Impact of dosing schedules on performance of rotavirus vaccines in Ghana.

Background: Available live-oral rotavirus vaccines are associated with low to moderate performance in low- and middle-income settings. There is limited evidence relating to how the vaccine dosing schedule might be adjusted to improve vaccine performance in these settings. Methods: We used mathematical models fitted to rotavirus surveillance data for children <5 years of age from three different hospitals in Ghana (Korle-Bu Teaching Hospital in Accra, Komfo Anokye Teaching Hospital in Kumasi and War Memorial Hospital in Navrongo) to project the impact of rotavirus vaccination over a 10-year period (April 2012-March 2022). We quantified and compared the impact of the previous vaccination program in Ghana to the model-predicted impact for other vaccine dosing schedules across the three hospitals and the entire country, under different assumptions about vaccine protection. To project the rotavirus vaccine impact over Ghana, we sampled from the range of model parameters for Accra and Navrongo, assuming that these two settings represent the "extremes" of rotavirus epidemiology within Ghana. Results: For the previously implemented 6/10-week monovalent Rotarix vaccine (RV1) schedule, the model-estimated average annual incidence of moderate-to-severe rotavirus-associated gastroenteritis (RVGE) ranged between 1,151 and 3,002 per 100,000 people per year over the 10-year period for the three sites. Compared to no vaccination, the model-estimated median percentage reductions in RVGE ranged from 28-85% and 12-71% among children <1 year and <5 years of age respectively, with the highest and lowest percentage reductions predicted using model parameters estimated for Accra and Navrongo, respectively. The median predicted reductions in RVGE for the whole country ranged from 57-66% and 35-45% among children <1 year and <5 years of age, respectively. The 1/6/10- and 6/10/14-week schedules provided the best and comparable reductions in RVGE compared to the original 6/10-week schedule, whereas there was no improvement in impact for the 10/14-week schedule. Conclusions: We found that administering an additional dose of RV1 might be an effective strategy to improve rotavirus vaccine impact, particularly in settings with low vaccine effectiveness. The results could be extrapolated to other countries using a 2-dose vaccine schedule with low to moderate vaccine performance.

Variability in the Timing of Respiratory Syncytial Virus Epidemics in Guatemala, 2008-2018.

BACKGROUND: The description of local seasonality patterns in respiratory syncytial virus (RSV) incidence is important to guide the timing of administration of RSV immunization products. METHODS: We characterized RSV seasonality in Guatemala using the moving epidemic method (MEM) with absolute counts of RSV-associated acute respiratory infections (ARI) from hospital surveillance in Santa Rosa and Quetzaltenango departments of Guatemala. RESULTS: From Week 17 of 2008 through Week 16 of 2018, 8487 ARI cases tested positive for RSV by rRT-PCR. Season onsets varied up to 5 months; early seasons starting in late May to early August and finishing in September to November were most common, but late seasons starting in October to November and finishing in March to April were also observed. Both epidemic patterns had similar durations ranging from 4 to 6 months. Epidemic thresholds (the levels of virus activity that signal the onset and end of a seasonal epidemic) calculated prospectively using previous seasons' data captured between 70% and 99% of annual RSV detections. Onset weeks differed by 2-10 weeks, and offset weeks differed by 2-16 weeks between the two surveillance sites. CONCLUSIONS: Variability in the timing of seasonal RSV epidemics in Guatemala demonstrates the difficulty in precisely predicting the timing of seasonal RSV epidemics based on onset weeks from past seasons and suggests that maximal reduction in RSV disease burden would be achieved through year-round vaccination and immunoprophylaxis administration to at-risk infants.

Comprehensive profiling of social mixing patterns in resource poor countries: A mixed methods research protocol.

BACKGROUND: Low-and-middle-income countries (LMICs) bear a disproportionate burden of communicable diseases. Social interaction data inform infectious disease models and disease prevention strategies. The variations in demographics and contact patterns across ages, cultures, and locations significantly impact infectious disease dynamics and pathogen transmission. LMICs lack sufficient social interaction data for infectious disease modeling. METHODS: To address this gap, we will collect qualitative and quantitative data from eight study sites (encompassing both rural and urban settings) across Guatemala, India, Pakistan, and Mozambique. We will conduct focus group discussions and cognitive interviews to assess the feasibility and acceptability of our data collection tools at each site. Thematic and rapid analyses will help to identify key themes and categories through coding, guiding the design of quantitative data collection tools (enrollment survey, contact diaries, exit survey, and wearable proximity sensors) and the implementation of study procedures. We will create three age-specific contact matrices (physical, nonphysical, and both) at each study site using data from standardized contact diaries to characterize the patterns of social mixing. Regression analysis will be conducted to identify key drivers of contacts. We will comprehensively profile the frequency, duration, and intensity of infants' interactions with household members using high resolution data from the proximity sensors and calculating infants' proximity score (fraction of time spent by each household member in proximity with the infant, over the total infant contact time) for each household member. DISCUSSION: Our qualitative data yielded insights into the perceptions and acceptability of contact diaries and wearable proximity sensors for collecting social mixing data in LMICs. The quantitative data will allow a more accurate representation of human interactions that lead to the transmission of pathogens through close contact in LMICs. Our findings will provide more appropriate social mixing data for parameterizing mathematical models of LMIC populations. Our study tools could be adapted for other studies.

Estimating the health effects of COVID-19-related immunisation disruptions in 112 countries during 2020-30: a modelling study.

BACKGROUND: There have been declines in global immunisation coverage due to the COVID-19 pandemic. Recovery has begun but is geographically variable. This disruption has led to under-immunised cohorts and interrupted progress in reducing vaccine-preventable disease burden. There have, so far, been few studies of the effects of coverage disruption on vaccine effects. We aimed to quantify the effects of vaccine-coverage disruption on routine and campaign immunisation services, identify cohorts and regions that could particularly benefit from catch-up activities, and establish if losses in effect could be recovered. METHODS: For this modelling study, we used modelling groups from the Vaccine Impact Modelling Consortium from 112 low-income and middle-income countries to estimate vaccine effect for 14 pathogens. One set of modelling estimates used vaccine-coverage data from 1937 to 2021 for a subset of vaccine-preventable, outbreak-prone or priority diseases (ie, measles, rubella, hepatitis B, human papillomavirus [HPV], meningitis A, and yellow fever) to examine mitigation measures, hereafter referred to as recovery runs. The second set of estimates were conducted with vaccine-coverage data from 1937 to 2020, used to calculate effect ratios (ie, the burden averted per dose) for all 14 included vaccines and diseases, hereafter referred to as full runs. Both runs were modelled from Jan 1, 2000, to Dec 31, 2100. Countries were included if they were in the Gavi, the Vaccine Alliance portfolio; had notable burden; or had notable strategic vaccination activities. These countries represented the majority of global vaccine-preventable disease burden. Vaccine coverage was informed by historical estimates from WHO-UNICEF Estimates of National Immunization Coverage and the immunisation repository of WHO for data up to and including 2021. From 2022 onwards, we estimated coverage on the basis of guidance about campaign frequency, non-linear assumptions about the recovery of routine immunisation to pre-disruption magnitude, and 2030 endpoints informed by the WHO Immunization Agenda 2030 aims and expert consultation. We examined three main scenarios: no disruption, baseline recovery, and baseline recovery and catch-up. FINDINGS: We estimated that disruption to measles, rubella, HPV, hepatitis B, meningitis A, and yellow fever vaccination could lead to 49 119 additional deaths (95% credible interval [CrI] 17 248-134 941) during calendar years 2020-30, largely due to measles. For years of vaccination 2020-30 for all 14 pathogens, disruption could lead to a 2·66% (95% CrI 2·52-2·81) reduction in long-term effect from 37 378 194 deaths averted (34 450 249-40 241 202) to 36 410 559 deaths averted (33 515 397-39 241 799). We estimated that catch-up activities could avert 78·9% (40·4-151·4) of excess deaths between calendar years 2023 and 2030 (ie, 18 900 [7037-60 223] of 25 356 [9859-75 073]). INTERPRETATION: Our results highlight the importance of the timing of catch-up activities, considering estimated burden to improve vaccine coverage in affected cohorts. We estimated that mitigation measures for measles and yellow fever were particularly effective at reducing excess burden in the short term. Additionally, the high long-term effect of HPV vaccine as an important cervical-cancer prevention tool warrants continued immunisation efforts after disruption. FUNDING: The Vaccine Impact Modelling Consortium, funded by Gavi, the Vaccine Alliance and the Bill & Melinda Gates Foundation. TRANSLATIONS: For the Arabic, Chinese, French, Portguese and Spanish translations of the abstract see Supplementary Materials section.

Disparities in Unmet Health Care Needs Among US Children During the COVID-19 Pandemic.

PURPOSE: The COVID-19 pandemic disrupted pediatric health care in the United States, and this disruption layered on existing barriers to health care. We sought to characterize disparities in unmet pediatric health care needs during this period. METHODS: We analyzed data from Wave 1 (October through November 2020) and Wave 2 (March through May 2021) of the COVID Experiences Survey, a national longitudinal survey delivered online or via telephone to parents of children aged 5 through 12 years using a probability-based sample representative of the US household population. We examined 3 indicators of unmet pediatric health care needs as outcomes: forgone care and forgone well-child visits during fall 2020 through spring 2021, and no well-child visit in the past year as of spring 2021. Multivariate models examined relationships of child-, parent-, household-, and county-level characteristics with these indicators, adjusting for child's age, sex, and race/ethnicity. RESULTS: On the basis of parent report, 16.3% of children aged 5 through 12 years had forgone care, 10.9% had forgone well-child visits, and 30.1% had no well-child visit in the past year. Adjusted analyses identified disparities in indicators of pediatric health care access by characteristics at the level of the child (eg, race/ethnicity, existing health conditions, mode of school instruction), parent (eg, childcare challenges), household (eg, income), and county (eg, urban-rural classification, availability of primary care physicians). Both child and parent experiences of racism were also associated with specific indicators of unmet health care needs. CONCLUSIONS: Our findings highlight the need for continued research examining unmet health care needs and for continued efforts to optimize the clinical experience to be culturally inclusive.

Comparative effectiveness of alternative intervals between first and second doses of the mRNA COVID-19 vaccines.

The optimal interval between the first and second doses of COVID-19 mRNA vaccines has not been thoroughly evaluated. Employing a target trial emulation approach, we compared the effectiveness of different interdose intervals among >6 million mRNA vaccine recipients in Georgia, USA, from December 2020 to March 2022. We compared three protocols defined by interdose interval: recommended by the Food and Drug Administration (FDA) (17-25 days for Pfizer-BioNTech; 24-32 days for Moderna), late-but-allowable (26-42 days for Pfizer-BioNTech; 33-49 days for Moderna), and late ( ≥ 43 days for Pfizer-BioNTech; ≥50 days for Moderna). In the short-term, the risk of SARS-CoV-2 infection was lowest under the FDA-recommended protocol. Longer-term, the late-but-allowable protocol resulted in the lowest risk (risk ratio on Day 120 after the first dose administration compared to the FDA-recommended protocol: 0.83 [95% confidence interval: 0.82-0.84]). Here, we showed that delaying the second dose by 1-2 weeks may provide stronger long-term protection.

Prevalence of COVID-19 Mitigation Behaviors in US Adults (August-December 2020): Nationwide Household Probability Survey.

BACKGROUND: COVID-19 mitigation behaviors, such as wearing masks, maintaining social distancing, and practicing hand hygiene, have been and will remain vital to slowing the pandemic. OBJECTIVE: This study aims to describe the period prevalence of consistent mask-wearing, social distancing, and hand hygiene practices during the peak of COVID-19 incidence (August-December 2020) and just before COVID-19 vaccine availability, overall and in demographic subgroups. METHODS: We used baseline survey data from a nationwide household probability sample to generate weighted estimates of mitigation behaviors: wearing masks, maintaining social distancing, and practicing hand hygiene. Weighted logistic regression explored differences in mitigation behaviors by demographics. Latent class analysis (LCA) identified patterns in mitigation behaviors. RESULTS: Among 4654 participants, most (n=2727, 58.6%) were female, were non-Hispanic White (n=3063, 65.8%), were aged 55 years or older (n=2099, 45.1%), lived in the South (n=2275, 48.9%), lived in metropolitan areas (n=4186, 89.9%), had at least a bachelor's degree (n=2547, 54.7%), had an income of US $50,000-$99,000 (n=1445, 31%), and were privately insured (n=2734, 58.7%). The period prevalence of consistent mask wearing was 71.1% (sample-weighted 95% CI 68.8-73.3); consistent social distancing, 42.9% (95% CI 40.5-45.3); frequent handwashing, 55.0% (95% CI 52.3-57.7); and frequent hand sanitizing, 21.5% (95% CI 19.4-23.8). Mitigation behaviors were more prevalent among women, older persons, Black or Hispanic persons, those who were not college graduates, and service-oriented workers. LCA identified an optimal-mitigation class that consistently practiced all behaviors (n=2656, 67% of US adults), a low-mitigation class that inconsistently practiced all behaviors (n=771, 20.6%), and a class that had optimal masking and social distancing but a high frequency of hand hygiene (n=463, 12.4%). CONCLUSIONS: Despite a high prevalence of COVID-19 mitigation behaviors, there were likely millions who did not consistently practice these behaviors during the time of the highest COVID-19 incidence. In future infectious disease outbreak responses, public health authorities should also consider addressing disparities in mitigation practices through more targeted prevention messaging.

Comprehensive profiling of social mixing patterns in resource poor countries: a mixed methods research protocol.

Background: Low-and-middle-income countries (LMICs) bear a disproportionate burden of communicable diseases. Social interaction data inform infectious disease models and disease prevention strategies. The variations in demographics and contact patterns across ages, cultures, and locations significantly impact infectious disease dynamics and pathogen transmission. LMICs lack sufficient social interaction data for infectious disease modeling. Methods: To address this gap, we will collect qualitative and quantitative data from eight study sites (encompassing both rural and urban settings) across Guatemala, India, Pakistan, and Mozambique. We will conduct focus group discussions and cognitive interviews to assess the feasibility and acceptability of our data collection tools at each site. Thematic and rapid analyses will help to identify key themes and categories through coding, guiding the design of quantitative data collection tools (enrollment survey, contact diaries, exit survey, and wearable proximity sensors) and the implementation of study procedures.We will create three age-specific contact matrices (physical, nonphysical, and both) at each study site using data from standardized contact diaries to characterize the patterns of social mixing. Regression analysis will be conducted to identify key drivers of contacts. We will comprehensively profile the frequency, duration, and intensity of infants' interactions with household members using high resolution data from the proximity sensors and calculating infants' proximity score (fraction of time spent by each household member in proximity with the infant, over the total infant contact time) for each household member. Discussion: Our qualitative data yielded insights into the perceptions and acceptability of contact diaries and wearable proximity sensors for collecting social mixing data in LMICs. The quantitative data will allow a more accurate representation of human interactions that lead to the transmission of pathogens through close contact in LMICs. Our findings will provide more appropriate social mixing data for parameterizing mathematical models of LMIC populations. Our study tools could be adapted for other studies.

Differences in Rotavirus Shedding and Duration by Infant Oral Rotavirus Vaccination Status in Dhaka, Bangladesh 2011 - 2014.

To evaluate how breakthrough rotavirus disease contributes to transmission, we examined the impact of rotavirus vaccination on fecal shedding and duration of illness. We used multivariable linear regression to analyze rotavirus quantity by RT-qPCR and duration among 184 episodes of rotavirus diarrhea positive by ELISA in the PROVIDE study. Vaccinated children had less fecal viral shedding compared to unvaccinated children (mean difference = -0.59 log copies per gram of stool, 95% CI: -0.99, -0.19). Duration of illness was on average 0.47 days (95% CI: -0.23, 1.17) shorter among vaccinated children. Rotarix vaccination reduces shedding burden among breakthrough cases of RVGE.

We estimated the effect of rotavirus vaccination on duration and quantity of rotavirus shed during rotavirus gastroenteritis in Bangladesh. Virus quantity was lower in symptomatic vaccinated children compared to symptomatic unvaccinated children, but differences in episode duration were small.

Social contact patterns among employees in U.S. long-term care facilities during the COVID-19 pandemic, December 2020 to June 2021.

OBJECTIVE: We measured contact patterns using social contact diaries for 157 U.S. long-term care facility employees from December 2020 - June 2021. These data are crucial for analyzing mathematical transmission models and for informing healthcare setting infection control policy. RESULTS: The median number of daily contacts was 10 (IQR 8-11). Household contacts were more likely partially masked than fully masked, more likely to involve physical contact, and longer in duration compared to facility contacts.

Rotavirus genotypes in the post-vaccine era: A systematic review and meta-analysis of global, regional, and temporal trends in settings with and without rotavirus vaccine introduction.

BACKGROUND: Even moderate differences in rotavirus vaccine effectiveness against non-vaccine genotypes may exert selective pressures on circulating rotaviruses. Whether this vaccine effect or natural temporal fluctuations underlie observed changes in genotype distributions is unclear. METHODS: We systematically reviewed studies reporting rotavirus genotypes from children <5 years of age globally between 2005 and 2023. We compared rotavirus genotypes between vaccine-introducing and non-introducing settings globally and by World Health Organization (WHO) region, calendar time, and time since vaccine introduction. RESULTS: Crude pooling of genotype data from 361 studies indicated higher G2P[4], a non-vaccine genotype, prevalence in vaccine-introducing settings, both globally and by WHO region. This difference did not emerge when examining genotypes over time in the Americas, the only region with robust longitudinal data. Relative to non-introducing settings, G2P[4] detections were more likely in settings with recent introduction (e.g. 1-2 years post-introduction aOR: 4.39 (95% CI: 2.87-6.72)) but were similarly likely in settings with more time elapsed since introduction, (e.g. 7 or more years aOR (1.62 95% CI: 0.49-5.37)). CONCLUSIONS: When accounting for both regional and temporal trends, there was no substantial evidence of long-term vaccine-related selective pressures on circulating genotypes. Increased prevalence of G2P[4] may be transient after rotavirus vaccine introduction.

Modelling the Interplay between Responsive Individual Vaccination Decisions and the Spread of SARS-CoV-2.

The uptake of COVID-19 vaccines remains low despite their high effectiveness. Epidemic models that represent decision-making psychology can provide insight into the potential impact of vaccine promotion interventions in the context of the COVID-19 pandemic. We coupled a network-based mathematical model of SARS-CoV-2 transmission in Georgia, USA with a social-psychological vaccination decision-making model in which vaccine side effects, post-vaccination infections, and other unidentified community-level factors could "nudge" individuals towards vaccine resistance while hospitalization spikes could nudge them towards willingness. Combining an increased probability of hospitalization-prompted resistant-to-willing switches with a decreased probability of willing-to-resistant switches prompted by unidentified community-level factors increased vaccine uptake and decreased SARS-CoV-2 incidence by as much as 30.7% and 24.0%, respectively. The latter probability had a greater impact than the former. This illustrates the disease prevention potential of vaccine promotion interventions that address community-level factors influencing decision-making and anticipate the case curve instead of reacting to it.

Effect of Norovirus Inoculum Dose on Virus Kinetics, Shedding, and Symptoms.

The effect of norovirus dose on outcomes such as virus shedding and symptoms after initial infection is not well understood. We performed a secondary analysis of a human challenge study by using Bayesian mixed-effects models. As the dose increased from 4.8 to 4,800 reverse transcription PCR units, the total amount of shed virus in feces increased from 4.5 × 1011 to 3.4 × 1012 genomic equivalent copies; in vomit, virus increased from 6.4 × 105 to 3.0 × 107 genomic equivalent copies. Onset time of viral shedding in feces decreased from 1.4 to 0.8 days, and time of peak viral shedding decreased from 2.3 to 1.5 days. Time to symptom onset decreased from 1.5 to 0.8 days. One type of symptom score increased. An increase in norovirus dose was associated with more rapid shedding and symptom onset and possibly increased severity. However, the effect on virus load and shedding was inconclusive.

Measuring indirect transmission-reducing effects in tuberculosis vaccine efficacy trials: why and how?

Tuberculosis is the leading bacterial cause of death globally. In 2021, 10·6 million people developed symptomatic tuberculosis and 1·6 million died. Seven promising vaccine candidates that aim to prevent tuberculosis disease in adolescents and adults are currently in late-stage clinical trials. Conventional phase 3 trials provide information on the direct protection conferred against infection or disease in vaccinated individuals, but they tell us little about possible indirect (ie, transmission-reducing) effects that afford protection to unvaccinated individuals. As a result, proposed phase 3 trial designs will not provide key information about the overall effect of introducing a vaccine programme. Information on the potential for indirect effects can be crucial for policy makers deciding whether and how to introduce tuberculosis vaccines into immunisation programmes. We describe the rationale for measuring indirect effects, in addition to direct effects, of tuberculosis vaccine candidates in pivotal trials and lay out several options for incorporating their measurement into phase 3 trial designs.

Use of COVIDTests.gov At-Home Test Kits Among Adults in a National Household Probability Sample - United States, 2022.

At-home rapid antigen COVID-19 tests were first authorized by the Food and Drug Administration in late 2020 (1-3). In January 2022, the White House launched COVIDTests.gov, which made all U.S. households eligible to receive free-to-the-user at-home test kits distributed by the U.S. Postal Service (2). By May 2022, more than 70 million test kit packages had been shipped to households across the United States (2); however, how these kits were used, and which groups were using them, has not been reported. Data from a national probability survey of U.S. households (COVIDVu), collected during April-May 2022, were used to evaluate awareness about and use of these test kits (4). Most respondent households (93.8%) were aware of the program, and more than one half (59.9%) had ordered kits. Among persons who received testing for COVID-19 during the preceding 6 months, 38.3% used a COVIDTests.gov kit. Among kit users, 95.5% rated the experience as acceptable, and 23.6% reported being unlikely to have tested without the COVIDTests.gov program. Use of COVIDTests.gov kits was similar among racial and ethnic groups (42.1% non-Hispanic Black or African American [Black]; 41.5% Hispanic or Latino [Hispanic]; 34.8% non-Hispanic White [White]; and 53.7% non-Hispanic other races [other races]). Use of other home COVID-19 tests differed by race and ethnicity (11.8% Black, 44.4% Hispanic, 45.8% White, 43.8% other races). Compared with White persons, Black persons were 72% less likely to use other home test kits (adjusted relative risk [aRR] = 0.28; 95% CI = 0.16-0.50). Provision of tests through this well-publicized program likely improved use of COVID-19 home testing and health equity in the United States, particularly among Black persons. National programs to address availability and accessibility of critical health services in a pandemic response have substantial health value.

Factors driving norovirus transmission in long-term care facilities: A case-level analysis of 107 outbreaks.

Norovirus is the most common cause of gastroenteritis outbreaks in long-term care facilities (LTCFs) in the United States, causing a high burden of disease in both residents and staff. Understanding how case symptoms and characteristics contribute to norovirus transmission can lead to more informed outbreak control measures in LTCFs. We examined line lists for 107 norovirus outbreaks that took place in LTCFs in five U.S. states from 2015 to 2019. We estimated the individual effective reproduction number, Ri, to quantify individual case infectiousness and examined the contribution of vomiting, diarrhea, and being a resident (vs. staff) to case infectiousness. The associations between case characteristics and Ri were estimated using a multivariable, log-linear mixed model with inverse variance weighting. We found that cases with vomiting infected 1.28 (95 % CI: 1.11, 1.48) times the number of secondary cases compared to cases without vomiting, and LTCF residents infected 1.31 (95 % CI: 1.15, 1.50) times the number of secondary cases compared to staff. There was no difference in infectiousness between cases with and without diarrhea (1.07; 95 % CI: 0.90, 1.29). This suggests that vomiting, particularly by LTCF residents, was a primary driver of norovirus transmission. These results support control measures that limit exposure to vomitus during norovirus outbreaks in LTCFs.

Population-Level Relative Effectiveness of the COVID-19 Vaccines and the Contribution of Naturally Acquired Immunity.

BACKGROUND: Immune protection against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can be induced by natural infection or vaccination or both. Interaction between vaccine-induced immunity and naturally acquired immunity at the population level has been understudied. METHODS: We used regression models to evaluate whether the impact of coronavirus disease 2019 (COVID-19) vaccines differed across states with different levels of naturally acquired immunity from March 2021 to April 2022 in the United States. Analysis was conducted for 3 evaluation periods separately (Alpha, Delta, and Omicron waves). As a proxy for the proportion of the population with naturally acquired immunity, we used either the reported seroprevalence or the estimated proportion of the population ever infected in each state. RESULTS: COVID-19 mortality decreased as coverage of ≥1 dose increased among people ≥65 years of age, and this effect did not vary by seroprevalence or proportion of the total population ever infected. Seroprevalence and proportion ever infected were not associated with COVID-19 mortality, after controlling for vaccine coverage. These findings were consistent in all evaluation periods. CONCLUSIONS: COVID-19 vaccination was associated with a sustained reduction in mortality at state level during the Alpha, Delta, and Omicron periods. The effect did not vary by naturally acquired immunity.

Monovalent Rotavirus Vaccine Efficacy Against Different Rotavirus Genotypes: A Pooled Analysis of Phase II and III Trial Data.

BACKGROUND: Rotavirus vaccine performance appears worse in countries with high rotavirus genotype diversity. Evidence suggests diminished vaccine efficacy (VE) against G2P[4], which is heterotypic with existing monovalent rotavirus vaccine formulations. Most studies assessing genotype-specific VE have been underpowered and inconclusive. METHODS: We pooled individual-level data from 10 Phase II and III clinical trials of rotavirus vaccine containing G1 and P[8] antigens (RV1) conducted between 2000 and 2012. We estimated VE against both any-severity and severe (Vesikari score ≥11) rotavirus gastroenteritis (RVGE) using binomial and multinomial logistic regression models for non-specific VE against any RVGE, genotype-specific VE, and RV1-typic VE against genotypes homotypic, partially heterotypic, or fully heterotypic with RV1 antigens. We adjusted models for concomitant oral poliovirus and RV1 vaccination and the country's designated child mortality stratum. RESULTS: Analysis included 87 644 infants from 22 countries in the Americas, Europe, Africa, and Asia. For VE against severe RVGE, non-specific VE was 91% (95% confidence interval [CI]: 87-94%). Genotype-specific VE ranged from 96% (95% CI: 89-98%) against G1P[8] to 71% (43-85%) against G2P[4]. RV1-typic VE was 92% (95% CI: 84-96%) against partially heterotypic genotypes but 83% (67-91%) against fully heterotypic genotypes. For VE against any-severity RVGE, non-specific VE was 82% (95% CI: 75-87%). Genotype-specific VE ranged from 94% (95% CI: 86-97%) against G1P[8] to 63% (41-77%) against G2P[4]. RV1-typic VE was 83% (95% CI: 72-90%) against partially heterotypic genotypes but 63% (40-77%) against fully heterotypic genotypes. CONCLUSIONS: RV1 VE is comparatively diminished against fully heterotypic genotypes including G2P[4].

Association of Guideline Complexity With Individuals' Ability to Determine Eligibility for COVID-19 Vaccination.

This cross-sectional study examines the association between the complexity of consumer guidelines for COVID-19 vaccination and identification of eligibility.