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Since May 6, 2022, mpox (formerly monkeypox) cases have been reported across the globe. According to the Centers for Disease Control and Prevention (CDC), 85,115 confirmed mpox cases and 182 [...]

Correction for “An open challenge to advance probabilistic forecasting for dengue epidemics,” by Michael A. Johansson, Karyn M. Apfeldorf, Scott Dobson, Jason Devita, Anna L. Buczak, Benjamin Baugher, Linda J. Moniz, Thomas Bagley, Steven M. Babin, Erhan Guven, Teresa K. Yamana, Jeffrey Shaman, Terry Moschou, Nick Lothian, Aaron Lane, Grant Osborne, Gao Jiang, Logan C. Brooks, David C. Farrow, Sangwon Hyun, Ryan J. Tibshirani, Roni Rosenfeld, Justin Lessler, Nicholas G. Reich, Derek A. T. Cummings, Stephen A. Lauer, Sean M. Moore, Hannah E. Clapham, Rachel Lowe, Trevor C. Bailey, Markel García-Díez, Marilia Sá Carvalho, Xavier Rodó, Tridip Sardar, Richard Paul, Evan L. Ray, Krzysztof Sakrejda, Alexandria C. Brown, Xi Meng, Osonde Osoba, Raffaele Vardavas, David Manheim, Melinda Moore, Dhananjai M. Rao, Travis C. Porco, Sarah Ackley, Fengchen Liu, Lee Worden, Matteo Convertino, Yang Liu, Abraham Reddy, Eloy Ortiz, Jorge Rivero, Humberto Brito, Alicia Juarrero, Leah R. Johnson, Robert B. Gramacy, Jeremy M. Cohen, Erin A. Mordecai, Courtney C. Murdock, Jason R. Rohr, Sadie J. Ryan, Anna M. Stewart-Ibarra, Daniel P. Weikel, Antarpreet Jutla, Rakibul Khan, Marissa Poultney, Rita R. Colwell, Brenda Rivera-García, Christopher M. Barker, Jesse E. Bell, Matthew Biggerstaff, David Swerdlow, Luis Mier-y-Teran-Romero, Brett M. Forshey, Juli Trtanj, Jason Asher, Matt Clay, Harold S. Margolis, Andrew M. Hebbeler, Dylan George, and Jean-Paul Chretien, which was first published November 11, 2019; 10.1073/pnas.1909865116 (Proc. Natl. Acad. Sci. U.S.A. 116, 24268–24274). The authors note that the following statement should be added to the Acknowledgments: “E.A.M. was supported by NIH Grant R35GM133439.

A wide range of research has promised new tools for forecasting infectious disease dynamics, but little of that research is currently being applied in practice, because tools do not address key public health needs, do not produce probabilistic forecasts, have not been evaluated on external data, or do not provide sufficient forecast skill to be useful. We developed an open collaborative forecasting challenge to assess probabilistic forecasts for seasonal epidemics of dengue, a major global public health problem. Sixteen teams used a variety of methods and data to generate forecasts for 3 epidemiological targets (peak incidence, the week of the peak, and total incidence) over 8 dengue seasons in Iquitos, Peru and San Juan, Puerto Rico. Forecast skill was highly variable across teams and targets. While numerous forecasts showed high skill for midseason situational awareness, early season skill was low, and skill was generally lowest for high incidence seasons, those for which forecasts would be most valuable. A comparison of modeling approaches revealed that average forecast skill was lower for models including biologically meaningful data and mechanisms and that both multimodel and multiteam ensemble forecasts consistently outperformed individual model forecasts. Leveraging these insights, data, and the forecasting framework will be critical to improve forecast skill and the application of forecasts in real time for epidemic preparedness and response. Moreover, key components of this project-integration with public health needs, a common forecasting framework, shared and standardized data, and open participation-can help advance infectious disease forecasting beyond dengue.

BackgroundEmerging 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.MethodsTo 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.ResultsParticipant 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.ConclusionWe 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.

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.

Guillain-Barre syndrome (GBS) is an autoimmune disorder characterized by varying degrees of weakness, sensory abnormalities, and autonomic dysfunction due to peripheral nerve or nerve root damage (1). Annual GBS incidence [...]

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. [ABSTRACT FROM AUTHOR]

To the Editor: By December 31, 2014, the Ebola epidemic in West Africa had resulted in treatment of 10 Ebola case-patients in the United States; a maximum of 4 patients [...]

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. [ABSTRACT FROM AUTHOR]

Background: In the 2022 multinational mpox outbreak, most cases have occurred among gay, bisexual, and other men who have sex with men (MSM), but sexual contacts between men and women may also transmit mpox. However, despite almost 30,000 cases of mpox reported in the United States, there is little evidence of sustained transmission among persons with opposite-sex partners (PWOSP). Here we explore the behavioral conditions that could produce sustained mpox transmission between PWOSP on college campuses, where smaller mixing pools and more frequent sexual activities relative to the general population may increase exposure. Methods: We develop a baseline dynamic network model (STERGM) using publicly available data from the 2011-2015 cycle of the National Survey of Family Growth (NSFG) to parameterize frequency and duration of three partnership types among collegeattending PWOSP: main, casual, and one-time. We then vary the frequency and duration of these partnerships. We track the infection generation of each case (where introduced cases have an infection generation of 0) across all scenarios. To summarize mpox transmission intensity, we calculate the mean infection generation (MIG) of infections. MIG is similar to R0 but provides a directly measurable estimate of spread across a structured population; MIG >1 indicates sustained transmission of mpox. Findings: In the baseline model and most additional scenarios, mpox transmission is not sustained. Conclusions: Rapid turnover of partners may be necessary for sustained mpox transmission. The MIG is low across many scenarios, suggesting that persistent mpox transmission is unlikely among college-attending PWOSP. However, the lack of recent, detailed data on the mixing patterns, frequency, and type of sexual behaviors of college students of all sexual orientations and gender identities could lead us to misclassify likely mpox transmission. Additional data collection should be considered for the development of robust models to understand the risk of mpox and other sexually transmitted infections among all college-attending students in the United States. [ABSTRACT FROM AUTHOR]