Benefit-Cost Analysis of the HHS COVID-19 Campaign: April 2021-March 2022.

INTRODUCTION: This study estimated the benefits and costs of the U.S. Department of Health and Human Services' We Can Do This COVID-19 public education campaign (the Campaign) and associated vaccination-related impacts. METHODS: Weekly media market and national Campaign expenditures were used to estimate weekly first-dose vaccinations that would not have occurred absent the Campaign, weekly Campaign-attributed complete vaccinations, and corresponding COVID-19 cases, hospitalizations, and deaths averted. Benefits were valued using estimated morbidity and mortality reductions and associated values of a statistical life and a statistical case. Costs were estimated using Campaign paid media expenditures and corresponding vaccination costs. The net Campaign and vaccination benefit and return on investment were calculated. Analyses were conducted from 2022 to 2024. RESULTS: Between April 2021 and March 2022, an estimated 55.9 million doses of COVID-19 vaccines would not have been administered absent the Campaign. Campaign-attributed vaccinations resulted in 2,576,133 fewer mild COVID-19 cases, 243,979 fewer nonfatal COVID-19 hospitalizations, and 51,675 lives saved from COVID-19. The total Campaign benefit was $740.2 billion, and Campaign and vaccination costs totaled $8.3 billion, with net benefits of approximately $732.0 billion. For every $1 spent, the Campaign and corresponding vaccination costs resulted in benefits of approximately $89.54. CONCLUSIONS: The We Can Do This COVID-19 public education campaign saved more than 50,000 lives and prevented hundreds of thousands of hospitalizations and millions of COVID-19 cases, representing hundreds of billions of dollars in benefits in less than one year. Findings suggest that public education campaigns are a cost-effective approach to reducing COVID-19 morbidity and mortality.

Assessment of detailed conformations suggests strategies for improving cryoEM models: Helix at lower resolution, ensembles, pre-refinement fixups, and validation at multi-residue length scale.

We find that the overall quite good methods used in the CryoEM Model Challenge could still benefit greatly from several strategies for improving local conformations. Our assessments primarily use validation criteria from the MolProbity web service. Those criteria include MolProbity's all-atom contact analysis, updated versions of standard conformational validations for protein and RNA, plus two recent additions: first, flags for cis-nonPro and twisted peptides, and second, the CaBLAM system for diagnosing secondary structure, validating Cα backbone, and validating adjacent peptide CO orientations in the context of the Cα trace. In general, automated ab initio building of starting models is quite good at backbone connectivity but often fails at local conformation or sequence register, especially at poorer than 3.5 Šresolution. However, we show that even if criteria (such as Ramachandran or rotamer) are explicitly restrained to improve refinement behavior and overall validation scores, automated optimization of a deposited structure seldom corrects specific misfittings that start in the wrong local minimum, but just hides them. Therefore, local problems should be identified, and as many as possible corrected, before starting refinement. Secondary structures are confusing at 3-4 Šbut can be better recognized at 6-8 Å. In future model challenges, specific steps being tested (such as segmentation) and the required documentation (such as PDB code of starting model) should each be explicitly defined, so competing methods on a given task can be meaningfully compared. Individual local examples are presented here, to understand what local mistakes and corrections look like in 3D, how they probably arise, and what possible improvements to methodology might help avoid them. At these resolutions, both structural biologists and end-users need meaningful estimates of local uncertainty, perhaps through explicit ensembles. Fitting problems can best be diagnosed by validation that spans multiple residues; CaBLAM is such a multi-residue tool, and its effectiveness is demonstrated.

Hepatitis A outbreak disproportionately affecting men who have sex with men (MSM) in the European Union and European Economic Area, June 2016 to May 2017.

Between 1 June 2016 and 31 May 2017, 17 European Union (EU) and European Economic Area countries reported 4,096 cases associated with a multi-country hepatitis A (HA) outbreak. Molecular analysis identified three co-circulating hepatitis A virus (HAV) strains of genotype IA: VRD_521_2016, V16-25801 and RIVM-HAV16-090. We categorised cases as confirmed, probable or possible, according to the EU outbreak case definitions. Confirmed cases were infected with one of the three outbreak strains. We investigated case characteristics and strain-specific risk factors for transmission. A total of 1,400 (34%) cases were confirmed; VRD_521_2016 and RIVM-HAV16-090 accounted for 92% of these. Among confirmed cases with available epidemiological data, 92% (361/393) were unvaccinated, 43% (83/195) travelled to Spain during the incubation period and 84% (565/676) identified as men who have sex with men (MSM). Results depict an HA outbreak of multiple HAV strains, within a cross-European population, that was particularly driven by transmission between non-immune MSM engaging in high-risk sexual behaviour. The most effective preventive measure to curb this outbreak is HAV vaccination of MSM, supplemented by primary prevention campaigns that target the MSM population and promote protective sexual behaviour.

The Economic Model of Retinopathy of Prematurity (EcROP) Screening and Treatment: Mexico and the United States.

PURPOSE: To describe an economic (Ec) model for estimating the impact of screening and treatment for retinopathy of prematurity (ROP). DESIGN: EcROP is a cost-effectiveness, cost-utility, and cost-benefit analysis. METHODS: We surveyed caregivers of 52 children at schools for the blind or pediatric eye clinics in Atlanta, Georgia and 43 in Mexico City. A decision analytic model with sensitivity analysis determined the incremental cost-effectiveness (primary outcome) and incremental monetary benefit (secondary outcome) of an ideal (100% screening) national ROP program as compared to estimates of current practice. Direct costs included screening and treatment expenditures. Indirect costs estimated lost productivity of caretaker(s) and blind individuals as determined by face-to-face surveys. Utility and effectiveness were measured in quality-adjusted life years and benefit in US dollars. EcROP includes a sensitivity analysis to assesses the incremental cost-effectiveness and societal impact of ROP screening and treatment within a country or economic region. Estimates are based on evidence-based clinical data and region-specific economic data acquired from direct field survey. RESULTS: In both Mexico and the United States, an ideal national ROP screening and treatment program was highly cost-saving. The incremental net benefit of an ideal ROP program over current practice is $5556 per child ($206 574 333 annually) and $3628 per child ($205 906 959 annually) in Mexico and the United States, respectively. CONCLUSION: EcROP demonstrates that ROP screening and treatment is highly beneficial for quality of life, cost saving, and cost-effectiveness in the United States and Mexico. EcROP can be applied to any country or region to provide data for informed allocation of limited health care resources.

Recruitment to online therapies for depression: pilot cluster randomized controlled trial.

BACKGROUND: Raising awareness of online cognitive behavioral therapy (CBT) could benefit many people with depression, but we do not know how purchasing online advertising compares to placing free links from relevant local websites in increasing uptake. OBJECTIVE: To pilot a cluster randomized controlled trial (RCT) comparing purchase of Google AdWords with placing free website links in raising awareness of online CBT resources for depression in order to better understand research design issues. METHODS: We compared two online interventions with a control without intervention. The pilot RCT had 4 arms, each with 4 British postcode areas: (A) geographically targeted AdWords, (B) adverts placed on local websites by contacting website owners and requesting links be added, (C) both interventions, (D) control. Participants were directed to our research project website linking to two freely available online CBT resource sites (Moodgym and Living Life To The Full (LLTTF)) and two other depression support sites. We used data from (1) AdWords, (2) Google Analytics for our project website and for LLTTF, and (3) research project website. We compared two outcomes: (1) numbers with depression accessing the research project website, and then chose an onward link to one of the two CBT websites, and (2) numbers registering with LLTTF. We documented costs, and explored intervention and assessment methods to make general recommendations to inform researchers aiming to use similar methodologies in future studies. RESULTS: Trying to place local website links appeared much less cost effective than AdWords and although may prove useful for service delivery, was not worth pursuing in the context of the current study design. Our AdWords intervention was effective in recruiting people to the project website but our location targeting "leaked" and was not as geographically specific as claimed. The impact on online CBT was also diluted by offering participants other choices of destinations. Measuring the impact on LLTTF use was difficult as the total number using LLTTF was less than 5% of all users and record linkage across websites was impossible. Confounding activity may have resulted in some increase in registrations in the control arm. CONCLUSIONS: Practitioners should consider online advertising to increase uptake of online therapy but need to check its additional value. A cluster RCT using location targeted adverts is feasible and this research design provides the best evidence of cost-effectiveness. Although our British pilot study is limited to online CBT for depression, a cluster RCT with similar design would be appropriate for other online treatments and countries and our recommendations may apply. They include ways of dealing with possible contamination (buffer zones and AdWords techniques), confounding factors (large number of clusters), advertising dose (in proportion to total number of users), record linkage (landing within target website), and length of study (4-6 months). TRIAL REGISTRATION: clinicaltrials.gov (Registration No. NCT01469689); http://clinicaltrials.gov/ct2/show/NCT01469689 (Archived by WebCite at http://www.webcitation.org/6EtTthDOp).

The other 90% of the protein: assessment beyond the Calphas for CASP8 template-based and high-accuracy models.

For template-based modeling in the CASP8 Critical Assessment of Techniques for Protein Structure Prediction, this work develops and applies six new full-model metrics. They are designed to complement and add value to the traditional template-based assessment by the global distance test (GDT) and related scores (based on multiple superpositions of Calpha atoms between target structure and predictions labeled "Model 1"). The new metrics evaluate each predictor group on each target, using all atoms of their best model with above-average GDT. Two metrics evaluate how "protein-like" the predicted model is: the MolProbity score used for validating experimental structures, and a mainchain reality score using all-atom steric clashes, bond length and angle outliers, and backbone dihedrals. Four other new metrics evaluate match of model to target for mainchain and sidechain hydrogen bonds, sidechain end positioning, and sidechain rotamers. Group-average Z-score across the six full-model measures is averaged with group-average GDT Z-score to produce the overall ranking for full-model, high-accuracy performance. Separate assessments are reported for specific aspects of predictor-group performance, such as robustness of approximately correct template or fold identification, and self-scoring ability at identifying the best of their models. Fold identification is distinct from but correlated with group-average GDT Z-score if target difficulty is taken into account, whereas self-scoring is done best by servers and is uncorrelated with GDT performance. Outstanding individual models on specific targets are identified and discussed. Predictor groups excelled at different aspects, highlighting the diversity of current methodologies. However, good full-model scores correlate robustly with high Calpha accuracy.

Geographic correlation between deprivation and risk of meningococcal disease: an ecological study.

BACKGROUND: Meningitis caused by Neisseria meningitidis is a serious infection which is most common in young children and adolescents. This study investigated the relationships between the incidence and age distribution of meningococcal disease, and socioeconomic environment. METHODS: An ecological design was used, including mapping using a Geographical Information System (GIS) at census ward level. RESULTS: Incidence of meningococcal disease was highest in the most deprived wards, with a relative risk of 1.97 (1.55 - 2.51). Mapping revealed geographical coincidence of deprivation and meningococcal disease, particularly in urban areas. Two-thirds of the increased incidence was due to cases in the under fives. CONCLUSIONS: The results suggest that area deprivation is a risk factor for meningococcal disease, and that its effects are seen most in young children.