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BackgroundThe COVID-19 global pandemic has disrupted structures and communities across the globe. Numerous regions of the world have had varying responses in their attempts to contain the spread of the virus. Factors such as public health policies, governance, and sociopolitical climate have led to differential levels of success at controlling the spread of SARS-CoV-2. Ultimately, a more advanced surveillance metric for COVID-19 transmission is necessary to help government systems and national leaders understand which responses have been effective and gauge where outbreaks occur. ObjectiveThe goal of this study is to provide advanced COVID-19 surveillance metrics for Canada at the country, province, and territory level that account for shifts in the pandemic including speed, acceleration, jerk, and persistence. Enhanced surveillance identifies risks for explosive growth and regions that have controlled outbreaks successfully. MethodsUsing a longitudinal trend analysis study design, we extracted 62 days of COVID-19 data from Canadian public health registries for 13 provinces and territories. We used an empirical difference equation to measure the daily number of cases in Canada as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. ResultsWe compare the week of February 7-13, 2021, with the week of February 14-20, 2021. Canada, as a whole, had a decrease in speed from 8.4 daily new cases per 100,000 population to 7.5 daily new cases per 100,000 population. The persistence of new cases during the week of February 14-20 reported 7.5 cases that are a result of COVID-19 transmissions 7 days earlier. The two most populous provinces of Ontario and Quebec both experienced decreases in speed from 7.9 and 11.5 daily new cases per 100,000 population for the week of February 7-13 to speeds of 6.9 and 9.3 for the week of February 14-20, respectively. Nunavut experienced a significant increase in speed during this time, from 3.3 daily new cases per 100,000 population to 10.9 daily new cases per 100,000 population. ConclusionsCanada excelled at COVID-19 control early on in the pandemic, especially during the first COVID-19 shutdown. The second wave at the end of 2020 resulted in a resurgence of the outbreak, which has since been controlled. Enhanced surveillance identifies outbreaks and where there is the potential for explosive growth, which informs proactive health policy.

BackgroundThe COVID-19 pandemic has placed unprecedented stress on economies, food systems, and health care resources in Latin America and the Caribbean (LAC). Existing surveillance provides a proxy of the COVID-19 caseload and mortalities; however, these measures make it difficult to identify the dynamics of the pandemic and places where outbreaks are likely to occur. Moreover, existing surveillance techniques have failed to measure the dynamics of the pandemic. ObjectiveThis study aimed to provide additional surveillance metrics for COVID-19 transmission to track changes in the speed, acceleration, jerk, and persistence in the transmission of the pandemic more accurately than existing metrics. MethodsThrough a longitudinal trend analysis, we extracted COVID-19 data over 45 days from public health registries. We used an empirical difference equation to monitor the daily number of cases in the LAC as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano–Bond estimator in R. COVID-19 transmission rates were tracked for the LAC between September 30 and October 6, 2020, and between October 7 and 13, 2020. ResultsThe LAC saw a reduction in the speed, acceleration, and jerk for the week of October 13, 2020, compared to the week of October 6, 2020, accompanied by reductions in new cases and the 7-day moving average. For the week of October 6, 2020, Belize reported the highest acceleration and jerk, at 1.7 and 1.8, respectively, which is particularly concerning, given its high mortality rate. The Bahamas also had a high acceleration at 1.5. In total, 11 countries had a positive acceleration during the week of October 6, 2020, whereas only 6 countries had a positive acceleration for the week of October 13, 2020. The TAC displayed an overall positive trend, with a speed of 10.40, acceleration of 0.27, and jerk of –0.31, all of which decreased in the subsequent week to 9.04, –0.81, and –0.03, respectively. ConclusionsMetrics such as new cases, cumulative cases, deaths, and 7-day moving averages provide a static view of the pandemic but fail to identify where and the speed at which SARS-CoV-2 infects new individuals, the rate of acceleration or deceleration of the pandemic, and weekly comparison of the rate of acceleration of the pandemic indicate impending explosive growth or control of the pandemic. Enhanced surveillance will inform policymakers and leaders in the LAC about COVID-19 outbreaks.

BackgroundThe COVID-19 pandemic has severely impacted Europe, resulting in a high caseload and deaths that varied by country. The second wave of the COVID-19 pandemic has breached the borders of Europe. Public health surveillance is necessary to inform policy and guide leaders. ObjectiveThis study aimed to provide advanced surveillance metrics for COVID-19 transmission that account for weekly shifts in the pandemic, speed, acceleration, jerk, and persistence, to better understand countries at risk for explosive growth and those that are managing the pandemic effectively. MethodsWe performed a longitudinal trend analysis and extracted 62 days of COVID-19 data from public health registries. We used an empirical difference equation to measure the daily number of cases in Europe as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. ResultsNew COVID-19 cases slightly decreased from 158,741 (week 1, January 4-10, 2021) to 152,064 (week 2, January 11-17, 2021), and cumulative cases increased from 22,507,271 (week 1) to 23,890,761 (week 2), with a weekly increase of 1,383,490 between January 10 and January 17. France, Germany, Italy, Spain, and the United Kingdom had the largest 7-day moving averages for new cases during week 1. During week 2, the 7-day moving average for France and Spain increased. From week 1 to week 2, the speed decreased (37.72 to 33.02 per 100,000), acceleration decreased (0.39 to –0.16 per 100,000), and jerk increased (–1.30 to 1.37 per 100,000). ConclusionsThe United Kingdom, Spain, and Portugal, in particular, are at risk for a rapid expansion in COVID-19 transmission. An examination of the European region suggests that there was a decrease in the COVID-19 caseload between January 4 and January 17, 2021. Unfortunately, the rates of jerk, which were negative for Europe at the beginning of the month, reversed course and became positive, despite decreases in speed and acceleration. Finally, the 7-day persistence rate was higher during week 2 than during week 1. These measures indicate that the second wave of the pandemic may be subsiding, but some countries remain at risk for new outbreaks and increased transmission in the absence of rapid policy responses.

BackgroundSARS-CoV-2, the virus that caused the global COVID-19 pandemic, has severely impacted Central Asia; in spring 2020, high numbers of cases and deaths were reported in this region. The second wave of the COVID-19 pandemic is currently breaching the borders of Central Asia. Public health surveillance is necessary to inform policy and guide leaders; however, existing surveillance explains past transmissions while obscuring shifts in the pandemic, increases in infection rates, and the persistence of the transmission of COVID-19. ObjectiveThe goal of this study is to provide enhanced surveillance metrics for SARS-CoV-2 transmission that account for weekly shifts in the pandemic, including speed, acceleration, jerk, and persistence, to better understand the risk of explosive growth in each country and which countries are managing the pandemic successfully. MethodsUsing a longitudinal trend analysis study design, we extracted 60 days of COVID-19–related data from public health registries. We used an empirical difference equation to measure the daily number of cases in the Central Asia region as a function of the prior number of cases, level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. ResultsCOVID-19 transmission rates were tracked for the weeks of September 30 to October 6 and October 7-13, 2020, in Central Asia. The region averaged 11,730 new cases per day for the first week and 14,514 for the second week. Infection rates increased across the region from 4.74 per 100,000 persons to 5.66. Russia and Turkey had the highest 7-day moving averages in the region, with 9836 and 1469, respectively, for the week of October 6 and 12,501 and 1603, respectively, for the week of October 13. Russia has the fourth highest speed in the region and continues to have positive acceleration, driving the negative trend for the entire region as the largest country by population. Armenia is experiencing explosive growth of COVID-19; its infection rate of 13.73 for the week of October 6 quickly jumped to 25.19, the highest in the region, the following week. The region overall is experiencing increases in its 7-day moving average of new cases, infection, rate, and speed, with continued positive acceleration and no sign of a reversal in sight. ConclusionsThe rapidly evolving COVID-19 pandemic requires novel dynamic surveillance metrics in addition to static metrics to effectively analyze the pandemic trajectory and control spread. Policy makers need to know the magnitude of transmission rates, how quickly they are accelerating, and how previous cases are impacting current caseload due to a lag effect. These metrics applied to Central Asia suggest that the region is trending negatively, primarily due to minimal restrictions in Russia.

BackgroundThe COVID-19 pandemic has had a profound global impact on governments, health care systems, economies, and populations around the world. Within the East Asia and Pacific region, some countries have mitigated the spread of the novel coronavirus effectively and largely avoided severe negative consequences, while others still struggle with containment. As the second wave reaches East Asia and the Pacific, it becomes more evident that additional SARS-CoV-2 surveillance is needed to track recent shifts, rates of increase, and persistence associated with the pandemic. ObjectiveThe goal of this study is to provide advanced surveillance metrics for COVID-19 transmission that account for speed, acceleration, jerk, persistence, and weekly shifts, to better understand country risk for explosive growth and those countries who are managing the pandemic successfully. Existing surveillance coupled with our dynamic metrics of transmission will inform health policy to control the COVID-19 pandemic until an effective vaccine is developed. We provide novel indicators to measure disease transmission. MethodsUsing a longitudinal trend analysis study design, we extracted 330 days of COVID-19 data from public health registries. We used an empirical difference equation to measure the daily number of cases in East Asia and the Pacific as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. ResultsThe standard surveillance metrics for Indonesia, the Philippines, and Myanmar were concerning as they had the largest new caseloads at 4301, 2588, and 1387, respectively. When looking at the acceleration of new COVID-19 infections, we found that French Polynesia, Malaysia, and the Philippines had rates at 3.17, 0.22, and 0.06 per 100,000. These three countries also ranked highest in terms of jerk at 15.45, 0.10, and 0.04, respectively. ConclusionsTwo of the most populous countries in East Asia and the Pacific, Indonesia and the Philippines, have alarming surveillance metrics. These two countries rank highest in new infections in the region. The highest rates of speed, acceleration, and positive upwards jerk belong to French Polynesia, Malaysia, and the Philippines, and may result in explosive growth. While all countries in East Asia and the Pacific need to be cautious about reopening their countries since outbreaks are likely to occur in the second wave of COVID-19, the country of greatest concern is the Philippines. Based on standard and enhanced surveillance, the Philippines has not gained control of the COVID-19 epidemic, which is particularly troubling because the country ranks 4th in population in the region. Without extreme and rigid social distancing, quarantines, hygiene, and masking to reverse trends, the Philippines will remain on the global top 5 list of worst COVID-19 outbreaks resulting in high morbidity and mortality. The second wave will only exacerbate existing conditions and increase COVID-19 transmissions.

BackgroundThe COVID-19 pandemic has disrupted the lives of millions and forced countries to devise public health policies to reduce the pace of transmission. In the Middle East and North Africa (MENA), falling oil prices, disparities in wealth and public health infrastructure, and large refugee populations have significantly increased the disease burden of COVID-19. In light of these exacerbating factors, public health surveillance is particularly necessary to help leaders understand and implement effective disease control policies to reduce SARS-CoV-2 persistence and transmission. ObjectiveThe goal of this study is to provide advanced surveillance metrics, in combination with traditional surveillance, for COVID-19 transmission that account for weekly shifts in the pandemic speed, acceleration, jerk, and persistence to better understand a country’s risk for explosive growth and to better inform those who are managing the pandemic. Existing surveillance coupled with our dynamic metrics of transmission will inform health policy to control the COVID-19 pandemic until an effective vaccine is developed. MethodsUsing a longitudinal trend analysis study design, we extracted 30 days of COVID-19 data from public health registries. We used an empirical difference equation to measure the daily number of cases in MENA as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel data model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. ResultsThe regression Wald statistic was significant (χ25=859.5, P

BackgroundThe emergence of SARS-CoV-2, the virus that causes COVID-19, has led to a global pandemic. The United States has been severely affected, accounting for the most COVID-19 cases and deaths worldwide. Without a coordinated national public health plan informed by surveillance with actionable metrics, the United States has been ineffective at preventing and mitigating the escalating COVID-19 pandemic. Existing surveillance has incomplete ascertainment and is limited by the use of standard surveillance metrics. Although many COVID-19 data sources track infection rates, informing prevention requires capturing the relevant dynamics of the pandemic. ObjectiveThe aim of this study is to develop dynamic metrics for public health surveillance that can inform worldwide COVID-19 prevention efforts. Advanced surveillance techniques are essential to inform public health decision making and to identify where and when corrective action is required to prevent outbreaks. MethodsUsing a longitudinal trend analysis study design, we extracted COVID-19 data from global public health registries. We used an empirical difference equation to measure daily case numbers for our use case in 50 US states and the District of Colombia as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. ResultsExamination of the United States and state data demonstrated that most US states are experiencing outbreaks as measured by these new metrics of speed, acceleration, jerk, and persistence. Larger US states have high COVID-19 caseloads as a function of population size, density, and deficits in adherence to public health guidelines early in the epidemic, and other states have alarming rates of speed, acceleration, jerk, and 7-day persistence in novel infections. North and South Dakota have had the highest rates of COVID-19 transmission combined with positive acceleration, jerk, and 7-day persistence. Wisconsin and Illinois also have alarming indicators and already lead the nation in daily new COVID-19 infections. As the United States enters its third wave of COVID-19, all 50 states and the District of Colombia have positive rates of speed between 7.58 (Hawaii) and 175.01 (North Dakota), and persistence, ranging from 4.44 (Vermont) to 195.35 (North Dakota) new infections per 100,000 people. ConclusionsStandard surveillance techniques such as daily and cumulative infections and deaths are helpful but only provide a static view of what has already occurred in the pandemic and are less helpful in prevention. Public health policy that is informed by dynamic surveillance can shift the country from reacting to COVID-19 transmissions to being proactive and taking corrective action when indicators of speed, acceleration, jerk, and persistence remain positive week over week. Implicit within our dynamic surveillance is an early warning system that indicates when there is problematic growth in COVID-19 transmissions as well as signals when growth will become explosive without action. A public health approach that focuses on prevention can prevent major outbreaks in addition to endorsing effective public health policies. Moreover, subnational analyses on the dynamics of the pandemic allow us to zero in on where transmissions are increasing, meaning corrective action can be applied with precision in problematic areas. Dynamic public health surveillance can inform specific geographies where quarantines are necessary while preserving the economy in other US areas.

BackgroundCache Valley virus (CVV) is a mosquito-borne virus that is a rare cause of disease in humans. In the fall of 2020, a patient developed encephalitis 6 weeks following kidney transplantation and receipt of multiple blood transfusions.MethodsAfter ruling out more common etiologies, metagenomic next-generation sequencing (mNGS) of cerebrospinal fluid (CSF) was performed. We reviewed the medical histories of the index kidney recipient, organ donor, and recipients of other organs from the same donor and conducted a blood traceback investigation to evaluate blood transfusion as a possible source of infection in the kidney recipient. We tested patient specimens using reverse-transcription polymerase chain reaction (RT-PCR), the plaque reduction neutralization test, cell culture, and whole-genome sequencing.ResultsCVV was detected in CSF from the index patient by mNGS, and this result was confirmed by RT-PCR, viral culture, and additional whole-genome sequencing. The organ donor and other organ recipients had no evidence of infection with CVV by molecular or serologic testing. Neutralizing antibodies against CVV were detected in serum from a donor of red blood cells received by the index patient immediately prior to transplant. CVV neutralizing antibodies were also detected in serum from a patient who received the co-component plasma from the same blood donation.ConclusionsOur investigation demonstrates probable CVV transmission through blood transfusion. Clinicians should consider arboviral infections in unexplained meningoencephalitis after blood transfusion or organ transplantation. The use of mNGS might facilitate detection of rare, unexpected infections, particularly in immunocompromised patients.

IntroductionMost studies of solid organ transplant (SOT) recipients with COVID-19 focus on outcomes within one month of illness onset. Delayed mortality in SOT recipients hospitalized for COVID-19 has not been fully examined.MethodsWe used data from a multicenter registry to calculate mortality by 90 days following initial SARS-CoV-2 detection in SOT recipients hospitalized for COVID-19 and developed multivariable Cox proportional-hazards models to compare risk factors for death by days 28 and 90.ResultsVital status at day 90 was available for 936 of 1117 (84%) SOT recipients hospitalized for COVID-19: 190 of 936 (20%) died by 28 days and an additional 56 of 246 deaths (23%) occurred between days 29 and 90. Factors associated with mortality by day 90 included: age > 65 years [aHR 1.8 (1.3-2.4), p =20% of deaths occurred between 28 and 90 days following SARS-CoV-2 diagnosis. Future investigations should consider extending follow-up duration to 90 days for more complete mortality assessment.

Mortality among patients hospitalized for COVID-19 has declined over the course of the pandemic. Mortality trends specifically in solid organ transplant recipients (SOTR) are unknown. Using data from a multicenter registry of SOTR hospitalized for COVID-19, we compared 28-day mortality between early 2020 (March 1, 2020-June 19, 2020) and late 2020 (June 20, 2020-December 31, 2020). Multivariable logistic regression was used to assess comorbidity-adjusted mortality. Time period of diagnosis was available for 1435/1616 (88.8%) SOTR and 971/1435 (67.7%) were hospitalized: 571/753 (75.8%) in early 2020 and 402/682 (58.9%) in late 2020 (p

BackgroundThe coronavirus disease 2019 (COVID-19) pandemic has led to significant reductions in transplantation, motivated in part by concerns of disproportionately more severe disease among solid organ transplant (SOT) recipients. However, clinical features, outcomes, and predictors of mortality in SOT recipients are not well described.MethodsWe performed a multicenter cohort study of SOT recipients with laboratory-confirmed COVID-19. Data were collected using standardized intake and 28-day follow-up electronic case report forms. Multivariable logistic regression was used to identify risk factors for the primary endpoint, 28-day mortality, among hospitalized patients.ResultsFour hundred eighty-two SOT recipients from >50 transplant centers were included: 318 (66%) kidney or kidney/pancreas, 73 (15.1%) liver, 57 (11.8%) heart, and 30 (6.2%) lung. Median age was 58 (interquartile range [IQR] 46-57), median time post-transplant was 5 years (IQR 2-10), 61% were male, and 92% had ≥1 underlying comorbidity. Among those hospitalized (376 [78%]), 117 (31%) required mechanical ventilation, and 77 (20.5%) died by 28 days after diagnosis. Specific underlying comorbidities (age >65 [adjusted odds ratio [aOR] 3.0, 95% confidence interval [CI] 1.7-5.5, P

Lung transplant recipients (LTR) with coronavirus disease 2019 (COVID-19) may have higher mortality than non-lung solid organ transplant recipients (SOTR), but direct comparisons are limited. Risk factors for mortality specifically in LTR have not been explored. We performed a multicenter cohort study of adult SOTR with COVID-19 to compare mortality by 28 days between hospitalized LTR and non-lung SOTR. Multivariable logistic regression models were used to assess comorbidity-adjusted mortality among LTR vs. non-lung SOTR and to determine risk factors for death in LTR. Of 1,616 SOTR with COVID-19, 1,081 (66%) were hospitalized including 120/159 (75%) LTR and 961/1457 (66%) non-lung SOTR (p = .02). Mortality was higher among LTR compared to non-lung SOTR (24% vs. 16%, respectively, p = .032), and lung transplant was independently associated with death after adjusting for age and comorbidities (aOR 1.7, 95% CI 1.0-2.6, p = .04). Among LTR, chronic lung allograft dysfunction (aOR 3.3, 95% CI 1.0-11.3, p = .05) was the only independent risk factor for mortality and age >65 years, heart failure and obesity were not independently associated with death. Among SOTR hospitalized for COVID-19, LTR had higher mortality than non-lung SOTR. In LTR, chronic allograft dysfunction was independently associated with mortality.

BackgroundInfluenza causes substantial morbidity and mortality despite available treatments. Anecdotal reports suggest that plasma with high antibody titres to influenza might be of benefit in the treatment of severe influenza.MethodsIn this randomised, open-label, multicentre, phase 2 trial, 29 academic medical centres in the USA assessed the safety and efficacy of anti-influenza plasma with haemagglutination inhibition antibody titres of 1:80 or more to the infecting strain. Hospitalised children and adults (including pregnant women) with severe influenza A or B (defined as the presence of hypoxia or tachypnoea) were randomly assigned to receive either two units (or paediatric equivalent) of anti-influenza plasma plus standard care, versus standard care alone, and were followed up for 28 days. The primary endpoint was time to normalisation of patients' respiratory status (respiratory rate of ≤20 breaths per min for adults or age-defined thresholds of 20-38 breaths per min for children) and a room air oxygen saturation of 93% or more. This study is registered with ClinicalTrials.gov, number NCT01052480.FindingsBetween Jan 13, 2011, and March 2, 2015, 113 participants were screened for eligibility and 98 were randomly assigned from 20 out of 29 participating sites. Of the participants with confirmed influenza (by PCR), 28 (67%) of 42 in the plasma plus standard care group normalised their respiratory status by day 28 compared with 24 (53%) of 45 participants on standard care alone (p=0·069). The hazard ratio (HR) comparing plasma plus standard care with standard care alone was 1·71 (95% CI 0·96-3·06). Six participants died, one (2%) from the plasma plus standard care group and five (10%) from the standard care group (HR 0·19 [95% CI 0·02-1·65], p=0·093). Participants in the plasma plus standard care group had non-significant reductions in days in hospital (median 6 days [IQR 4-16] vs 11 days [5-25], p=0·13) and days on mechanical ventilation (median 0 days [IQR 0-6] vs 3 days [0-14], p=0·14). Fewer plasma plus standard care participants had serious adverse events compared with standard care alone recipients (nine [20%] of 46 vs 20 [38%] of 52, p=0·041), the most frequent of which were acute respiratory distress syndrome (one [2%] vs two [4%] patients) and stroke (one [2%] vs two [4%] patients).InterpretationAlthough there was no significant effect of plasma treatment on the primary endpoint, the treatment seemed safe and well tolerated. A phase 3 randomised trial is now underway to further assess this intervention.FundingNational Institute of Allergy and Infectious Diseases, US National Institutes of Health.

Background The adjuvanted RSV prefusion F protein–based vaccine (RSVPreF3 OA) was efficacious against RSV-related lower respiratory tract disease (RSV-LRTD) in ≥60-years-olds over 1 RSV season. We evaluated efficacy and safety of 1 RSVPreF3 OA dose and of 2 RSVPreF3 OA doses given 1 year apart against RSV-LRTD over 2 RSV seasons post–dose 1. Methods In this phase 3, blinded trial, ≥60-year-olds were randomized (1:1) to receive RSVPreF3 OA or placebo pre–season 1. RSVPreF3 OA recipients were re-randomized (1:1) to receive a second RSVPreF3 OA dose (RSV_revaccination group) or placebo (RSV_1dose group) pre–season 2; participants who received placebo pre–season 1 received placebo pre–season 2 (placebo group). Efficacy of both vaccine regimens against RSV-LRTD was evaluated over 2 seasons combined (confirmatory secondary objective, success criterion: lower limits of 2-sided CIs around efficacy estimates >20%). Results The efficacy analysis comprised 24 967 participants (RSV_1dose: 6227; RSV_revaccination: 6242; placebo: 12 498). Median efficacy follow-up was 17.8 months. Efficacy over 2 seasons of 1 RSVPreF3 OA dose was 67.2% (97.5% CI: 48.2–80.0%) against RSV-LRTD and 78.8% (95% CI: 52.6–92.0%) against severe RSV-LRTD. Efficacy over 2 seasons of a first dose followed by revaccination was 67.1% (97.5% CI: 48.1–80.0%) against RSV-LRTD and 78.8% (95% CI: 52.5–92.0%) against severe RSV-LRTD. Reactogenicity/safety of the revaccination dose were similar to dose 1. Conclusions One RSVPreF3 OA dose was efficacious against RSV-LRTD over 2 RSV seasons in ≥60-year-olds. Revaccination 1 year post–dose 1 was well tolerated but did not seem to provide additional efficacy benefit in the overall study population. Clinical Trials Registration ClinicalTrials.gov: NCT04886596. [ABSTRACT FROM AUTHOR]

There are limited real‐world data on the effectiveness of tixagevimab‐cilgavimab as pre‐exposure prophylaxis of COVID‐19. We describe lessons learned when coordinating data collection and identifying breakthrough SARS‐CoV‐2 infections among patients across indications and institutions in a major US city. The Chicago Department of Public Health requested patient‐level tixagevimab‐cilgavimab administration data from all prescribing providers in Chicago, for treatments December 8, 2021 through June 30, 2022. Records were matched to COVID‐19 vaccinations and laboratory‐confirmed SARS‐CoV‐2 infections through December 31, 2022. Due to difficulty collecting data from all providers, targeted follow‐up was conducted to improve completeness on key variables (demographics, vaccination status, clinical indication for prophylaxis). Over half of reported tixagevimab‐cilgavimab administrations were to patients residing outside Chicago. Five hundred forty‐four Chicago residents who received at least one dose of tixagevimab‐cilgavimab were included in this analysis. Most were age 50 years or older (72%), Black non‐Latinx (33%) or White non‐Latinx (29%), and fully vaccinated (80%). Seventy‐five patients (14%) had laboratory‐confirmed COVID‐19. Patients with and without breakthrough infections were demographically similar. Clinical indication was missing for >95% of cases, improved to 64% after follow‐up; the most frequently specified was hematologic malignancy (10%). Severe outcomes were uncommon: 16% had documented COVID‐19‐related hospitalizations, one death was identified. Tixagevimab‐cilgavimab recipients in Chicago had a lower rate of severe SARS‐CoV‐2 infection than reported among other untreated high‐risk patients, including during predominance of non‐neutralizing variants. Improving stakeholder collaboration is essential for generation of real‐world effectiveness data, informing pandemic preparedness and optimizing use of medical countermeasures. [ABSTRACT FROM AUTHOR]

Background Older adults with chronic cardiorespiratory or endocrine/metabolic conditions are at increased risk of respiratory syncytial virus (RSV)-related acute respiratory illness (RSV-ARI) and severe respiratory disease. In an ongoing, randomized, placebo-controlled, multicountry, phase 3 trial in ≥60-year-old participants, an AS01E-adjuvanted RSV prefusion F protein-based vaccine (RSVPreF3 OA) was efficacious against RSV-related lower respiratory tract disease (RSV-LRTD), severe RSV-LRTD, and RSV-ARI. We evaluated efficacy and immunogenicity among participants with coexisting cardiorespiratory or endocrine/metabolic conditions that increase the risk of severe RSV disease ("conditions of interest"). Methods Medically stable ≥60-year-old participants received 1 dose of RSVPreF3 OA or placebo. Efficacy against first RSV-LRTD and RSV-ARI episodes was assessed in subgroups with/without coexisting cardiorespiratory or endocrine/metabolic conditions of interest. Immunogenicity was analyzed post hoc in these subgroups. Results In total, 12 467 participants received RSVPreF3 OA and 12 499 received placebo. Of these, 39.6% (RSVPreF3 OA) and 38.9% (placebo) had ≥1 coexisting condition of interest. The median efficacy follow-up was 6.7 months. Efficacy against RSV-LRTD was high in participants with ≥1 condition of interest (94.6%), ≥1 cardiorespiratory (92.1%), ≥1 endocrine/metabolic (100%), and ≥2 conditions of interest (92.0%). Efficacy against RSV-ARI was 81.0% in participants with ≥1 condition of interest (88.1% for cardiorespiratory, 79.4% for endocrine/metabolic conditions) and 88.0% in participants with ≥2 conditions of interest. Postvaccination neutralizing titers were at least as high in participants with ≥1 condition of interest as in those without. Conclusions RSVPreF3 OA was efficacious against RSV-LRTD and RSV-ARI in older adults with coexisting medical conditions associated with an increased risk of severe RSV disease. Clinical Trials Registration ClinicalTrials.gov: NCT04886596. [ABSTRACT FROM AUTHOR]