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Most pneumococcal disease occurs among infants and older adults and is thought to be driven by the transmission of Streptococcus pneumoniae from young children to these vulnerable age groups. However, pneumococcal disease outbreaks also affect non-elderly adults living or working in congregate, close-contact settings. Little is known about pneumococcal carriage in such populations. From July to November 2020, we collected saliva from low-income adult farmworkers in Monterey County, California, and tested for pneumococcal carriage following culture enrichment via quantitative PCR assays targeting the pneumococcal lytA and piaB genes. Participants were considered to carry pneumococci if lytA and piaB cycle threshold values were both below 40. Among 1,283 participants enrolled in our study, 117 (9.1%) carried pneumococci. Carriers tended more often than non-carriers to be exposed to children aged 2-4 and >4 persons per bedroom vs ≤2 persons per bedroom]. Household overcrowding remained associated with increased risk of carriage among participants not exposed to children aged 2 vs ≤2 persons per bedroom]. Exposure to children aged

ImportanceA SARS-CoV-2 vaccine was approved for adolescents aged 12 to 15 years on May 10, 2021, with approval for younger age groups following thereafter. The population level impact of the pediatric COVID-19 vaccination program has not yet been established.ObjectiveTo identify whether California's pediatric COVID-19 immunization program was associated with changes in pediatric COVID-19 incidence and hospitalizations.Design, setting, and participantsA case series on COVID-19 vaccination including children aged 6 months to 15 years was conducted in California. Data were obtained on COVID-19 cases in California between April 1, 2020, and February 27, 2023.ExposurePostvaccination evaluation periods spanned 141 days (June 10 to October 29, 2021) for adolescents aged 12 to 15 years, 199 days (November 29, 2021, to June 17, 2022) for children aged 5 to 11 years, and 225 days (July 17, 2022, to February 27, 2023) for those aged 6 to 59 months. During these periods, statewide vaccine coverage reached 53.5% among adolescents aged 12 to 15 years, 34.8% among children aged 5 to 11 years, and 7.9% among those aged 6 to 59 months.Main outcomes and measuresAge-stepped implementation of COVID-19 vaccination was used to compare observed county-level incidence and hospitalization rates during periods when each age group became vaccine eligible to counterfactual rates predicted from observations among other age groups. COVID-19 case and hospitalization data were obtained from the California reportable disease surveillance system.ResultsBetween April 1, 2020, and February 27, 2023, a total of 3 913 063 pediatric COVID-19 cases and 12 740 hospitalizations were reported in California. Reductions of 146 210 cases (95% prediction interval [PI], 136 056-158 948) were estimated among adolescents aged 12 to 15 years, corresponding to a 37.1% (35.5%-39.1%) reduction from counterfactual predictions. Reductions of 230 134 (200 170-265 149) cases were estimated among children aged 5 to 11 years, corresponding to a 23.7% (20.6%-27.3%) reduction from counterfactual predictions. No evidence of reductions in COVID-19 cases statewide were found among children aged 6 to 59 months (estimated averted cases, -259; 95% PI, -1938 to 1019), although low transmission during the evaluation period may have limited the ability to do so. An estimated 168 hospitalizations (95% PI, 42-324) were averted among children aged 6 to 59 months, corresponding to a 24.4% (95% PI, 6.1%-47.1%) reduction. In meta-analyses, county-level vaccination coverage was associated with averted cases for all age groups. Despite low vaccination coverage, pediatric COVID-19 immunization in California averted 376 085 (95% PI, 348 355-417 328) reported cases and 273 (95% PI, 77-605) hospitalizations among children aged 6 months to 15 years over approximately 4 to 7 months following vaccination availability.Conclusions and relevanceThe findings of this case series analysis of 3 913 063 cases suggest reduced pediatric SARS-CoV-2 transmission following immunization. These results support the use of COVID-19 vaccines to reduce COVID-19 incidence and hospitalization in pediatric populations.

A clear understanding of real-world uptake of nirmatrelvir-ritonavir for treatment of SARS-CoV-2 can inform treatment allocation strategies and improve interpretation of effectiveness studies. We used data from a large US healthcare system to describe nirmatrelvir-ritonavir dispenses among all SARS-CoV-2 positive patients aged ≥ 12 years meeting recommended National Institutes of Health treatment eligibility criteria for the study period between 1 January and 31 December, 2022. Overall, 10.9% (N = 34,791/319,900) of treatment eligible patients with SARS-CoV-2 infections received nirmatrelvir-ritonavir over the study period. Although uptake of nirmatrelvir-ritonavir increased over time, by the end of 2022, less than a quarter of treatment eligible patients with SARS-CoV-2 infections had received nirmatrelvir-ritonavir. Across patient demographics, treatment was generally consistent with tiered treatment guidelines, with dispenses concentrated among patients aged ≥ 65 years (14,706/63,921; 23.0%), and with multiple comorbidities (10,989/54,431; 20.1%). However, neighborhoods of lower socioeconomic status (upper third of neighborhood deprivation index [NDI]) had between 12% (95% CI: 7-18%) and 28% (25-32%) lower odds of treatment dispense over the time periods studied compared to the lower third of NDI distribution, even after accounting for demographic and clinical characteristics. A limited chart review (N = 40) confirmed that in some cases a decision not to treat was appropriate and aligned with national guidelines to use clinical judgement on a case-by-case basis. There is a need to enhance patient and provider awareness on the availability and benefits of nirmatrelvir-ritonavir for the treatment of COVID-19 illness.

OBJECTIVE: To describe the implementation of a test-negative design case-control study in California during the Coronavirus Disease 2019 (COVID-19) pandemic. STUDY DESIGN: Test-negative case-control study. METHODS: Between February 24, 2021 - February 24, 2022, a team of 34 interviewers called 38,470 Californians, enrolling 1,885 that tested positive for SARS-CoV-2 (cases) and 1,871 testing negative for SARS-CoV-2 (controls) for 20-minute telephone survey. We estimated adjusted odds ratios for answering the phone and consenting to participate using mixed effects logistic regression. We used a web-based anonymous survey to compile interviewer experiences. RESULTS: Cases had 1.29-fold (95% CI: 1.24-1.35) higher adjusted odds of answering the phone and 1.69-fold (1.56-1.83) higher adjusted odds of consenting to participate compared to controls. Calls placed from 4pm to 6pm had the highest adjusted odds of being answered. Some interviewers experienced mental wellness challenges interacting with participants with physical (e.g., food, shelter, etc.) and emotional (e.g., grief counseling) needs, and enduring verbal harassment from individuals called. CONCLUSIONS: Calls placed during afternoon hours may optimize response rate when enrolling controls to a case-control study during a public health emergency response. Proactive check-ins and continual collection of interviewer experience(s) and may help maintain mental wellbeing of investigation workforce. Remaining adaptive to the dynamic needs of the investigation team is critical to a successful study, especially in emergent public health crises, like that represented by the COVID-19 pandemic.

BACKGROUND: Shigella is a leading cause of diarrhea and dysentery in children in low-resource settings, which is frequently treated with antibiotics. The primary goal of a Shigella vaccine would be to reduce mortality and morbidity associated with Shigella diarrhea. However, ancillary benefits could include reducing antibiotic use and antibiotic exposures for bystander pathogens carried at the time of treatment, specifically for fluoroquinolones and macrolides (F/M), which are the recommended drug classes to treat dysentery. The aim of the study was to quantify the reduction in Shigella attributable diarrhea, all diarrhea, and antibiotic use in the first 2 years of life that could be prevented by a Shigella vaccine. METHODS AND FINDINGS: We used data from the Etiology, Risk Factors, and Interactions of Enteric Infections and Malnutrition and the Consequences for Child Health and Development (MAL-ED) study, a birth cohort study that followed 1,715 children with twice weekly surveillance for enteric infections, illnesses, and antibiotic use for the first 2 years of life from November 2009 to February 2014 at 8 sites. We estimated the impact of 2 one-dose (6 or 9 months) and 3 two-dose (6 and 9 months, 9 and 12 months, and 12 and 15 months) Shigella vaccines on diarrheal episodes, overall antibiotic use, and F/M use. Further, we considered additional protection through indirect and boosting effects. We used Monte Carlo simulations to estimate the absolute and relative reductions in the incidence of diarrhea and antibiotic use comparing each vaccination scenario to no vaccination. We analyzed 9,392 diarrhea episodes and 15,697 antibiotic courses among 1,715 children in the MAL-ED birth cohort study. There were 273.8 diarrhea episodes, 30.6 shigellosis episodes, and 457.6 antibiotic courses per 100 child-years. A Shigella vaccine with a mean vaccine efficacy of 60% against severe disease given at 9 and 12 months prevented 10.6 (95% CI [9.5, 11.5]) Shigella diarrhea episodes of any severity per 100 child-years (relative 34.5% reduction), 3.0 (95% CI [2.5, 3.5]) F/M courses for Shigella treatment per 100 child-years (relative 35.8% reduction), and 5.6 (95% CI [5.0, 6.3]) antibiotic courses of any drug class for Shigella treatment per 100 child-years (relative 34.5% reduction). This translated to a relative 3.8% reduction in all diarrhea, a relative 2.8% reduction in all F/M courses, a relative 3.1% reduction in F/M exposures to bystander pathogens, and a relative 0.9% reduction in all antibiotic courses. These results reflect Shigella incidence and antibiotic use patterns at the 8 MAL-ED sites and may not be generalizable to all low-resource settings. CONCLUSIONS: Our simulation results suggest that a Shigella vaccine meeting WHO targets for efficacy could prevent about a third of Shigella diarrhea episodes, antibiotic use to treat shigellosis, and bystander exposures due to shigellosis treatment. However, the reductions in overall diarrhea episodes and antibiotic use are expected to be modest (

BackgroundIn the USA, oral nirmatrelvir-ritonavir is authorised for use in patients aged 12 years or older with mild-to-moderate COVID-19 who are at risk of progression to severe disease and hospitalisation. We aimed to establish the effectiveness of nirmatrelvir-ritonavir in preventing hospital admissions and death in people with COVID-19 in an outpatient prescribing context in the USA.MethodsIn this matched observational outpatient cohort study in the Kaiser Permanente Southern California (CA, USA) health-care system, data were extracted from electronic health records of non-hospitalised patients aged 12 years or older who received a positive SARS-CoV-2 PCR test result (their index test) between April 8 and Oct 7, 2022, and had not received another positive test result within the preceding 90 days. We compared outcomes between people who received nirmatrelvir-ritonavir and those who did not receive nirmatrelvir-ritonavir by matching cases by date, age, sex, clinical status (including care received, the presence or absence of acute COVID-19 symptoms at testing, and time from symptom onset to testing), vaccination history, comorbidities, health-care seeking during the previous year, and BMI. Our primary endpoint was the estimated effectiveness of nirmatrelvir-ritonavir in preventing hospital admissions or death within 30 days of a positive test for SARS-CoV-2.Findings7274 nirmatrelvir-ritonavir recipients and 126 152 non-recipients with positive SARS-CoV-2 tests were included in our study. 5472 (75·2%) treatment recipients and 84 657 (67·1%) non-recipients were tested within 5 days of symptom onset. Nirmatrelvir-ritonavir had an overall estimated effectiveness of 53·6% (95% CI 6·6-77·0) in preventing hospital admission or death within 30 days of a positive test for SARS-CoV-2, which increased to 79·6% (33·9-93·8) when nirmatrelvir-ritonavir was dispensed within 5 days of symptom onset. Within the subgroup of patients tested within 5 days of symptom onset and whose treatment was dispensed on the day of their test, the estimated effectiveness of nirmatrelvir-ritonavir was 89·6% (50·2-97·8).InterpretationIn a setting with high levels of COVID-19 vaccine uptake, nirmatrelvir-ritonavir effectively reduced the risk of hospital admission or death within 30 days of a positive outpatient SARS-CoV-2 test.FundingUS Centers for Disease Control and Prevention and US National Institutes of Health.

Concerns about the duration of protection conferred by coronavirus disease 2019 (COVID-19) vaccines have arisen in postlicensure evaluations. "Depletion of susceptibles," a bias driven by differential accrual of infection among vaccinated and unvaccinated individuals, may obscure vaccine effectiveness (VE) estimates, hindering interpretation. We enrolled California residents who received molecular SARS-CoV-2 tests in a matched, test-negative design, case-control study to estimate VE of mRNA-based COVID-19 vaccines between February 23 and December 5, 2021. We analyzed waning protection following 2 vaccine doses using conditional logistic regression models. Additionally, we used data from a population-based serological study to adjust for "depletion-of-susceptibles" bias and estimated VE for 3 doses, by time since second dose receipt. Pooled VE of BNT162b2 and mRNA-1273 against symptomatic SARS-CoV-2 infection was 91.3% (95% confidence interval (CI): 83.8, 95.4) at 14 days after second-dose receipt and declined to 50.8% (95% CI: 19.7, 69.8) at 7 months. Adjusting for depletion-of-susceptibles bias, we estimated VE of 53.2% (95% CI: 23.6, 71.2) at 7 months after primary mRNA vaccination series. A booster dose of BN162b2 or mRNA-1273 increased VE to 95.0% (95% CI: 82.8, 98.6). These findings confirm that observed waning of protection is not attributable to epidemiologic bias and support ongoing efforts to administer additional vaccine doses to mitigate burden of COVID-19.

Globally, excess deaths during 2020-21 outnumbered documented COVID-19 deaths by 9.5 million, primarily driven by deaths in low- and middle-income countries (LMICs) with limited vital surveillance. Here we unravel the contributions of probable COVID-19 deaths from other changes in mortality related to pandemic control measures using medically-certified death registrations from Madurai, India-an urban center with well-functioning vital surveillance. Between March, 2020 and July, 2021, all-cause deaths in Madurai exceeded expected levels by 30% (95% confidence interval: 27-33%). Although driven by deaths attributed to cardiovascular or cerebrovascular conditions, diabetes, senility, and other uncategorized causes, increases in these attributions were restricted to medically-unsupervised deaths, and aligned with surges in confirmed or attributed COVID-19 mortality, likely reflecting mortality among unconfirmed COVID-19 cases. Implementation of lockdown measures was associated with a 7% (0-13%) reduction in all-cause mortality, driven by reductions in deaths attributed to injuries, infectious diseases and maternal conditions, and cirrhosis and other liver conditions, respectively, but offset by a doubling in cancer deaths. Our findings help to account for gaps between documented COVID-19 mortality and excess all-cause mortality during the pandemic in an LMIC setting.

As of March 31, 2023, more than 30,000 monkeypox (mpox) cases had been reported in the United States in an outbreak that has disproportionately affected gay, bisexual, and other men who have sex with men (MSM) and transgender persons (1). JYNNEOS vaccine (Modified Vaccinia Ankara vaccine, Bavarian Nordic) was approved by the Food and Drug Administration (FDA) in 2019 for the prevention of smallpox and mpox via subcutaneous injection as a 2-dose series (0.5 mL per dose, administered 4 weeks apart) (2). To expand vaccine access, an Emergency Use Authorization was issued by FDA on August 9, 2022, for dose-sparing intradermal injection of JYNNEOS as a 2-dose series (0.1 mL per dose, administered 4 weeks apart) (3). Vaccination was available to persons with known or presumed exposure to a person with mpox (postexposure prophylaxis [PEP]), as well as persons at increased risk for mpox or who might benefit from vaccination (preexposure mpox prophylaxis [PrEP]) (4). Because information on JYNNEOS vaccine effectiveness (VE) is limited, a matched case-control study was conducted in 12 U.S. jurisdictions,† including nine Emerging Infections Program sites and three Epidemiology and Laboratory Capacity sites,§ to evaluate VE against mpox among MSM and transgender adults aged 18-49 years. During August 19, 2022-March 31, 2023, a total of 309 case-patients were matched to 608 control patients. Adjusted VE was 75.2% (95% CI = 61.2% to 84.2%) for partial vaccination (1 dose) and 85.9% (95% CI = 73.8% to 92.4%) for full vaccination (2 doses). Adjusted VE for full vaccination by subcutaneous, intradermal, and heterologous routes of administration was 88.9% (95% CI = 56.0% to 97.2%), 80.3% (95% CI = 22.9% to 95.0%), and 86.9% (95% CI = 69.1% to 94.5%), respectively. Adjusted VE for full vaccination among immunocompromised participants was 70.2% (95% CI = -37.9% to 93.6%) and among immunocompetent participants was 87.8% (95% CI = 57.5% to 96.5%). JYNNEOS is effective at reducing the risk for mpox. Because duration of protection of 1 versus 2 doses remains unknown, persons at increased risk for mpox exposure should receive the 2-dose series as recommended by the Advisory Committee on Immunization Practices (ACIP),¶ regardless of administration route or immunocompromise status.

BackgroundDespite significant global progress in reducing neonatal mortality, bacterial sepsis remains a major cause of neonatal deaths. Klebsiella pneumoniae (K. pneumoniae) is the leading pathogen globally underlying cases of neonatal sepsis and is frequently resistant to antibiotic treatment regimens recommended by the World Health Organization (WHO), including first-line therapy with ampicillin and gentamicin, second-line therapy with amikacin and ceftazidime, and meropenem. Maternal vaccination to prevent neonatal infection could reduce the burden of K. pneumoniae neonatal sepsis in low- and middle-income countries (LMICs), but the potential impact of vaccination remains poorly quantified. We estimated the potential impact of such vaccination on cases and deaths of K. pneumoniae neonatal sepsis and project the global effects of routine immunization of pregnant women with the K. pneumoniae vaccine as antimicrobial resistance (AMR) increases.Methods and findingsWe developed a Bayesian mixture-modeling framework to estimate the effects of a hypothetical K. pneumoniae maternal vaccine with 70% efficacy administered with coverage equivalent to that of the maternal tetanus vaccine on neonatal sepsis infections and mortality. To parameterize our model, we used data from 3 global studies of neonatal sepsis and/or mortality-with 2,330 neonates who died with sepsis surveilled from 2016 to 2020 undertaken in 18 mainly LMICs across all WHO regions (Ethiopia, Kenya, Mali, Mozambique, Nigeria, Rwanda, Sierra Leone, South Africa, Uganda, Brazil, Italy, Greece, Pakistan, Bangladesh, India, Thailand, China, and Vietnam). Within these studies, 26.95% of fatal neonatal sepsis cases were culture-positive for K. pneumoniae. We analyzed 9,070 K. pneumoniae genomes from human isolates gathered globally from 2001 to 2020 to quantify the temporal rate of acquisition of AMR genes in K. pneumoniae isolates to predict the future number of drug-resistant cases and deaths that could be averted by vaccination. Resistance rates to carbapenems are increasing most rapidly and 22.43% [95th percentile Bayesian credible interval (CrI): 5.24 to 41.42] of neonatal sepsis deaths are caused by meropenem-resistant K. pneumoniae. Globally, we estimate that maternal vaccination could avert 80,258 [CrI: 18,084 to 189,040] neonatal deaths and 399,015 [CrI: 334,523 to 485,442] neonatal sepsis cases yearly worldwide, accounting for more than 3.40% [CrI: 0.75 to 8.01] of all neonatal deaths. The largest relative benefits are in Africa (Sierra Leone, Mali, Niger) and South-East Asia (Bangladesh) where vaccination could avert over 6% of all neonatal deaths. Nevertheless, our modeling only considers country-level trends in K. pneumoniae neonatal sepsis deaths and is unable to consider within-country variability in bacterial prevalence that may impact the projected burden of sepsis.ConclusionsA K. pneumoniae maternal vaccine could have widespread, sustained global benefits as AMR in K. pneumoniae continues to increase.

IntroductionUptake of COVID-19 vaccination remains suboptimal in the United States and other settings. Though early reports indicated that a strong majority of people were interested in receiving the COVID-19 vaccine, the association between vaccine intention and uptake is not yet fully understood. Ourobjective was todescribe predictors of vaccine uptake, and estimate the sensitivity, specificity, and predictive values of self-reported COVID-19 vaccine status compared to a comprehensive statewide COVID-19 vaccine registry.MethodsA cohort of California residents that received a molecular test for SARS-CoV-2 infection during 24 February-5 December 2021 were enrolled in a telephone-administered survey. Survey participants were matched with records in a statewide immunization registry. Cox proportional hazards model were used to compare time to vaccination among those unvaccinated at survey enrollment by self-reported COVID-19 vaccination intention.ResultsAmong 864 participants who were unvaccinated at the time of interview, 272 (31%) had documentation of receipt of COVID-19 vaccination at a later date; including 194/423 (45.9%) who had initially reported being willing to receive vaccination, 41/185 (22.2%) who reported being unsure about vaccination, and 37/278 (13.3%) who reported unwillingness to receive vaccination.Adjusted hazard ratios (aHRs) for registry-confirmed COVID-19 vaccination were 0.49 (95% confidence interval: 0.32-0.76) and 0.21 (0.12-0.36) for participants expressing uncertainty and unwillingness to receive vaccination, respectively, as compared with participants who reported being willing to receive vaccination. Time to vaccination was shorter among participants from higher-income households (aHR = 3.30 [2.02-5.39]) and who reported co-morbidities or immunocompromising conditions (aHR = 1.54 [1.01-2.36]).Sensitivity of self-reported COVID-19 vaccination status was 82% (80-85%) overall, and 98% (97-99%) among those referencing vaccination records; specificity was 87% (86-89%).ConclusionWillingness to receive COVID-19 vaccination was an imperfect predictor of real-world vaccine uptake. Improved messaging about COVID-19 vaccination regardless of previous SARS-CoV-2 infection status may help improve uptake.

Expansion of the SARS-CoV-2 BA.4 and BA.5 Omicron subvariants in populations with prevalent immunity from prior infection and vaccination, and associated burden of severe COVID-19, has raised concerns about epidemiologic characteristics of these lineages including their association with immune escape or severe clinical outcomes. Here we show that BA.4/BA.5 cases in a large US healthcare system had at least 55% (95% confidence interval: 43-69%) higher adjusted odds of prior documented infection than time-matched BA.2 cases, as well as 15% (9-21%) and 38% (27-49%) higher adjusted odds of having received 3 and ≥4 COVID-19 vaccine doses, respectively. However, after adjusting for differences in epidemiologic characteristics among cases with each lineage, BA.4/BA.5 infection was not associated with differential risk of emergency department presentation, hospital admission, or intensive care unit admission following an initial outpatient diagnosis. This finding held in sensitivity analyses correcting for potential exposure misclassification resulting from unascertained prior infections. Our results demonstrate that the reduced severity associated with prior (BA.1 and BA.2) Omicron lineages, relative to the Delta variant, has persisted with BA.4/BA.5, despite the association of BA.4/BA.5 with increased risk of breakthrough infection among previously vaccinated or infected individuals.

BackgroundInteractions of Streptococcus pneumoniae with viruses feature in the pathogenesis of numerous respiratory illnesses.MethodsWe undertook a case-control study among adults at Kaiser Permanente Southern California between 2015 and 2019. Case patients had diagnoses of lower respiratory tract infection (LRTI; including pneumonia or nonpneumonia LRTI diagnoses), with viral infections detected by multiplex polymerase chain reaction testing. Controls without LRTI diagnoses were matched to case patients by demographic and clinical attributes. We measured vaccine effectiveness (VE) for 13-valent (PCV13) against virus-associated LRTI by determining the adjusted odds ratio for PCV13 receipt, comparing case patients and controls.ResultsPrimary analyses included 13 856 case patients with virus-associated LRTI and 227 887 matched controls. Receipt of PCV13 was associated with a VE of 24.9% (95% confidence interval, 18.4%-30.9%) against virus-associated pneumonia and 21.5% (10.9%-30.9%) against other (nonpneumonia) virus-associated LRTIs. We estimated VEs of 26.8% (95% confidence interval, 19.9%-33.1%) and 18.6% (9.3%-27.0%) against all virus-associated LRTI episodes diagnosed in inpatient and outpatient settings, respectively. We identified statistically significant protection against LRTI episodes associated with influenza A and B viruses, endemic human coronaviruses, parainfluenza viruses, human metapneumovirus, and enteroviruses but not respiratory syncytial virus or adenoviruses.ConclusionsAmong adults, PCV13 conferred moderate protection against virus-associated LRTI. The impacts of pneumococcal conjugate vaccines may be mediated, in part, by effects on polymicrobial interactions between pneumococci and respiratory viruses.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) breakthrough infections in vaccinated individuals and reinfections in previously infected individuals have become increasingly common. Such infections highlight a broader need to understand the contribution of vaccination, including booster doses, and natural immunity to the infectiousness of individuals with SARS-CoV-2 infections, especially in high-risk populations with intense transmission, such as in prisons. Here we show that both vaccine-derived and naturally acquired immunity independently reduce the infectiousness of persons with Omicron variant SARS-CoV-2 infections in a prison setting. Analyzing SARS-CoV-2 surveillance data from December 2021 to May 2022 across 35 California state prisons with a predominately male population, we estimate that unvaccinated Omicron cases had a 36% (95% confidence interval (CI): 31-42%) risk of transmitting infection to close contacts, as compared to a 28% (25-31%) risk among vaccinated cases. In adjusted analyses, we estimated that any vaccination, prior infection alone and both vaccination and prior infection reduced an index cases risk of transmitting infection by 22% (6-36%), 23% (3-39%) and 40% (20-55%), respectively. Receipt of booster doses and more recent vaccination further reduced infectiousness among vaccinated cases. These findings suggest that, although vaccinated and/or previously infected individuals remain highly infectious upon SARS-CoV-2 infection in this prison setting, their infectiousness is reduced compared to individuals without any history of vaccination or infection. This study underscores benefit of vaccination to reduce, but not eliminate, transmission.

BackgroundDespite lower circulation of influenza virus throughout 2020-2022 during the COVID-19 pandemic, seasonal influenza vaccination has remained a primary tool to reduce influenza-associated illness and death. The relationship between the decision to receive a COVID-19 vaccine and/or an influenza vaccine is not well understood.MethodsWe assessed predictors of receipt of 2021-2022 influenza vaccine in a secondary analysis of data from a case-control study enrolling individuals who received SARS-CoV-2 testing. We used mixed effects logistic regression to estimate factors associated with receipt of seasonal influenza vaccine. We also constructed multinomial adjusted marginal probability models of being vaccinated for COVID-19 only, seasonal influenza only, or both as compared with receipt of neither vaccination.ResultsAmong 1261 eligible participants recruited between 22 October 2021-22 June 2022, 43% (545) were vaccinated with both seasonal influenza vaccine and >1 dose of a COVID-19 vaccine, 34% (426) received >1 dose of a COVID-19 vaccine only, 4% (49) received seasonal influenza vaccine only, and 19% (241) received neither vaccine. Receipt of >1 COVID-19 vaccine dose was associated with seasonal influenza vaccination (adjusted odds ratio [aOR]: 3.72; 95% confidence interval [CI]: 2.15-6.43); this association was stronger among participants receiving >1 COVID-19 booster dose (aOR = 16.50 [10.10-26.97]). Compared with participants testing negative for SARS- CoV-2 infection, participants testing positive had lower odds of receipt of 2021-2022 seasonal influenza vaccine (aOR = 0.64 [0.50-0.82]).ConclusionsRecipients of a COVID-19 vaccine were more likely to receive seasonal influenza vaccine during the 2021-2022 season. Factors associated with individuals' likelihood of receiving COVID-19 and seasonal influenza vaccines will be important to account for in future studies of vaccine effectiveness against both conditions. Participants who tested positive for SARS-CoV-2 in our sample were less likely to have received seasonal influenza vaccine, suggesting an opportunity to offer influenza vaccination before or after a COVID-19 diagnosis.

Human papillomavirus (HPV) is an important cause of anogenital and oropharyngeal cancers, anogenital warts, and recurrent respiratory papillomatosis. Beginning in 2019, US guidelines recommended shared clinical decision-making (SCDM) for HPV vaccination among midadults (27-45 years). We conducted a narrative review of existing literature on HPV vaccination in midadults. The available evidence demonstrates that HPV vaccination in midadults is safe, efficacious, and likely to benefit both HPV-naïve midadults and those with previous infections. However, gaps in knowledge related to HPV vaccination have been identified among clinicians and midadult patients. Universal midadult HPV vaccination in the United States could avert 20 934-37 856 cancer cases over 100 years, costing $141 000-$1 471 000 per quality-adjusted life-year gained. Wide variation in these estimates reflects uncertainties in sexual behavior, HPV natural history, and naturally acquired immunity. Greater awareness among clinicians and midadult patients and broad implementation of SCDM may accelerate progress toward eliminating HPV-associated cancers and other diseases.

Host immune responses are a key source of selective pressure driving pathogen evolution. Emergence of many SARS-CoV-2 lineages has been associated with enhancements in their ability to evade population immunity resulting from both vaccination and infection. Here we show diverging trends of escape from vaccine-derived and infection-derived immunity for the emerging XBB/XBB.1.5 Omicron lineage. Among 31,739 patients tested in ambulatory settings in Southern California from December, 2022 to February, 2023, adjusted odds of prior receipt of 2, 3, 4, and ≥5 COVID-19 vaccine doses were 10% (95% confidence interval: 1-18%), 11% (3-19%), 13% (3-21%), and 25% (15-34%) lower, respectively, among cases infected with XBB/XBB.1.5 than among cases infected with other co-circulating lineages. Similarly, prior vaccination was associated with greater point estimates of protection against progression to hospitalization among cases with XBB/XBB.1.5 than among non-XBB/XBB.1.5 cases (70% [30-87%] and 48% [7-71%], respectively, for recipients of ≥4 doses). In contrast, cases infected with XBB/XBB.1.5 had 17% (11-24%) and 40% (19-65%) higher adjusted odds of having experienced 1 and ≥2 prior documented infections, respectively, including with pre-Omicron variants. As immunity acquired from SARS-CoV-2 infection becomes increasingly widespread, fitness costs associated with enhanced vaccine sensitivity in XBB/XBB.1.5 may be offset by increased ability to evade infection-derived host responses.

BackgroundThe San Francisco Bay Area was the first region in the United States to enact school closures to mitigate SARS-CoV-2 transmission. The effects of closures on contact patterns for schoolchildren and their household members remain poorly understood.MethodsWe conducted serial cross-sectional surveys (May 2020, September 2020, February 2021) of Bay Area households with children to estimate age-structured daily contact rates for children and their adult household members. We examined changes in contact rates over the course of the COVID-19 pandemic, including after vaccination of household members, and compared contact patterns by household demographics using generalized estimating equations clustered by household.ResultsWe captured contact histories for 1,967 households on behalf of 2,674 children, comprising 15,087 non-household contacts over the three waves of data collection. Shortly after the start of shelter-in-place orders in May 2020, daily contact rates were higher among children from Hispanic families (1.52 more contacts per child per day; [95% CI: 1.14-2.04]), households whose parents were unable to work from home (1.82; [1.40-2.40]), and households with income

The basic reproduction number, R 0, and its real-time analogue, Rt , are summary measures that reflect the ability of an infectious disease to spread through a population. Estimation methods for Rt  have a long history, have been widely developed and are now enhanced by application to the COVID-19 pandemic. While retrospective analyses of Rt have provided insight into epidemic dynamics and the effects of control strategies in prior outbreaks, misconceptions around the interpretation of Rt have arisen with broader recognition and near real-time monitoring of this parameter alongside reported case data during the COVID-19 pandemic. Here, we discuss some widespread misunderstandings regarding the use of Rt  as a barometer for population risk and its related use as an 'on/off' switch for policy decisions regarding relaxation of non-pharmaceutical interventions. Computation of Rt  from downstream data (e.g. hospitalizations) when infection counts are unreliable exacerbates lags between when transmission happens and when events are recorded. We also discuss analyses that have shown various relationships between Rt  and measures of mobility, vaccination coverage and a test-trace-isolation intervention in different settings.

Epidemiologic surveillance has revealed decoupling of Coronavirus Disease 2019 (COVID-19) hospitalizations and deaths from case counts after emergence of the Omicron (B.1.1.529) severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant globally. However, assessment of the relative severity of Omicron variant infections presents challenges because of differential acquired immune protection against Omicron and prior variants and because longer-term changes have occurred in testing and healthcare practices. Here we show that Omicron variant infections were associated with substantially reduced risk of progression to severe clinical outcomes relative to time-matched Delta (B.1.617.2) variant infections within a large, integrated healthcare system in Southern California. Adjusted hazard ratios (aHRs) for any hospital admission, symptomatic hospital admission, intensive care unit admission, mechanical ventilation and death comparing individuals with Omicron versus Delta variant infection were 0.59 (95% confidence interval: 0.51-0.69), 0.59 (0.51-0.68), 0.50 (0.29-0.87), 0.36 (0.18-0.72) and 0.21 (0.10-0.44), respectively. This reduced severity could not be explained by differential history of prior infection among individuals with Omicron or Delta variant infection and was starkest among individuals not previously vaccinated against COVID-19 (aHR = 0.40 (0.33-0.49) for any hospital admission and 0.14 (0.07-0.28) for death). Infections with the Omicron BA.2 subvariant were not associated with differential risk of severe outcomes in comparison to BA.1/BA.1.1 subvariant infections. Lower risk of severe clinical outcomes among individuals with Omicron variant infection should inform public health response amid establishment of the Omicron variant as the dominant SARS-CoV-2 lineage globally.

Children in low-resource settings carry enteric pathogens asymptomatically and are frequently treated with antibiotics, resulting in opportunities for pathogens to be exposed to antibiotics when not the target of treatment (i.e., bystander exposure). We quantified the frequency of bystander antibiotic exposures for enteric pathogens and estimated associations with resistance among children in eight low-resource settings. We analyzed 15,697 antibiotic courses from 1,715 children aged 0 to 2 y from the MAL-ED birth cohort. We calculated the incidence of bystander exposures and attributed exposures to respiratory and diarrheal illnesses. We associated bystander exposure with phenotypic susceptibility of E. coli isolates in the 30 d following exposure and at the level of the study site. There were 744.1 subclinical pathogen exposures to antibiotics per 100 child-years. Enteroaggregative Escherichia coli was the most frequently exposed pathogen, with 229.6 exposures per 100 child-years. Almost all antibiotic exposures for Campylobacter (98.8%), enterotoxigenic E. coli (95.6%), and typical enteropathogenic E. coli (99.4%), and the majority for Shigella (77.6%), occurred when the pathogens were not the target of treatment. Respiratory infections accounted for half (49.9%) and diarrheal illnesses accounted for one-fourth (24.6%) of subclinical enteric bacteria exposures to antibiotics. Bystander exposure of E. coli to class-specific antibiotics was associated with the prevalence of phenotypic resistance at the community level. Antimicrobial stewardship and illness-prevention interventions among children in low-resource settings would have a large ancillary benefit of reducing bystander selection that may contribute to antimicrobial resistance.

BackgroundNon-pharmaceutical interventions (NPIs) are recommended for COVID-19 prevention. However, the effectiveness of NPIs in preventing SARS-CoV-2 transmission remains poorly quantified.MethodsWe conducted a test-negative design case-control study enrolling cases (testing positive for SARS-CoV-2) and controls (testing negative) with molecular SARS-CoV-2 diagnostic test results reported to California Department of Public Health between 24 February-12 November, 2021. We used conditional logistic regression to estimate adjusted odds ratios (aORs) of case status among participants who reported contact with an individual known or suspected to have been infected with SARS-CoV-2 ("high-risk exposure") ≤14 days before testing.Results751 of 1448 cases (52%) and 255 of 1443 controls (18%) reported high-risk exposures ≤14 days before testing. Adjusted odds of case status were 3.02-fold (95% confidence interval: 1.75-5.22) higher when high-risk exposures occurred with household members (vs. other contacts), 2.10-fold (1.05-4.21) higher when exposures occurred indoors (vs. outdoors only), and 2.15-fold (1.27-3.67) higher when exposures lasted ≥3 hours (vs. shorter durations) among unvaccinated and partially-vaccinated individuals; excess risk associated with such exposures was mitigated among fully-vaccinated individuals. Cases were less likely than controls to report mask usage during high-risk exposures (aOR = 0.50 [0.29-0.85]). The adjusted odds of case status was lower for fully-vaccinated (aOR = 0.25 [0.15-0.43]) participants compared to unvaccinated participants. Benefits of mask usage were greatest among unvaccinated and partially-vaccinated participants, and in interactions involving non-household contacts or interactions occurring without physical contact.ConclusionsNPIs reduced the likelihood of SARS-CoV-2 infection following high-risk exposure. Vaccine effectiveness was substantial for partially and fully vaccinated persons.

Accurate measurement of daily infection incidence is crucial to epidemic response. However, delays in symptom onset, testing, and reporting obscure the dynamics of transmission, necessitating methods to remove the effects of stochastic delays from observed data. Existing estimators can be sensitive to model misspecification and censored observations; many analysts have instead used methods that exhibit strong bias. We develop an estimator with a regularization scheme to cope with stochastic delays, which we term the robust incidence deconvolution estimator. We compare the method to existing estimators in a simulation study, measuring accuracy in a variety of experimental conditions. We then use the method to study COVID-19 records in the United States, highlighting its stability in the face of misspecification and right censoring. To implement the robust incidence deconvolution estimator, we release incidental, a ready-to-use R implementation of our estimator that can aid ongoing efforts to monitor the COVID-19 pandemic.

Postauthorization observational studies play a key role in understanding COVID-19 vaccine effectiveness following the demonstration of efficacy in clinical trials. Although bias due to confounding, selection bias, and misclassification can be mitigated through careful study design, unmeasured confounding is likely to remain in these observational studies. Phase III trials of COVID-19 vaccines have shown that protection from vaccination does not occur immediately, meaning that COVID-19 risk should be similar in recently vaccinated and unvaccinated individuals, in the absence of confounding or other bias. Several studies have used the estimated effectiveness among recently vaccinated individuals as a negative control exposure to detect bias in vaccine effectiveness estimates. In this paper, we introduce a theoretical framework to describe the interpretation of such a bias indicator in test-negative studies, and outline strong assumptions that would allow vaccine effectiveness among recently vaccinated individuals to serve as a negative control exposure.

Mathematical modeling studies are frequently conducted to guide policy in global health. However, the contribution of mathematical modeling studies to World Health Organization (WHO) guideline recommendations, and the quality of evidence contributed by these studies remains unknown. We conducted a systematic review of the WHO Guidelines Review Committee database to identify guideline recommendations that included evidence from mathematical modeling studies since inception of the Guidelines Review Committee on 1 December, 2007. We included WHO guideline recommendations citing a mathematical modeling study in the primary evidence base. We defined a mathematical model as a framework that predicted epidemiologic, health or economic impact of an intervention or decision in the clinical or public health context. The primary outcome was inclusion of evidence from mathematical modeling studies in a guideline recommendation. We evaluated each unique modeling study across multiple domains of quality. Between 1 December 2007 and 1 April 2019, the WHO Guidelines Review Committee approved 154 guidelines providing 1619 guideline recommendations. Mathematical modeling studies informed 46 WHO guidelines (29.9%) and 101 unique guideline recommendations (6.2%). Modeling evidence addressed topics related to infectious diseases in 38 guidelines (82.6%) and 81 recommendations (80.2%), most commonly for HIV and tuberculosis. Evidence from modeling studies was assessed in the GRADE evidence profile for 12 recommendations (12.9%) and GRADE evidence-to-decision framework for 45 recommendations (44.6%). Modeling-informed recommendations were more likely than other recommendations within the same guidelines to be issued with a "conditional" rather than "strong" strength of recommendation (53.5% versus 37.8%), and the evidence underlying modeling-informed recommendations was more likely to be assessed as very low quality (41.6% versus 24.1%). Upon review of individual modeling studies, we estimated that 33.8% of models performed a calibration, 29.4% of models performed a validation of results, and 20.6% of models reported a change in the study conclusion in the sensitivity analysis. While policy recommendations in WHO guidelines are informed by evidence from modeling studies, the validity of modeling studies included in guidelines development is heterogeneous. Quality assessment is needed to support the evaluation and incorporation of evidence from mathematical modeling studies in guidelines development.

BackgroundWhile secondary pneumococcal pneumonia occurs less commonly after coronavirus disease 2019 (COVID-19) than after other viral infections, it remains unclear whether other interactions occur between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and Streptococcus pneumoniae.MethodsWe probed potential interactions between these pathogens among adults aged ≥65 years by measuring associations of COVID-19 outcomes with pneumococcal vaccination (13-valent conjugate vaccine [PCV13] and 23-valent pneumococcal polysaccharide vaccine [PPSV23]). We estimated adjusted hazard ratios (aHRs) using Cox proportional hazards models with doubly robust inverse-propensity weighting. We assessed effect modification by antibiotic exposure to further test the biologic plausibility of a causal role for pneumococci.ResultsAmong 531 033 adults, there were 3677 COVID-19 diagnoses, leading to 1075 hospitalizations and 334 fatalities, between 1 March and 22 July 2020. Estimated aHRs for COVID-19 diagnosis, hospitalization, and mortality associated with prior PCV13 receipt were 0.65 (95% confidence interval [CI], .59-.72), 0.68 (95% CI, .57-.83), and 0.68 (95% CI, .49-.95), respectively. Prior PPSV23 receipt was not associated with protection against the 3 outcomes. COVID-19 diagnosis was not associated with prior PCV13 within 90 days following antibiotic receipt, whereas aHR estimates were 0.65 (95% CI, .50-.84) and 0.62 (95% CI, .56-.70) during the risk periods 91-365 days and >365 days, respectively, following antibiotic receipt.ConclusionsReduced risk of COVID-19 among PCV13 recipients, transiently attenuated by antibiotic exposure, suggests that pneumococci may interact with SARS-CoV-2.

BackgroundEstimates of coronavirus disease 2019 (COVID-19) vaccine effectiveness under real-world conditions, and understanding of barriers to uptake, are necessary to inform vaccine rollout.MethodsWe enrolled cases (testing positive) and controls (testing negative) from among the population whose SARS-CoV-2 molecular diagnostic test results from 24 February to 29 April 2021 were reported to the California Department of Public Health. Participants were matched on age, sex, and geographic region. We assessed participants' self-reported history of mRNA-based COVID-19 vaccine receipt (BNT162b2 and mRNA-1273). Participants were considered fully vaccinated 2 weeks after second dose receipt. Among unvaccinated participants, we assessed willingness to receive vaccination. We measured vaccine effectiveness (VE) via the matched odds ratio of prior vaccination, comparing cases with controls.ResultsWe enrolled 1023 eligible participants aged ≥18 years. Among 525 cases, 71 (13.5%) received BNT162b2 or mRNA-1273; 20 (3.8%) were fully vaccinated with either product. Among 498 controls, 185 (37.1%) received BNT162b2 or mRNA-1273; 86 (16.3%) were fully vaccinated with either product. Two weeks after second dose receipt, VE was 87.0% (95% confidence interval: 68.6-94.6%) and 86.2% (68.4-93.9%) for BNT162b2 and mRNA-1273, respectively. Fully vaccinated participants receiving either product experienced 91.3% (79.3-96.3%) and 68.3% (27.9-85.7%) VE against symptomatic and asymptomatic infection, respectively. Among unvaccinated participants, 42.4% (159/375) residing in rural regions and 23.8% (67/281) residing in urban regions reported hesitancy to receive COVID-19 vaccination.ConclusionsAuthorized mRNA-based vaccines are effective at reducing documented SARS-CoV-2 infections within the general population of California. Vaccine hesitancy presents a barrier to reaching coverage levels needed for herd immunity.

ObjectiveTo quantify the frequency of antibiotic treatments attributable to specific enteric pathogens due to the treatment of diarrhoea among children in the first 2 years of life in low-resource settings.DesignSecondary analysis of a longitudinal birth cohort study, Etiology, Risk Factors, and Interactions of Enteric Infections and Malnutrition and the Consequences for Child Health and Development (MAL-ED).SettingThis study was conducted at eight sites in Bangladesh, Brazil, India, Nepal, Peru, Pakistan, South Africa and Tanzania.ParticipantsWe analysed 9392 reported diarrhoea episodes, including 6677 with molecular diagnostic test results, as well as 31 408 non-diarrhoeal stools from 1715 children aged 0-2 years with 2 years of complete follow-up data.Primary and secondary outcome measuresWe estimated incidence rates and the proportions of antibiotic use for diarrhoea and for all indications attributable to the top 10 aetiologies of diarrhoea. We estimated associations between specific aetiologies and antibiotic treatment, and assessed whether clinical characteristics of the diarrhoea episodes mediated these relationships.ResultsShigella and rotavirus were the leading causes of antibiotic treatment, responsible for 11.7% and 8.6% of diarrhoea treatments and 14.8 and 10.9 courses per 100 child-years, respectively. Shigella and rotavirus-attributable diarrhoea episodes were 46% (RR: 1.46; 95% CI: 1.33 to 1.60), and 19% (RR: 1.19; 95% CI: 1.09 to 1.31) more likely to be treated with antibiotics, respectively, compared with other aetiologies. Considering antibiotic uses for all indications, these two pathogens accounted for 5.6% of all antibiotic courses, 19.3% of all fluoroquinolone courses and 9.5% of all macrolide courses. Among indicated treatments for dysentery, Shigella and Campylobacter jenjui/Campylobacter coli were responsible for 27.5% and 8.5% of treated episodes, respectively.ConclusionsThe evidence that Shigella and rotavirus were disproportionately responsible for antibiotic use due to their high burden and severity further strengthens the value of interventions targeted to these pathogens. Interventions against Campylobacter could further prevent a large burden of indicated antibiotic treatment for dysentery, which could not be averted by antibiotic stewardship interventions.

BackgroundIndia has been severely affected by the ongoing COVID-19 pandemic. However, due to shortcomings in disease surveillance, the burden of mortality associated with COVID-19 remains poorly understood. We aimed to assess changes in mortality during the pandemic in Chennai, Tamil Nadu, using data on all-cause mortality within the district.MethodsFor this observational study, we analysed comprehensive death registrations in Chennai, from Jan 1, 2016, to June 30, 2021. We estimated expected mortality without the effects of the COVID-19 pandemic by fitting models to observed mortality time series during the pre-pandemic period, with stratification by age and sex. Additionally, we considered three periods of interest: the first 4 weeks of India's first lockdown (March 24 to April 20, 2020), the 4-month period including the first wave of the pandemic in Chennai (May 1 to Aug 31, 2020), and the 4-month period including the second wave of the pandemic in Chennai (March 1 to June 30, 2021). We computed the difference between observed and expected mortality from March 1, 2020, to June 30, 2021, and compared pandemic-associated mortality across socioeconomically distinct communities (measured with use of 2011 census of India data) with regression analyses.FindingsBetween March 1, 2020, and June 30, 2021, 87 870 deaths were registered in areas of Chennai district represented by the 2011 census, exceeding expected deaths by 25 990 (95% uncertainty interval 25 640-26 360) or 5·18 (5·11-5·25) excess deaths per 1000 people. Stratified by age, excess deaths numbered 21·02 (20·54-21·49) excess deaths per 1000 people for individuals aged 60-69 years, 39·74 (38·73-40·69) for those aged 70-79 years, and 96·90 (93·35-100·16) for those aged 80 years or older. Neighbourhoods with lower socioeconomic status had 0·7% to 2·8% increases in pandemic-associated mortality per 1 SD increase in each measure of community disadvantage, due largely to a disproportionate increase in mortality within these neighbourhoods during the second wave. Conversely, differences in excess mortality across communities were not clearly associated with socioeconomic status measures during the first wave. For each increase by 1 SD in measures of community disadvantage, neighbourhoods had 3·6% to 8·6% lower pandemic-associated mortality during the first 4 weeks of India's country-wide lockdown, before widespread SARS-CoV-2 circulation was underway in Chennai. The greatest reductions in mortality during this early lockdown period were observed among men aged 20-29 years, with 58% (54-62) fewer deaths than expected from pre-pandemic trends.InterpretationMortality in Chennai increased substantially but heterogeneously during the COVID-19 pandemic, with the greatest burden concentrated in disadvantaged communities. Reported COVID-19 deaths greatly underestimated pandemic-associated mortality.FundingNational Institute of General Medical Sciences, Bill & Melinda Gates Foundation, National Science Foundation.TranslationFor the Hindi translation of the abstract see Supplementary Materials section.

SignificanceStrategies to reduce consumption of antimicrobial drugs are needed to contain the growing burden of antimicrobial resistance. Respiratory syncytial virus (RSV) is a prominent cause of upper and lower respiratory tract infections, as a single agent and in conjunction with bacterial pathogens, and may thus contribute to the burden of both inappropriately treated viral infections and appropriately treated polymicrobial infections involving bacteria. In a double-blind, randomized, placebo-controlled trial, administering an RSV vaccine to pregnant mothers reduced antimicrobial prescribing among their infants by 12.9% over the first 3 mo of life. Our findings implicate RSV as an important contributor to antimicrobial exposure among infants and demonstrate that this exposure is preventable by use of effective maternal vaccines against RSV.

The use of face masks or respirators (N95/KN95) is recommended to reduce transmission of SARS-CoV-2, the virus that causes COVID-19 (1). Well-fitting face masks and respirators effectively filter virus-sized particles in laboratory conditions (2,3), though few studies have assessed their real-world effectiveness in preventing acquisition of SARS-CoV-2 infection (4). A test-negative design case-control study enrolled randomly selected California residents who had received a test result for SARS-CoV-2 during February 18-December 1, 2021. Face mask or respirator use was assessed among 652 case-participants (residents who had received positive test results for SARS-CoV-2) and 1,176 matched control-participants (residents who had received negative test results for SARS-CoV-2) who self-reported being in indoor public settings during the 2 weeks preceding testing and who reported no known contact with anyone with confirmed or suspected SARS-CoV-2 infection during this time. Always using a face mask or respirator in indoor public settings was associated with lower adjusted odds of a positive test result compared with never wearing a face mask or respirator in these settings (adjusted odds ratio [aOR] = 0.44; 95% CI = 0.24-0.82). Among 534 participants who specified the type of face covering they typically used, wearing N95/KN95 respirators (aOR = 0.17; 95% CI = 0.05-0.64) or surgical masks (aOR = 0.34; 95% CI = 0.13-0.90) was associated with significantly lower adjusted odds of a positive test result compared with not wearing any face mask or respirator. These findings reinforce that in addition to being up to date with recommended COVID-19 vaccinations, consistently wearing a face mask or respirator in indoor public settings reduces the risk of acquiring SARS-CoV-2 infection. Using a respirator offers the highest level of personal protection against acquiring infection, although it is most important to wear a mask or respirator that is comfortable and can be used consistently.

Comprehensive data on transmission mitigation behaviors and both SARS-CoV-2 infection and serostatus are needed from large, community-based cohorts to identify COVID-19 risk factors and the impact of public health measures. We conducted a longitudinal, population-based study in the East Bay Area of Northern California. From July 2020-March 2021, approximately 5,500 adults were recruited and followed over three data collection rounds to investigate the association between geographic and demographic characteristics and transmission mitigation behavior with SARS-CoV-2 prevalence. We estimated the populated-adjusted prevalence of antibodies from SARS-CoV-2 infection and COVID-19 vaccination, and self-reported COVID-19 test positivity. Population-adjusted SARS-CoV-2 seroprevalence was low, increasing from 1.03% (95% CI: 0.50-1.96) in Round 1 (July-September 2020), to 1.37% (95% CI: 0.75-2.39) in Round 2 (October-December 2020), to 2.18% (95% CI: 1.48-3.17) in Round 3 (February-March 2021). Population-adjusted seroprevalence of COVID-19 vaccination was 21.64% (95% CI: 19.20-24.34) in Round 3, with White individuals having 4.35% (95% CI: 0.35-8.32) higher COVID-19 vaccine seroprevalence than individuals identifying as African American or Black, American Indian or Alaskan Native, Asian, Hispanic, two or more races, or other. No evidence for an association between transmission mitigation behavior and seroprevalence was observed. Despite >99% of participants reporting wearing masks individuals identifying as African American or Black, American Indian or Alaskan Native, Asian, Hispanic, two or more races, or other, as well as those in lower-income households, and lower-educated individuals had the highest SARS-CoV-2 seroprevalence and lowest vaccination seroprevalence. Results demonstrate that more effective policies are needed to address these disparities and inequities.

With the aid of laboratory typing techniques, infectious disease surveillance networks have the opportunity to obtain powerful information on the emergence, circulation, and evolution of multiple genotypes, serotypes or other subtypes of pathogens, informing understanding of transmission dynamics and strategies for prevention and control. The volume of typing performed on clinical isolates is typically limited by its ability to inform clinical care, cost and logistical constraints, especially in comparison with the capacity to monitor clinical reports of disease occurrence, which remains the most widespread form of public health surveillance. Viewing clinical disease reports as arising from a latent mixture of pathogen subtypes, laboratory typing of a subset of clinical cases can provide inference on the proportion of clinical cases attributable to each subtype (i.e., the mixture components). Optimizing protocols for the selection of isolates for typing by weighting specific subpopulations, locations, time periods, or case characteristics (e.g., disease severity), may improve inference of the frequency and distribution of pathogen subtypes within and between populations. Here, we apply the Disease Surveillance Informatics Optimization and Simulation (DIOS) framework to simulate and optimize hand foot and mouth disease (HFMD) surveillance in a high-burden region of western China. We identify laboratory surveillance designs that significantly outperform the existing network: the optimal network reduced mean absolute error in estimated serotype-specific incidence rates by 14.1%; similarly, the optimal network for monitoring severe cases reduced mean absolute error in serotype-specific incidence rates by 13.3%. In both cases, the optimal network designs achieved improved inference without increasing subtyping effort. We demonstrate how the DIOS framework can be used to optimize surveillance networks by augmenting clinical diagnostic data with limited laboratory typing resources, while adapting to specific, local surveillance objectives and constraints.

BackgroundSARS-CoV-2 has spread substantially within India over multiple waves of the ongoing COVID-19 pandemic. However, the risk factors and disease burden associated with COVID-19 in India remain poorly understood. We aimed to assess predictors of infection and mortality within an active surveillance study, and to probe the completeness of case and mortality surveillance.MethodsIn this prospective, active surveillance study, we used data collected under expanded programmatic surveillance testing for SARS-CoV-2 in the district of Madurai, Tamil Nadu, India (population of 3 266 000 individuals). Prospective testing via RT-PCR was done in individuals with fever or acute respiratory symptoms as well as returning travellers, frontline workers, contacts of laboratory-confirmed COVID-19 cases, residents of containment zones, patients undergoing medical procedures, and other risk groups. Standardised data collection on symptoms and chronic comorbid conditions was done as part of routine intake. Additionally, seroprevalence of anti-SARS-CoV-2 immunoglobulin G was assessed via a cross-sectional survey recruiting adults across 38 clusters within Madurai District from Oct 19, 2020, to Nov 5, 2020. We estimated adjusted odds ratios (aORs) for positive RT-PCR results comparing individuals by age, sex, comorbid conditions, and aspects of clinical presentation. We estimated case-fatality ratios (CFRs) over the 30-day period following RT-PCR testing stratified by the same variables, and adjusted hazard ratios (aHRs) for death associated with age, sex, and comorbidity. We estimated infection-fatality ratios (IFRs) on the basis of age-specific seroprevalence.ResultsBetween May 20, 2020, and Oct 31, 2020, 13·5 diagnostic tests were done per 100 inhabitants within Madurai, as compared to 7·9 tests per 100 inhabitants throughout India. From a total of 440 253 RT-PCR tests, 15 781 (3·6%) SARS-CoV-2 infections were identified, with 8720 (5·4%) of 160 273 being positive among individuals with symptoms, and 7061 (2·5%) of 279 980 being positive among individuals without symptoms, at the time of presentation. Estimated aORs for symptomatic RT-PCR-confirmed infection increased continuously by a factor of 4·3 from ages 0-4 years to 80 years or older. By contrast, risk of asymptomatic RT-PCR-confirmed infection did not differ across ages 0-44 years, and thereafter increased by a factor of 1·6 between ages 45-49 years and 80 years or older. Seroprevalence was 40·1% (95% CI 35·8-44·6) at age 15 years or older by the end of the study period, indicating that RT-PCR clinical testing and surveillance testing identified only 1·4% (1·3-1·6%) of all infections in this age group. Among RT-PCR-confirmed cases, older age, male sex, and history of cancer, diabetes, other endocrine disorders, hypertension, other chronic circulatory disorders, respiratory disorders, and chronic kidney disease were each associated with elevated risk of mortality. The CFR among RT-PCR-confirmed cases was 2·4% (2·2-2·6); after age standardisation. At age 15 years or older, the IFR based on reported deaths was 0·043% (0·039-0·049), with reported deaths being only 11·0% (8·2-14·5) of the expected count.InterpretationIn a large-scale SARS-CoV-2 surveillance programme in Madurai, India, we identified equal risk of asymptomatic infection among children, teenagers, and working-age adults, and increasing risk of infection and death associated with older age and comorbidities. Establishing whether surveillance practices or differences in infection severity account for gaps between observed and expected mortality is of crucial importance to establishing the burden of COVID-19 in India.FundingThe Bill & Melinda Gates Foundation, the National Science Foundation, and the National Institute of General Medical Sciences.TranslationFor the Hindi translation of the abstract see Supplementary Materials section.

IntroductionStreptococcus pneumoniae is a leading cause of pneumonia among children. However, owing to diagnostic limitations, the protection conferred by pneumococcal conjugate vaccines (PCVs) against pediatric pneumonia attributable to vaccine-serotype pneumococci remains unknown.MethodsWe analyzed data on vaccination and nasopharyngeal pneumococcal detection among children

Observational studies of the effectiveness of vaccines to prevent COVID-19 are needed to inform real-world use. Such studies are now underway amid the ongoing rollout of SARS-CoV-2 vaccines globally. Although traditional case-control and test-negative design studies feature prominently among strategies used to assess vaccine effectiveness, such studies may encounter important threats to validity. Here, we review the theoretical basis for estimation of vaccine direct effects under traditional case-control and test-negative design frameworks, addressing specific natural history parameters of SARS-CoV-2 infection and COVID-19 relevant to these designs. Bias may be introduced by misclassification of cases and controls, particularly when clinical case criteria include common, nonspecific indicators of COVID-19. When using diagnostic assays with high analytical sensitivity for SARS-CoV-2 detection, individuals testing positive may be counted as cases even if their symptoms are due to other causes. The traditional case-control design may be particularly prone to confounding due to associations of vaccination with healthcare-seeking behavior or risk of infection. The test-negative design reduces but may not eliminate this confounding, for instance, if individuals who receive vaccination seek care or testing for less-severe illness. These circumstances indicate the two study designs cannot be applied naively to datasets gathered through public health surveillance or administrative sources. We suggest practical strategies to reduce bias in vaccine effectiveness estimates at the study design and analysis stages.

BackgroundRotavirus vaccine effectiveness is reduced among children in low-income countries. Indirect (transmission-mediated) effects of rotavirus vaccine might contribute to the total population effect of vaccination. We aimed to examine risk factors for transmission of rotavirus to household contacts in Blantyre, Malawi, and estimated the effectiveness of rotavirus vaccine in preventing transmission of infection to household contacts.MethodsIn this prospective household cohort study, we recruited children born after Sept 17, 2012, and aged at least 6 weeks (vaccine-eligible children) with acute rotavirus gastroenteritis and their household contacts, in four government health facilities in Blantyre, Malawi. Clinical data, a bulk stool sample, and 1-2 mL of serum were collected from case children at presentation. Clinical data and stool samples were also prospectively collected from household contacts over 14 days from presentation. A single stool sample was collected from control households containing asymptomatic children who were frequency age-matched to case children. Samples were tested for rotavirus using semi-quantitative real-time PCR and for anti-rotavirus IgA using a semi-quantitative sandwich ELISA. Risk factors for household transmission of rotavirus infection and clinical disease, including disease severity and faecal shedding density, were identified using mixed effects logistic regression. Vaccine effectiveness against transmission was estimated as 1 minus the ratio of secondary attack rates in vaccinated and counterfactual unvaccinated populations, using vaccine effectiveness estimates from the associated diarrhoeal surveillance platform to estimate the counterfactual secondary attack rate without vaccination.FindingsBetween Feb 16, 2015, and Nov 11, 2016, we recruited 196 case households (705 members) and 55 control households (153 members). Household secondary attack rate for rotavirus infection was high (434 [65%] of 665 individuals) and secondary attack rate for clinical disease was much lower (37 [5%] of 698). Asymptomatic infection in control households was common (40 [28%] of 144). Increasing disease severity in an index child (as measured by Vesikari score) was associated with increased risk of transmission of infection (odds ratio 1·17 [95% CI 1·06-1·30) and disease (1·28 [1·08-1·52]) to household contacts. Estimated vaccine effectiveness against transmission was 39% (95% CI 16-57).InterpretationRotavirus vaccine has the potential to substantially reduce household rotavirus transmission. This finding should be considered in clinical and health economic assessments of vaccine effectiveness.FundingWellcome Trust, US National Institutes of Health, and US National Institute of Allergy and Infectious Diseases.

During the ongoing coronavirus disease (COVID-19) pandemic, farmworkers in the United States are considered essential personnel and continue in-person work. We conducted prospective surveillance for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and antibody prevalence among farmworkers in Salinas Valley, California, during June 15-November 30, 2020. We observed 22.1% (1,514/6,864) positivity for SARS-CoV-2 infection among farmworkers compared with 17.2% (1,255/7,305) among other adults from the same communities (risk ratio 1.29, 95% CI 1.20-1.37). In a nested study enrolling 1,115 farmworkers, prevalence of current infection was 27.7% among farmworkers reporting >1 COVID-19 symptom and 7.2% among farmworkers without symptoms (adjusted odds ratio 4.16, 95% CI 2.85-6.06). Prevalence of SARS-CoV-2 antibodies increased from 10.5% (95% CI 6.0%-18.4%) during July 16-August 31 to 21.2% (95% CI 16.6%-27.4%) during November 1-30. High SARS-CoV-2 infection prevalence among farmworkers underscores the need for vaccination and other preventive interventions.

School closures may reduce the size of social networks among children, potentially limiting infectious disease transmission. To estimate the impact of K-12 closures and reopening policies on children's social interactions and COVID-19 incidence in California's Bay Area, we collected data on children's social contacts and assessed implications for transmission using an individual-based model. Elementary and Hispanic children had more contacts during closures than high school and non-Hispanic children, respectively. We estimated that spring 2020 closures of elementary schools averted 2167 cases in the Bay Area (95% CI: -985, 5572), fewer than middle (5884; 95% CI: 1478, 11.550), high school (8650; 95% CI: 3054, 15 940) and workplace (15 813; 95% CI: 9963, 22 617) closures. Under assumptions of moderate community transmission, we estimated that reopening for a four-month semester without any precautions will increase symptomatic illness among high school teachers (an additional 40.7% expected to experience symptomatic infection, 95% CI: 1.9, 61.1), middle school teachers (37.2%, 95% CI: 4.6, 58.1) and elementary school teachers (4.1%, 95% CI: -1.7, 12.0). However, we found that reopening policies for elementary schools that combine universal masking with classroom cohorts could result in few within-school transmissions, while high schools may require masking plus a staggered hybrid schedule. Stronger community interventions (e.g. remote work, social distancing) decreased the risk of within-school transmission across all measures studied, with the influence of community transmission minimized as the effectiveness of the within-school measures increased.

Host adaptive immune responses may protect against infection or disease when a pathogen is repeatedly encountered. The hazard ratio of infection or disease, given previous infection, is typically sought to estimate the strength of protective immunity. However, variation in individual exposure or susceptibility to infection may introduce frailty bias, whereby a tendency for infections to recur among individuals with greater risk confounds the causal association between previous infection and susceptibility. We introduce a self-matched "case-only" inference method to control for unmeasured individual heterogeneity, making use of negative-control endpoints not attributable to the pathogen of interest. To control for confounding, this method compares event times for endpoints due to the pathogen of interest and negative-control endpoints during counterfactual risk periods, defined according to individuals' infection history. We derive a standard Mantel-Haenszel (matched) odds ratio conveying the effect of prior infection on time to recurrence. We compare performance of this approach to several proportional hazards modeling frameworks and estimate statistical power of the proposed strategy under various conditions. In an example application, we use the proposed method to reestimate naturally acquired protection against rotavirus gastroenteritis using data from previously published cohort studies. This self-matched negative-control design may present a flexible alternative to existing approaches for analyzing naturally acquired immunity, as well as other exposures affecting the distribution of recurrent event times.

There have been notable advances in the development of vaccines against active tuberculosis (TB) disease for adults and adolescents. Using mathematical models, we seek to estimate the potential impact of a post-exposure TB vaccine, having 50% efficacy in reducing active disease, on global rifampicin-resistant (RR-) TB burden. In 30 countries that together accounted for 90% of global RR-TB incidence in 2018, a future TB vaccine could avert 10% (95% credible interval: 9.7-11%) of RR-TB cases and 7.3% (6.6-8.1%) of deaths over 2020-2035, with India, China, Indonesia, Pakistan, and the Russian Federation having the greatest contribution. This impact would increase to 14% (12-16%) and 31% (29-33%) respectively, when combined with improvements in RR-TB diagnosis and treatment relative to a scenario of no vaccine and no such improvements. A future TB vaccine could have important implications for the global control of RR-TB, especially if implemented alongside enhancements in management of drug resistance.

This study uses US Immigration and Customs Enforcement (ICE) Health Service Corps data to describe incident cases and outbreaks of influenza, varicella, and mumps in 22 US ICE detention centers between 2017 and March 2020.

BackgroundEnterovirus 71 (EV71) is a major causative agent of hand, foot, and mouth disease (HFMD), associated with severe manifestations of the disease. Pediatric immunization with inactivated EV71 vaccine was initiated in 2016 in the Asia-Pacific region, including China. We analyzed a time series of HFMD cases attributable to EV71, coxsackievirus A16 (CA16), and other enteroviruses in Chengdu, a major transmission center in China, to assess early impacts of immunization.MethodsReported HFMD cases were obtained from China's notifiable disease surveillance system. We compared observed postvaccination incidence rates during 2017-2018 with counterfactual predictions made from a negative binomial regression and a random forest model fitted to prevaccine years (2011-2015). We fit a change point model to the full time series to evaluate whether the trend of EV71 HFMD changed following vaccination.ResultsBetween 2011 and 2018, 279 352 HFMD cases were reported in the study region. The average incidence rate of EV71 HFMD in 2017-2018 was 60% (95% prediction interval [PI], 41%-72%) lower than predicted in the absence of immunization, corresponding to an estimated 6911 (95% PI, 3246-11 542) EV71 cases averted over 2 years. There were 52% (95% PI, 42%-60%) fewer severe HFMD cases than predicted. However, the incidence rate of non-CA16 and non-EV71 HFMD was elevated in 2018. We identified a significant decline in the trend of EV71 HFMD 4 months into the postvaccine period.ConclusionsWe provide the first real-world evidence that programmatic vaccination against EV71 is effective against childhood HFMD and present an approach to detect early vaccine impact or intended consequences from surveillance data.

Infectious disease surveillance systems provide vital data for guiding disease prevention and control policies, yet the formalization of methods to optimize surveillance networks has largely been overlooked. Decisions surrounding surveillance design parameters-such as the number and placement of surveillance sites, target populations, and case definitions-are often determined by expert opinion or deference to operational considerations, without formal analysis of the influence of design parameters on surveillance objectives. Here we propose a simulation framework to guide evidence-based surveillance network design to better achieve specific surveillance goals with limited resources. We define evidence-based surveillance design as an optimization problem, acknowledging the many operational constraints under which surveillance systems operate, the many dimensions of surveillance system design, the multiple and competing goals of surveillance, and the complex and dynamic nature of disease systems. We describe an analytical framework-the Disease Surveillance Informatics Optimization and Simulation (DIOS) framework-for the identification of optimal surveillance designs through mathematical representations of disease and surveillance processes, definition of objective functions, and numerical optimization. We then apply the framework to the problem of selecting candidate sites to expand an existing surveillance network under alternative objectives of: (1) improving spatial prediction of disease prevalence at unmonitored sites; or (2) estimating the observed effect of a risk factor on disease. Results of this demonstration illustrate how optimal designs are sensitive to both surveillance goals and the underlying spatial pattern of the target disease. The findings affirm the value of designing surveillance systems through quantitative and adaptive analysis of network characteristics and performance. The framework can be applied to the design of surveillance systems tailored to setting-specific disease transmission dynamics and surveillance needs, and can yield improved understanding of tradeoffs between network architectures.

Although most cases of coronavirus disease 2019 (COVID-19) have occurred in low-resource countries, little is known about the epidemiology of the disease in such contexts. Data from the Indian states of Tamil Nadu and Andhra Pradesh provide a detailed view into severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission pathways and mortality in a high-incidence setting. Reported cases and deaths have been concentrated in younger cohorts than would be expected from observations in higher-income countries, even after accounting for demographic differences across settings. Among 575,071 individuals exposed to 84,965 confirmed cases, infection probabilities ranged from 4.7 to 10.7% for low-risk and high-risk contact types, respectively. Same-age contacts were associated with the greatest infection risk. Case fatality ratios spanned 0.05% at ages of 5 to 17 years to 16.6% at ages of 85 years or more. Primary data from low-resource countries are urgently needed to guide control measures.

BackgroundReduced-dose pneumococcal conjugate vaccine (PCV) schedules are under consideration in countries where children are recommended to receive 3 doses. Whereas PCV-derived protection against vaccine-serotype colonization is responsible for herd effects of vaccination, dose-specific PCV effectiveness against colonization endpoints is not known. We aimed to assess the performance of differing PCV schedules against vaccine-serotype colonization in children.MethodsFrom 2009-2016, we monitored pneumococcal carriage in southern Israel, where children should receive PCV at ages 2 months, 4 months, and 12 months (2 primary [p] +1 booster [b] schedule). We analyzed nasopharyngeal swabs and vaccination histories from 5928 children aged 0-59 months without symptoms of diseases potentially attributable to pneumococci. Matching individuals on age, sex, ethnicity, visit timing, and recent antibiotic receipt, we measured schedule-specific 7-valent PCV (PCV7) and 13-valent PCV (PCV13) effectiveness against vaccine-serotype colonization in a modified case-control framework. We sampled from the distribution of all possible case-control match assignments for statistical analyses.ResultsReceiving 2 primary-series PCV13 doses conferred 53% (95% confidence interval [CI], 32-67%) protection against PCV13-serotype colonization at ages ≤12 months; 1 primary-series dose was not protective. A 2p+1b PCV13 series conferred 40% (95% CI, 4-67%) and 62% (95% CI, 33-83%) protection against PCV13-serotype colonization at ages 13-24 months and 25-59 months, respectively. Estimates suggested greater PCV13-conferred protection against PCV7-targeted serotypes than the 6 PCV13-only serotypes. As compared to children receiving 2p+1b PCV13 dosing, those receiving 1p+1b and 2p+0b schedules experienced 2.05-fold (95% CI, 1.12-5.00) and 3.33-fold (95% CI, 2.28-4.93) greater odds, respectively, of vaccine-serotype pneumococcal colonization at ages 13-24 months.ConclusionsOur results demonstrate real-world effectiveness of 2p+1b PCV dosing against vaccine-serotype colonization. Reduced-dose schedules may confer lower protection against vaccine-serotype carriage during and beyond the first year of life.