magnitude of the reported effects has varied widely across studies. In addition, the potential risk of transmitting drug-resistant variants exists with all approved classes of influenza antivirals. A controlled trial examining baloxavir treatment efficacy to reduce transmission, including the risk of transmitting virus with reduced baloxavir susceptibility, is currently in progress. If reduced transmission risk is confirmed, modeling studies indicate that early treatment could have major epidemiologic benefits in seasonal and pandemic influenza.

Improving pandemic preparedness through better, faster influenza vaccines.

Introduction. Timely availability of effective influenza vaccine will be critical to mitigate the next influenza pandemic. The mission of Biomedical Advanced Research and Development Authority (BARDA) is to develop medical countermeasures against pandemics, including influenza and other health security threats.Areas covered. Despite considerable gains in pandemic vaccine preparedness since 2009, old and new challenges threaten the pandemic influenza response capabilities of the U.S. Government: insufficient U.S.-based vaccine production, two-dose vaccination regimen, logistically complex adjuvanted formulation, and sustained surge manufacturing capacity despite no commercial market for pandemic vaccines. Although the coronavirus disease 2019 (COVID-19) pandemic has re-exposed these gaps in preparedness and response, previous investments into flexible influenza vaccine technologies proved to be critical to accelerate COVID-19 vaccine development.Expert opinion. BARDA addresses these challenges by implementing a pandemic influenza vaccine strategy with two key goals: 1) accelerating vaccine development and production (faster) and 2) improving vaccine performance (better). This strategy involves an end-to-end approach, including increasing manufacturing and fill-finish capacity; improving release testing speed; and funding clinical trials to improve current vaccine utilization. As demonstrated by the COVID-19 response, continued investments into this pandemic influenza vaccine strategy will further enhance the ability to respond to future emerging pandemic pathogens.

Vaccine effectiveness of cell-culture relative to egg-based inactivated influenza vaccine during the 2017-18 influenza season.

There is concern that influenza vaccine effectiveness (VE) may be attenuated by passage in eggs during manufacture. We compared quadrivalent cell-culture vaccine with egg-based vaccines, most of which were trivalent, against influenza A and B during 2017-2018 when A(H3N2) and B/Yamagata (present only in quadrivalent vaccines) predominated. We retrospectively examined risk of PCR-confirmed influenza A and B in members of Kaiser Permanente Northern California aged 4-64 years. We estimated the relative VE (rVE) of cell-culture vaccine versus egg-based vaccines, and the absolute VE (aVE) of each vaccine comparing vaccinated to unvaccinated individuals. Analyses used Cox regression with a calendar timeline, stratified by birth year, and adjusted for demographics, co-morbidities and utilization. One-third (1,016,965/3,053,248) of the population was vaccinated; 932,545 (91.7% of vaccinees) received egg-based and 84,420 (8.3%) received cell-culture vaccines. The rVE against influenza A was 8.0% (95% CI: -10, 23); aVE was 31.7% (CI: 18.7, 42.6) for cell-culture and 20.1% (CI: 14.5, 25.4) for egg-based vaccines. The rVE against influenza B was 39.6% (CI: 27.9, 49.3); aVE was 40.9% (CI: 30, 50.1) for cell-culture and 9.7% (CI 3.5, 15.6) for egg-based trivalent vaccines. Inclusion of the B/Yamagata lineage in the quadrivalent cell-based vaccine provided better protection against influenza B but vaccine effectiveness against influenza A was low for both the cell-culture vaccine and the egg-based vaccines. Improving influenza vaccines requires ongoing comparative vaccine effectiveness monitoring.

Efficacy, immunogenicity, and safety of an oral influenza vaccine: a placebo-controlled and active-controlled phase 2 human challenge study.

BACKGROUND: Influenza is an important public health problem and existing vaccines are not completely protective. New vaccines that protect by alternative mechanisms are needed to improve efficacy of influenza vaccines. In 2015, we did a phase 1 trial of an oral influenza vaccine, VXA-A1.1. A favourable safety profile and robust immunogenicity results in that trial supported progression of the vaccine to the current phase 2 trial. The aim of this study was to evaluate efficacy of the vaccine in a human influenza challenge model. METHODS: We did a single-site, placebo-controlled and active-controlled, phase 2 study at WCCT Global, Costa Mesa, CA, USA. Eligible individuals had an initial A/California/H1N1 haemagglutination inhibition titre of less than 20 and were aged 18-49 years and in good health. Individuals were randomly assigned (2:2:1) to receive a single immunisation of either 1011 infectious units of VXA-A1.1 (a monovalent tablet vaccine) orally, a full human dose of quadrivalent inactivated influenza vaccine (IIV) via intramuscular injection, or matched placebo. Randomisation was done by computer-generated assignments with block size of five. An unmasked pharmacist provided the appropriate vaccines and placebos to the administrating nurse. Individuals receiving the treatments, investigators, and staff were all masked to group assignments. 90 days after immunisation, individuals without clinically significant symptoms or signs of influenza, an oral temperature of higher than 37·9°C, a positive result for respiratory viral shedding on a Biofire test, and any investigator-assessed contraindications were challenged intranasally with 0·5 mL wild-type A/CA/like(H1N1)pdm09 influenza virus. The primary outcomes were safety, which was assessed in all immunised participants through 365 days, and influenza-positive illness after viral challenge, which was assessed in individuals that received the viral challenge and the required number of assessments post viral challenge. This trial is registered with ClinicalTrials.gov, number NCT02918006. RESULTS: Between Aug 31, 2016, and Jan 23, 2017, 374 individuals were assessed for eligibility, of whom 179 were randomly assigned to receive either VXA-A1.1 (n=71 [one individual did not provide a diary card, thus the solicited events were assessed in 70 individuals]), IIV (n=72), or placebo (n=36). Between Dec 2, 2016, and April 26, 2017, 143 eligible individuals (58 in the VXA-A1.1 group, 54 in the IIV group, and 31 in the placebo group) were challenged with influenza virus. VXA-A1.1 was well tolerated with no serious or medically significant adverse events. The most prevalent solicited adverse events for each of the treatment groups after immunisation were headache in the VXA-A1.1 (in five [7%] of 70 participants) and placebo (in seven [19%] of 36 participants) groups and tenderness at injection site in the IIV group (in 19 [26%] of 72 participants) Influenza-positive illness after challenge was detected in 17 (29%) of 58 individuals in the VXA-A1.1 group, 19 (35%) of 54 in the IIV group, and 15 (48%) of 31 in the placebo group. INTERPRETATION: Orally administered VXA-A1.1 was well tolerated and generated protective immunity against virus shedding, similar to a licensed intramuscular IIV. These results represent a major step forward in developing a safe and effective oral influenza vaccine. FUNDING: Department of Health and Human Services, Office of the Assistant Secretary for Preparedness and Response, and Biomedical Advanced Research and Development Authority.

A semiempirical effective Hamiltonian based approach for analyzing excited state wave functions and computing excited state absorption spectra using real-time dynamics.

We describe a new approach to extract information about an excited state wave function using a reduced orbital space molecular orbital decomposition approach for time-dependent density obtained from real-time dynamics. We also show how this information about the excited state wave function can be used to accelerate the convergence of real-time spectra and model excited state electron dynamics. We have combined this approach with our recent implementation of the real-time intermediate neglect of differential overlap for spectroscopy (INDO/S) to study the solvatochromic shift of Nile Red in acetone, ethanol, toluene and n-hexane solvents, and, for the first time, the excited state absorption spectra of coronene, 5,10,15,20-tetra(4-pyridyl)porphyrin (TPyP), zinc phthalocyanine, and nickel TPyP using a semiempirical Hamiltonian.

Modeling Cutaneous Radiation Injury from Fallout.

OBJECTIVE: Beta radiation from nuclear weapons fallout could pose a risk of cutaneous radiation injury (CRI) to evacuating populations but has been investigated only cursorily. This work examines 2 components of CRI necessary for estimating the potential public health consequences of exposure to fallout: dose protraction and depth of dose. METHODS: Dose protraction for dry and moist desquamation was examined by adapting the biological effective dose (BED) calculation to a hazard function calculation similar to those recommended by the National Council on Radiation Protection and Measurements for other acute radiation injuries. Depth of burn was examined using Monte Carlo neutral Particle version 5 to model the penetration of beta radiation from fallout to different skin tissues. RESULTS: Nonlinear least squares analysis of the BED calculation estimated the hazard function parameter θ1 (dose rate effectiveness factors) as 25.5 and 74.5 (Gy-eq)2 h-1 for dry and moist desquamation, respectively. Depth of dose models revealed that beta radiation is primarily absorbed in the dead skin layers and basal layer and that dose to underlying tissues is small (<5% of dose to basal layer). CONCLUSIONS: The low relative dose to tissues below the basal layer suggests that radiation-induced necrosis or deep skin burns are unlikely from direct skin contamination with fallout. These results enable future modeling studies to better examine CRI risk and facilitate effectively managing and treating populations with specialized injuries from a nuclear detonation. (Disaster Med Public Health Preparedness. 2019;13:463-469).

Summary results of the 2014-2015 DARPA Chikungunya challenge.

BACKGROUND: Emerging pathogens such as Zika, chikungunya, Ebola, and dengue viruses are serious threats to national and global health security. Accurate forecasts of emerging epidemics and their severity are critical to minimizing subsequent mortality, morbidity, and economic loss. The recent introduction of chikungunya and Zika virus to the Americas underscores the need for better methods for disease surveillance and forecasting. METHODS: To explore the suitability of current approaches to forecasting emerging diseases, the Defense Advanced Research Projects Agency (DARPA) launched the 2014-2015 DARPA Chikungunya Challenge to forecast the number of cases and spread of chikungunya disease in the Americas. Challenge participants (n=38 during final evaluation) provided predictions of chikungunya epidemics across the Americas for a six-month period, from September 1, 2014 to February 16, 2015, to be evaluated by comparison with incidence data reported to the Pan American Health Organization (PAHO). This manuscript presents an overview of the challenge and a summary of the approaches used by the winners. RESULTS: Participant submissions were evaluated by a team of non-competing government subject matter experts based on numerical accuracy and methodology. Although this manuscript does not include in-depth analyses of the results, cursory analyses suggest that simpler models appear to outperform more complex approaches that included, for example, demographic information and transportation dynamics, due to the reporting biases, which can be implicitly captured in statistical models. Mosquito-dynamics, population specific information, and dengue-specific information correlated best with prediction accuracy. CONCLUSION: We conclude that with careful consideration and understanding of the relative advantages and disadvantages of particular methods, implementation of an effective prediction system is feasible. However, there is a need to improve the quality of the data in order to more accurately predict the course of epidemics.

Forecasting Ebola with a regression transmission model.

We describe a relatively simple stochastic model of Ebola transmission that was used to produce forecasts with the lowest mean absolute error among Ebola Forecasting Challenge participants. The model enabled prediction of peak incidence, the timing of this peak, and final size of the outbreak. The underlying discrete-time compartmental model used a time-varying reproductive rate modeled as a multiplicative random walk driven by the number of infectious individuals. This structure generalizes traditional Susceptible-Infected-Recovered (SIR) disease modeling approaches and allows for the flexible consideration of outbreaks with complex trajectories of disease dynamics.

Excited-state absorption in tetrapyridyl porphyrins: comparing real-time and quadratic-response time-dependent density functional theory.

Three meso-substituted tetrapyridyl porphyrins (free base, Ni(ii), and Cu(ii)) were investigated for their optical limiting (OL) capabilities using real-time (RT-), linear-response (LR-), and quadratic-response (QR-) time-dependent density functional theory (TDDFT) methods. These species are experimentally known to display a prominent reverse saturable absorption feature between the Q and B bands of the ground-state absorption (GSA), which has been attributed to increased excited-state absorption (ESA) relative to GSA. A recently developed RT-TDDFT based method for calculating ESA from a LR-TDDFT density was utilized with eight exchange-correlation functionals (BLYP, PBE, B3LYP, CAM-B3LYP, PBE0, M06, BHLYP, and BHandH) and contrasted with calculations of ESA using QR-TDDFT with five exchange-correlation functionals (BLYP, B3LYP, CAM-B3LYP, BHLYP, and BHandH). This allowed for comparison between functionals with varying amounts of exact exchange as well as between the ability of RT-TDDFT and QR-TDDFT to reproduce OL behavior in porphyrin systems. The absorption peak positions and intensities for GSA and ESA are significantly impacted by the choice of DFT functional, with the most critical factor identified as the amount of exact exchange in the functional form. Calculating ESA with QR-TDDFT is found to be significantly more sensitive to the amount of exact exchange than GSA and ESA with RT-TDDFT, as well as GSA with LR-TDDFT. An analogous behavior is also demonstrated for the polycyclic aromatic hydrocarbon coronene. This is problematic when using the same approximate functional for calculation of both GSA and ESA, as the LR- and QR-TDDFT excitation energies will not have similar errors. Overall, the RT-TDDFT method with hybrid functionals reproduces the OL features for the porphyrin systems studied here and is a viable computational approach for efficient screening of molecular complexes for OL properties.

Guillain-Barré Syndrome and Healthcare Needs during Zika Virus Transmission, Puerto Rico, 2016.

To assist with public health preparedness activities, we estimated the number of expected cases of Zika virus in Puerto Rico and associated healthcare needs. Estimated annual incidence is 3.2-5.1 times the baseline, and long-term care needs are predicted to be 3-5 times greater than in years with no Zika virus.

Mind the Scales: Harnessing Spatial Big Data for Infectious Disease Surveillance and Inference.

Spatial big data have the velocity, volume, and variety of big data sources and contain additional geographic information. Digital data sources, such as medical claims, mobile phone call data records, and geographically tagged tweets, have entered infectious diseases epidemiology as novel sources of data to complement traditional infectious disease surveillance. In this work, we provide examples of how spatial big data have been used thus far in epidemiological analyses and describe opportunities for these sources to improve disease-mitigation strategies and public health coordination. In addition, we consider the technical, practical, and ethical challenges with the use of spatial big data in infectious disease surveillance and inference. Finally, we discuss the implications of the rising use of spatial big data in epidemiology to health risk communication, and public health policy recommendations and coordination across scales.

Improving pandemic influenza risk assessment.

Assessing the pandemic risk posed by specific non-human influenza A viruses is an important goal in public health research. As influenza virus genome sequencing becomes cheaper, faster, and more readily available, the ability to predict pandemic potential from sequence data could transform pandemic influenza risk assessment capabilities. However, the complexities of the relationships between virus genotype and phenotype make such predictions extremely difficult. The integration of experimental work, computational tool development, and analysis of evolutionary pathways, together with refinements to influenza surveillance, has the potential to transform our ability to assess the risks posed to humans by non-human influenza viruses and lead to improved pandemic preparedness and response.