IMPORTANCE: Universal screening to identify unfavorable lipid levels is recommended for US children aged 9 to 11 years and adolescents aged 17 to 21 years (hereafter, young adults); however, screening benefits in these individuals have been questioned. Current use of lipid screening and prevalence of elevated lipid measurements among US youths is not well understood. OBJECTIVE: To investigate the prevalence of ambulatory pediatric lipid screening and elevated or abnormal lipid measurements among US screened youths by patient characteristic and test type. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study used data from the IQVIA Ambulatory Electronic Medical Record database and included youths aged 9 to 21 years with 1 or more valid measurement of height and weight during the observation period (2018-2021). Body mass index (BMI) was calculated and categorized using standard pediatric BMI percentiles (9-19 years) and adult BMI categories (≥20 years). The data were analyzed from October 6, 2022, to January 18, 2023. MAIN OUTCOMES AND MEASURES: Lipid measurements were defined as abnormal if 1 or more of the following test results was identified: total cholesterol (≥200 mg/dL), low-density lipoprotein cholesterol (≥130 mg/dL), very low-density lipoprotein cholesterol (≥31 mg/dL), non-high-density lipoprotein cholesterol (≥145 mg/dL), and triglycerides (≥100 mg/dL for children aged 9 years or ≥130 mg/dL for patients aged 10-21 years). After adjustment for age group, sex, race and ethnicity, and BMI category, adjusted prevalence ratios (aPRs) and 95% CIs were calculated. RESULTS: Among 3 226 002 youths (23.9% aged 9-11 years, 34.8% aged 12-16 years, and 41.3% aged 17-21 years; 1 723 292 females [53.4%]; 60.0% White patients, 9.5% Black patients, and 2.4% Asian patients), 11.3% had 1 or more documented lipid screening tests. The frequency of lipid screening increased by age group (9-11 years, 9.0%; 12-16 years, 11.1%; 17-21 years, 12.9%) and BMI category (range, 9.2% [healthy weight] to 21.9% [severe obesity]). Among those screened, 30.2% had abnormal lipid levels. Compared with youths with a healthy weight, prevalence of an abnormal result was higher among those with overweight (aPR, 1.58; 95% CI, 1.56-1.61), moderate obesity (aPR, 2.16; 95% CI, 2.14-2.19), and severe obesity (aPR, 2.53; 95% CI, 2.50-2.57). CONCLUSIONS AND RELEVANCE: In this cross-sectional study of prevalence of lipid screening among US youths aged 9 to 21 years, approximately 1 in 10 were screened. Among them, abnormal lipid levels were identified in 1 in 3 youths overall and 1 in 2 youths with severe obesity. Health care professionals should consider implementing lipid screening among children aged 9 to 11 years, young adults aged 17 to 21 years, and all youths at high cardiovascular risk.

Marburg viral disease (MVD) is a highly infectious disease with a case fatality rate of up to 90%, particularly impacting resource-limited countries where implementing Infection Prevention and Control (IPC) measures is challenging. This paper shares the experience of how Tanzania has improved its capacity to prevent and control highly infectious diseases, and how this capacity was utilized during the outbreak of the MVD disease that occurred for the first time in the country in 2023.In 2016 and the subsequent years, Tanzania conducted self and external assessments that revealed limited IPC capacity in responding to highly infectious diseases. To address these gaps, initiatives were undertaken, including the enhancement of IPC readiness through the development and dissemination of guidelines, assessments of healthcare facilities, supportive supervision and mentorship, procurement of supplies, and the renovation or construction of environments to bolster IPC implementation.The official confirmation and declaration of MVD on March 21, 2023, came after five patients had already died of the disease. MVD primarily spreads through contact and presents with severe symptoms, which make patient care and prevention challenging, especially in resource-limited settings. However, with the use of a trained workforce; IPC rapid needs assessment was conducted, identifying specific gaps. Based on the results; mentorship programs were carried out, specific policies and guidelines were developed, security measures were enhanced, all burial activities in the area were supervised, and both patients and staff were monitored across all facilities. By the end of the outbreak response on June 1, 2023, a total of 212 contacts had been identified, with the addition of only three deaths. Invasive procedures like dialysis and Manual Vacuum Aspiration prevented some deaths in infected patients, procedures previously discouraged.In summary, this experience underscores the critical importance of strict adherence to IPC practices in controlling highly infectious diseases. Recommendations for low-income countries include motivating healthcare providers and improving working conditions to enhance commitment in challenging environments. This report offers valuable insights and practical interventions for preparing for and addressing highly infectious disease outbreaks through implementation of IPC measures.

Transgender women are disproportionately impacted by HIV infection. We report herein the findings of a pre-post evaluation of the TransLife Care (TLC) project in Chicago, Illinois, on behaviors associated with HIV transmission among transgender women. Participants who received any TLC component versus those who did not were compared using mixed-effects logistic regression with random intercepts across follow-up time points. Ninety-seven participants aged 18 to 59 (median age 24) enrolled; 76.3% were transgender women of color. There was a decrease in condomless sex without consistent PrEP use at 8 months, which was not significantly different between those who did and did not receive the TLC intervention, controlling for calendar time. Evidence does not indicate that the TLC reduces condomless sex without PrEP protection among urban transgender women. However, given the preponderance of evidence of the influence of structural barriers on condomless sex, future research should continue to test the efficacy of structural interventions.

Stroke was the fifth leading cause of death in the United States in 2021, and cost U.S. residents approximately $56.2 billion during 2019-2020. During 2006-2010, self-reported stroke prevalence among noninstitutionalized adults had a relative decrease of 3.7%. Data from the Behavioral Risk Factor Surveillance System were used to analyze age-standardized stroke prevalence during 2011-2022 among adults aged ≥18 years. From 2011-2013 to 2020-2022, overall self-reported stroke prevalence increased by 7.8% nationwide. Increases occurred among adults aged 18-64 years; females and males; non-Hispanic Black or African American (Black), non-Hispanic White (White), and Hispanic or Latino (Hispanic) persons; and adults with less than a college degree. Stroke prevalence was higher among adults aged ≥65 years than among younger adults; among non-Hispanic American Indian or Alaska Native, non-Hispanic Native Hawaiian or Pacific Islander, and Black adults than among White adults; and among adults with less than a high school education than among those with higher levels of education. Stroke prevalence decreased in the District of Columbia and increased in 10 states. Initiatives to promote knowledge of the signs and symptoms of stroke, and the identification of disparities in stroke prevalence, might help to focus clinical and programmatic interventions, such as the Million Hearts 2027 initiative or the Paul Coverdell National Acute Stroke Program, to improve prevention and treatment of stroke.

AIMS AND METHODS: In the United States, blacklegged Ixodes spp. ticks are the primary vector of Lyme disease. Minnesota is among the states with the highest reported incidence of Lyme disease, having an average of 1857 cases reported annually during 2011-2019. In contrast to the Northeast and mid-Atlantic United States where exposure to ticks predominately occurs around the home, the circumstances regarding risk for exposure to blacklegged ticks in Minnesota are not well understood, and risk is thought to be highest in rural areas where people often participate in recreational activities (e.g. hiking, visiting cabins). We analysed enhanced surveillance data collected by the Minnesota Department of Health during 2011-2019 to describe epidemiologic and tick exposure characteristics among people with reported Lyme disease. RESULTS: We found that younger age, male gender, residence in a county with lower Lyme disease risk, residence in the Minneapolis-St. Paul metropolitan area, and an illness onset date later in the year were independently associated with higher odds of reporting tick exposures away from the home. We also describe the range of activities associated with tick exposure away from the home, including both recreational and occupational activities. CONCLUSIONS: These findings refine our understanding of Lyme disease risk in Minnesota and highlight the need for heterogeneous public health prevention messaging, including an increased focus on peridomestic prevention measures among older individuals living in high-risk rural areas and recreational and occupational prevention measures among younger individuals living in the Minneapolis-St. Paul metropolitan area.

BACKGROUND: People with HIV (PWH) have higher rates of cardiovascular disease than people without HIV. However, limited information exists about hypertension prevalence and associated risk factors in PWH. METHODS: This cross-sectional study included adult patients in the 2022 IQVIATM Ambulatory Electronic Medical Record - US data. HIV was identified based on ≥2 HIV diagnosis codes or a positive HIV test. Hypertension was identified by diagnosis codes, ≥2 blood pressure (BP) readings ≥130/80 mmHg, or an antihypertensive medication prescription. Among those with hypertension, control was defined as most recent BP <130/80 mmHg. Logistic models using marginal standardization method were used to estimate adjusted prevalence ratios (aPR) of hypertension and hypertension control among all patients and PWH specifically, controlling for covariates. RESULTS: Of 7,533,379 patients, 19,102 (0.3%) had HIV. PWH had higher hypertension prevalence (66% vs 54%, aPR:1.14, 95% CI: 1.13-1.15) compared with people without HIV. Among persons with hypertension, PWH were more likely to have controlled hypertension (aPR: 1.10, 95% CI: 1.07-1.13) compared with people without HIV. Among PWH, those from the South were more likely to have hypertension (aPR: 1.07, 95% CI: 1.02-1.12) than PWH from the Northeast, while Black PWH were less likely to have controlled hypertension (aPR: 0.72, 95% CI: 0.67-0.77) than White PWH. CONCLUSIONS: PWH were more likely to have hypertension than people without HIV. Geographic and racial disparities in hypertension prevalence and control were observed among PWH. Optimal care for PWH includes comprehensive strategies to screen for, prevent, and manage hypertension.

Dengue is the most prevalent mosquito-borne viral disease in humans, and cases are continuing to rise globally. In particular, islands in the Caribbean have experienced more frequent outbreaks, and all four dengue virus (DENV) serotypes have been reported in the region, leading to hyperendemicity and increased rates of severe disease. However, there is significant variability regarding virus surveillance and reporting between islands, making it difficult to obtain an accurate understanding of the epidemiological patterns in the Caribbean. To investigate this, we used travel surveillance and genomic epidemiology to reconstruct outbreak dynamics, DENV serotype turnover, and patterns of spread within the region from 2009-2022. We uncovered two recent DENV-3 introductions from Asia, one of which resulted in a large outbreak in Cuba, which was previously under-reported. We also show that while outbreaks can be synchronized between islands, they are often caused by different serotypes. Our study highlights the importance of surveillance of infected travelers to provide a snapshot of local introductions and transmission in areas with limited local surveillance and suggests that the recent DENV-3 introductions may pose a major public health threat in the region.

IMPORTANCE: The function-based eat, sleep, console (ESC) care approach substantially reduces the proportion of infants who receive pharmacologic treatment for neonatal opioid withdrawal syndrome (NOWS). This reduction has led to concerns for increased postnatal opioid exposure in infants who receive pharmacologic treatment. However, the effect of the ESC care approach on hospital outcomes for infants pharmacologically treated for NOWS is currently unknown. OBJECTIVE: To evaluate differences in opioid exposure and total length of hospital stay (LOS) for pharmacologically treated infants managed with the ESC care approach vs usual care with the Finnegan tool. DESIGN, SETTING, AND PARTICIPANTS: This post hoc subgroup analysis involved infants pharmacologically treated in ESC-NOW, a stepped-wedge cluster randomized clinical trial conducted at 26 US hospitals. Hospitals maintained pretrial practices for pharmacologic treatment, including opioid type, scheduled opioid dosing, and use of adjuvant medications. Infants were born at 36 weeks' gestation or later, had evidence of antenatal opioid exposure, and received opioid treatment for NOWS between September 2020 and March 2022. Data were analyzed from November 2022 to January 2024. EXPOSURE: Opioid treatment for NOWS and the ESC care approach. MAIN OUTCOMES AND MEASURES: For each outcome (total opioid exposure, peak opioid dose, time from birth to initiation of first opioid dose, length of opioid treatment, and LOS), we used generalized linear mixed models to adjust for the stepped-wedge design and maternal and infant characteristics. RESULTS: In the ESC-NOW trial, 463 of 1305 infants were pharmacologically treated (143/603 [23.7%] in the ESC care approach group and 320/702 [45.6%] in the usual care group). Mean total opioid exposure was lower in the ESC care approach group with an absolute difference of 4.1 morphine milligram equivalents per kilogram (MME/kg) (95% CI, 1.3-7.0) when compared with usual care (4.8 MME/kg vs 8.9 MME/kg, respectively; P = .001). Mean time from birth to initiation of pharmacologic treatment was 22.4 hours (95% CI, 7.1-37.7) longer with the ESC care approach vs usual care (75.4 vs 53.0 hours, respectively; P = .002). No significant difference in mean peak opioid dose was observed between groups (ESC care approach, 0.147 MME/kg, vs usual care, 0.126 MME/kg). The mean length of treatment was 6.3 days shorter (95% CI, 3.0-9.6) in the ESC care approach group vs usual care group (11.8 vs 18.1 days, respectively; P < .001), and mean LOS was 6.2 days shorter (95% CI, 3.0-9.4) with the ESC care approach than with usual care (16.7 vs 22.9 days, respectively; P < .001). CONCLUSION AND RELEVANCE: When compared with usual care, the ESC care approach was associated with less opioid exposure and shorter LOS for infants pharmacologically treated for NOWS. The ESC care approach was not associated with a higher peak opioid dose, although pharmacologic treatment was typically initiated later. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04057820.

IMPORTANCE: Emtricitabine and tenofovir disoproxil fumarate (F/TDF) for HIV preexposure prophylaxis (PrEP) is highly effective in cisgender men who have sex with men (MSM) when adherence is high (>4 doses/week). Real-world effectiveness and adherence with F/TDF for PrEP in cisgender women is less well characterized. OBJECTIVE: To characterize the effectiveness of F/TDF for PrEP and its relationship with adherence in cisgender women. DESIGN, SETTING, AND PARTICIPANTS: Data were pooled from 11 F/TDF PrEP postapproval studies conducted in 6 countries that included 6296 cisgender women aged 15 to 69 years conducted from 2012 to 2020. HIV incidence was evaluated according to adherence level measured objectively (tenofovir diphosphate concentration in dried blood spots or tenofovir concentration in plasma; n = 288) and subjectively (electronic pill cap monitoring, pill counts, self-report, and study-reported adherence scale; n = 2954) using group-based trajectory modeling. EXPOSURES: F/TDF prescribed orally once a day. HIV incidence was analyzed in subgroups based on adherence trajectory. MAIN OUTCOMES AND MEASURES: HIV incidence. RESULTS: Of the 6296 participants, 46% were from Kenya, 28% were from South Africa, 21% were from India, 2.9% were from Uganda, 1.6% were from Botswana, and 0.8% were from the US. The mean (SD) age at PrEP initiation across all studies was 25 (7) years, with 61% of participants being younger than 25 years. The overall HIV incidence was 0.72 per 100 person-years (95% CI, 0.51-1.01; 32 incident HIV diagnoses among 6296 participants). Four distinct groups of adherence trajectories were identified: consistently daily (7 doses/week), consistently high (4-6 doses/week), high but declining (from a mean of 4-6 doses/week and then declining), and consistently low (less than 2 doses/week). None of the 498 women with consistently daily adherence acquired HIV. Only 1 of the 658 women with consistently high adherence acquired HIV (incidence rate, 0.13/100 person-years [95% CI, 0.02-0.92]). The incidence rate was 0.49 per 100 person-years (95% CI, 0.22-1.08) in the high but declining adherence group (n = 1166) and 1.27 per 100 person-years (95% CI, 0.53-3.04) in the consistently low adherence group (n = 632). CONCLUSIONS AND RELEVANCE: In a pooled analysis of 11 postapproval studies of F/TDF for PrEP among cisgender women, overall HIV incidence was 0.72 per 100 person-years; individuals with consistently daily or consistently high adherence (4-6 doses/week) to PrEP experienced very low HIV incidence.

During May 2022-April 2023, dengue virus serotype 3 was identified among 601 travel-associated and 61 locally acquired dengue cases in Florida, USA. All 203 sequenced genomes belonged to the same genotype III lineage and revealed potential transmission chains in which most locally acquired cases occurred shortly after introduction, with little sustained transmission.

PURPOSE: As epidemiological studies expand to examine gene-environment interaction effects, it is important to identify factors associated with participation in genetic studies. The National Birth Defects Prevention Study is a multisite case-control study designed to investigate environmental and genetic risk factors for major birth defects. The National Birth Defects Prevention Study includes maternal telephone interviews and mailed buccal cell self-collection kits. Because subjects can participate in the interview, independent of buccal cell collection, detailed analysis of factors associated with participation in buccal cell collection was possible. METHODS: Multivariable logistic regression models were used to identify the factors associated with participation in the genetic component of the study. RESULTS: Buccal cell participation rates varied by race/ethnicity (non-Hispanic whites, 66.9%; Hispanics, 60.4%; and non-Hispanic blacks, 47.3%) and study site (50.2-74.2%). Additional monetary incentive following return of buccal cell kit and shorter interval between infant's estimated date of delivery and interview were associated with increased participation across all racial/ethnic groups. Higher education and delivering an infant with a birth defect were associated with increased participation among non-Hispanic whites and Hispanics. CONCLUSION: Factors associated with participation varied by race/ethnicity. Improved understanding of factors associated with participation may facilitate strategies to increase participation, thereby improving generalizability of study findings.

New developments in the treatment and management of phenylketonuria (PKU) as well as advances in molecular testing have emerged since the National Institutes of Health 2000 PKU Consensus Statement was released. An NIH State-of-the-Science Conference was convened in 2012 to address new findings, particularly the use of the medication sapropterin to treat some individuals with PKU, and to develop a research agenda. Prior to the 2012 conference, five working groups of experts and public members met over a 1-year period. The working groups addressed the following: long-term outcomes and management across the lifespan; PKU and pregnancy; diet control and management; pharmacologic interventions; and molecular testing, new technologies, and epidemiologic considerations. In a parallel and independent activity, an Evidence-based Practice Center supported by the Agency for Healthcare Research and Quality conducted a systematic review of adjuvant treatments for PKU; its conclusions were presented at the conference. The conference included the findings of the working groups, panel discussions from industry and international perspectives, and presentations on topics such as emerging treatments for PKU, transitioning to adult care, and the U.S. Food and Drug Administration regulatory perspective. Over 85 experts participated in the conference through information gathering and/or as presenters during the conference, and they reached several important conclusions. The most serious neurological impairments in PKU are preventable with current dietary treatment approaches. However, a variety of more subtle physical, cognitive, and behavioral consequences of even well-controlled PKU are now recognized. The best outcomes in maternal PKU occur when blood phenylalanine (Phe) concentrations are maintained between 120 and 360 μmol/L before and during pregnancy. The dietary management treatment goal for individuals with PKU is a blood Phe concentration between 120 and 360 μmol/L. The use of genotype information in the newborn period may yield valuable insights about the severity of the condition for infants diagnosed before maximal Phe levels are achieved. While emerging and established genotype-phenotype correlations may transform our understanding of PKU, establishing correlations with intellectual outcomes is more challenging. Regarding the use of sapropterin in PKU, there are significant gaps in predicting response to treatment; at least half of those with PKU will have either minimal or no response. A coordinated approach to PKU treatment improves long-term outcomes for those with PKU and facilitates the conduct of research to improve diagnosis and treatment. New drugs that are safe, efficacious, and impact a larger proportion of individuals with PKU are needed. However, it is imperative that treatment guidelines and the decision processes for determining access to treatments be tied to a solid evidence base with rigorous standards for robust and consistent data collection. The process that preceded the PKU State-of-the-Science Conference, the conference itself, and the identification of a research agenda have facilitated the development of clinical practice guidelines by professional organizations and serve as a model for other inborn errors of metabolism.

To end the largest known outbreak of Ebola virus disease (EVD) in West Africa and to prevent new transmissions, rapid epidemiological tracing of cases and contacts was required. The ability to quickly identify unknown sources and chains of transmission is key to ending the EVD epidemic and of even greater importance in the context of recent reports of Ebola virus (EBOV) persistence in survivors. Phylogenetic analysis of complete EBOV genomes can provide important information on the source of any new infection. A local deep sequencing facility was established at the Mateneh Ebola Treatment Centre in central Sierra Leone. The facility included all wetlab and computational resources to rapidly process EBOV diagnostic samples into full genome sequences. We produced 554 EBOV genomes from EVD cases across Sierra Leone. These genomes provided a detailed description of EBOV evolution and facilitated phylogenetic tracking of new EVD cases. Importantly, we show that linked genomic and epidemiological data can not only support contact tracing but also identify unconventional transmission chains involving body fluids, including semen. Rapid EBOV genome sequencing, when linked to epidemiological information and a comprehensive database of virus sequences across the outbreak, provided a powerful tool for public health epidemic control efforts.

In a broad sense, molecular epidemiology is the axis that unites insights at the molecular level and understanding of disease at the population level. It is also a partnership between epidemiologists and laboratory scientists in which investigations are conducted using the principles of both disciplines. A key trait of molecular epidemiology is to evaluate and establish the relationship between a biomarker and important exogenous and endogenous exposures, susceptibility, or disease, providing understanding that can be used in future research and public health and clinical practice. When potential solutions or interventions are identified, molecular epidemiology is also useful in developing and conducting clinical and intervention trials. It can then contribute to the translation of biomedical research into practical public health and clinical applications by addressing the medical and population implications of molecular phenomena in terms of reducing risk of disease. This chapter summarizes the contributions and research endeavours of molecular epidemiology and how they link with public health initiatives and clinical practice.

The epidemiologic and genetic characteristics of mumps viruses detected in China from 1995 to 2010 were analyzed in this study. Mumps remains endemic in China with a high overall incidence rate. The incidence of mumps in Western China was higher than that in other regions of the country. Each year, most of mumps cases occurred between April and July, but a small peak also occurred in November and December. Mumps cases primarily affected the under 15 year old age group. Virologic data demonstrated that genotype F was the predominant circulating genotype throughout China for at least 15 years and no other genotype was detected between 1995 and 2010. Analysis of sequence data from the small hydrophobic (SH) gene indicated that multiple transmission chains of genotype F were found in various provinces of China, with no apparent chronologic and geographic restriction. This is the first report describing the epidemiology of mumps and genetic characterization of mumps viruses at the national level in China.

BACKGROUND AND PURPOSE: To understand the association of sex-specific race and ethnicity on the short-term outcomes of initial and recurrent ischemic stroke events. METHODS: Using the Paul Coverdell National Acute Stroke Program from 2016-2020, we examined 426,062 ischemic stroke admissions from 629 hospitals limited to non-Hispanic White (NHW), non-Hispanic Black (NHB), and Hispanic patients. We performed multivariate logistic regression analyses to assess the combined effects of sex-specific race and ethnicity on short-term outcomes for acute ischemic stroke patients presenting with initial or recurrent stroke events. Outcomes assessed include rates of in-hospital death, discharge to home, and symptomatic intracranial hemorrhage (sICH) after reperfusion treatment. RESULTS: Among studied patients, the likelihood of developing sICH after reperfusion treatment for initial ischemic stroke was not significantly different. The likelihood of experiencing in-hospital death among patients presenting with initial stroke was notably higher among NHW males (AOR 1.59 [95% CI 1.46, 1.73]), NHW females (AOR 1.34 [95% CI 1.23, 1.45]), and Hispanic males (AOR 1.57 [95% CI 1.36, 1.81]) when compared to NHB females. Hispanic females were more likely to be discharged home when compared to NHB females after initial stroke event (AOR 1.32 [95% CI 1.23, 1.41]). NHB males (AOR 0.90 [95% CI 0.87, 0.94]) and NHW females (AOR 0.89 [95% CI 0.86, 0.92]) were less likely to be discharged to home. All groups with recurrent ischemic strokes experienced higher likelihood of in-hospital death when compared to NHB females with the highest likelihood among NHW males (AOR 2.13 [95% CI 1.87, 2.43]). Hispanic females had a higher likelihood of discharging home when compared to NHB females hospitalized for recurrent ischemic stroke, while NHB males and NHW females with recurrent ischemic stroke hospitalizations were less likely to discharge home. CONCLUSIONS: Sex-specific race and ethnic disparities remain for short-term outcomes in both initial and recurrent ischemic stroke hospitalizations. Further studies are needed to address disparities among recurrent ischemic stroke hospitalizations.

BACKGROUND: Antiviral chemoprophylaxis is recommended for use during influenza outbreaks in nursing homes to prevent transmission and severe disease among non-ill residents. Centers for Disease Control and Prevention (CDC) guidance recommends prophylaxis be initiated for all non-ill residents once an influenza outbreak is detected and be continued for at least 14 days and until seven days after the last laboratory-confirmed influenza case is identified. However, not all facilities strictly adhere to this guidance and the impact of such partial adherence is not fully understood. METHODS: We developed a stochastic compartmental framework to model influenza transmission within an average-sized U.S. nursing home. We compared the number of symptomatic illnesses and hospitalizations under varying prophylaxis implementation strategies, in addition to different levels of prophylaxis uptake and adherence by residents and healthcare personnel (HCP). RESULTS: Prophylaxis implemented according to current guidance reduced total symptomatic illnesses and hospitalizations among residents by an average of 12% and 36%, respectively, compared with no prophylaxis. We did not find evidence that alternative implementations of prophylaxis were more effective: compared to full adoption of current guidance, partial adoption resulted in increased symptomatic illnesses and/or hospitalizations, and longer or earlier adoption offered no additional improvements. In addition, increasing uptake and adherence among nursing home residents was effective in reducing resident illnesses and hospitalizations, but increasing HCP uptake had minimal indirect impacts for residents. CONCLUSIONS: The greatest benefits of influenza prophylaxis during nursing home outbreaks will likely be achieved through increasing uptake and adherence among residents and following current CDC guidance.

Current U.S. guidelines recommend integrase strand transfer inhibitor (INSTI)-based antiretroviral therapy (ART) as initial treatment for people with HIV (PWH). We assessed long-term effects of INSTI use on lipid profiles in routine HIV care. We analyzed medical record data from the HIV Outpatient Study's participants in care from 2007 to 2021. Hyperlipidemia was defined based on clinical diagnoses, treatments, and laboratory results. We calculated hyperlipidemia incidence rates and rate ratios (RRs) during initial ART and assessed predictors of incident hyperlipidemia by using Poisson regression. Among 349 eligible ART-naïve PWH, 168 were prescribed INSTI-based ART (36 raltegravir (RAL), 51 dolutegravir (DTG), and 81 INSTI-others (elvitegravir and bictegravir)) and 181 non-INSTI-based ART, including 68 protease inhibitor (PI)-based ART. During a median follow-up of 1.4 years, hyperlipidemia rates were 12.8, 22.3, 22.7, 17.4, and 12.6 per 100 person years for RAL-, DTG-, INSTI-others-, non-INSTI-PI-, and non-INSTI-non-PI-based ART, respectively. In multivariable analysis, compared with the RAL group, hyperlipidemia rates were higher in INSTI-others (RR = 2.25; 95% confidence interval (CI): 1.29-3.93) and non-INSTI-PI groups (RR = 1.89; CI: 1.12-3.19) but not statistically higher for the DTG (RR = 1.73; CI: 0.95-3.17) and non-INSTI-non-PI groups (RR = 1.55; CI: 0.92-2.62). Other factors independently associated with hyperlipidemia included older age, non-Hispanic White race/ethnicity, and ART without tenofovir disoproxil fumarate. PWH using RAL-based regimens had lower rates of incident hyperlipidemia than PWH receiving non-INSTI-PI-based ART but had similar rates as those receiving DTG-based ART, supporting federal recommendations for using DTG-based regimens as the initial therapy for ART-naïve PWH.

Our ability to forecast epidemics far into the future is constrained by the many complexities of disease systems. Realistic longer-term projections may, however, be possible under well-defined scenarios that specify the future state of critical epidemic drivers. Since December 2020, the U.S. COVID-19 Scenario Modeling Hub (SMH) has convened multiple modeling teams to make months ahead projections of SARS-CoV-2 burden, totaling nearly 1.8 million national and state-level projections. Here, we find SMH performance varied widely as a function of both scenario validity and model calibration. We show scenarios remained close to reality for 22 weeks on average before the arrival of unanticipated SARS-CoV-2 variants invalidated key assumptions. An ensemble of participating models that preserved variation between models (using the linear opinion pool method) was consistently more reliable than any single model in periods of valid scenario assumptions, while projection interval coverage was near target levels. SMH projections were used to guide pandemic response, illustrating the value of collaborative hubs for longer-term scenario projections.

BACKGROUND: The SARS-CoV-2 pandemic has underscored the need for field specimen collection and transport to diagnostic and public health laboratories. Self-collected nasal swabs transported without dependency on a cold chain have the potential to remove critical barriers to testing, expand testing capacity, and reduce opportunities for exposure of health professionals in the context of a pandemic. OBJECTIVE: We compared nasal swab collection by study participants from themselves and their children at home to collection by trained research staff. METHODS: Each adult participant collected 1 nasal swab, sampling both nares with the single swab, after which they collected 1 nasal swab from 1 child. After all the participant samples were collected for the household, the research staff member collected a separate single duplicate sample from each individual. Immediately after the sample collection, the adult participants completed a questionnaire about the acceptability of the sampling procedures. Swabs were placed in temperature-stable preservative and respiratory viruses were detected by shotgun RNA sequencing, enabling viral genome analysis. RESULTS: In total, 21 households participated in the study, each with 1 adult and 1 child, yielding 42 individuals with paired samples. Study participants reported that self-collection was acceptable. Agreement between identified respiratory viruses in both swabs by RNA sequencing demonstrated that adequate collection technique was achieved by brief instructions. CONCLUSIONS: Our results support the feasibility of a scalable and convenient means for the identification of respiratory viruses and implementation in pandemic preparedness for novel respiratory pathogens.

INTRODUCTION: Hypertension is a risk factor for cardiovascular disease, a leading cause of death among women of reproductive age (WRA, women aged 18-44 years). This study estimated hypertension prevalence and control among WRA at the national and state levels using electronic health record (EHR) data. METHODS: Non-pregnant WRA were included in this cross-sectional study using 2019 IQVIA™ Ambulatory Electronic Medical Records - US national data (analyzed in 2023). Suspected hypertension was identified using any of these criteria: ≥1 hypertension diagnosis code, ≥2 blood pressure (BP) readings ≥140/90 mmHg on separate days, or ≥1 antihypertensive medication. Among WRA with hypertension, the latest BP in 2019 was used to identify hypertension control (BP <140/90 mmHg). Estimates were age standardized and stratified by race or Hispanic ethnicity, region, and states with sufficient data. Tukey tests compared estimates by race or Hispanic ethnicity, region, and comorbidities. RESULTS: Among 2,125,084 WRA (62.1% White, 8.8% Black, and 29.1% other [including Hispanic, Asian, other, or unknown]) with a mean age of 31.7 years, hypertension prevalence was 14.5%. Of those with hypertension, 71.9% had controlled BP. Black WRA had a higher hypertension prevalence (22.3% vs. 14.4%, p<0.05) but lower control (60.6% vs. 73.9%, p<0.05) than White WRA. State-level hypertension prevalence ranged from 13.7% (Massachusetts) to 36% (Alabama), and control ranged from 82.9% (Kansas) to 59.2% (the District of Columbia). CONCLUSIONS: This study provides the first state-level estimates of hypertension control among WRA. EHR data complements traditional hypertension surveillance data and provides further information for efforts to prevent and manage hypertension among WRA.

OBJECTIVE: A 2015 survey of primary care providers (PCPs) found that while many believed that milliliter (mL)-only dosing was safest for oral liquid medications, few would use mL alone in dosing instructions. Since 2015, many recommendations have promoted "mL-only" dosing. In 2019, a follow-up survey was conducted to assess if PCP perceptions and practices have changed. METHODS: Pediatricians, family medicine physicians, nurse practitioners, and internists participating in the 2015 and 2019 DocStyles cross-sectional, web-based surveys were asked about their perceptions and practices regarding dosing units for oral liquid medications. RESULTS: In 2019, among 1392 respondents, the proportion of PCPs who reported they believed using mL-only is the safest dosing instruction ranged from 55.1% of internists to 80.8% of pediatricians. While fewer PCPs believed patients/caregivers prefer dosing instructions in mL-only (23.9% of nurse practitioners to 48.4% of pediatricians), more held this belief in 2019 compared to 2015; pediatricians had the greatest absolute increase (+14.4%) and family medicine physicians had the smallest increase (+1.3%). While 61.6% of pediatricians reported they would use mL-only dosing, only 36.0% of internists, 36.6% of nurse practitioners, and 42.5% of family medicine physicians reported they would do so. After controlling for age, gender, region, and specialty, 2019 PCP survey participants were more likely to report that they would use mL-only dosing compared to 2015 participants (adjusted odds ratio 1.51, 95% confidence interval 1.29-1.77). CONCLUSIONS: Broader educational efforts may be necessary to reach non-pediatricians, to encourage prescribing and communication with patients/caregivers using mL-only dosing.

PURPOSE: To examine rural and urban disparities in cardiovascular disease (CVD) death rates by poverty level and region. METHODS: Using 2021 county-level population and mortality data for CVD deaths listed as the underlying cause among adults aged 35-64 years, we calculated age-standardized CVD death rates and rate ratios (RR) for 4 categories of counties: high-poverty rural, high-poverty urban, low-poverty rural, and low-poverty urban (referent). Results are presented nationally and by US Census region. FINDINGS: Rural and urban disparities in CVD mortality varied markedly by poverty and region. Nationally, the CVD death rate was highest among high-poverty rural areas (191 deaths per 100,000, RR: 1.76, CI: 1.73-1.78). By region, Southern high-poverty rural areas had the highest CVD death rate (256 deaths per 100,000) and largest disparity relative to low-poverty urban areas (RR: 2.05; CI: 2.01-2.09). In the Midwest and West, CVD death rates among high-poverty areas were higher than low-poverty areas, regardless of rural or urban classification. CONCLUSIONS: Results reinforce the importance of prioritizing high-poverty rural areas, especially in the South, in efforts to reduce CVD mortality. These efforts may need to consider socioeconomic conditions and region, in addition to rural and urban disparities.

BACKGROUND: On Aug 29, 2021, Operation Allies Welcome (OAW) was established to support the resettlement of more than 80 000 Afghan evacuees in the USA. After identification of measles among evacuees, incoming evacuee flights were temporarily paused, and mass measles vaccination of evacuees aged 6 months or older was introduced domestically and overseas, with a 21-day quarantine period after vaccination. We aimed to evaluate patterns of measles virus transmission during this outbreak and the impact of control measures. METHODS: We conducted a measles outbreak investigation among Afghan evacuees who were resettled in the USA as part of OAW. Patients with measles were defined as individuals with an acute febrile rash illness between Aug 29, 2021, and Nov 26, 2021, and either laboratory confirmation of infection or epidemiological link to a patient with measles with laboratory confirmation. We analysed the demographics and clinical characteristics of patients with measles and used epidemiological information and whole-genome sequencing to track transmission pathways. A transmission model was used to evaluate the effects of vaccination and other interventions. FINDINGS: 47 people with measles (attack rate: 0·65 per 1000 evacuees) were reported in six US locations housing evacuees in four states. The median age of patients was 1 year (range 0-26); 33 (70%) were younger than 5 years. The age distribution shifted during the outbreak towards infants younger than 12 months. 20 (43%) patients with wild-type measles virus had rash onset after vaccination. No fatalities or community spread were identified, nor further importations after flight resumption. In a non-intervention scenario, transmission models estimated that a median of 5506 cases (IQR 10-5626) could have occurred. Infection clusters based on epidemiological criteria could be delineated into smaller clusters using phylogenetic analyses; however, sequences with few substitution count differences did not always indicate single lines of transmission. INTERPRETATION: Implementation of control measures limited measles transmission during OAW. Our findings highlight the importance of integration between epidemiological and genetic information in discerning between individual lines of transmission in an elimination setting. FUNDING: US Centers for Disease Control and Prevention.

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident hospitalizations, incident cases, incident deaths, and cumulative deaths due to COVID-19 at national, state, and county levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages.Competing Interest StatementAV, MC, and APP report grants from Metabiota Inc outside the submitted work. Funding StatementFor teams that reported receiving funding for their work, we report the sources and disclosures below: AIpert-pwllnod: Natural Sciences and Engineering Research Council of Canada; Caltech-CS156: Gary Clinard Innovation Fund; CEID-Walk: University of Georgia; CMU-TimeSeries: CDC Center of Excellence, gifts from Google and Facebook; COVIDhub: This work has been supported by the US Centers for Disease Control and Prevention (1U01IP001122) and the National Institutes of General Medical Sciences (R35GM119582). The content is solely the responsibility of the authors and does not necessarily represent the official views of CDC, NIGMS or the National Institutes of Health; Johannes Bracher was supported by the Helmholtz Foundation via the SIMCARD Information &amp; Data Science Pilot Project; Tilmann Gneiting gratefully acknowledges support by the Klaus Tschira Foundation; CU-select: NSF DMS-2027369 and a gift from the Morris-Singer Foundation; DDS-NBDS: NSF III-1812699; epiforecasts-ensemble1: Wellcome Trust (210758/Z/18/Z) FDANIHASU: supported by the Intramural Research Program of the NIH/NIDDK; GT_CHHS-COVID19: William W. George Endowment, Virginia C. and Joseph C. Mello Endowment, NSF DGE-1650044, NSF MRI 1828187, research cyberinfrastructure resources and services provided by the Partnership for an Advanced Computing Environment (PACE) at Georgia Tech, and the following benefactors at Georgia Tech: Andrea Laliberte, Joseph C. Mello, Richard Rick E. &amp; Charlene Zalesky, and Claudia &amp; Paul Raines, CDC MInD-Healthcare U01CK000531-Supplement; IHME: This work was supported by the Bill &amp; Melinda Gates Foundation, as well as funding from the state of Washington and the National Science Foundation (award no. FAIN: 2031096); Imperial-ensemble1: SB acknowledges funding from the Wellcome Trust (219415); Institute of Business Forecasting: IBF; IowaStateLW-STEM: NSF DMS-1916204, Iowa State University Plant Sciences Institute Scholars Program, NSF DMS-1934884, Laurence H. Baker Center for Bioinformatics and Biological Statistics; IUPUI CIS: NSF; JHU_CSSE-DECOM: JHU CSSE: National Science Foundation (NSF) RAPID Real-time Forecasting of COVID-19 risk in the USA. 2021-2022. Award ID: 2108526. National Science Foundation (NSF) RAPID Development of an interactive web-based dashboard to track COVID-19 in real-time. 2020. Award ID: 2028604; JHU_IDD-CovidSP: State of California, US Dept of Health and Human Services, US Dept of Homeland Security, Johns Hopkins Health System, Office of the Dean at Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University Modeling and Policy Hub, Centers for Disease Control and Prevention (5U01CK000538-03), University of Utah Immunology, Inflammation, &amp; Infectious Disease Initiative (26798 Seed Grant); JHU_UNC_GAS-StatMechP ol: NIH NIGMS: R01GM140564; JHUAPL-Bucky: US Dept of Health and Human Services; KITmetricslab-select_ensemble: Daniel Wolffram gratefully acknowledges support by the Klaus Tschira Foundation; LANL-GrowthRate: LANL LDRD 20200700ER; MIT-Cassandra: MIT Quest for Intelligence; MOBS-GLEAM_COVID: COVID Supplement CDC-HHS-6U01IP001137-01; CA NU38OT000297 from the Council of State and Territorial Epidemiologists (CSTE); NotreDame-FRED: NSF RAPID DEB 2027718; NotreDame-mobility: NSF RAPID DEB 2027718; PSI-DRAFT: NSF RAPID Grant # 2031536; QJHong-Encounter: NSF DMR-2001411 and DMR-1835939; SDSC_ISG-TrendModel: The development of the dashboard was partly funded by the Fondation Privee des Hopitaux Universitaires de Geneve; UA-EpiCovDA: NSF RAPID Grant # 2028401; UChicagoCHATTOPADHYAY-UnIT: Defense Advanced Research Projects Agency (DARPA) #HR00111890043/P00004 (I. Chattopadhyay, University of Chicago); UCSB-ACTS: NSF RAPID IIS 2029626; UCSD_NEU-DeepGLEAM: Google Faculty Award, W31P4Q-21-C-0014; UMass-MechBayes: NIGMS #R35GM119582, NSF #1749854, NIGMS #R35GM119582; UMich-RidgeTfReg: This project is funded by the University of Michigan Physics Department and the University of Michigan Office of Research; UVA-Ensemble: National Institutes of Health (NIH) Grant 1R01GM109718, NSF BIG DATA Grant IIS-1633028, NSF Grant No.: OAC-1916805, NSF Expeditions in Computing Grant CCF-1918656, CCF-1917819, NSF RAPID CNS-2028004, NSF RAPID OAC-2027541, US Centers for Disease Control and Prevention 75D30119C05935, a grant from Google, University of Virginia Strategic Investment Fund award number SIF160, Defense Threat Reduction Agency (DTRA) under Contract No. HDTRA1-19-D-0007, and Virginia Dept of Health Grant VDH-21-501-0141; Wadnwani_AI-BayesOpt: This study is made possible by the generous support of the American People through the United States Agency for International Development (USAID). The work described in this article was implemented under the TRACETB Project, managed by WIAI under the terms of Cooperative Agreement Number 72038620CA00006. The contents of this manuscript are the sole responsibility of the authors and do not necessarily reflect the views of USAID or the United States Government; WalmartLabsML-LogForecasting: Team acknowledges Walmart to support this study Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesI confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll data produced are available online at https://github.com/reichlab/covid19-forecast-hub https://github.com/reichlab/covid19-forecast-hub

Background SARS-CoV-2 outbreaks in nursing homes can be large with high case fatality. Identifying asymptomatic individuals early through serial testing is recommended to control COVID-19 in nursing homes, both in response to an outbreak (“outbreak testing” of residents and healthcare personnel) and in facilities without outbreaks (“non-outbreak testing” of healthcare personnel). The effectiveness of outbreak testing and isolation with or without non-outbreak testing was evaluated.Methods Using published SARS-CoV-2 transmission parameters, the fraction of SARS-CoV-2 transmissions prevented through serial testing (weekly, every three days, or daily) and isolation of asymptomatic persons compared to symptom-based testing and isolation was evaluated through mathematical modeling using a Reed-Frost model to estimate the percentage of cases prevented (i.e., “effectiveness”) through either outbreak testing alone or outbreak plus non-outbreak testing. The potential effect of simultaneous decreases (by 10%) in the effectiveness of isolating infected individuals when instituting testing strategies was also evaluated.Results Modeling suggests that outbreak testing could prevent 54% (weekly testing with 48-hour test turnaround) to 92% (daily testing with immediate results and 50% relative sensitivity) of SARS-CoV-2 infections. Adding non-outbreak testing could prevent up to an additional 8% of SARS-CoV-2 infections (depending on test frequency and turnaround time). However, added benefits of non-outbreak testing were mostly negated if accompanied by decreases in infection control practice.Conclusions When combined with high-quality infection control practices, outbreak testing could be an effective approach to preventing COVID-19 in nursing homes, particularly if optimized through increased test frequency and use of tests with rapid turnaround.Summary Mathematical modeling evaluated the effectiveness of serially testing asymptomatic persons in a nursing home in response to a SARS-CoV-2 outbreak with or without serial testing of asymptomatic staff in the absence of known SARS-CoV-2 infections.Competing Interest StatementThe authors have declared no competing interest.Funding StatementNo external funding was received. All work was conducted as part of government duties.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:This activity was reviewed by CDC and was conducted consistent with applicable federal law and CDC policy (see e.g., 45 C.F.R. part 46, 21 C.F.R. part 56; 42 U.S.C. 241(d); 5 U.S.C 552a; 44 U.S.C. 351 et seq.).All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesData provided in supplemental materials or publicly available through links in the manuscript. https://github.com/cdcepi/Nursing-home-SARS-CoV-2-testing-model/

We updated a published mathematical model of SARS-CoV-2 transmission with laboratory-derived source and wearer protection efficacy estimates for a variety of face masks to estimate their impact on COVID-19 incidence and related mortality in the United States. When used at already-observed population rates of 80% for those ≥65 years and 60% for those &lt;65 years, face masks are associated with 69% (cloth) to 78% (medical procedure mask) reductions in cumulative COVID-19 infections and 82% (cloth) to 87% (medical procedure mask) reductions in related deaths over a 6-month timeline in the model, assuming a basic reproductive number of 2.5. If cloth or medical procedure masks’ source control and wearer protection efficacies are boosted about 30% each to 84% and 60% by cloth over medical procedure masking, fitters, or braces, the COVID-19 basic reproductive number of 2.5 could be reduced to an effective reproductive number ≤ 1.0, and from 6.0 to 2.3 for a variant of concern similar to delta (B.1.617.2).Article Summary Line Adapting a published SARS-CoV-2 transmission model together with updated, laboratory-derived source control and wearer protection efficacy estimates for a variety of face coverings as well as N95 respirators, we demonstrate that community masking as currently practiced has likely reduced cases and deaths and that this benefit can be increased with wider adoption of better performing masks.Competing Interest StatementThe authors have declared no competing interest.Clinical TrialThis is an epidemiological modeling study, not a clinical trialFunding StatementNo external funding was received.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:No IRB was needed as this is an epidemiological modeling study.All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll data/parameters used in the models are reported in the manuscript. Code is available upon request.

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. In 2020, the COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized hundreds of thousands of specific predictions from more than 50 different academic, industry, and independent research groups. This manuscript systematically evaluates 23 models that regularly submitted forecasts of reported weekly incident COVID-19 mortality counts in the US at the state and national level. One of these models was a multi-model ensemble that combined all available forecasts each week. The performance of individual models showed high variability across time, geospatial units, and forecast horizons. Half of the models evaluated showed better accuracy than a naïve baseline model. In combining the forecasts from all teams, the ensemble showed the best overall probabilistic accuracy of any model. Forecast accuracy degraded as models made predictions farther into the future, with probabilistic accuracy at a 20-week horizon more than 5 times worse than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.Competing Interest StatementAV, MC, and APP report grants from Metabiota Inc outside the submitted work.Funding StatementFor teams that reported receiving funding for their work, we report the sources and disclosures below. CMU-TimeSeries: CDC Center of Excellence, gifts from Google and Facebook. CU-select: NSF DMS-2027369 and a gift from the Morris-Singer Foundation. COVIDhub: This work has been supported by the US Centers for Disease Control and Prevention (1U01IP001122) and the National Institutes of General Medical Sciences (R35GM119582). The content is solely the responsibility of the authors and does not necessarily represent the official views of CDC, NIGMS or the National Institutes of Health. Johannes Bracher was supported by the Helmholtz Foundation via the SIMCARD Information&amp; Data Science Pilot Project. Tilmann Gneiting gratefully acknowledges support by the Klaus Tschira Foundation. DDS-NBDS: NSF III-1812699. EPIFORECASTS-ENSEMBLE1: Wellcome Trust (210758/Z/18/Z) GT_CHHS-COVID19: William W. George Endowment, Virginia C. and Joseph C. Mello Endowments, NSF DGE-1650044, NSF MRI 1828187, research cyberinfrastructure resources and services provided by the Partnership for an Advanced Computing Environment (PACE) at Georgia Tech, and the following benefactors at Georgia Tech: Andrea Laliberte, Joseph C. Mello, Richard Rick E. &amp; Charlene Zalesky, and Claudia &amp; Paul Raines GT-DeepCOVID: CDC MInD-Healthcare U01CK000531-Supplement. NSF (Expeditions CCF-1918770, CAREER IIS-2028586, RAPID IIS-2027862, Medium IIS-1955883, NRT DGE-1545362), CDC MInD program, ORNL and funds/computing resources from Georgia Tech and GTRI. IHME: This work was supported by the Bill &amp; Melinda Gates Foundation, as well as funding from the state of Washington and the National Science Foundation (award no. FAIN: 2031096). IowaStateLW-STEM: Iowa State University Plant Sciences Institute Scholars Program, NSF DMS-1916204, NSF CCF-1934884, Laurence H. Baker Center for Bioinformatics and Biological Statistics. JHU_IDD-CovidSP: State of California, US Dept of Health and Human Services, US Dept of Homeland Security, US Office of Foreign Disaster Assistance, Johns Hopkins Health System, Office of the Dean at Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University Modeling and Policy Hub, Centers fo Disease Control and Prevention (5U01CK000538-03), University of Utah Immunology, Inflammation, &amp; Infectious Disease Initiative (26798 Seed Grant). LANL-GrowthRate: LANL LDRD 20200700ER. MOBS-GLEAM_COVID: COVID Supplement CDC-HHS-6U01IP001137-01. NotreDame-mobility and NotreDame-FRED: NSF RAPID DEB 2027718 UA-EpiCovDA: NSF RAPID Grant # 2028401. UCSB-ACTS: NSF RAPID IIS 2029626. UCSD-NEU: Google Faculty Award, DARPA W31P4Q-21-C-0014, COVID Supplement CDC-HHS-6U01IP001137-01. UMass-MechBayes: NIGMS R35GM119582, NSF 1749854. UMich-RidgeTfReg: The University of Michigan Physics Department and the University of Michigan Office of Research.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:UMass-Amherst IRBAll necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll data and code referred to in the manuscript are publicly available. https://github.com/reichlab/covid19-forecast-hub/ https://github.com/reichlab/covidEnsembles https://zoltardata.com/project/44

Balancing the control of SARS-CoV-2 transmission with the resumption of travel is a global priority. Current recommendations include mitigation measures before, during, and after travel. Pre- and post-travel strategies including symptom monitoring, testing, and quarantine can be combined in multiple ways considering different trade-offs in feasibility, adherence, effectiveness, cost and adverse consequences. Here we use a mathematical model to analyze the expected effectiveness of symptom monitoring, testing, and quarantine under different estimates of the infectious period, test-positivity relative to time of infection, and test sensitivity to reduce the risk of transmission from infected travelers during and after travel. If infection occurs 0-7 days prior to travel, immediate isolation following symptom onset prior to or during travel reduces risk of transmission while traveling by 26-30%. Pre-departure testing can further reduce risk if testing is close to the time of departure. For example, testing on the day of departure can reduce risk while traveling by 37-61%. For transmission risk after travel with infection time up to 7 days prior to arrival at the destination, isolation based on symptom monitoring reduced introduction risk at the destination by 42-56%. A 14-day quarantine after arrival, without symptom monitoring or testing, can reduce risk by 97-100% on its own. However, a shorter quarantine of 7 days combined with symptom monitoring and a test on day 3-4 after arrival is also effective (95-99%) at reducing introduction risk and is less burdensome, which may improve adherence. To reduce the risk of introduction without quarantine, optimal test timing after arrival is close to the time of arrival; with effective quarantine after arrival, testing a few days later optimizes sensitivity to detect those infected immediately before or while traveling. These measures can complement recommendations such as social distancing, using masks, and hand hygiene, to further reduce risk during and after travel.Competing Interest StatementThe authors have declared no competing interest.Funding StatementNo external funding supported this research.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:Centers for Disease Control and PreventionAll necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesOnly publicly available data informed this research.

Pockets of susceptibility resulting from spatial or social heterogeneity in vaccine coverage can drive measles outbreaks, as cases imported into such pockets are likely to cause further transmission and lead to large transmission clusters. Characterising the dynamics of transmission is essential for identifying which individuals and regions might be most at risk.As data from detailed contact tracing investigations are not available in many settings, we developed a R package called o2geosocial to reconstruct the transmission clusters and the importation status of the cases from their age, location, genotype, and onset date.We compared our inferred cluster size distributions to 737 transmission clusters identified through detailed contact-tracing in the United States between 2001 and 2016. We were able to reconstruct the importation status of the cases and found good agreement between the inferred and reference clusters. The results were improved when the contact-tracing investigations were used to set the importation status before running the model.Spatial heterogeneity in vaccine coverage is difficult to measure directly. Our approach was able to highlight areas with potential for local transmission using a minimal number of variables and could be applied to assess the intensity of ongoing transmission in a region.Competing Interest StatementThe authors have declared no competing interest.Funding StatementAR was supported by the Medical Research Council (MR/N013638/1). SF was supported by a Wellcome Trust Senior Research Fellowship in Basic Biomedical Science (210758/Z/18/Z). AJK was supported by a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (206250/Z/17/Z).Author DeclarationsAll relevant ethical guidelines have been followed; any necessary IRB and/or ethics committee approvals have been obtained and details of the IRB/oversight body are included in the manuscript.YesAll necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesThe package we developed is publicly available on Github (https://github.com/alxsrobert/o2geosocial), along with the code used to analyse the data and generate the figures (https://github.com/alxsrobert/datapaperMO). Combinations of variables in the surveillance data used to validate this algorithm may contain sensitive personally identifiable health information which are subject to the Privacy Act and cannot be shared publicly. A toy dataset was attached to the o2geosocial package (in o2geosocial/data). The script analysis_generated_data.R in the datapaperMO repository generates toy datasets with different parameters (distance kernel, number of cases, reproduction numbers..) and can be used to re-run the model and test its performance. https://github.com/alxsrobert/o2geosocial https://github.com/alxsrobert/datapaperMO