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Medicine has separated the two cultures of biological science and social science in research, even though they are intimately connected in the lives of our patients. To understand the cause, progression, and treatment of long COVID , biology and biography, the patient's lived experience, must be studied together.

The Russian invasion of Ukraine on February 24, 2022, has displaced more than a quarter of the population. Assessing disease burdens among displaced people is instrumental in informing global public health and humanitarian aid efforts. We estimated the disease burden in Ukrainians displaced both within Ukraine and to other countries by combining a spatiotemporal model of forcible displacement with age- and gender-specific estimates of cardiovascular disease (CVD), diabetes, cancer, HIV, and tuberculosis (TB) in each of Ukraine’s 629 raions (i.e., districts). Among displaced Ukrainians as of May 13, we estimated that more than 2.63 million have CVDs, at least 615,000 have diabetes, and over 98,500 have cancer. In addition, more than 86,000 forcibly displaced individuals are living with HIV, and approximately 13,500 have TB. We estimated that the disease prevalence among refugees was lower than the national disease prevalence before the invasion. Accounting for internal displacement and healthcare facilities impacted by the conflict, we estimated that the number of people per hospital has increased by more than two-fold in some areas. As regional healthcare systems come under increasing strain, these estimates can inform the allocation of critical resources under shifting disease burdens.

Quarantine and serial testing strategies for a disease depend principally on its incubation period and infectiousness profile. In the context of COVID-19, these primary public health tools must be modulated with successive SARS CoV-2 variants of concern that dominate transmission. Our analysis shows that (1) vaccination status of an individual makes little difference to the determination of the appropriate quarantine duration of an infected case, whereas vaccination coverage of the population can have a substantial effect on this duration, (2) successive variants can challenge disease control efforts by their earlier and increased transmission in the disease time course relative to prior variants, and (3) sufficient vaccine boosting of a population substantially aids the suppression of local transmission through frequent serial testing. For instance, with Omicron, increasing immunity through vaccination and boosters—for instance with 100% of the population is fully immunized and at least 24% having received a third dose—can reduce quarantine durations by up to 2 d, as well as substantially aid in the repression of outbreaks through serial testing. Our analysis highlights the paramount importance of maintaining high population immunity, preferably by booster uptake, and the role of quarantine and testing to control the spread of SARS CoV-2.

The fragmented and inefficient healthcare system in the United States leads to many preventable deaths and unnecessary costs every year. During a pandemic, the lives saved and economic benefits of a single-payer universal healthcare system relative to the status quo would be even greater. For Americans who are uninsured and underinsured, financial barriers to COVID-19 care delayed diagnosis and exacerbated transmission. Concurrently, deaths beyond COVID-19 accrued from the background rate of uninsurance. Universal healthcare would alleviate the mortality caused by the confluence of these factors. To evaluate the repercussions of incomplete insurance coverage in 2020, we calculated the elevated mortality attributable to the loss of employer-sponsored insurance and to background rates of uninsurance, summing with the increased COVID-19 mortality due to low insurance coverage. Incorporating the demography of the uninsured with age-specific COVID-19 and nonpandemic mortality, we estimated that a single-payer universal healthcare system would have saved about 212,000 lives in 2020 alone. We also calculated that US$105.6 billion of medical expenses associated with COVID-19 hospitalization could have been averted by a single-payer universal healthcare system over the course of the pandemic. These economic benefits are in addition to US$438 billion expected to be saved by single-payer universal healthcare during a nonpandemic year.

Background Global vaccine development efforts have been accelerated in response to the devastating coronavirus disease 2019 (COVID-19) pandemic. We evaluated the impact of a 2-dose COVID-19 vaccination campaign on reducing incidence, hospitalizations, and deaths in the United States. Methods We developed an agent-based model of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission and parameterized it with US demographics and age-specific COVID-19 outcomes. Healthcare workers and high-risk individuals were prioritized for vaccination, whereas children under 18 years of age were not vaccinated. We considered a vaccine efficacy of 95% against disease following 2 doses administered 21 days apart achieving 40% vaccine coverage of the overall population within 284 days. We varied vaccine efficacy against infection and specified 10% preexisting population immunity for the base-case scenario. The model was calibrated to an effective reproduction number of 1.2, accounting for current nonpharmaceutical interventions in the United States. Results Vaccination reduced the overall attack rate to 4.6% (95% credible interval [CrI]: 4.3%–5.0%) from 9.0% (95% CrI: 8.4%–9.4%) without vaccination, over 300 days. The highest relative reduction (54%–62%) was observed among individuals aged 65 and older. Vaccination markedly reduced adverse outcomes, with non-intensive care unit (ICU) hospitalizations, ICU hospitalizations, and deaths decreasing by 63.5% (95% CrI: 60.3%–66.7%), 65.6% (95% CrI: 62.2%–68.6%), and 69.3% (95% CrI: 65.5%–73.1%), respectively, across the same period. Conclusions Our results indicate that vaccination can have a substantial impact on mitigating COVID-19 outbreaks, even with limited protection against infection. However, continued compliance with nonpharmaceutical interventions is essential to achieve this impact.

Significance An individual’s decision to vaccinate can be motivated by both self-interest and prosociality, making it difficult to delineate the contribution of prosociality to vaccination uptake. A silent polio epidemic in Israel in which the primary purpose of vaccination was to avert transmission to the general community provides a unique case study through which we quantify, using game-theoretical models, the contribution of prosociality to vaccination decisions. We find that prosociality was a significant driver to rapidly achieving a high coverage of polio vaccination. To further boost coverage, public health communication efforts should be directed toward allaying fears about vaccine risks. Our approach is useful for enhancing participation in diverse disease control measures, Regions with insufficient vaccination have hindered worldwide poliomyelitis eradication, as they are vulnerable to sporadic outbreaks through reintroduction of the disease. Despite Israel’s having been declared polio-free in 1988, a routine sewage surveillance program detected polio in 2013. To curtail transmission, the Israel Ministry of Health launched a vaccine campaign to vaccinate children—who had only received the inactivated polio vaccine—with the oral polio vaccine (OPV). Determining the degree of prosocial motivation in vaccination behavior is challenging because vaccination typically provides direct benefits to the individual as well as indirect benefits to the community by curtailing transmission. However, the Israel OPV campaign provides a unique and excellent opportunity to quantify and model prosocial vaccination as its primary objective was to avert transmission. Using primary survey data and a game-theoretical model, we examine and quantify prosocial behavior during the OPV campaign. We found that the observed vaccination behavior in the Israeli OPV campaign is attributable to prosocial behavior and heterogeneous perceived risk of paralysis based on the individual’s comprehension of the prosocial nature of the campaign. We also found that the benefit of increasing comprehension of the prosocial nature of the campaign would be limited if even 24% of the population acts primarily from self-interest, as greater vaccination coverage provides no personal utility to them. Our results suggest that to improve coverage, communication efforts should also focus on alleviating perceived fears surrounding the vaccine.

Environmental disasters, pandemics, and other major traumatic events such as the Covid-19 pandemic or war contribute to psychosocial stress which manifests in a wide range of mental and physical consequences. The increasing frequency and severity of such events suggest that the adverse effects of toxic stress are likely to become more widespread and pervasive in the future. The allostatic load (AL) model has important elements that lend themselves well for identifying adverse health effects of disasters. Here we examine several articulations of AL from the standpoint of using AL to gauge short- and long-term health effects of disasters and to provide predictive capacity that would enable mitigation or prevention of some disaster-related health consequences. We developed a transdisciplinary framework combining indices of psychosocial AL and physiological AL to produce a robust estimate of overall AL in people affected by disasters and other traumatic events. In conclusion, we urge researchers to consider the potential of using AL as a component in a proposed disaster-oriented human health observing system.

Clinical and translational medicine studies of disease risk or treatment response typically include a table 1 comparing groups on age, sex, and race/ethnicity. Although customarily treated as biological variables, each denote biography, elements of a person's lived experience. Capturing these biographical features is essential to achieving the ambition of personalized medicine

Biosocial Medicine, with its emphasis on the full integration of the person's biology and biography, proposes a strategy for clinical research and the practice of medicine that is transformative for the care of individual patients. In this paper, we argue that Biology is one component of what makes a person unique, but it does not do so alone. Biography, the lived experience of the person, integrates with biology to create a unique signature for each individual and is the foundational concept on which Biosocial Medicine is based. Biosocial Medicine starts with the premise that the individual patient is the focus of clinical care, and that average results for “ideal” patients in population level research cannot substitute for the “real” patient for whom clinical decisions are needed. The paper begins with a description of the case-based method of clinical reasoning, considers the strengths and limitations of Randomized Controlled Trials and Evidence Based Medicine, reviews the increasing focus on precision medicine and then explores the neglected role of biography as part of a new approach to the tailored care of patients. After a review of the analytical challenges in Biosocial Medicine, the paper concludes by linking the physician's commitment to understanding the patient's biography as a critical element in developing trust with the patient.

BackgroundRapid antigen (RA) tests are being increasingly employed to detect SARS-CoV-2 infections in quarantine and surveillance. Prior research has focused on RT-PCR testing, a single RA test, or generic diagnostic characteristics of RA tests in assessing testing strategies.MethodsFor 18 RA tests with emergency use authorization from the United States of America FDA and an RT-PCR test, we conducted a comparative analysis of the post-quarantine transmission, the effective reproduction number during serial testing, and the false-positive rates. To quantify the extent of transmission, we developed an analytical mathematical framework informed by COVID-19 infectiousness, test specificity, and temporal diagnostic sensitivity data.ResultsWe demonstrate that the relative effectiveness of RA and RT-PCR tests in reducing post-quarantine transmission depends on the quarantine duration and the turnaround time of testing results. For quarantines of two days or shorter, conducting a RA test on exit from quarantine reduces onward transmission more than a single RT-PCR test (with a 24-h delay) conducted upon exit. Applied to a complementary approach of performing serial testing at a specified frequency paired with isolation of positives, we have shown that RA tests outperform RT-PCR with a 24-h delay. The results from our modeling framework are consistent with quarantine and serial testing data collected from a remote industry setting.ConclusionsThese RA test-specific results are an important component of the tool set for policy decision-making, and demonstrate that judicious selection of an appropriate RA test can supply a viable alternative to RT-PCR in efforts to control the spread of disease.Plain language summaryPrevious research has determined optimal timing for testing in quarantine and the utility of different frequencies of testing for disease surveillance using RT-PCR and generalized rapid antigen tests.However, these strategies can depend on the specific rapid antigen test used. By examining 18 rapid antigen tests, we demonstrate that a single rapid antigen test performs better than RT-PCR when quarantines are two days or less in duration. In the context of disease surveillance, the ability of a rapid antigen test to provide results quickly counteracts its lower sensitivity with potentially more false positives. These analytical results based on highly controlled test validation were consistent with real-world data obtained from quarantine and serial testing in an industrial setting.

Quantification of asymptomatic infections is fundamental for effective public health responses to the COVID-19 pandemic. Discrepancies regarding the extent of asymptomaticity have arisen from inconsistent terminology as well as conflation of index and secondary cases which biases toward lower asymptomaticity. We searched PubMed, Embase, Web of Science, and World Health Organization Global Research Database on COVID-19 between January 1, 2020 and April 2, 2021 to identify studies that reported silent infections at the time of testing, whether presymptomatic or asymptomatic. Index cases were removed to minimize representational bias that would result in overestimation of symptomaticity. By analyzing over 350 studies, we estimate that the percentage of infections that never developed clinical symptoms, and thus were truly asymptomatic, was 35.1% (95% CI: 30.7 to 39.9%). At the time of testing, 42.8% (95% prediction interval: 5.2 to 91.1%) of cases exhibited no symptoms, a group comprising both asymptomatic and presymptomatic infections. Asymptomaticity was significantly lower among the elderly, at 19.7% (95% CI: 12.7 to 29.4%) compared with children at 46.7% (95% CI: 32.0 to 62.0%). We also found that cases with comorbidities had significantly lower asymptomaticity compared to cases with no underlying medical conditions. Without proactive policies to detect asymptomatic infections, such as rapid contact tracing, prolonged efforts for pandemic control may be needed even in the presence of vaccination.

ImportanceRandomized clinical trials have shown that the COVID-19 vaccines currently approved in the US are highly efficacious. However, more evidence is needed to understand the population-level impact of the US vaccination rollout in the face of the changing landscape of COVID-19 pandemic in the US, including variants with higher transmissibility and immune escape.ObjectiveTo quantify the population-level impact of the US vaccination campaign in averting cases, hospitalizations and deaths from December 12, 2020 to June 28, 2021.DesignAge-stratified agent-based model which included transmission dynamics of the Alpha, Gamma and Delta variants in addition to the original Wuhan-1 variant.SettingOur model was calibrated to COVID-19 outbreak and vaccine rollout in the US. Model predictions were made at the country level.ParticipantsSimulated age-stratified population representing US demographics.Main Outcomes and MeasuresCases, hospitalizations and deaths averted by vaccination against COVID-19 in the US, compared to the counterfactuals of no vaccination and vaccination administered at half the actual pace.ResultsThe swift vaccine rollout in the US curbed a potential resurgence of cases in April 2021, which would have been otherwise fuelled by the Alpha variant. Compared to the scenario without vaccines, we estimated that the actual vaccination program averted more than 26 million cases, 1.2 million hospitalizations and saved 279,000 lives. A vaccination campaign with half the actual rollout rate would have led to an additional 460,000 hospitalizations and 121,000 deaths.Conclusions and RelevanceThe COVID-19 vaccination campaign in the US has had an extraordinary impact on reducing disease burden despite the emergence of highly transmissible variants. These findings highlight that the pace of vaccination was essential for mitigating COVID-19 in the US, and underscore the urgent need to close the vaccine coverage gaps in communities across the country.Key PointsQuestionHow effective was the United States (US) vaccination campaign in suppressing COVID-19 burden?FindingsThe vaccination campaign was highly effective in curbing the COVID-19 outbreak in the US. We estimated that the vaccine rollout saved over 275,000 lives and averted 1.2 million hospitalizations.MeaningThe swift vaccine rollout in the US averted a remarkable number of cases, hospitalizations and deaths despite the emergence of highly transmissible variants.

Successful public health regimes for COVID-19 push below unity long-term regional R t —the average number of secondary cases caused by an infectious individual. We use a susceptible-infectious-recovered (SIR) model for two coupled populations to make the conceptual point that asynchronous, variable local control, together with movement between populations, elevates long-term regional R t , and cumulative cases, and may even prevent disease eradication that is otherwise possible. For effective pandemic mitigation strategies, it is critical that models encompass both spatiotemporal heterogeneity in transmission and movement.

Robert (Bob) May, Baron May of Oxford, a long-time International Member of the National Academy of Sciences, passed away on April 28, 2020, in Oxford, United Kingdom, from “frailties of old age, Alzheimer's disease, and pneumonia,” at the age of 84. He is survived by his wife Judith, his daughter Nome, and legions of students and colleagues. Across six decades, Bob had a transformative impact on myriad fields: mathematical biology, ecology, epidemiology, public policy, and finance. His intellect, sense of loyalty to colleagues and students, and commitment to humanity made him a towering giant in science and science policy. Robert M. May, c. 2004. Image credit: Royal Society/Laurence Bulaitis. Bob May was born in Sydney, Australia, where his talents as a mathematician were evident from an early age. Bob was trained in theoretical physics at the University of Sydney by the distinguished physicist Robbie Schafroth, receiving his PhD at 24 years old for his work on bosons and superconductivity. Nonetheless, May traced his good luck in mentorships back to his high school chemistry teacher Lenny Basser and was always quick to give accolades to the many influences on his development, from teachers and colleagues alike. For those who knew him, it was clear that he made it a point to pay forward this debt through his investment in his own students and others. After a postdoctoral stint with Max Krook at Harvard University—during which he met his future wife, Judith—Bob accepted a faculty position at the University of Sydney, and within a few years had risen to one of the first “Personal Professorships” at the university. In his early work, he focused on problems in plasma physics and related fields and quickly rose to prominence. However, soon after, concerned for the fate of the planet and feeling he had a … [↵][1]1To whom correspondence may be addressed. Email: slevin{at}princeton.edu. [1]: #xref-corresp-1-1

Since the emergence of coronavirus disease 2019 (COVID-19), unprecedented movement restrictions and social distancing measures have been implemented worldwide. The socioeconomic repercussions have fueled calls to lift these measures. In the absence of population-wide restrictions, isolation of infected individuals is key to curtailing transmission. However, the effectiveness of symptom-based isolation in preventing a resurgence depends on the extent of presymptomatic and asymptomatic transmission. We evaluate the contribution of presymptomatic and asymptomatic transmission based on recent individual-level data regarding infectiousness prior to symptom onset and the asymptomatic proportion among all infections. We found that the majority of incidences may be attributable to silent transmission from a combination of the presymptomatic stage and asymptomatic infections. Consequently, even if all symptomatic cases are isolated, a vast outbreak may nonetheless unfold. We further quantified the effect of isolating silent infections in addition to symptomatic cases, finding that over one-third of silent infections must be isolated to suppress a future outbreak below 1% of the population. Our results indicate that symptom-based isolation must be supplemented by rapid contact tracing and testing that identifies asymptomatic and presymptomatic cases, in order to safely lift current restrictions and minimize the risk of resurgence.

Summary Citrus huanglongbing (HLB) is the most devastating citrus disease worldwide. ‘Candidatus Liberibacter asiaticus’ (Las) is the most prevalent HLB causal agent that is yet to be cultured. Here, we analysed the flagellar genes of Las and Rhizobiaceae and observed two characteristics unique to the flagellar proteins of Las: (i) a shorter primary structure of the rod capping protein FlgJ than other Rhizobiaceae bacteria and (ii) Las contains only one flagellin‐encoding gene flaA (CLIBASIA_02090), whereas other Rhizobiaceae species carry at least three flagellin‐encoding genes. Only flgJAtu but not flgJLas restored the swimming motility of Agrobacterium tumefaciens flgJ mutant. Pull‐down assays demonstrated that FlgJLas interacts with FlgB but not with FliE. Ectopic expression of flaALas in A. tumefaciens mutants restored the swimming motility of ∆flaA mutant and ∆flaAD mutant, but not that of the null mutant ∆flaABCD. No flagellum was observed for Las in citrus and dodder. The expression of flagellar genes was higher in psyllids than in planta. In addition, western blotting using flagellin‐specific antibody indicates that Las expresses flagellin protein in psyllids, but not in planta. The flagellar features of Las in planta suggest that Las movement in the phloem is not mediated by flagella. We also characterized the movement of Las after psyllid transmission into young flush. Our data support a model that Las remains inside young flush after psyllid transmission and before the flush matures. The delayed movement of Las out of young flush after psyllid transmission provides opportunities for targeted treatment of young flush for HLB control.

Following the April 2018 reemergence of Ebola in a rural region of the Democratic Republic of the Congo (DRC), the virus spread to an urban center by early May. Within 2 wk of the first case confirmation, a vaccination campaign was initiated in which 3,017 doses were administered to contacts of cases and frontline healthcare workers. To evaluate the spatial dynamics of Ebola transmission and quantify the impact of vaccination, we developed a geographically explicit model that incorporates high-resolution data on poverty and population density. We found that while Ebola risk was concentrated around sites initially reporting infections, longer-range dissemination also posed a risk to areas with high population density and poverty. We estimate that the vaccination program contracted the geographical area at risk for Ebola by up to 70.4% and reduced the level of risk within that region by up to 70.1%. The early implementation of vaccination was critical. A delay of even 1 wk would have reduced these effects to 33.3 and 44.8%, respectively. These results underscore the importance of the rapid deployment of Ebola vaccines during emerging outbreaks to containing transmission and preventing global spread. The spatiotemporal framework developed here provides a tool for identifying high-risk regions, in which surveillance can be intensified and preemptive control can be implemented during future outbreaks.

Reports of spatial patterns of ‘Candidatus Liberibacter asiaticus’-infected asymptomatic citrus trees and ‘Ca. L. asiaticus’-positive Asian citrus psyllids (ACP) are rare, as are published relationships between huanglongbing (HLB), ACP, and weather. Here, spatial patterns of ‘Ca. L. asiaticus’-positive asymptomatic and symptomatic trees were determined every half year in a small grove over 2.5 years, and of HLB-symptomatic trees and (‘Ca. L. asiaticus’-positive) ACP populations every month in two commercial groves for 1 year. Spread of symptomatic trees followed that of asymptomatic ‘Ca. L. asiaticus’-positive trees with −1. No spatial relationship was detected between ACP populations and HLB-infected trees. HLB incidence and ‘Ca. L. asiaticus’-positive ACP dynamics were tentatively positively correlated with monthly rainfall data and, to a lesser extent, with average minimum temperature.

Construction of a patient narrative (case history) is a core strategy in the care of patients. Recent advances in biomarker identification and digital sensors to monitor physiological and behavioral features have made constructing a case history more complex. Notably, however, although a biological profile is increasingly a part of the patient’s profile, an analogous patient-based biographical (life experience) profile is typically overlooked. Evolving concepts such as allostasis and allostatic load refer to processes promoting stability of physiological systems in the presence of diverse life experiences. Integrating details of both biology and biography is a goal of “precision medicine.” In this review, we describe how complex interactions between biology and biography affect disease risk and treatment response and highlight a strategy to develop narratives that establish the integration of biology and biography as the scientific basis for precision medicine.

Background More contagious variants of SARS-CoV-2 have emerged around the world, sparking concerns about impending surge in cases and severe outcomes. Despite the development of effective vaccines, rollout has been slow. We evaluated the impact of accelerated vaccine distribution on curbing the disease burden of novel SARS-CoV-2 variants. Methods We used an agent-based model of SARS-CoV-2 transmission and vaccination to simulate the spread of novel variants with S-Gene Target Failure (SGTF) in addition to the original strain. We incorporated age-specific risk and contact patterns and implemented a two-dose vaccination campaign in accord with CDC-recommended prioritization. As a base case, we projected hospitalizations and deaths at a daily vaccination rate of 1 million doses in the United States (US) and compared with accelerated campaigns in which daily doses were expanded to 1.5, 2, 2.5, or 3 million. Findings We found that at a vaccination rate of 1 million doses per day, an emergent SGTF variant that is 20–70% more transmissible than the original variant would become dominant within 2 to 9 weeks, accounting for as much as 99% of cases at the outbreak peak. Our results show that accelerating vaccine delivery would substantially reduce severe health outcomes. For a SGTF with 30% higher transmissibility, increasing vaccine doses from 1 to 3 million per day would avert 152,048 (95% CrI: 134,772–168,696) hospitalizations and 48,448 (95% CrI: 42,042–54,285) deaths over 300 days. Accelerated vaccination would also prevent additional COVID-19 waves that would otherwise be fuelled by waning adherence to non-pharmaceutical interventions (NPIs). Interpretation We found that the current pace of vaccine rollout is insufficient to prevent the exacerbation of the pandemic that will be attributable to the novel, more contagious SARS-CoV-2 variants. Accelerating the vaccination rate should be a public health priority for averting the expected surge in COVID-19 hospitalizations and deaths that would be associated with widespread dissemination of the SGTF variants. Our results underscore the need to bolster the production and distribution of COVID-19 vaccines, to rapidly expand vaccination priority groups and distribution sites.

On March 11, 2020, the World Health Organization declared the spread of a novel coronavirus to be a pandemic. Subsequently, and only 272 d afterward, the Pfizer vaccine started to be applied in the United Kingdom. Never before had a vaccine been developed in such a short time. Currently, four COVID-19 vaccines are approved for full use, and another eight are in early or limited use (1). However, the supply of vaccines is still inadequate to meet current needs. In such a scenario, prioritization strategies are required, ideally guided by ethical values (2). In many countries, health care professionals were initially prioritized, followed by different groups (depending on the country) such as individuals with comorbidities associated with a higher risk of COVID-19 mortality, elderly people living in crowded settings, K-12 teachers and school staff, people in homeless shelters, people in prisons, and critical workers in high-risk … [↵][1]1To whom correspondence may be addressed. Email: bhsinger{at}epi.ufl.edu. [1]: #xref-corresp-1-1

Unmitigated spread in Brazil Despite an extensive network of primary care availability, Brazil has suffered profoundly during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Using daily data from state health offices, Castro et al. analyzed the pattern of spread of COVID-19 cases and deaths in the country from February to October 2020. Clusters of deaths before cases became apparent indicated unmitigated spread. SARS-CoV-2 circulated undetected in Brazil for more than a month as it spread north from Sã o Paulo. In Manaus, transmission reached unprecedented levels after a momentary respite in mid-2020. Faria et al. tracked the evolution of a new, more aggressive lineage called P.1, which has 17 mutations, including three (K417T, E484K, and N501Y) in the spike protein. After a period of accelerated evolution, this variant emerged in Brazil during November 2020. Coupled with the emergence of P.1, disease spread was accelerated by stark local inequalities and political upheaval, which compromised a prompt federal response. Science , abh1558 and abh2644, this issue p. 821 and p. 815

For COVID-19, it is vital to understand if quarantines shorter than 14 days can be equally effective with judiciously deployed testing. Here, we develop a mathematical model that quantifies the probability of post-quarantine transmission incorporating testing into travel quarantine, quarantine of traced contacts with an unknown time of infection, and quarantine of cases with a known time of exposure. We find that testing on exit (or entry and exit) can reduce the duration of a 14-day quarantine by 50%, while testing on entry shortens quarantine by at most one day. In a real-world test of our theory applied to offshore oil rig employees, 47 positives were obtained with testing on entry and exit to quarantine, of which 16 had tested negative at entry; preventing an expected nine offshore transmission events that each could have led to outbreaks. We show that appropriately timed testing can make shorter quarantines effective., Safely reducing the necessary duration of quarantine for COVID-19 could lessen the economic impacts of the pandemic. Here, the authors demonstrate that testing on exit from quarantine is more effective than testing on entry, and can enable quarantine to be reduced from fourteen to seven days.

Contains fulltext : 235695.pdf (Publisher’s version ) (Closed access) Individuals who are minoritized as a result of race, sexual identity, gender, or socioeconomic status experience a higher prevalence of many diseases. Understanding the biological processes that cause and maintain these socially driven health inequities is essential for addressing them. The gut microbiome is strongly shaped by host environments and affects host metabolic, immune, and neuroendocrine functions, making it an important pathway by which differences in experiences caused by social, political, and economic forces could contribute to health inequities. Nevertheless, few studies have directly integrated the gut microbiome into investigations of health inequities. Here, we argue that accounting for host-gut microbe interactions will improve understanding and management of health inequities, and that health policy must begin to consider the microbiome as an important pathway linking environments to population health.

BackgroundGlobal vaccine development efforts have been accelerated in response to the devastating COVID-19 pandemic. We evaluated the impact of a 2-dose COVID-19 vaccination campaign on reducing incidence, hospitalizations, and deaths in the United States (US).MethodsWe developed an agent-based model of SARS-CoV-2 transmission and parameterized it with US demographics and age-specific COVID-19 outcomes. Healthcare workers and high-risk individuals were prioritized for vaccination, while children under 18 years of age were not vaccinated. We considered a vaccine efficacy of 95% against disease following 2 doses administered 21 days apart achieving 40% vaccine coverage of the overall population within 284 days. We varied vaccine efficacy against infection, and specified 10% pre-existing population immunity for the base-case scenario. The model was calibrated to an effective reproduction number of 1.2, accounting for current non-pharmaceutical interventions in the US.ResultsVaccination reduced the overall attack rate to 4.6% (95% CrI: 4.3% - 5.0%) from 9.0% (95% CrI: 8.4% - 9.4%) without vaccination, over 300 days. The highest relative reduction (54-62%) was observed among individuals aged 65 and older. Vaccination markedly reduced adverse outcomes, with non-ICU hospitalizations, ICU hospitalizations, and deaths decreasing by 63.5% (95% CrI: 60.3% - 66.7%), 65.6% (95% CrI: 62.2% - 68.6%), and 69.3% (95% CrI: 65.5% - 73.1%), respectively, across the same period.ConclusionsOur results indicate that vaccination can have a substantial impact on mitigating COVID-19 outbreaks, even with limited protection against infection. However, continued compliance with non-pharmaceutical interventions is essential to achieve this impact.Key pointsVaccination with a 95% efficacy against disease could substantially mitigate future attack rates, hospitalizations, and deaths, even if only adults are vaccinated. Non-pharmaceutical interventions remain an important part of outbreak response as vaccines are distributed over time.

RESUME: CONTEXTE: La hausse des cas de maladie a coronavirus 2019 (COVID-19) au Canada peut creer une forte demande de soins hospitaliers et de soins intensifs Nous avons evalue la mesure dans laquelle l'isolement volontaire des personnes presentant des symptomes legers retarde le sommet epidemique et reduit la demande de soins dans chaque province canadienne METHODES: Nous avons concu un modele de calcul et fait des simulations de la propagation de la COVID-19 dans chaque province A partir des estimations des caracteristiques de la COVID-19, nous avons evalue la demande de lits d'hopital et de lits de soins intensifs en l'absence d'isolement volontaire en supposant une moyenne de 2,5 cas secondaires, et avons compare des scenarios en faisant varier le taux d'isolement volontaire des cas legers 24 heures apres l'apparition des symptomes RESULTATS: En l'absence d'isolement volontaire, l'epidemie atteindrait son sommet dans la premiere moitie de juin, et il faudrait en moyenne 569 jours-lits de soins intensifs par 10 000 habitants Avec un taux d'isolement volontaire de 20 %, l'atteinte du sommet serait repoussee de 2 a 4 semaines, et la demande de lits diminuerait de 23,5 %;avec un taux de 40 %, le sommet serait repousse de 2 a 4 semaines supplementaires, et la demande de lits connaitrait une baisse de 53,6 % En fixant le taux d'occupation actuel des lits de soins intensifs a plus de 80 % et le taux d'isolement volontaire a 40 %, la demande de lits demeure superieure au nombre de lits disponibles INTERPRETATION: Au sommet de l'epidemie de COVID-19 au Canada, la demande de lits de soins intensifs excedera le nombre total de lits disponibles, meme avec un taux d'isolement volontaire de 40 % Nos resultats montrent que la situation sera difficile pour le systeme de sante et que l'isolement volontaire pourrait reduire la demande de soins hospitaliers et de soins intensifs (French) [ABSTRACT FROM AUTHOR] Copyright of CMAJ: Canadian Medical Association Journal is the property of Joule Inc and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission However, users may print, download, or email articles for individual use This abstract may be abridged No warranty is given about the accuracy of the copy Users should refer to the original published version of the material for the full abstract (Copyright applies to all Abstracts )

Successful public health regimes for COVID-19 push below unity long-term global Rt –the average number of secondary cases caused by an infectious individual. Most assessments use local information. Populations differ in Rt, amongst themselves and over time. We use a SIR model for two populations to make the conceptual point that even if each locality averages Rt < 1, the overall epidemic can still grow, provided these populations have asynchronous variation in transmission, and are coupled by movement of infectious individuals. This emergent effect in pandemic dynamics instantiates “Parrondo’s Paradox,” -- an entity comprised of distinct but interacting units can behave qualitatively differently than each part on its own. For effective COVID-19 disease mitigation strategies, it is critical that infectious individuals moving among locations be identified and quarantined. This does not warrant indiscriminate prevention of movement, but rather rational, targeted testing and national coordination.

Significance Our results highlight that the growing coronavirus disease 2019 (COVID-19) outbreak in the United States could gravely challenge the critical care capacity, thereby exacerbating case fatality rates. In the absence of a preventive vaccine, efforts to contain the outbreak, such as improving self-isolation rates and encouraging better hygiene practices, can alleviate some of the pressures faced by the healthcare system during an outbreak. Both emergency expansion of hospital facilities to treat COVID-19 and government appropriations to facilitate voluntary case isolation are urgently needed., In the wake of community coronavirus disease 2019 (COVID-19) transmission in the United States, there is a growing public health concern regarding the adequacy of resources to treat infected cases. Hospital beds, intensive care units (ICUs), and ventilators are vital for the treatment of patients with severe illness. To project the timing of the outbreak peak and the number of ICU beds required at peak, we simulated a COVID-19 outbreak parameterized with the US population demographics. In scenario analyses, we varied the delay from symptom onset to self-isolation, the proportion of symptomatic individuals practicing self-isolation, and the basic reproduction number R0. Without self-isolation, when R0 = 2.5, treatment of critically ill individuals at the outbreak peak would require 3.8 times more ICU beds than exist in the United States. Self-isolation by 20% of cases 24 h after symptom onset would delay and flatten the outbreak trajectory, reducing the number of ICU beds needed at the peak by 48.4% (interquartile range 46.4–50.3%), although still exceeding existing capacity. When R0 = 2, twice as many ICU beds would be required at the peak of outbreak in the absence of self-isolation. In this scenario, the proportional impact of self-isolation within 24 h on reducing the peak number of ICU beds is substantially higher at 73.5% (interquartile range 71.4–75.3%). Our estimates underscore the inadequacy of critical care capacity to handle the burgeoning outbreak. Policies that encourage self-isolation, such as paid sick leave, may delay the epidemic peak, giving a window of time that could facilitate emergency mobilization to expand hospital capacity.

Significance To contain the global spread of the 2019 novel coronavirus epidemic (COVID-19), border control measures, such as airport screening and travel restrictions, have been implemented in several countries. Our results show that these measures likely slowed the rate of exportation from mainland China to other countries, but are insufficient to contain the global spread of COVID-19. With most cases arriving during the asymptomatic incubation period, our results suggest that rapid contact tracing is essential both within the epicenter and at importation sites to limit human-to-human transmission outside of mainland China., The novel coronavirus outbreak (COVID-19) in mainland China has rapidly spread across the globe. Within 2 mo since the outbreak was first reported on December 31, 2019, a total of 566 Severe Acute Respiratory Syndrome (SARS CoV-2) cases have been confirmed in 26 other countries. Travel restrictions and border control measures have been enforced in China and other countries to limit the spread of the outbreak. We estimate the impact of these control measures and investigate the role of the airport travel network on the global spread of the COVID-19 outbreak. Our results show that the daily risk of exporting at least a single SARS CoV-2 case from mainland China via international travel exceeded 95% on January 13, 2020. We found that 779 cases (95% CI: 632 to 967) would have been exported by February 15, 2020 without any border or travel restrictions and that the travel lockdowns enforced by the Chinese government averted 70.5% (95% CI: 68.8 to 72.0%) of these cases. In addition, during the first three and a half weeks of implementation, the travel restrictions decreased the daily rate of exportation by 81.3% (95% CI: 80.5 to 82.1%), on average. At this early stage of the epidemic, reduction in the rate of exportation could delay the importation of cases into cities unaffected by the COVID-19 outbreak, buying time to coordinate an appropriate public health response.

Summary Although health care expenditure per capita is higher in the USA than in any other country, more than 37 million Americans do not have health insurance, and 41 million more have inadequate access to care. Efforts are ongoing to repeal the Affordable Care Act which would exacerbate health-care inequities. By contrast, a universal system, such as that proposed in the Medicare for All Act, has the potential to transform the availability and efficiency of American health-care services. Taking into account both the costs of coverage expansion and the savings that would be achieved through the Medicare for All Act, we calculate that a single-payer, universal health-care system is likely to lead to a 13% savings in national health-care expenditure, equivalent to more than US$450 billion annually (based on the value of the US$ in 2017). The entire system could be funded with less financial outlay than is incurred by employers and households paying for health-care premiums combined with existing government allocations. This shift to single-payer health care would provide the greatest relief to lower-income households. Furthermore, we estimate that ensuring health-care access for all Americans would save more than 68 000 lives and 1·73 million life-years every year compared with the status quo.

Socioeconomic status is consistently linked to population health and specifically to the finding that there is decreasing health associated with decreasing social position. Despite the substantial literature, an analogous literature that is focused on clinical practice, and especially consideration of the individual, is almost nonexistent. Even in the absence of these data, physicians routinely incorporate patient life experience (biography) into their estimation of a patient's clinical trajectory (prognosis) and when making therapeutic decisions. Some advances have occurred that strengthen the evidence base, such as the US Food and Drug Administration decision to show all results from randomized controlled trials on newly approved drugs by age, sex, and race. In this article we review the current status of research on the impact of social determinants of treatment response and illustrate the important role of the therapeutic context in both research and practice. Examples are provided in which a patient's "biography" alters treatment response in subgroups of the population studied. We also provide examples in which multi-omic data and biographical information in a single individual can illuminate the clinical expression of disease. Finally, we suggest a research agenda that would better support physicians who use social and behavioral features as important elements in their decision making in clinical care.

The efficacy of influenza vaccines varies from one year to the next, with efficacy during the 2017-2018 season anticipated to be lower than usual. However, the impact of low-efficacy vaccines at the population level and their optimal age-specific distribution have yet to be ascertained. Applying an optimization algorithm to a mathematical model of influenza transmission and vaccination in the United States, we determined the optimal age-specific uptake of low-efficacy vaccine that would minimize incidence, hospitalization, mortality, and disability-adjusted life-years (DALYs), respectively. We found that even relatively low-efficacy influenza vaccines can be highly impactful, particularly when vaccine uptake is optimally distributed across age groups. As vaccine efficacy declines, the optimal distribution of vaccine uptake shifts toward the elderly to minimize mortality and DALYs. Health practitioner encouragement and concerted recruitment efforts are required to achieve optimal coverage among target age groups, thereby minimizing influenza morbidity and mortality for the population overall.

Although great progress has been made to advance the scientific understanding of oil spills, tools for integrated assessment modeling of the long-term impacts on ecosystems, socioeconomics and human health are lacking. The objective of this study was to develop a conceptual framework that could be used to answer stakeholder questions about oil spill impacts and to identify knowledge gaps and future integration priorities. The framework was initially separated into four knowledge domains (ocean environment, biological ecosystems, socioeconomics, and human health) whose interactions were explored by gathering stakeholder questions through public engagement, assimilating expert input about existing models, and consolidating information through a system dynamics approach. This synthesis resulted in a causal loop diagram from which the interconnectivity of the system could be visualized. Results of this analysis indicate that the system naturally separates into two tiers, ocean environment and biological ecosystems versus socioeconomics and human health. As a result, ocean environment and ecosystem models could be used to provide input to explore human health and socioeconomic variables in hypothetical scenarios. At decadal-plus time scales, the analysis emphasized that human domains influence the natural domains through changes in oil-spill related laws and regulations. Although data gaps were identified in all four model domains, the socioeconomics and human health domains are the least established. Considerable future work is needed to address research gaps and to create fully coupled quantitative integrative assessment models that can be used in strategic decision-making that will optimize recoveries from future large oil spills.

Evidence based medicine, using randomized controlled trials and meta-analyses as the major tools and sources of evidence about average results for heterogeneous groups of patients, developed as a reaction against poorly designed observational treatment research and physician reliance on personal experience with other patients as a guide to decision-making about a patient at hand. However, these tools do not answer the clinician's question: "Will a given therapeutic regimen help my patient at a given point in her/his clinical course?" We introduce fine-grained profiling of the patient at hand, accompanied by comparative evidence of responses from approximate matches to this patient on whom a contemplated treatment has/has not been administered. This represents medicine based evidence that is tuned to decision-making for the particular patient.

An error in a previous publication in the calculation of the average age at first infection for the model is corrected here. The average age at first infection for the effective contact rates used to generate the data ranges from 1.2 to 3.3 years of age instead of 3–5 years of age as advertised in the previous version of the paper. This change has an effect on the force of infection generated by this model. In this corrigendum, we demonstrate the correct method to calculate the average age at first infection for the model. We compare the forces of infection that correspond to these ages in our model with the forces of infection in other endemic populations. We show that the modified age range corresponds to forces of infection which are higher than those that are known to exist in historical studies of polio-endemic regions. Thus, the results in the paper have limited applicability to real-world endemic situations. Keywords: Poliovirus, Silent circulation, Acute flaccid paralysis surveillance, Microsimulation model, Gillespie algorithm