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COVID-19 case rates in the US wax and wane in wave-like patterns over time, but the spatial patterns of these temporal epidemic waves have not been well characterized. By analyzing state- and county-level COVID-19 case rate data for spatiotemporal decomposition modes and oscillatory patterns, we demonstrate that the transmission dynamics of COVID-19 feature recurrent spatiotemporal patterns. In addition to the well-recognized national-level annual mid-winter surges, we demonstrate a prominent but previously unrecognized six-month north-south oscillation in the eastern US (Eastern US COVID-19 Oscillator-EUCO) that gives rise to regional sub-epidemics and travelling epidemic waves. We also demonstrate a second less prominent pattern that oscillates east-west in the northern US (Northern US COVID-19 Oscillator-NUCO). The drivers of these newly recognized oscillatory epidemic patterns remain to be elucidated., (© 2024. The Author(s).)

Antigenic similarities between Zika virus (ZIKV) and other flaviviruses pose challenges to the development of virus-specific diagnostic tools and effective vaccines. Starting with a DNA-encoded one-bead-one-compound combinatorial library of 508,032 synthetic, non-natural oligomers, we selected and characterized small molecules that mimic ZIKV epitopes. High-throughput fluorescence-activated cell sorter-based bead screening was used to select molecules that bound IgG from ZIKV-immune but not from dengue-immune sera. Deep sequencing of the DNA from the "Zika-only" beads identified 40 candidate molecular structures. A lead candidate small molecule "CZV1-1" was selected that correctly identifies serum specimens from Zika-experienced patients with good sensitivity and specificity (85.3% and 98.4%, respectively). Binding competition studies of purified anti-CZV1-1 IgG against known ZIKV-specific monoclonal antibodies (mAbs) showed that CZV1-1 mimics a nonlinear, neutralizing conformational epitope in the domain III of the ZIKV envelope. Purified anti-CZV1-1 IgG neutralized infection of ZIKV in cell cultures with potencies comparable to highly specific ZIKV-neutralizing mAbs. This study demonstrates an innovative approach for identification of synthetic non-natural molecular mimics of conformational virus epitopes. Such molecular mimics may have value in the development of accurate diagnostic assays for Zika, as well as for other viruses., Competing Interests: Competing interests statement:T.K. is a cofounder of the company Deluge Biotechnologies and a coowner of the company Deluge Biotechnologies.

During the COVID-19 pandemic, over one thousand papers were published on "Susceptible-Exposed-Infectious-Removed" (SEIR) epidemic computational models. The English word "exposed" in its vernacular and public health usage means a state of having been in contact with an infectious individual, but not necessarily infected. In contrast, the term "exposed" in SEIR modeling usage typically stands for a state of already being infected but not yet being infectious to others, a state more properly termed "latently infected." In public health language, "exposed" means possibly infected , yet in SEIR modeling language, "exposed" means already infected. This paper retraces the conceptual and mathematical origins of this terminological disconnect and concludes that epidemic modelers should consider using the "SLIR" notational short-hand (L for Latent) instead of SEIR., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Donald S. Burke reports a relationship with Epistemix, Inc. that includes: board membership and equity or stocks., (© 2024 The Authors.)

Surprisingly, the 1977 "Russian flu" H1N1 pandemic influenza virus was genetically indistinguishable from strains that had circulated decades earlier but had gone extinct in 1957. This essay puts forward the most plausible chronology to explain the reemergence of the 1977 H1N1 pandemic virus: (1) in January-February 1976, a self-limited small outbreak of a swine H1N1 influenza virus occurred among Army personnel at Fort Dix, New Jersey; (2) in March 1976, the US launched a nationwide H1N1 swine influenza vaccine program; (3) other countries then also launched their own H1N1 R&D efforts; (4) a new H1N1 outbreak, genetically unrelated to the Fort Dix swine virus but indistinguishable from previously extinct H1N1 viruses, was detected early in 1977 in China; (5) the leading Chinese influenza virologist later disclosed that the Chinese military had conducted large H1N1 vaccine R&D studies in 1976. It is likely that the resurrected H1N1 influenza viruses were laboratory-stored strains that were unfrozen and studied as part of the emergency response to a perceived epidemic threat, and that accidentally escaped. The fear of a possible H1N1 pandemic was the critical factor that gave rise to the actual H1N1 pandemic, resulting in an avoidable "self-fulfilling prophecy pandemic."

Competing Interests: Declarations of Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: DSB is co-founder and president of Epistemix, Inc., a start up company that creates and distributes software for computational modeling of complex health and social dynamics.

Live oral vaccines have been explored for their protective efficacy against respiratory viruses, particularly for adenovirus serotypes 4 and 7. The potential of a live oral vaccine against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), however, remains unclear. In this study, we assessed the immunogenicity of live SARS-CoV-2 delivered to the gastrointestinal tract in rhesus macaques and its protective efficacy against intranasal and intratracheal SARS-CoV-2 challenge. Postpyloric administration of SARS-CoV-2 by esophagogastroduodenoscopy resulted in limited virus replication in the gastrointestinal tract and minimal to no induction of mucosal antibody titers in rectal swabs, nasal swabs, and bronchoalveolar lavage fluid. Low levels of serum neutralizing antibodies were induced and correlated with modestly diminished viral loads in nasal swabs and bronchoalveolar lavage fluid following intranasal and intratracheal SARS-CoV-2 challenge. Overall, our data show that postpyloric inoculation of live SARS-CoV-2 is weakly immunogenic and confers partial protection against respiratory SARS-CoV-2 challenge in rhesus macaques. IMPORTANCE SARS-CoV-2 remains a global threat, despite the rapid deployment but limited coverage of multiple vaccines. Alternative vaccine strategies that have favorable manufacturing timelines, greater ease of distribution, and improved coverage may offer significant public health benefits, especially in resource-limited settings. Live oral vaccines have the potential to address some of these limitations; however, no studies have yet been conducted to assess the immunogenicity and protective efficacy of a live oral vaccine against SARS-CoV-2. Here, we report that oral administration of live SARS-CoV-2 in nonhuman primates may offer prophylactic benefits, but the formulation and route of administration will require further optimization.

Background: Influenza activity in the 2020-2021 season was remarkably low, likely due to implementation of public health preventive measures such as social distancing, mask wearing, and school closure. With waning immunity, the impact of low influenza activity in the 2020-2021 season on the following season is unknown., Methods: We built a multistrain compartmental model that captures immunity over multiple influenza seasons in the United States. Compared with the counterfactual case, where influenza activity remained at the normal level in 2020-2021, we estimated the change in the number of hospitalizations when the transmission rate was decreased by 20% in 2020-2021. We varied the level of vaccine uptake and effectiveness in 2021-2022. We measured the change in population immunity over time by varying the number of seasons with lowered influenza activity., Results: With the lowered influenza activity in 2020-2021, the model estimated 102 000 (95% CI, 57 000-152 000) additional hospitalizations in 2021-2022, without changes in vaccine uptake and effectiveness. The estimated changes in hospitalizations varied depending on the level of vaccine uptake and effectiveness in the following year. Achieving a 50% increase in vaccine coverage was necessary to avert the expected increase in hospitalization in the next influenza season. If the low influenza activity were to continue over several seasons, population immunity would remain low during those seasons, with 48% of the population susceptible to influenza infection., Conclusions: Our study projected a large compensatory influenza season in 2021-2022 due to a light season in 2020-2021. However, higher influenza vaccine uptake would reduce this projected increase in influenza., (© The Author(s) 2021. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)

Background and Aims: It is widely believed that the 2018 decline in overdose deaths in the United States was attributable to a range of public health interventions, however, this decline also coincided with the regulation and decline in use of potent fentanyl analogs, especially carfentanil. The aim of this study was to investigate the association between overdose deaths and carfentanil availability in the United States., Design: Secondary analysis of drug overdose deaths from the Center for Disease Control and Prevention (CDC) and carfentanil exhibit data from drug seizures submitted to drug crime labs and published by the Drug Enforcement Administration (DEA). Trends in overdose deaths were compared in states with high carfentanil exhibits with states with low or no carfentanil exhibits., Setting: United States., Participants: A total of 1 035 923 drug overdose death records in the United States from 1979 through 2019 were studied., Measurements: The outcomes studied were number of overdose deaths and mortality rates by state., Findings: Drug overdose deaths have been closely tracked along an exponential curve. The years 2016 and 2017 witnessed a hyper-exponential surge with increases in overdose deaths of 11 228 (+21.4%) and 6605 (+10.4%), respectively. Subsequently in 2018, drug overdose deaths declined by -2870 (-4.1%). This rise and then fall coincided with a surge and then decline in carfentanil drug seizure exhibits during these same years: 0 (2015), 1292 (2016), 5857 (2017) and 804 (2018). The majority of carfentanil exhibits were localized to a few states. The 2018 decline in overdose deaths in the top five states with the greatest spike in carfentanil exhibits in 2017 (Ohio, Florida, Pennsylvania, Kentucky and Michigan) was 2848, which accounted for nearly all of the total US decline., Conclusions: The 2016-2017 acceleration and then 2018 decline in drug overdose deaths in the United States was associated with the sudden rise and then fall of carfentanil availability. Given the regional variation, carfentanil's decreased availability may have contributed to the reduction in overdose deaths in 2018., (©2020 Society for the Study of Addiction.)

Many public health responses and modeled scenarios for COVID-19 outbreaks caused by SARS-CoV-2 assume that infection results in an immune response that protects individuals from future infections or illness for some amount of time. The presence or absence of protective immunity due to infection or vaccination (when available) will affect future transmission and illness severity. Here, we review the scientific literature on antibody immunity to coronaviruses, including SARS-CoV-2 as well as the related SARS-CoV, MERS-CoV and endemic human coronaviruses (HCoVs). We reviewed 2,452 abstracts and identified 491 manuscripts relevant to 5 areas of focus: 1) antibody kinetics, 2) correlates of protection, 3) immunopathogenesis, 4) antigenic diversity and cross-reactivity, and 5) population seroprevalence. While further studies of SARS-CoV-2 are necessary to determine immune responses, evidence from other coronaviruses can provide clues and guide future research.

The ongoing substance misuse epidemic in the United States is complex and dynamic and should be approached as such in the development and evaluation of policy 1 . Drug overdose deaths (largely attributable to opioid misuse) in the United States have grown exponentially for almost four decades, but the mechanisms of this growth are poorly understood 2 . From analysis of 661,565 overdose deaths from 1999 to 2017, we show that the age-specific drug overdose mortality curve for each birth-year cohort rises and falls according to a Gaussian-shaped curve. The ascending portion of each successive birth-year cohort mortality curve is accelerated compared with that of all preceding birth-year cohorts. This acceleration can be attributed to either of two distinct processes: a stable peak age, with an increasing amplitude of mortality rate curves from one birth-year cohort to the next; or a youthward shift in the peak age of the mortality rate curves. The overdose epidemic emerged and increased in amplitude among the 1945-1964 cohort (Baby Boomers), shifted youthward among the 1965-1980 cohort (Generation X), and then resumed the pattern of increasing amplitude in the 1981-1990 Millennials. These shifting age and generational patterns are likely to be driven by socioeconomic factors and drug availability, the understanding of which is important for the development of effective overdose prevention measures.

Importance: Vaccine exemptions, which allow unvaccinated children to attend school, have increased by a factor of 28 since 2003 in Texas. Geographic clustering of unvaccinated children facilitates the spread of measles introductions, but the potential size of outbreaks is unclear., Objective: To forecast the range of measles outbreak sizes in each metropolitan area of Texas at 2018 and future reduced school vaccination rates., Design, Setting, and Participants: An agent-based decision analytical model using a synthetic population of Texas, derived from the 2010 US Census, was used to simulate measles transmission in the Texas population. Real schools were represented in the simulations, and the 2018 vaccination rate of each real school was applied to a simulated hypothetical equivalent. Single cases of measles were introduced, daily activities and interactions were modeled for each population member, and the number of infections over the course of 9 months was counted for 1000 simulated runs in each Texas metropolitan area., Interventions: To determine the outcomes of further decreases in vaccination coverage, additional simulations were performed with vaccination rates reduced by 1% to 10% in schools with populations that are currently undervaccinated., Main Outcomes and Measures: Expected distributions of outbreak sizes in each metropolitan area of Texas at 2018 and reduced vaccination rates., Results: At 2018 vaccination rates, the median number of cases in large metropolitan areas was typically small, ranging from 1 to 3 cases, which is consistent with outbreaks in Texas 2006 to 2017. However, the upper limit of the distribution of plausible outbreaks (the 95th percentile, associated with 1 in 20 measles introductions) exceeded 400 cases in both the Austin and Dallas metropolitan areas, similar to the largest US outbreaks since measles was eliminated in 2000. Decreases in vaccination rates in schools with undervaccinated populations in 2018 were associated with exponential increases in the potential size of outbreaks: a 5% decrease in vaccination rate was associated with a 40% to 4000% increase in potential outbreak size, depending on the metropolitan area. A mean (SD) of 64% (11%) of cases occurred in students for whom a vaccine had been refused, but a mean (SD) of 36% (11%) occurred in others (ie, bystanders)., Conclusions and Relevance: This study suggests that vaccination rates in some Texas schools are currently low enough to allow large measles outbreaks. Further decreases are associated with dramatic increases in the probability of large outbreaks. Limiting vaccine exemptions could be associated with a decrease in the risk of large measles outbreaks.

Objective: In 2013, we released Project Tycho, an open-access database comprising 3.6 million counts of infectious disease cases and deaths reported for over a century by public health surveillance in the United States. Our objective is to describe how Project Tycho version 1 (v1) data has been used to create new knowledge and technology and to present improvements made in the newly released version 2.0 (v2)., Materials and Methods: We analyzed our user database and conducted online searches to analyze the use of Project Tycho v1 data. For v2, we added new US data and dengue data for other countries, and grouped data into 360 datasets, each with a digital object identifier and rich metadata. In addition, we used standard vocabularies to encode data where possible, improving compliance with FAIR (findable, accessible, interoperable, reusable) guiding principles for data management., Results: Since release, 3174 people have registered to use Project Tycho data, leading to 18 new peer-reviewed papers and 27 other creative works, such as conference papers, student theses, and software applications. Project Tycho v2 comprises 5.7 million counts of infectious diseases in the United States and of dengue-related conditions in 98 additional countries., Discussion: Project Tycho v2 contributes to improving FAIR compliance of global health data, but more work is needed to develop community-accepted standard representations for global health data., Conclusion: FAIR principles are a valuable guide for improving the integration and reuse of data in global health to improve disease control and save lives.

Better understanding of the dynamics of the current U.S. overdose epidemic may aid in the development of more effective prevention and control strategies. We analyzed records of 599,255 deaths from 1979 through 2016 from the National Vital Statistics System in which accidental drug poisoning was identified as the main cause of death. By examining all available data on accidental poisoning deaths back to 1979 and showing that the overall 38-year curve is exponential, we provide evidence that the current wave of opioid overdose deaths (due to prescription opioids, heroin, and fentanyl) may just be the latest manifestation of a more fundamental longer-term process. The 38+ year smooth exponential curve of total U.S. annual accidental drug poisoning deaths is a composite of multiple distinctive subepidemics of different drugs (primarily prescription opioids, heroin, methadone, synthetic opioids, cocaine, and methamphetamine), each with its own specific demographic and geographic characteristics., (Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

New epidemics of infectious diseases can emerge any time, as illustrated by the emergence of chikungunya virus (CHIKV) and Zika virus (ZIKV) in Latin America. During new epidemics, public health officials face difficult decisions regarding spatial targeting of interventions to optimally allocate limited resources. We used a large-scale, data-driven, agent-based simulation model (ABM) to explore CHIKV mitigation strategies, including strategies based on previous DENV outbreaks. Our model represents CHIKV transmission in a realistic population of Colombia with 45 million individuals in 10.6 million households, schools, and workplaces. Our model uses high-resolution probability maps for the occurrence of the Ae. aegypti mosquito vector to estimate mosquito density in Colombia. We found that vector control in all 521 municipalities with mosquito populations led to 402,940 fewer clinical cases of CHIKV compared to a baseline scenario without intervention. We also explored using data about previous dengue virus (DENV) epidemics to inform CHIKV mitigation strategies. Compared to the baseline scenario, 314,437 fewer cases occurred when we simulated vector control only in 301 municipalities that had previously reported DENV, illustrating the value of available data from previous outbreaks. When varying the implementation parameters for vector control, we found that faster implementation and scale-up of vector control led to the greatest proportionate reduction in cases. Using available data for epidemic simulations can strengthen decision making against new epidemic threats.

Dengue virus (DENV) infections elicit antibody responses to the non-structural protein 1 (NS1) that are associated with protection against disease. However, the antibody isotypes and subclasses involved, and their kinetics have not been extensively studied. We characterized the antibody responses to DENV NS1 by enzyme-linked immunosorbent assay (ELISA) in a longitudinal cohort of 266 confirmed dengue cases in Recife, Northeast Brazil. Samples were collected during the febrile phase and up to over 3 years after onset of symptoms. The antibodies investigated [IgA, IgM, total IgG (all subclasses measured together) and each subclass (IgG2, IgG3 and IgG4) measured separately] had distinct kinetic profiles following primary or secondary DENV infections. Of interest, most of these antibodies were consistently detected greater than 6 months after onset of symptoms, except for IgG3. Anti-dengue NS1-specific IgG was consistently detected from the acute phase to beyond 3 years after symptom onset. In contrast, anti-dengue NS1-specific IgG3 was detected within the first week, peaked at week 2-3, and disappeared within 4-6 months after onset of symptoms. The mean duration of the IgG3 positive signal was 149 days (ranging from 126 to 172 days). In conclusion, anti-dengue NS1-specific IgG and IgG3 are potential biomarkers of long-term and recent (less than 6 months) DENV infections, respectively., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Objectives: A complete and accurate count of the number of opioid-related overdose deaths is essential to properly allocate resources. We determined the rate of unintentional overdose deaths (non-opioid-related, opioid-related, or unspecified) in the United States and by state from 1999 to 2015 and the possible effects of underreporting on national estimates of opioid abuse., Methods: We abstracted unintentional drug overdose deaths ( International Classification of Diseases, 10th Revision, codes X40-X44) with contributory drug-specific T codes (T36.0-T50.9) from the Mortality Multiple Cause Micro-Data Files. We assumed that the proportion of unspecified overdose deaths that might be attributed to opioids would be the same as the proportion of opioid-related overdose deaths among all overdose deaths and calculated the number of deaths that could be reallocated as opioid-related for each state and year. We then added these reallocated deaths to the reported deaths to determine their potential effect on total opioid-related deaths., Results: From 1999 to 2015, a total of 438 607 people died from unintentional drug overdoses. Opioid-related overdose deaths rose 401% (from 5868 to 29 383), non-opioid-related overdose deaths rose 150% (from 3005 to 7505), and unspecified overdose deaths rose 220% (from 2255 to 29 383). In 5 states (Alabama, Indiana, Louisiana, Mississippi, and Pennsylvania), more than 35% of unintentional overdose deaths were coded as unspecified. Our reallocation resulted in classifying more than 70 000 unspecified overdose deaths as potential additional opioid-related overdose deaths., Conclusions: States may be greatly underestimating the effect of opioid-related overdose deaths because of incomplete cause-of-death reporting, indicating that the current opioid overdose epidemic may be worse than it appears.

Objective: To examine changes in cause-specific Years of Life Lost (YLL) by age, race, and sex group in the USA from 1990 to 2014., Methods: 60 million death reports from the National Center for Health Statistics (NCHS) were categorized by age group, sex, race, and cause of death. YLL were calculated using age-specific life expectancies. Age groups were: infants <1, children 1-19, adults 20-64, and older adults 65+., Results: Blacks have historically experienced more years of life lost than whites or other racial groups in the USA. In the year 1990 the YLL per 100,000 population was 21,103 for blacks, 14,160 for whites, and 7,417 for others. Between 1990 and 2014 overall YLL in the USA improved by 10%, but with marked variations in the rate of change across age, race, and sex groups. Blacks (all ages, both sexes) showed substantial improvement with a 28% reduction in YLL, compared to whites (all ages, both sexes) who showed a 4% reduction. Among blacks, improvements were seen in all age groups: reductions of 43%, 48%, 28%, and 25% among infants, children, adults, and older adults, respectively. Among whites, reductions of 33%, 44%, and 18% were seen in infants, children, and older adults, but there was a 6% increase in YLL among white adults. YLL increased by 18% in white adult females and declined 1% in white adult males. American Indian/Alaska Native women also had worsening in YLL, with an 8% increase. Asian Pacific Islanders consistently had the lowest YLL across all ages. Whites had a higher proportion of YLL due to overdose; blacks had a higher proportion due to homicide at younger ages and to heart disease at older ages., Conclusions: Race-based disparities in YLL in the USA since 1990 have narrowed considerably, largely as a result of improvements among blacks compared to whites. Adult white and American Indian / Alaskan Native females have experienced worsening YLL, while white males have experienced essentially no change. If recent trajectories continue, adult black/white disparities in YLL will continue to narrow.

Infectious diseases impose considerable burden on society, despite significant advances in technology and medicine over the past century. Advanced warning can be helpful in mitigating and preparing for an impending or ongoing epidemic. Historically, such a capability has lagged for many reasons, including in particular the uncertainty in the current state of the system and in the understanding of the processes that drive epidemic trajectories. Presently we have access to data, models, and computational resources that enable the development of epidemiological forecasting systems. Indeed, several recent challenges hosted by the U.S. government have fostered an open and collaborative environment for the development of these technologies. The primary focus of these challenges has been to develop statistical and computational methods for epidemiological forecasting, but here we consider a serious alternative based on collective human judgment. We created the web-based "Epicast" forecasting system which collects and aggregates epidemic predictions made in real-time by human participants, and with these forecasts we ask two questions: how accurate is human judgment, and how do these forecasts compare to their more computational, data-driven alternatives? To address the former, we assess by a variety of metrics how accurately humans are able to predict influenza and chikungunya trajectories. As for the latter, we show that real-time, combined human predictions of the 2014-2015 and 2015-2016 U.S. flu seasons are often more accurate than the same predictions made by several statistical systems, especially for short-term targets. We conclude that there is valuable predictive power in collective human judgment, and we discuss the benefits and drawbacks of this approach.

Objectives: The purpose of this study was to examine US accidental poisoning death rates by demographic and geographic factors from 1979 to 2014, including High Intensity Drug Trafficking Areas., Methods: Crude and age-adjusted death rates were formed for age group, race, sex, and county for accidental poisonings (ICD 9th revision: E850-E869; ICD 10th revision: X40-X49) from 1979 to 2014 using the Mortality and Population Data System housed at the University of Pittsburgh. Rate ratios were calculated comparing rates from 2014 to 1979, overall, by sex, age group, race, and county. Joinpoint regression detected changes in trends and calculated the average annual percentage change (AAPC) as a summary measure of trend., Results: Drug poisoning mortality rates have risen an average of 6% per year since 1979. Increases are occurring in all ages 15+, and in all race-sex groups. HIDTA counties with the highest mortality rates were in Appalachia and New Mexico. Many of the HIDTA border counties had lower rates of mortality., Conclusions: The drug poisoning mortality epidemic is continuing to grow. While HIDTA resources are appropriately targeted at many areas in the US most affected, rates are also rapidly rising in some non-HIDTA areas., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Non-biological synthetic oligomers can serve as ligands for antibodies. We hypothesized that a random combinatorial library of synthetic poly-N-substituted glycine oligomers, or peptoids, could represent a random "shape library" in antigen space, and that some of these peptoids would be recognized by the antigen-binding pocket of disease-specific antibodies. We synthesized and screened a one bead one compound combinatorial library of peptoids, in which each bead displayed an 8-mer peptoid with ten possible different amines at each position (10(8) theoretical variants). By screening one million peptoid/beads we found 112 (approximately 1 in 10,000) that preferentially bound immunoglobulins from human sera known to be positive for anti-HIV antibodies. Reactive peptoids were then re-synthesized and rigorously evaluated in plate-based ELISAs. Four peptoids showed very good, and one showed excellent, properties for establishing a sero-diagnosis of HIV. These results demonstrate the feasibility of constructing sero-diagnostic assays for infectious diseases from libraries of random molecular shapes. In this study we sought a proof-of-principle that we could identify a potential diagnostic antibody ligand biomarker for an infectious disease in a random combinatorial library of 100 million peptoids. We believe that this is the first evidence that it is possible to develop sero-diagnostic assays - for any infectious disease - based on screening random libraries of non-biological molecular shapes., (Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.)

We have performed the first direct measurement of the ^{38}K(p,γ)^{39}Ca reaction using a beam of radioactive ^{38}K. A proposed ℓ=0 resonance in the ^{38}K+p system has been identified at 679(2) keV with an associated strength of 120&#95;{-30}^{+50}  meV. Upper limits of 1.16 (3.5) and 8.6 (26) meV at the 68% (95%) confidence level were also established for two further expected ℓ=0 resonances at 386 and 515 keV, respectively. The present results have reduced uncertainties in the ^{38}K(p,γ)^{39}Ca reaction rate at temperatures of 0.4 GK by more than 2 orders of magnitude and indicate that Ar and Ca may be ejected in observable quantities by oxygen-neon novae. However, based on the newly evaluated rate, the ^{38}K(p,γ)^{39}Ca path is unlikely to be responsible for the production of Ar and Ca in significantly enhanced quantities relative to solar abundances.

Introduction: The purpose of this study was to examine county and state-level accidental poisoning mortality trends in Pennsylvania from 1979 to 2014., Methods: Crude and age-adjusted death rates were formed for age group, race, sex, and county for accidental poisonings (ICD 10 codes X40-X49) from 1979 to 2014 for ages 15+ using the Mortality and Population Data System housed at the University of Pittsburgh. Rate ratios were calculated comparing rates from 1979 to 2014, overall and by sex, age group, and race. Joinpoint regression was used to detect statistically significant changes in trends of age-adjusted mortality rates., Results: Rate ratios for accidental poisoning mortality in Pennsylvania increased more than 14-fold from 1979 to 2014. The largest rate ratios were among 35-44 year olds, females, and White adults. The highest accidental poisoning mortality rates were found in the counties of Southwestern Pennsylvania, those surrounding Philadelphia, and those in Northeast Pennsylvania near Scranton., Conclusions: The patterns and locations of accidental poisoning mortality by race, sex, and age group provide direction for interventions and policy makers. In particular, this study found the highest rate ratios in PA among females, whites, and the age group 35-44.

Epidemics of infectious diseases often occur in predictable limit cycles. Theory suggests these cycles can be disrupted by high amplitude seasonal fluctuations in transmission rates, resulting in deterministic chaos. However, persistent deterministic chaos has never been observed, in part because sufficiently large oscillations in transmission rates are uncommon. Where they do occur, the resulting deep epidemic troughs break the chain of transmission, leading to epidemic extinction, even in large cities. Here we demonstrate a new path to locally persistent chaotic epidemics via subtle shifts in seasonal patterns of transmission, rather than through high-amplitude fluctuations in transmission rates. We base our analysis on a comparison of measles incidence in 80 major cities in the prevaccination era United States and United Kingdom. Unlike the regular limit cycles seen in the UK, measles cycles in US cities consistently exhibit spontaneous shifts in epidemic periodicity resulting in chaotic patterns. We show that these patterns were driven by small systematic differences between countries in the duration of the summer period of low transmission. This example demonstrates empirically that small perturbations in disease transmission patterns can fundamentally alter the regularity and spatiotemporal coherence of epidemics.

Dengue is a mosquito-transmitted virus infection that causes epidemics of febrile illness and hemorrhagic fever across the tropics and subtropics worldwide. Annual epidemics are commonly observed, but there is substantial spatiotemporal heterogeneity in intensity. A better understanding of this heterogeneity in dengue transmission could lead to improved epidemic prediction and disease control. Time series decomposition methods enable the isolation and study of temporal epidemic dynamics with a specific periodicity (e.g., annual cycles related to climatic drivers and multiannual cycles caused by dynamics in population immunity). We collected and analyzed up to 18 y of monthly dengue surveillance reports on a total of 3.5 million reported dengue cases from 273 provinces in eight countries in Southeast Asia, covering ∼ 10(7) km(2). We detected strong patterns of synchronous dengue transmission across the entire region, most markedly during a period of high incidence in 1997-1998, which was followed by a period of extremely low incidence in 2001-2002. This synchrony in dengue incidence coincided with elevated temperatures throughout the region in 1997-1998 and the strongest El Niño episode of the century. Multiannual dengue cycles (2-5 y) were highly coherent with the Oceanic Niño Index, and synchrony of these cycles increased with temperature. We also detected localized traveling waves of multiannual dengue epidemic cycles in Thailand, Laos, and the Philippines that were dependent on temperature. This study reveals forcing mechanisms that drive synchronization of dengue epidemics on a continental scale across Southeast Asia.

The enigmatic observation that the rapidly evolving influenza A (H3N2) virus exhibits, at any given time, a limited standing genetic diversity has been an impetus for much research. One of the first generative computational models to successfully recapitulate this pattern of consistently constrained diversity posits the existence of a strong and short-lived strain-transcending immunity. Building on that model, we explored a much broader set of scenarios (parameterizations) of a transient strain-transcending immunity, ran long-term simulations of each such scenario, and assessed its plausibility with respect to a set of known or estimated influenza empirical measures. We evaluated simulated outcomes using a variety of measures, both epidemiological (annual attack rate, epidemic duration, reproductive number, and peak weekly incidence), and evolutionary (pairwise antigenic diversity, fixation rate, most recent common ancestor, and kappa, which quantifies the potential for antigenic evolution). Taking cumulative support from all these measures, we show which parameterizations of strain-transcending immunity are plausible with respect to the set of empirically derived target values. We conclude that strain-transcending immunity which is milder and longer lasting than previously suggested is more congruent with the observed short- and long-term behavior of influenza.

Background: The use of high quality disease surveillance data has become increasingly important for public health action against new threats. In response, countries have developed a wide range of disease surveillance systems enabled by technological advancements. The heterogeneity and complexity of country data systems have caused a growing need for international organizations such as the World Health Organization (WHO) to coordinate the standardization, integration, and dissemination of country disease data at the global level for research and policy. The availability and consistency of currently available disease surveillance data at the global level are unclear. We investigated this for dengue surveillance data provided online by the WHO., Methods and Findings: We extracted all dengue surveillance data provided online by WHO Headquarters and Regional Offices (RO's). We assessed the availability and consistency of these data by comparing indicators within and between sources. We also assessed the consistency of dengue data provided online by two example countries (Brazil and Indonesia). Data were available from WHO for 100 countries since 1955 representing a total of 23 million dengue cases and 82 thousand deaths ever reported to WHO. The availability of data on DengueNet and some RO's declined dramatically after 2005. Consistency was lacking between sources (84% across all indicators representing a discrepancy of almost half a million cases). Within sources, data at high spatial resolution were often incomplete., Conclusions: The decline of publicly available, integrated dengue surveillance data at the global level will limit opportunities for research, policy, and advocacy. A new financial and operational framework will be necessary for innovation and for the continued availability of integrated country disease data at the global level.

Background: In the current information age, the use of data has become essential for decision making in public health at the local, national, and global level. Despite a global commitment to the use and sharing of public health data, this can be challenging in reality. No systematic framework or global operational guidelines have been created for data sharing in public health. Barriers at different levels have limited data sharing but have only been anecdotally discussed or in the context of specific case studies. Incomplete systematic evidence on the scope and variety of these barriers has limited opportunities to maximize the value and use of public health data for science and policy., Methods: We conducted a systematic literature review of potential barriers to public health data sharing. Documents that described barriers to sharing of routinely collected public health data were eligible for inclusion and reviewed independently by a team of experts. We grouped identified barriers in a taxonomy for a focused international dialogue on solutions., Results: Twenty potential barriers were identified and classified in six categories: technical, motivational, economic, political, legal and ethical. The first three categories are deeply rooted in well-known challenges of health information systems for which structural solutions have yet to be found; the last three have solutions that lie in an international dialogue aimed at generating consensus on policies and instruments for data sharing., Conclusions: The simultaneous effect of multiple interacting barriers ranging from technical to intangible issues has greatly complicated advances in public health data sharing. A systematic framework of barriers to data sharing in public health will be essential to accelerate the use of valuable information for the global good.

Background: Agent based models (ABM) are useful to explore population-level scenarios of disease spread and containment, but typically characterize infected individuals using simplified models of infection and symptoms dynamics. Adding more realistic models of individual infections and symptoms may help to create more realistic population level epidemic dynamics., Methods: Using an equation-based, host-level mathematical model of influenza A virus infection, we develop a function that expresses the dependence of infectivity and symptoms of an infected individual on initial viral load, age, and viral strain phenotype. We incorporate this response function in a population-scale agent-based model of influenza A epidemic to create a hybrid multiscale modeling framework that reflects both population dynamics and individualized host response to infection., Results: At the host level, we estimate parameter ranges using experimental data of H1N1 viral titers and symptoms measured in humans. By linearization of symptoms responses of the host-level model we obtain a map of the parameters of the model that characterizes clinical phenotypes of influenza infection and immune response variability over the population. At the population-level model, we analyze the effect of individualizing viral response in agent-based model by simulating epidemics across Allegheny County, Pennsylvania under both age-specific and age-independent severity assumptions., Conclusions: We present a framework for multi-scale simulations of influenza epidemics that enables the study of population-level effects of individual differences in infections and symptoms, with minimal additional computational cost compared to the existing population-level simulations.

Dengue vaccine development efforts have focused on the development of tetravalent vaccines. However, a recent Phase IIb trial of a tetravalent vaccine indicates a protective effect against only 3 of the 4 serotypes. While vaccines effective against a subset of serotypes may reduce morbidity and mortality, particular profiles could result in an increased number of cases due to immune enhancement and other peculiarities of dengue epidemiology. Here, we use a compartmental transmission model to assess the impact of partially effective vaccines in a hyperendemic Thai population. Crucially, we evaluate the effects that certain serotype heterogeneities may have in the presence of mass-vaccination campaigns. In the majority of scenarios explored, partially effective vaccines lead to 50% or greater reductions in the number of cases. This is true even of vaccines that we would not expect to proceed to licensure due to poor or incomplete immune responses. Our results show that a partially effective vaccine can have significant impacts on serotype distribution and mean age of cases., (Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Of the seven known species of human retroviruses only one, human T-cell lymphotropic virus type 4 (HTLV-4), lacks a known animal reservoir. We report the largest screening for simian T-cell lymphotropic virus (STLV-4) to date in a wide range of captive and wild non-human primate (NHP) species from Cameroon. Among the 681 wild and 426 captive NHPs examined, we detected STLV-4 infection only among gorillas by using HTLV-4-specific quantitative polymerase chain reaction. The large number of samples analyzed, the diversity of NHP species examined, the geographic distribution of infected animals relative to the known HTLV-4 case, as well as detailed phylogenetic analyses on partial and full genomes, indicate that STLV-4 is endemic to gorillas, and that rather than being an ancient virus among humans, HTLV-4 emerged from a gorilla reservoir, likely through the hunting and butchering of wild gorillas. Our findings shed further light on the importance of gorillas as keystone reservoirs for the evolution and emergence of human infectious diseases and provide a clear course for preventing HTLV-4 emergence through management of human contact with wild gorillas, the development of improved assays for HTLV-4/STLV-4 detection and the ongoing monitoring of STLV-4 among gorillas and for HTLV-4 zoonosis among individuals exposed to gorilla populations.

The effect of school-based non-pharmaceutical interventions (NPIs) on influenza A and B transmission in children's households has not been estimated in published literature. We use data from a large school-based cluster randomized trial of improved hand and respiratory hygiene measures to explore the secondary transmission of influenza A and B in households of laboratory confirmed influenza cases. Data were taken from the Pittsburgh Influenza Prevention Project, a cluster-randomized trial of NPIs conducted in ten Pittsburgh, PA elementary schools during the 2007-2008 influenza season. We estimated two measures of influenza transmissibility in households; the susceptible infectious transmission probability, using variants of the Reed-Frost chain binomial model, and the secondary attack rate. We identified predictors of ILI using a logistic generalized estimating equation model. We estimate the secondary attack rates in intervention households to be 0.26 (95% confidence interval (CI) 0.19-0.34) compared to 0.30 (95% CI 0.23-0.38) in control households. Race and age were significant risk factors for secondary ILI acquisition in this study. We found no significant differences between the transmission probabilities for infectious individuals in intervention (0.19, 95% CI 0.14-0.25), and control households (0.22, 95% CI 0.16-0.29). Similarly, estimates for secondary attack rates and transmission probabilities for households with confirmed influenza A (0.31 and 0.22) were not significantly different from estimates from households with confirmed influenza B (0.25 and 0.20). While influenza A and B are thought to have different transmission characteristics, we find no significant differences in their transmissibility within households. Though our results suggest a potential effect, we found no statistically significant effect of school-based non-pharmaceutical interventions on transmission in symptomatic children's homes., (Copyright © 2013 Elsevier B.V. All rights reserved.)

Background: Mathematical and computational models provide valuable tools that help public health planners to evaluate competing health interventions, especially for novel circumstances that cannot be examined through observational or controlled studies, such as pandemic influenza. The spread of diseases like influenza depends on the mixing patterns within the population, and these mixing patterns depend in part on local factors including the spatial distribution and age structure of the population, the distribution of size and composition of households, employment status and commuting patterns of adults, and the size and age structure of schools. Finally, public health planners must take into account the health behavior patterns of the population, patterns that often vary according to socioeconomic factors such as race, household income, and education levels., Results: FRED (a Framework for Reconstructing Epidemic Dynamics) is a freely available open-source agent-based modeling system based closely on models used in previously published studies of pandemic influenza. This version of FRED uses open-access census-based synthetic populations that capture the demographic and geographic heterogeneities of the population, including realistic household, school, and workplace social networks. FRED epidemic models are currently available for every state and county in the United States, and for selected international locations., Conclusions: State and county public health planners can use FRED to explore the effects of possible influenza epidemics in specific geographic regions of interest and to help evaluate the effect of interventions such as vaccination programs and school closure policies. FRED is available under a free open source license in order to contribute to the development of better modeling tools and to encourage open discussion of modeling tools being used to evaluate public health policies. We also welcome participation by other researchers in the further development of FRED.

Objective: To develop a conceptual computational agent-based model (ABM) to explore community-wide versus spatially focused crime reporting interventions to reduce community crime perpetrated by youth., Method: Agents within the model represent individual residents and interact on a two-dimensional grid representing an abstract nonempirically grounded community setting. Juvenile agents are assigned initial random probabilities of perpetrating a crime and adults are assigned random probabilities of witnessing and reporting crimes. The agents' behavioral probabilities modify depending on the individual's experience with criminal behavior and punishment, and exposure to community crime interventions. Cost-effectiveness analyses assessed the impact of activating different percentages of adults to increase reporting and reduce community crime activity. Community-wide interventions were compared with spatially focused interventions, in which activated adults were focused in areas of highest crime prevalence., Results: The ABM suggests that both community-wide and spatially focused interventions can be effective in reducing overall offenses, but their relative effectiveness may depend on the intensity and cost of the interventions. Although spatially focused intervention yielded localized reductions in crimes, such interventions were shown to move crime to nearby communities. Community-wide interventions can achieve larger reductions in overall community crime offenses than spatially focused interventions, as long as sufficient resources are available., Conclusion: The ABM demonstrates that community-wide and spatially focused crime strategies produce unique intervention dynamics influencing juvenile crime behaviors through the decisions and actions of community adults. It shows how such models might be used to investigate community-supported crime intervention programs by integrating community input and expertise and provides a simulated setting for assessing dimensions of cost comparison and intervention effect sustainability. ABM illustrates how intervention models might be used to investigate community-supported crime intervention programs.

This paper describes an international collaboration to carry out studies that contributed to the understanding of pathogenesis, diagnosis, treatment, and prevention of several diseases of public health importance for Thailand and the United States. In Kamphaeng Phet Province, Thailand, febrile syndromes, including encephalitis, hepatitis, hemorrhagic fever, and influenza-like illnesses, occurred commonly and were clinically diagnosed, but the etiology was rarely confirmed. Since 1982, the Kamphaeng Phet Provincial Hospital, the Thai Ministry of Public Health, and the US Army Component of the Armed Forces Research Institute of Medical Sciences, along with vaccine manufacturers and universities, have collaborated on studies that evaluated and capitalized on improved diagnostic capabilities for infections caused by Japanese encephalitis, hepatitis A, dengue, and influenza viruses. The collaboration clarified clinical and epidemiological features of these infections and, in large clinical trials, demonstrated that vaccines against Japanese encephalitis and hepatitis A viruses were over 90% efficacious, supporting licensure of both vaccines. With the introduction of Japanese encephalitis vaccines in Thailand's Expanded Program on Immunization, reported encephalitis rates dropped substantially. Similarly, in the US, particularly in the military populations, rates of hepatitis A disease have dropped with the use of hepatitis A vaccine. Studies of the pathogenesis of dengue infections have increased understanding of the role of cellular immunity in responding to these infections, and epidemiological studies have prepared the province for studies of dengue vaccines. Approximately 80 publications resulted from this collaboration. Studies conducted in Kamphaeng Phet provided experience that contributed to clinical trials of hepatitis E and HIV vaccines, conducted elsewhere. To provide a base for continuing studies, The Kamphaeng Phet-AFRIMS Virology Research Unit (KAVRU) was established. This paper reviews the origins of the collaboration and the scientific observations made between 1982 and 2012., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Objectives: We examined the impact of access to paid sick days (PSDs) and stay-at-home behavior on the influenza attack rate in workplaces., Methods: We used an agent-based model of Allegheny County, Pennsylvania, with PSD data from the US Bureau of Labor Statistics, standard influenza epidemic parameters, and the probability of staying home when ill. We compared the influenza attack rate among employees resulting from workplace transmission, focusing on the effects of presenteeism (going to work when ill)., Results: In a simulated influenza epidemic (R0 = 1.4), the attack rate among employees owing to workplace transmission was 11.54%. A large proportion (72.00%) of this attack rate resulted from exposure to employees engaging in presenteeism. Universal PSDs reduced workplace infections by 5.86%. Providing 1 or 2 "flu days"-allowing employees with influenza to stay home-reduced workplace infections by 25.33% and 39.22%, respectively., Conclusions: PSDs reduce influenza transmission owing to presenteeism and, hence, the burden of influenza illness in workplaces.

Dengue, a mosquito-borne virus of humans, infects over 50 million people annually. Infection with any of the four dengue serotypes induces protective immunity to that serotype, but does not confer long-term protection against infection by other serotypes. The immunological interactions between serotypes are of central importance in understanding epidemiological dynamics and anticipating the impact of dengue vaccines. We analysed a 38-year time series with 12 197 serotyped dengue infections from a hospital in Bangkok, Thailand. Using novel mechanistic models to represent different hypothesized immune interactions between serotypes, we found strong evidence that infection with dengue provides substantial short-term cross-protection against other serotypes (approx. 1-3 years). This is the first quantitative evidence that short-term cross-protection exists since human experimental infection studies performed in the 1950s. These findings will impact strategies for designing dengue vaccine studies, future multi-strain modelling efforts, and our understanding of evolutionary pressures in multi-strain disease systems.

Background: It has been suggested that the true case-fatality rate of human H5N1 influenza infection is appreciably less than the figure of approximately 60% that is based on official World Health Organization (WHO)-confirmed case reports because asymptomatic cases may have been missed. A number of seroepidemiologic studies have been conducted in an attempt to identify such missed cases., Methods: We conducted a comprehensive literature review of all English-language H5N1 human serology surveys with detailed attention to laboratory methodology used (including whether investigators used criteria set by the WHO to define positive cases), laboratory controls used, and the clades/genotypes involved., Results: Twenty-nine studies were included in the analysis. Few reported using unexposed control groups and one-third did not apply WHO criteria. Of studies that used WHO criteria, only 4 found any seropositive results to clades/genotypes of H5N1 that are currently circulating. No studies reported seropositive results to the clade 2/genotype Z viruses that have spread throughout Eurasia and Africa., Conclusions: This review suggests that the frequency of positive H5 serology results is likely to be low; therefore, it is essential that future studies adhere to WHO criteria and include unexposed controls in their laboratory assays to limit the likelihood of false-positive results.

GB Virus Type C (GBV-C), a blood-borne flavivirus currently infects about one sixth of the world's population. Its transmission has been reported through parenteral, sexual and vertical routes. Unusually for RNA viruses, it exhibits a high degree of conservation of the polyprotein sequence. The geographical distribution of GBV-C suggests an African origin and a long-term co-evolution in the human population but without any known pathogenicity. The aim of this study was to describe the different sub-types of this virus in Southern Cameroon. We studied the genetic epidemiology of GBV-C among rural populations where many HIV-1 and HCV genotypes have been identified. Plasma samples of 345 subjects with evidence of HCV exposure were tested for GBV-C infection. To detect GBV-C RNA, reverse transcription followed by a nested PCR of 5'UTR were performed. Direct sequencing and phylogenetic studies using PHYLIP, PAUP* and SimPlot were carried out. In total, 31 GBV-C RNA-positive samples were detected giving a prevalence of 9.0% among HCV-exposed individuals. Phylogenetic analysis of the 5'UTR showed two distinct clusters: Genotype 1 and Genotype 2. Twenty-eight isolates (8.0%) clustered with Genotype 1 and 3 (1.0%) with Genotype 2. More than one genotype of GBV-C is prevalent in Cameroon of which GBV-C Genotype 1 is more common, confirming reports in the literature. Studying the near full-length genome sequences of GBV-C isolates from primates in this region may provide clues of viral recombination, evolution and origin., Competing Interests: Conflict of interests: the authors declare no potential conflict of interests.

Pathogenesis studies of SIV infection have not been performed to date in wild monkeys due to difficulty in collecting and storing samples on site and the lack of analytical reagents covering the extensive SIV diversity. We performed a large scale study of molecular epidemiology and natural history of SIVagm infection in 225 free-ranging AGMs from multiple locations in South Africa. SIV prevalence (established by sequencing pol, env, and gag) varied dramatically between infant/juvenile (7%) and adult animals (68%) (p<0.0001), and between adult females (78%) and males (57%). Phylogenetic analyses revealed an extensive genetic diversity, including frequent recombination events. Some AGMs harbored epidemiologically linked viruses. Viruses infecting AGMs in the Free State, which are separated from those on the coastal side by the Drakensberg Mountains, formed a separate cluster in the phylogenetic trees; this observation supports a long standing presence of SIV in AGMs, at least from the time of their speciation to their Plio-Pleistocene migration. Specific primers/probes were synthesized based on the pol sequence data and viral loads (VLs) were quantified. VLs were of 10(4)-10(6) RNA copies/ml, in the range of those observed in experimentally-infected monkeys, validating the experimental approaches in natural hosts. VLs were significantly higher (10(7)-10(8) RNA copies/ml) in 10 AGMs diagnosed as acutely infected based on SIV seronegativity (Fiebig II), which suggests a very active transmission of SIVagm in the wild. Neither cytokine levels (as biomarkers of immune activation) nor sCD14 levels (a biomarker of microbial translocation) were different between SIV-infected and SIV-uninfected monkeys. This complex algorithm combining sequencing and phylogeny, VL quantification, serology, and testing of surrogate markers of microbial translocation and immune activation permits a systematic investigation of the epidemiology, viral diversity and natural history of SIV infection in wild African natural hosts.